Exact solutions to a spatially extended model of kinase-receptor interaction.

PubMed

Szopa, Piotr; Lipniacki, Tomasz; Kazmierczak, Bogdan

2011-10-01

B and Mast cells are activated by the aggregation of the immune receptors. Motivated by this phenomena we consider a simple spatially extended model of mutual interaction of kinases and membrane receptors. It is assumed that kinase activates membrane receptors and in turn the kinase molecules bound to the active receptors are activated by transphosphorylation. Such a type of interaction implies positive feedback and may lead to bistability. In this study we apply the Steklov eigenproblem theory to analyze the linearized model and find exact solutions in the case of non-uniformly distributed membrane receptors. This approach allows us to determine the critical value of receptor dephosphorylation rate at which cell activation (by arbitrary small perturbation of the inactive state) is possible. We found that cell sensitivity grows with decreasing kinase diffusion and increasing anisotropy of the receptor distribution. Moreover, these two effects are cooperating. We showed that the cell activity can be abruptly triggered by the formation of the receptor aggregate. Since the considered activation mechanism is not based on receptor crosslinking by polyvalent antigens, the proposed model can also explain B cell activation due to receptor aggregation following binding of monovalent antigens presented on the antigen presenting cell.

Interpersonal distance modeling during fighting activities.

PubMed

Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves

2010-10-01

The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities.

Improving science and mathematics education with computational modelling in interactive engagement environments

NASA Astrophysics Data System (ADS)

Neves, Rui Gomes; Teodoro, Vítor Duarte

2012-09-01

A teaching approach aiming at an epistemologically balanced integration of computational modelling in science and mathematics education is presented. The approach is based on interactive engagement learning activities built around computational modelling experiments that span the range of different kinds of modelling from explorative to expressive modelling. The activities are designed to make a progressive introduction to scientific computation without requiring prior development of a working knowledge of programming, generate and foster the resolution of cognitive conflicts in the understanding of scientific and mathematical concepts and promote performative competency in the manipulation of different and complementary representations of mathematical models. The activities are supported by interactive PDF documents which explain the fundamental concepts, methods and reasoning processes using text, images and embedded movies, and include free space for multimedia enriched student modelling reports and teacher feedback. To illustrate, an example from physics implemented in the Modellus environment and tested in undergraduate university general physics and biophysics courses is discussed.

A Small-molecule Inhibitor, 5′-O-Tritylthymidine, targets FAK and Mdm-2 Interaction, and Blocks Breast and Colon Tumorigenesis in vivo

PubMed Central

Golubovskaya, Vita; Palma, Nadia L.; Zheng, Min; Ho, Baotran; Magis, Andrew; Ostrov, David; Cance, William G.

2013-01-01

Focal Adhesion Kinase (FAK) is overexpressed in many types of tumors and plays an important role in survival. We developed a novel approach, targeting FAK-protein interactions by computer modeling and screening of NCI small molecule drug database. In this report we targeted FAK and Mdm-2 protein interaction to decrease tumor growth. By macromolecular modeling we found a model of FAK and Mdm-2 interaction and performed screening of >200,000 small molecule compounds from NCI database with drug-like characteristics, targeting the FAK-Mdm-2 interaction. We identified 5′-O-Tritylthymidine, called M13 compound that significantly decreased viability in different cancer cells. M13 was docked into the pocket of FAK and Mdm-2 interaction and was directly bound to the FAK-N terminal domain by ForteBio Octet assay. In addition, M13 compound affected FAK and Mdm-2 levels and decreased complex of FAK and Mdm-2 proteins in breast and colon cancer cells. M13 re-activated p53 activity inhibited by FAK with Mdm-2 promoter. M13 decreased viability, clonogenicity, increased detachment and apoptosis in a dose-dependent manner in BT474 breast and in HCT116 colon cancer cells in vitro. M13 decreased FAK, activated p53 and caspase-8 in both cell lines. In addition, M13 decreased breast and colon tumor growth in vivo. M13 activated p53 and decreased FAK in tumor samples consistent with decreased tumor growth. The data demonstrate a novel approach for targeting FAK and Mdm-2 protein interaction, provide a model of FAK and Mdm-2 interaction, identify M13 compound targeting this interaction and decreasing tumor growth that is critical for future targeted therapeutics. PMID:22292771

Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons

PubMed Central

Apollo, Nicholas V.; Garrett, David J.

2018-01-01

Implantable retinal stimulators activate surviving neurons to restore a sense of vision in people who have lost their photoreceptors through degenerative diseases. Complex spatial and temporal interactions occur in the retina during multi-electrode stimulation. Due to these complexities, most existing implants activate only a few electrodes at a time, limiting the repertoire of available stimulation patterns. Measuring the spatiotemporal interactions between electrodes and retinal cells, and incorporating them into a model may lead to improved stimulation algorithms that exploit the interactions. Here, we present a computational model that accurately predicts both the spatial and temporal nonlinear interactions of multi-electrode stimulation of rat retinal ganglion cells (RGCs). The model was verified using in vitro recordings of ON, OFF, and ON-OFF RGCs in response to subretinal multi-electrode stimulation with biphasic pulses at three stimulation frequencies (10, 20, 30 Hz). The model gives an estimate of each cell’s spatiotemporal electrical receptive fields (ERFs); i.e., the pattern of stimulation leading to excitation or suppression in the neuron. All cells had excitatory ERFs and many also had suppressive sub-regions of their ERFs. We show that the nonlinearities in observed responses arise largely from activation of presynaptic interneurons. When synaptic transmission was blocked, the number of sub-regions of the ERF was reduced, usually to a single excitatory ERF. This suggests that direct cell activation can be modeled accurately by a one-dimensional model with linear interactions between electrodes, whereas indirect stimulation due to summated presynaptic responses is nonlinear. PMID:29432411

Testing Predictions of the Interactive Activation Model in Recovery from Aphasia after Treatment

ERIC Educational Resources Information Center

Jokel, Regina; Rochon, Elizabeth; Leonard, Carol

2004-01-01

This paper presents preliminary results of pre- and post-treatment error analysis from an aphasic patient with anomia. The Interactive Activation (IA) model of word production (Dell, Schwartz, Martin, Saffran, & Gagnon, 1997) is utilized to make predictions about the anticipated changes on a picture naming task and to explain emerging patterns.…

Using Clickers to Facilitate Interactive Engagement Activities in a Lecture Room for Improved Performance by Students

ERIC Educational Resources Information Center

Tlhoaele, Malefyane; Hofman, Adriaan; Naidoo, Ari; Winnips, Koos

2014-01-01

What impact can interactive engagement (IE) activities using clickers have on students' motivation and academic performance during lectures as compared to attending traditional types of lectures? This article positions the research on IE within the comprehensive model of educational effectiveness and Gagné's instructional events model. For the…

Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

PubMed

Takaguchi, Taro; Masuda, Naoki; Holme, Petter

2013-01-01

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.

A Model for Enhancing Social Communication and Interaction in Everyday Activities for Primary School Children with ASD

ERIC Educational Resources Information Center

Peters, Brenda

2016-01-01

Children with a diagnosis of Autism Spectrum Disorder may find the social aspects of learning particularly challenging because of the traits of diffculty with social communication and interaction. This paper evaluates the impact of an interactive model designed to support social communication and interaction for twelve students with ASD, who…

Miming the cancer-immune system competition by kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Lemarchand, Annie

2016-10-01

In order to mimic the interactions between cancer and the immune system at cell scale, we propose a minimal model of cell interactions that is similar to a chemical mechanism including autocatalytic steps. The cells are supposed to bear a quantity called activity that may increase during the interactions. The fluctuations of cell activity are controlled by a so-called thermostat. We develop a kinetic Monte Carlo algorithm to simulate the cell interactions and thermalization of cell activity. The model is able to reproduce the well-known behavior of tumors treated by immunotherapy: the first apparent elimination of the tumor by the immune system is followed by a long equilibrium period and the final escape of cancer from immunosurveillance.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when transcription factors and RNA polymerase interact by means of three-body interactions. Overall, we show that versatility of transcriptional activation is brought about by nonlinearities of transcriptional response functions and interactions between transcription factors, RNA polymerase and DNA. PMID:22506020

Speech Perception as a Cognitive Process: The Interactive Activation Model.

ERIC Educational Resources Information Center

Elman, Jeffrey L.; McClelland, James L.

Research efforts to model speech perception in terms of a processing system in which knowledge and processing are distributed over large numbers of highly interactive--but computationally primative--elements are described in this report. After discussing the properties of speech that demand a parallel interactive processing system, the report…

Use of a PhET Interactive Simulation in General Chemistry Laboratory: Models of the Hydrogen Atom

ERIC Educational Resources Information Center

Clark, Ted M.; Chamberlain, Julia M.

2014-01-01

An activity supporting the PhET interactive simulation, Models of the Hydrogen Atom, has been designed and used in the laboratory portion of a general chemistry course. This article describes the framework used to successfully accomplish implementation on a large scale. The activity guides students through a comparison and analysis of the six…

Competition and cooperation among similar representations: toward a unified account of facilitative and inhibitory effects of lexical neighbors.

PubMed

Chen, Qi; Mirman, Daniel

2012-04-01

One of the core principles of how the mind works is the graded, parallel activation of multiple related or similar representations. Parallel activation of multiple representations has been particularly important in the development of theories and models of language processing, where coactivated representations (neighbors) have been shown to exhibit both facilitative and inhibitory effects on word recognition and production. Researchers generally ascribe these effects to interactive activation and competition, but there is no unified explanation for why the effects are facilitative in some cases and inhibitory in others. We present a series of simulations of a simple domain-general interactive activation and competition model that is broadly consistent with more specialized domain-specific models of lexical processing. The results showed that interactive activation and competition can indeed account for the complex pattern of reversals. Critically, the simulations revealed a core computational principle that determines whether neighbor effects are facilitative or inhibitory: strongly active neighbors exert a net inhibitory effect, and weakly active neighbors exert a net facilitative effect.

Screening of benzamidine-based thrombin inhibitors via a linear interaction energy in continuum electrostatics model

NASA Astrophysics Data System (ADS)

Nicolotti, Orazio; Giangreco, Ilenia; Miscioscia, Teresa Fabiola; Convertino, Marino; Leonetti, Francesco; Pisani, Leonardo; Carotti, Angelo

2010-02-01

A series of 27 benzamidine inhibitors covering a wide range of biological activity and chemical diversity was analysed to derive a Linear Interaction Energy in Continuum Electrostatics (LIECE) model for analysing the thrombin inhibitory activity. The main interactions occurring at the thrombin binding site and the preferred binding conformations of inhibitors were explicitly biased by including into the LIECE model 10 compounds extracted from X-ray solved thrombin-inhibitor complexes available from the Protein Data Bank (PDB). Supported by a robust statistics ( r 2 = 0.698; q 2 = 0.662), the LIECE model was successful in predicting the inhibitory activity for about 76% of compounds ( r ext 2 ≥ 0.600) from a larger external test set encompassing 88 known thrombin inhibitors and, more importantly, in retrieving, at high sensitivity and with better performance than docking and shape-based methods, active compounds from a thrombin combinatorial library of 10240 mimetic chemical products. The herein proposed LIECE model has the potential for successfully driving the design of novel thrombin inhibitors with benzamidine and/or benzamidine-like chemical structure.

Modeling the Surface Water-Groundwater Interaction in Arid and Semi-Arid Regions Impacted by Agricultural Activities

NASA Astrophysics Data System (ADS)

Tian, Y.; Wu, B.; Zheng, Y.

2013-12-01

In many semi-arid and arid regions, interaction between surface water and groundwater plays an important role in the eco-hydrological system. The interaction is often complicated by agricultural activities such as surface water diversion, groundwater pumping, and irrigation. In existing surface water-groundwater integrated models, simulation of the interaction is often simplified, which could introduce significant simulation uncertainty under certain circumstance. In this study, GSFLOW, a USGS model coupling PRMS and MODFLOW, was improved to better characterize the surface water-groundwater interaction. The practices of water diversion from rivers, groundwater pumping and irrigation are explicitly simulated. In addition, the original kinematic wave routing method was replaced by a dynamic wave routing method. The improved model was then applied in Zhangye Basin (the midstream part of Heihe River Baisn), China, where the famous 'Silk Road' came through. It is a typical semi-arid region of the western China, with extensive agriculture in its oasis. The model was established and calibrated using the data in 2000-2008. A series of numerical experiments were conducted to evaluate the effect of those improvements. It has been demonstrated that with the improvements, the observed streamflow and groundwater level were better reproduced by the model. The improvements have a significant impact on the simulation of multiple fluxes associated with the interaction, such as groundwater discharge, riverbed seepage, infiltration, etc. Human activities were proved to be key elements of the water cycle in the study area. The study results have important implications to the water resources modeling and management in semi-arid and arid basins.

Synergistic effect of interaction between perceived health and social activity on depressive symptoms in the middle-aged and elderly: a population-based longitudinal study.

PubMed

Chun, Sung-Youn; Han, Kyu-Tae; Lee, Seo Yoon; Kim, Chan Ok; Park, Eun-Cheol

2015-03-13

To examine the synergistic effect of interaction between perceived health and social activity on depressive symptoms. We investigated whether the interaction between perceived health and social activity has a synergistic effect on depressive symptoms in the middle-aged and elderly using data from 6590 respondents aged 45 and older in the Korean Longitudinal Study on Aging (KLoSA), 2006-2012. A generalised linear mixed-effects model was used to investigate the association in a longitudinal data form. Depressive symptoms were measured using the Center for Epidemiological Studies Depression 10 Scale (CES-D10). Perceived health and level of social activity were categorical variables with three values. Participation in six social activities was assessed. Interactions between perceived health status and social activity were statistically significant for almost all social activity/perceived health combinations. Addition of the interaction term significantly decreased CES-D10 scores, confirming the synergistic effect of the interaction between perceived health status and social activity ('normal×moderate', β=-0.1826; 'poor×moderate', β=-0.5739; 'poor×active', β=-0.8935). In addition, we performed stratified analyses by region: urban or rural. In urban respondents, the additional effect of the interaction term decreased CES-D10 scores and all social activity/perceived health combinations were statistically significant ('normal×moderate', β=-0.2578; 'normal×active', β=-0.3945; 'poor×moderate', β=-0.5739; 'poor×active', β=-0.8935). In rural respondents, only one social activity/perceived health combination was statistically significant, and the additional effect of the interaction term showed no consistent trend on CES-D10 scores. The interaction between perceived health and social activity has a synergistic effect on depressive symptoms; the additional effect of the interaction term significantly decreased CES-D10 scores in our models. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Unfolding large-scale online collaborative human dynamics

PubMed Central

Zha, Yilong; Zhou, Tao; Zhou, Changsong

2016-01-01

Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with a precise record of event timing provide unprecedented opportunity. Our empirical analysis of the history of millions of updates in Wikipedia shows a universal double–power-law distribution of time intervals between consecutive updates of an article. We then propose a generic model to unfold collaborative human activities into three modules: (i) individual behavior characterized by Poissonian initiation of an action, (ii) human interaction captured by a cascading response to previous actions with a power-law waiting time, and (iii) population growth due to the increasing number of interacting individuals. This unfolding allows us to obtain an analytical formula that is fully supported by the universal patterns in empirical data. Our modeling approaches reveal “simplicity” beyond complex interacting human activities. PMID:27911766

How Model Can Help Inquiry--A Qualitative Study of Model Based Inquiry Learning (Mobile) in Engineering Education

ERIC Educational Resources Information Center

Gong, Yu

2017-01-01

This study investigates how students can use "interactive example models" in inquiry activities to develop their conceptual knowledge about an engineering phenomenon like electromagnetic fields and waves. An interactive model, for example a computational model, could be used to develop and teach principles of dynamic complex systems, and…

Contact processes with competitive dynamics in bipartite lattices: effects of distinct interactions

NASA Astrophysics Data System (ADS)

Pianegonda, Salete; Fiore, Carlos E.

2014-05-01

The two-dimensional contact process (CP) with a competitive dynamics proposed by Martins et al (2011 Phys. Rev. E 84 011125) leads to the appearance of an unusual active-asymmetric phase, in which the system sublattices are unequally populated. It differs from the usual CP only by the fact that particles also interact with their next-nearest neighbor sites via a distinct strength creation rate, and for the inclusion of an inhibition effect, proportional to the local density. Aimed at investigating the robustness of such an asymmetric phase, in this paper we study the influence of distinct interactions for two bidimensional CPs. In the first model, the interaction between first neighbors requires a minimal neighborhood of adjacent particles for creating new offspring, whereas second neighbors interact as usual (e.g. at least one neighboring particle is required). The second model takes the opposite situation, in which the restrictive dynamics is in the interaction between next-nearest neighbor sites. Both models are investigated under mean field theory (MFT) and Monte Carlo simulations. In similarity with results by Martins et al, the inclusion of distinct sublattice interactions maintains the occurrence of an asymmetric active phase and re-entrant transition lines. In contrast, remarkable differences are presented, such as discontinuous phase transitions (even between the active phases), the appearance of tricritical points and the stabilization of active phases under larger values of control parameters. Finally, we have shown that the critical behaviors are not altered due to the change of interactions, in which the absorbing transitions belong to the directed percolation (DP) universality class, whereas second-order active phase transitions belong to the Ising universality class.

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

NASA Technical Reports Server (NTRS)

DeBoer, G.; Bauer, S. E.; Toto, T.; Menon, Surabi; Vogelmann, A. M.

2013-01-01

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

Effect of ultraviolet irradiation on free radical scavenging activity of immunosuppressants used in lung transplantation and comparative electron paramagnetic resonance study of kinetics of their interactions with model free radicals.

PubMed

Stanjek-Cichoracka, A; Żegleń, S; Ramos, P; Pilawa, B; Wojarski, J

2018-06-01

The immunosuppressive drugs used in solid organ transplantation or autoimmunological processes were studied by electron paramagnetic resonance (EPR) spectroscopy to estimate their free radical scavenging activity. The interactions of immunosuppressants with free radicals were examined by an X-band (9.3 GHz) EPR spectroscopy and a model of DPPH free radicals. The EPR spectra of DPPH and DPPH interacting with individual drugs were compared. Kinetic studies were performed, and the effect of ultraviolet (UV) irradiation on the free radical scavenging activity of the tested drugs was determined. The free radical scavenging activity of non-irradiated drugs decreased in the order: rapamycin > mycophenolate mofetil > ciclosporin > tacrolimus. UV irradiation increased the free radical scavenging activity of all the tested immunosuppressive drugs, and the effect was highest for tacrolimus. For the non-irradiated samples, the speed of free radical interactions decreased in the order: ciclosporin > tacrolimus > mycophenolate mofetil > rapamycin. UV irradiation only slightly affected the speed of interactions of the immunosuppressive drugs with the model DPPH free radicals. Electron paramagnetic resonance spectroscopy is useful for obtaining information on interactions of immunosuppressive drugs with free radicals. We hypothesized that the long-term immunosuppressive effects of these drugs after transplantation or during autoimmune disorders may be mediated by anti-inflammatory action in addition to the known receptor/cell cycle inhibition. © 2018 John Wiley & Sons Ltd.

Combined molecular modelling and 3D-QSAR study for understanding the inhibition of NQO1 by heterocyclic quinone derivatives.

PubMed

López-Lira, Claudia; Alzate-Morales, Jans H; Paulino, Margot; Mella-Raipán, Jaime; Salas, Cristian O; Tapia, Ricardo A; Soto-Delgado, Jorge

2018-01-01

A combination of three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular modelling methods were used to understand the potent inhibitory NAD(P)H:quinone oxidoreductase 1 (NQO1) activity of a set of 52 heterocyclic quinones. Molecular docking results indicated that some favourable interactions of key amino acid residues at the binding site of NQO1 with these quinones would be responsible for an improvement of the NQO1 activity of these compounds. The main interactions involved are hydrogen bond of the amino group of residue Tyr128, π-stacking interactions with Phe106 and Phe178, and electrostatic interactions with flavin adenine dinucleotide (FADH) cofactor. Three models were prepared by 3D-QSAR analysis. The models derived from Model I and Model III, shown leave-one-out cross-validation correlation coefficients (q 2 LOO ) of .75 and .73 as well as conventional correlation coefficients (R 2 ) of .93 and .95, respectively. In addition, the external predictive abilities of these models were evaluated using a test set, producing the predicted correlation coefficients (r 2 pred ) of .76 and .74, respectively. The good concordance between the docking results and 3D-QSAR contour maps provides helpful information about a rational modification of new molecules based in quinone scaffold, in order to design more potent NQO1 inhibitors, which would exhibit highly potent antitumor activity. © 2017 John Wiley & Sons A/S.

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

A dynamical systems model of progesterone receptor interactions with inflammation in human parturition.

PubMed

Brubaker, Douglas; Barbaro, Alethea; R Chance, Mark; Mesiano, Sam

2016-08-19

Progesterone promotes uterine relaxation and is essential for the maintenance of pregnancy. Withdrawal of progesterone activity and increased inflammation within the uterine tissues are key triggers for parturition. Progesterone actions in myometrial cells are mediated by two progesterone receptor (PR) isoforms, PR-A and PR-B, that function as ligand-activated transcription factors. PR-B mediates relaxatory actions of progesterone, in part, by decreasing myometrial cell responsiveness to pro-inflammatory stimuli. These same pro-inflammatory stimuli promote the expression of PR-A which inhibits the anti-inflammatory activity of PR-B. Competitive interaction between the progesterone receptors then augments myometrial responsiveness to pro-inflammatory stimuli. The interaction between PR-B transcriptional activity and inflammation in the pregnancy myometrium is examined using a dynamical systems model in which quiescence and labor are represented as phase-space equilibrium points. Our model shows that PR-B transcriptional activity and the inflammatory load determine the stability of the quiescent and laboring phenotypes. The model is tested using published transcriptome datasets describing the mRNA abundances in the myometrium before and after the onset of labor at term. Surrogate transcripts were selected to reflect PR-B transcriptional activity and inflammation status. The model coupling PR-B activity and inflammation predicts contractile status (i.e., laboring or quiescent) with high precision and recall and outperforms uncoupled single and two-gene classifiers. Linear stability analysis shows that phase space bifurcations exist in our model that may reflect the phenotypic states of the pregnancy uterus. The model describes a possible tipping point for the transition of the quiescent to the contractile laboring phenotype. Our model describes the functional interaction between the PR-A:PR-B hypothesis and tissue level inflammation in the pregnancy uterus and is a first step in more sophisticated dynamical systems modeling of human partition. The model explains observed biochemical dynamics and as such will be useful for the development of a range of systems-based models using emerging data to predict preterm birth and identify strategies for its prevention.

Neural dynamics of social tie formation in economic decision-making.

PubMed

Bault, Nadège; Pelloux, Benjamin; Fahrenfort, Johannes J; Ridderinkhof, K Richard; van Winden, Frans

2015-06-01

The disposition for prosocial conduct, which contributes to cooperation as arising during social interaction, requires cortical network dynamics responsive to the development of social ties, or care about the interests of specific interaction partners. Here, we formulate a dynamic computational model that accurately predicted how tie formation, driven by the interaction history, influences decisions to contribute in a public good game. We used model-driven functional MRI to test the hypothesis that brain regions key to social interactions keep track of dynamics in tie strength. Activation in the medial prefrontal cortex (mPFC) and posterior cingulate cortex tracked the individual's public good contributions. Activation in the bilateral posterior superior temporal sulcus (pSTS), and temporo-parietal junction was modulated parametrically by the dynamically developing social tie-as estimated by our model-supporting a role of these regions in social tie formation. Activity in these two regions further reflected inter-individual differences in tie persistence and sensitivity to behavior of the interaction partner. Functional connectivity between pSTS and mPFC activations indicated that the representation of social ties is integrated in the decision process. These data reveal the brain mechanisms underlying the integration of interaction dynamics into a social tie representation which in turn influenced the individual's prosocial decisions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Effects of multiple enzyme-substrate interactions in basic units of cellular signal processing

NASA Astrophysics Data System (ADS)

Seaton, D. D.; Krishnan, J.

2012-08-01

Covalent modification cycles are a ubiquitous feature of cellular signalling networks. In these systems, the interaction of an active enzyme with the unmodified form of its substrate is essential for signalling to occur. However, this interaction is not necessarily the only enzyme-substrate interaction possible. In this paper, we analyse the behaviour of a basic model of signalling in which additional, non-essential enzyme-substrate interactions are possible. These interactions include those between the inactive form of an enzyme and its substrate, and between the active form of an enzyme and its product. We find that these additional interactions can result in increased sensitivity and biphasic responses, respectively. The dynamics of the responses are also significantly altered by the presence of additional interactions. Finally, we evaluate the consequences of these interactions in two variations of our basic model, involving double modification of substrate and scaffold-mediated signalling, respectively. We conclude that the molecular details of protein-protein interactions are important in determining the signalling properties of enzymatic signalling pathways.

Bone sialoprotein does not interact with pro-gelatinase A (MMP-2) or mediate MMP-2 activation.

PubMed

Hwang, Queena; Cheifetz, Sela; Overall, Christopher M; McCulloch, Christopher A; Sodek, Jaro

2009-04-22

A recent model for activation of the zymogen form of matrix metalloproteinase 2 (MMP-2, also known as gelatinase A) has suggested that interactions between the SIBLING protein bone sialoprotein (BSP) and MMP-2 leads to conformational change in MMP-2 that initiates the conversion of the pro-enzyme into a catalytically active form. This model is particularly relevant to cancer cell metastasis to bone since BSP, bound to the alphavbeta3 integrin through its arginine-glycine-aspartic acid motif, could recruit MMP-2 to the cell surface. We critically assessed the relationship between BSP and proMMP-2 and its activation using various forms of recombinant and purified BSP and MMP-2. Gelatinase and collagenase assays, fluorescence binding assays, real-time PCR, cell culture and pull-down assays were employed to test the model. Studies with a fluorogenic substrate for MMP-2 showed no activation of proMMP-2 by BSP. Binding and pull-down assays demonstrated no interaction between MMP-2 and BSP. While BSP-mediated invasiveness has been shown to depend on its integrin-binding RGD sequence, analysis of proMMP-2 activation and the level of membrane type 1 (MT1)-MMP in cells grown on a BSP substratum showed that the BSP-alphavbeta3 integrin interaction does not induce the expression of MT1-MMP. These studies do not support a role for BSP in promoting metastasis through interactions with pro-MMP-2.

Multilevel depth and image fusion for human activity detection.

PubMed

Ni, Bingbing; Pei, Yong; Moulin, Pierre; Yan, Shuicheng

2013-10-01

Recognizing complex human activities usually requires the detection and modeling of individual visual features and the interactions between them. Current methods only rely on the visual features extracted from 2-D images, and therefore often lead to unreliable salient visual feature detection and inaccurate modeling of the interaction context between individual features. In this paper, we show that these problems can be addressed by combining data from a conventional camera and a depth sensor (e.g., Microsoft Kinect). We propose a novel complex activity recognition and localization framework that effectively fuses information from both grayscale and depth image channels at multiple levels of the video processing pipeline. In the individual visual feature detection level, depth-based filters are applied to the detected human/object rectangles to remove false detections. In the next level of interaction modeling, 3-D spatial and temporal contexts among human subjects or objects are extracted by integrating information from both grayscale and depth images. Depth information is also utilized to distinguish different types of indoor scenes. Finally, a latent structural model is developed to integrate the information from multiple levels of video processing for an activity detection. Extensive experiments on two activity recognition benchmarks (one with depth information) and a challenging grayscale + depth human activity database that contains complex interactions between human-human, human-object, and human-surroundings demonstrate the effectiveness of the proposed multilevel grayscale + depth fusion scheme. Higher recognition and localization accuracies are obtained relative to the previous methods.

Simulation of the effect of hydrogen bonds on water activity of glucose and dextran using the Veytsman model.

PubMed

De Vito, Francesca; Veytsman, Boris; Painter, Paul; Kokini, Jozef L

2015-03-06

Carbohydrates exhibit either van der Waals and ionic interactions or strong hydrogen bonding interactions. The prominence and large number of hydrogen bonds results in major contributions to phase behavior. A thermodynamic framework that accounts for hydrogen bonding interactions is therefore necessary. We have developed an extension of the thermodynamic model based on the Veytsman association theory to predict the contribution of hydrogen bonds to the behavior of glucose-water and dextran-water systems and we have calculated the free energy of mixing and its derivative leading to chemical potential and water activity. We compared our calculations with experimental data of water activity for glucose and dextran and found excellent agreement far superior to the Flory-Huggins theory. The validation of our calculations using experimental data demonstrated the validity of the Veytsman model in properly accounting for the hydrogen bonding interactions and successfully predicting water activity of glucose and dextran. Our calculations of the concentration of hydrogen bonds using the Veytsman model were instrumental in our ability to explain the difference between glucose and dextran and the role that hydrogen bonds play in contributing to these differences. The miscibility predictions showed that the Veytsman model is also able to correctly describe the phase behavior of glucose and dextran. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interaction in Spoken Word Recognition Models: Feedback Helps.

PubMed

Magnuson, James S; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.

Interaction in Spoken Word Recognition Models: Feedback Helps

PubMed Central

Magnuson, James S.; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D.

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis. PMID:29666593

Particle-based simulations of self-motile suspensions

NASA Astrophysics Data System (ADS)

Hinz, Denis F.; Panchenko, Alexander; Kim, Tae-Yeon; Fried, Eliot

2015-11-01

A simple model for simulating flows of active suspensions is investigated. The approach is based on dissipative particle dynamics. While the model is potentially applicable to a wide range of self-propelled particle systems, the specific class of self-motile bacterial suspensions is considered as a modeling scenario. To mimic the rod-like geometry of a bacterium, two dissipative particle dynamics particles are connected by a stiff harmonic spring to form an aggregate dissipative particle dynamics molecule. Bacterial motility is modeled through a constant self-propulsion force applied along the axis of each such aggregate molecule. The model accounts for hydrodynamic interactions between self-propelled agents through the pairwise dissipative interactions conventional to dissipative particle dynamics. Numerical simulations are performed using a customized version of the open-source software package LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) software package. Detailed studies of the influence of agent concentration, pairwise dissipative interactions, and Stokes friction on the statistics of the system are provided. The simulations are used to explore the influence of hydrodynamic interactions in active suspensions. For high agent concentrations in combination with dominating pairwise dissipative forces, strongly correlated motion patterns and a fluid-like spectral distributions of kinetic energy are found. In contrast, systems dominated by Stokes friction exhibit weaker spatial correlations of the velocity field. These results indicate that hydrodynamic interactions may play an important role in the formation of spatially extended structures in active suspensions.

Integrative Approach for Computationally Inferring Interactions between the Alpha and Beta Subunits of the Calcium-Activated Potassium Channel (BK): a Docking Study

PubMed Central

González, Janneth; Gálvez, Angela; Morales, Ludis; Barreto, George E.; Capani, Francisco; Sierra, Omar; Torres, Yolima

2013-01-01

Three-dimensional models of the alpha- and beta-1 subunits of the calcium-activated potassium channel (BK) were predicted by threading modeling. A recursive approach comprising of sequence alignment and model building based on three templates was used to build these models, with the refinement of non-conserved regions carried out using threading techniques. The complex formed by the subunits was studied by means of docking techniques, using 3D models of the two subunits, and an approach based on rigid-body structures. Structural effects of the complex were analyzed with respect to hydrogen-bond interactions and binding-energy calculations. Potential interaction sites of the complex were determined by referencing a study of the difference accessible surface area (DASA) of the protein subunits in the complex. PMID:23492851

Insight into the interaction mechanism of human SGLT2 with its inhibitors: 3D-QSAR studies, homology modeling, and molecular docking and molecular dynamics simulations.

PubMed

Dong, Lili; Feng, Ruirui; Bi, Jiawei; Shen, Shengqiang; Lu, Huizhe; Zhang, Jianjun

2018-03-06

Human sodium-dependent glucose co-transporter 2 (hSGLT2) is a crucial therapeutic target in the treatment of type 2 diabetes. In this study, both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to generate three-dimensional quantitative structure-activity relationship (3D-QSAR) models. In the most accurate CoMFA-based and CoMSIA-based QSAR models, the cross-validated coefficients (r 2 cv ) were 0.646 and 0.577, respectively, while the non-cross-validated coefficients (r 2 ) were 0.997 and 0.991, respectively, indicating that both models were reliable. In addition, we constructed a homology model of hSGLT2 in the absence of a crystal structure. Molecular docking was performed to explore the bonding mode of inhibitors to the active site of hSGLT2. Molecular dynamics (MD) simulations and binding free energy calculations using MM-PBSA and MM-GBSA were carried out to further elucidate the interaction mechanism. With regards to binding affinity, we found that hydrogen-bond interactions of Asn51 and Glu75, located in the active site of hSGLT2, with compound 40 were critical. Hydrophobic and electrostatic interactions were shown to enhance activity, in agreement with the results obtained from docking and 3D-QSAR analysis. Our study results shed light on the interaction mode between inhibitors and hSGLT2 and may aid in the development of C-aryl glucoside SGLT2 inhibitors.

Induced Star Formation

NASA Astrophysics Data System (ADS)

Kennicutt, Robert C., Jr.

Overview: Induced Star Formation and Interactions Introduction Historical Background: First Hints Systematic Studies: Starbursts Interactions and Nuclear activity IRAS and Ultralumious starburst Galaxies The 1990's: HST, Supercomputers, and the Distant Universe Key Questions and Issues Organization of Lectures Star Formation Properties of Normal Galaxies Observational Techniques Results: Star Formation in Normal Galaxies Interpretation: Star Formation Histories Global Star Formation in interacting Galaxies A Gallery of Interactions and Mergers Star Formation Statistics: Guilt By Association Tests SFRs in Interacting vs Noninteracting Galaxies Kinematic Properties and Regulation of SFRs Induced Nuclear Activity and Star Formation Background: Nuclear Spectra and Classification Nuclear Star Formation and Starbursts Nuclear Star Formation and Interactions Induced AGN Activity: Statistics of Seyfert Galaxies Environments of Quasars Kinematic Clues to the Triggering of AGNs Infrared Luminous Galaxies and Starbursts Background: IR Luminous Galaxies and IRAS Infrared Luminosity Function and Spectra Infrared Structure and Morphology Interstellar Gas X-Ray Emission and Superwinds Optical, UV, and Near-Infrared Spectra Radio Continuum Emission Evidence for Interactions and Mergers The Power Source: Starbursts or Dusty AGNs? Spectral Diagnostics of Starbursts Evolutionary Synthesis Models Applications: Integrated Colors of Interacting Galaxies Applications: Hα Emission, Colors, and SFRs Applications: Spectral Modelling of Evolved Starbursts Infrared Starbursts and the IMF in starbursts Triggering and Regulation of Star Formation: The Problem Introduction: Star Formation as a Nonlinear Process The schmidt Law in Normal Galaxies Star Formation Regimes in Interacting Galaxies Summary Triggering and Regulation of Starbusts: Theoretical Ideas Gravitational Star Formation Thresholds Cloud Collision Models Radial Transport of Gas: Clues from Barred Galaxies Simulations of Starbursts in Merging Galaxies The Cosmological Role of Interactions and Starbursts Interactions in Hierarchical Cosmology Interaction-Induced Star Formation Today Interaction-Induced Star Formation in the Past Disk kinematics and the Merger Rate Global Effects of Starbursts and Superwinds Concluding Remarks References

A minimal kinetic model for a viral DNA packaging machine.

PubMed

Yang, Qin; Catalano, Carlos Enrique

2004-01-20

Terminase enzymes are common to both eukaryotic and prokaryotic double-stranded DNA viruses. These enzymes possess ATPase and nuclease activities that work in concert to "package" a viral genome into an empty procapsid, and it is likely that terminase enzymes from disparate viruses utilize a common packaging mechanism. Bacteriophage lambda terminase possesses a site-specific nuclease activity, a so-called helicase activity, a DNA translocase activity, and multiple ATPase catalytic sites that function to package viral DNA. Allosteric interactions between the multiple catalytic sites have been reported. This study probes these catalytic interactions using enzyme kinetic, photoaffinity labeling, and vanadate inhibition studies. The ensemble of data forms the basis for a minimal kinetic model for lambda terminase. The model incorporates an ADP-driven conformational reorganization of the terminase subunits assembled on viral DNA, which is central to the activation of a catalytically competent packaging machine. The proposed model provides a unifying mechanism for allosteric interaction between the multiple catalytic sites of the holoenzyme and explains much of the kinetic data in the literature. Given that similar packaging mechanisms have been proposed for viruses as dissimilar as lambda and the herpes viruses, the model may find general utility in our global understanding of the enzymology of virus assembly.

Discover the pythagorean theorem using interactive multimedia learning

NASA Astrophysics Data System (ADS)

Adhitama, I.; Sujadi, I.; Pramudya, I.

2018-04-01

In learning process students are required to play an active role in learning. They do not just accept the concept directly from teachers, but also build their own knowledge so that the learning process becomes more meaningful. Based on the observation, when learning Pythagorean theorem, students got difficulty on determining hypotenuse. One of the solution to solve this problem is using an interactive multimedia learning. This article aims to discuss the interactive multimedia as learning media for students. This was a Research and Development (R&D) by using ADDIE model of development. The results obtained was multimedia which was developed proper for students as learning media. Besides, on Phytagorian theorem learning activity we also compare Discovery Learning (DL) model with interactive multimedia and DL without interactive multimedia, and obtained that DL with interactive gave positive effect better than DL without interactive multimedia. It was also obtainde that interactive multimedia can attract and increase the interest ot the students on learning math. Therefore, the use of interactive multimedia on DL procees can improve student learning achievement.

Recognition of human activity characteristics based on state transitions modeling technique

NASA Astrophysics Data System (ADS)

Elangovan, Vinayak; Shirkhodaie, Amir

2012-06-01

Human Activity Discovery & Recognition (HADR) is a complex, diverse and challenging task but yet an active area of ongoing research in the Department of Defense. By detecting, tracking, and characterizing cohesive Human interactional activity patterns, potential threats can be identified which can significantly improve situation awareness, particularly, in Persistent Surveillance Systems (PSS). Understanding the nature of such dynamic activities, inevitably involves interpretation of a collection of spatiotemporally correlated activities with respect to a known context. In this paper, we present a State Transition model for recognizing the characteristics of human activities with a link to a prior contextbased ontology. Modeling the state transitions between successive evidential events determines the activities' temperament. The proposed state transition model poses six categories of state transitions including: Human state transitions of Object handling, Visibility, Entity-entity relation, Human Postures, Human Kinematics and Distance to Target. The proposed state transition model generates semantic annotations describing the human interactional activities via a technique called Casual Event State Inference (CESI). The proposed approach uses a low cost kinect depth camera for indoor and normal optical camera for outdoor monitoring activities. Experimental results are presented here to demonstrate the effectiveness and efficiency of the proposed technique.

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review

PubMed Central

McClelland, James L.

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered. PMID:23970868

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

PubMed

McClelland, James L

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

Creating and Using Interactive, 3D-Printed Models to Improve Student Comprehension of the Bohr Model of the Atom, Bond Polarity, and Hybridization

ERIC Educational Resources Information Center

Smiar, Karen; Mendez, J. D.

2016-01-01

Molecular model kits have been used in chemistry classrooms for decades but have seen very little recent innovation. Using 3D printing, three sets of physical models were created for a first semester, introductory chemistry course. Students manipulated these interactive models during class activities as a supplement to existing teaching tools for…

Interactions of psychosocial factors with built environments in explaining adolescents' active transportation.

PubMed

Wang, Xiaobo; Conway, Terry L; Cain, Kelli L; Frank, Lawrence D; Saelens, Brian E; Geremia, Carrie; Kerr, Jacqueline; Glanz, Karen; Carlson, Jordan A; Sallis, James F

2017-07-01

The present study examined independent and interacting associations of psychosocial and neighborhood built environment variables with adolescents' reported active transportation. Moderating effects of adolescent sex were explored. Mixed-effects regression models were conducted on data from the Teen Environment and Neighborhood observational study (N=928) in the Seattle, WA and Baltimore regions 2009-2011. Frequency index of active transportation to neighborhood destinations (dependent variable) and 7 psychosocial measures were reported by adolescents. Built environment measures included home walkability and count of nearby parks and recreation facilities using GIS procedures and streetscape quality from environmental audits. Results indicated all 3 environmental variables and 3 psychosocial variables (self-efficacy, social support from peers, and enjoyment of physical activity) had significant positive main effects with active transportation (Ps<0.05). Three of 21 two-way interactions were significant in explaining active transportation (Ps<0.1): self-efficacy×GIS-based walkability index, barriers to activity in neighborhood×MAPS streetscape scores, and self-efficacy×GIS-based counts of parks and recreation facilities. In each two-way interaction the highest active transportation was found among adolescents with the combination of activity-supportive built environment and positive psychosocial characteristics. Three-way interactions with sex indicated similar associations for girls and boys, with one exception. Results provided modest support for the ecological model principle of interactions across levels, highlight the importance of both built environment and psychosocial factors in shaping adolescents' active transportation, demonstrated the possibility of sex-specific findings, and suggested strategies for improving adolescents' active transportation may be most effective when targeting multiple levels of influence. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Designing and Evaluating Tutoring Feedback Strategies for Digital Learning Environments on the Basis of the Interactive Tutoring Feedback Model

ERIC Educational Resources Information Center

Narciss, Susanne

2013-01-01

This paper describes the interactive tutoring feedback model (ITF-model; Narciss, 2006; 2008), and how it can be applied to the design and evaluation of feedback strategies for digital learning environments. The ITF-model conceptualizes formative tutoring feedback as a multidimensional instructional activity that aims at contributing to the…

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

PubMed

Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

2017-06-01

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Spatial signals link exit from mitosis to spindle position.

PubMed

Falk, Jill Elaine; Tsuchiya, Dai; Verdaasdonk, Jolien; Lacefield, Soni; Bloom, Kerry; Amon, Angelika

2016-05-11

In budding yeast, if the spindle becomes mispositioned, cells prevent exit from mitosis by inhibiting the mitotic exit network (MEN). The MEN is a signaling cascade that localizes to spindle pole bodies (SPBs) and activates the phosphatase Cdc14. There are two competing models that explain MEN regulation by spindle position. In the 'zone model', exit from mitosis occurs when a MEN-bearing SPB enters the bud. The 'cMT-bud neck model' posits that cytoplasmic microtubule (cMT)-bud neck interactions prevent MEN activity. Here we find that 1) eliminating cMT- bud neck interactions does not trigger exit from mitosis and 2) loss of these interactions does not precede Cdc14 activation. Furthermore, using binucleate cells, we show that exit from mitosis occurs when one SPB enters the bud despite the presence of a mispositioned spindle. We conclude that exit from mitosis is triggered by a correctly positioned spindle rather than inhibited by improper spindle position.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from 50 {× } 5 -fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93 . As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger ( AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients ( r) from 50 {× } 5-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity.

PubMed

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from [Formula: see text]-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of [Formula: see text] and [Formula: see text]. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from [Formula: see text] to [Formula: see text] respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Mathematical Model Of Nerve/Muscle Interaction

NASA Technical Reports Server (NTRS)

Hannaford, Blake

1990-01-01

Phasic Excitation/Activation (PEA) mathematical model simulates short-term nonlinear dynamics of activation and control of muscle by nerve. Includes electronic and mechanical elements. Is homeomorphic at level of its three major building blocks, which represent motoneuron, dynamics of activation of muscle, and mechanics of muscle.

Bone sialoprotein does not interact with pro-gelatinase A (MMP-2) or mediate MMP-2 activation

PubMed Central

2009-01-01

Background A recent model for activation of the zymogen form of matrix metalloproteinase 2 (MMP-2, also known as gelatinase A) has suggested that interactions between the SIBLING protein bone sialoprotein (BSP) and MMP-2 leads to conformational change in MMP-2 that initiates the conversion of the pro-enzyme into a catalytically active form. This model is particularly relevant to cancer cell metastasis to bone since BSP, bound to the αvβ3 integrin through its arginine-glycine-aspartic acid motif, could recruit MMP-2 to the cell surface. Methods We critically assessed the relationship between BSP and proMMP-2 and its activation using various forms of recombinant and purified BSP and MMP-2. Gelatinase and collagenase assays, fluorescence binding assays, real-time PCR, cell culture and pull-down assays were employed to test the model. Results Studies with a fluorogenic substrate for MMP-2 showed no activation of proMMP-2 by BSP. Binding and pull-down assays demonstrated no interaction between MMP-2 and BSP. While BSP-mediated invasiveness has been shown to depend on its integrin-binding RGD sequence, analysis of proMMP-2 activation and the level of membrane type 1 (MT1)-MMP in cells grown on a BSP substratum showed that the BSP-αvβ3 integrin interaction does not induce the expression of MT1-MMP. Conclusion These studies do not support a role for BSP in promoting metastasis through interactions with pro-MMP-2. PMID:19386107

Using Virtual Pets to Promote Physical Activity in Children: An Application of the Youth Physical Activity Promotion Model.

PubMed

Ahn, Sun Joo Grace; Johnsen, Kyle; Robertson, Tom; Moore, James; Brown, Scott; Marable, Amanda; Basu, Aryabrata

2015-01-01

A virtual pet was developed based on the framework of the youth physical activity promotion model and tested as a vehicle for promoting physical activity in children. Children in the treatment group interacted with the virtual pet for three days, setting physical activity goals and teaching tricks to the virtual pet when their goals were met. The virtual pet became more fit and learned more sophisticated tricks as the children achieved activity goals. Children in the control group interacted with a computer system presenting equivalent features but without the virtual pet. Physical activity and goal attainment were evaluated using activity monitors. Results indicated that children in the treatment group engaged in 1.09 more hours of daily physical activity (156% more) than did those in the control group. Physical activity self-efficacy and beliefs served as mediators driving this increase in activity. Children that interacted with the virtual pet also expressed higher intentions than children in the control group to continue physical activity in the future. Theoretical and practical potentials of using a virtual pet to systematically promote physical activity in children are discussed.

On the contributions of diffusion and thermal activation to electron transfer between Phormidium laminosum plastocyanin and cytochrome f: Brownian dynamics simulations with explicit modeling of nonpolar desolvation interactions and electron transfer events.

PubMed

Gabdoulline, Razif R; Wade, Rebecca C

2009-07-08

The factors that determine the extent to which diffusion and thermal activation processes govern electron transfer (ET) between proteins are debated. The process of ET between plastocyanin (PC) and cytochrome f (CytF) from the cyanobacterium Phormidium laminosum was initially thought to be diffusion-controlled but later was found to be under activation control (Schlarb-Ridley, B. G.; et al. Biochemistry 2005, 44, 6232). Here we describe Brownian dynamics simulations of the diffusional association of PC and CytF, from which ET rates were computed using a detailed model of ET events that was applied to all of the generated protein configurations. The proteins were modeled as rigid bodies represented in atomic detail. In addition to electrostatic forces, which were modeled as in our previous simulations of protein-protein association, the proteins interacted by a nonpolar desolvation (hydrophobic) force whose derivation is described here. The simulations yielded close to realistic residence times of transient protein-protein encounter complexes of up to tens of microseconds. The activation barrier for individual ET events derived from the simulations was positive. Whereas the electrostatic interactions between P. laminosum PC and CytF are weak, simulations for a second cyanobacterial PC-CytF pair, that from Nostoc sp. PCC 7119, revealed ET rates influenced by stronger electrostatic interactions. In both cases, the simulations imply significant contributions to ET from both diffusion and thermal activation processes.

Different responses of influenza epidemic to weather factors among Shanghai, Hong Kong, and British Columbia.

PubMed

Wang, Xi-Ling; Yang, Lin; He, Dai-Hai; Chiu, Alice Py; Chan, Kwok-Hung; Chan, King-Pan; Zhou, Maigeng; Wong, Chit-Ming; Guo, Qing; Hu, Wenbiao

2017-06-01

Weather factors have long been considered as key sources for regional heterogeneity of influenza seasonal patterns. As influenza peaks coincide with both high and low temperature in subtropical cities, weather factors may nonlinearly or interactively affect influenza activity. This study aims to assess the nonlinear and interactive effects of weather factors with influenza activity and compare the responses of influenza epidemic to weather factors in two subtropical regions of southern China (Shanghai and Hong Kong) and one temperate province of Canada (British Columbia). Weekly data on influenza activity and weather factors (i.e., mean temperature and relative humidity (RH)) were obtained from pertinent government departments for the three regions. Absolute humidity (AH) was measured by vapor pressure (VP), which could be converted from temperature and RH. Generalized additive models were used to assess the exposure-response relationship between weather factors and influenza virus activity. Interactions of weather factors were further assessed by bivariate response models and stratification analyses. The exposure-response curves of temperature and VP, but not RH, were consistent among three regions/cities. Bivariate response model revealed a significant interactive effect between temperature (or VP) and RH (P < 0.05). Influenza peaked at low temperature or high temperature with high RH. Temperature and VP are important weather factors in developing a universal model to explain seasonal outbreaks of influenza. However, further research is needed to assess the association between weather factors and influenza activity in a wider context of social and environmental conditions.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

NASA Astrophysics Data System (ADS)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

Agent based models for wealth distribution with preference in interaction

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Sen, Parongama

2014-12-01

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

NASA Astrophysics Data System (ADS)

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-09-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics.

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

PubMed Central

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-01-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics. PMID:27671239

The Cool and Belkin Faceted Classification of Information Interactions Revisited

ERIC Educational Resources Information Center

Huvila, Isto

2010-01-01

Introduction: The complexity of human information activity is a challenge for both practice and research in information sciences and information management. Literature presents a wealth of approaches to analytically structure and make sense of human information activity including a faceted classification model of information interactions published…

The Interaction-Activity Connection

NASA Technical Reports Server (NTRS)

Borne, Kirk D.

1996-01-01

A review is presented of the numerous studies that have been undertaken to investigate the likely interaction-activity connection among galaxies. Both observational evidence and theoretical supporting models are reviewed. Some specific examples of "interactive" galaxies from the author's own research are presented: (a) the collision-induced AGN (Active Galactic Nuclei) activity in the radio jet source 3C278; and (b) the collision-induced starburst activity in the spectacular "Cartwheel" ring galaxy. Some comments are offered concerning some of the more promising theoretical investigations that are now taking place. A few words of warning are also offered about the possible misinterpretation of putative collision-induced morphologies among some galaxy samples.

Complex networks generated by the Penna bit-string model: Emergence of small-world and assortative mixing

NASA Astrophysics Data System (ADS)

Li, Chunguang; Maini, Philip K.

2005-10-01

The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.

Chemical-controlled Activation of Antiviral Myxovirus Resistance Protein 1.

PubMed

Verhelst, Judith; Van Hoecke, Lien; Spitaels, Jan; De Vlieger, Dorien; Kolpe, Annasaheb; Saelens, Xavier

2017-02-10

The antiviral myxovirus resistance protein 1 (MX1) is an interferon-induced GTPase that plays an important role in the defense of mammalian cells against influenza A viruses. Mouse MX1 interacts with the influenza ribonucleoprotein complexes (vRNPs) and can prevent the interaction between polymerase basic 2 (PB2) and the nucleoprotein (NP) of influenza A viruses. However, it is unclear whether mouse MX1 disrupts the PB2-NP interaction in the context of pre-existing vRNPs or prevents the assembly of new vRNP components. Here, we describe a conditionally active mouse MX1 variant that only exerts antiviral activity in the presence of a small molecule drug. Once activated, this MX1 construct phenocopies the antiviral and NP binding activity of wild type MX1. The interaction between PB2 and NP is disrupted within minutes after the addition of the small molecule activator. These findings support a model in which mouse MX1 interacts with the incoming influenza A vRNPs and inhibits their activity by disrupting the PB2-NP interaction. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Chemical-controlled Activation of Antiviral Myxovirus Resistance Protein 1*

PubMed Central

Verhelst, Judith; Van Hoecke, Lien; Spitaels, Jan; De Vlieger, Dorien; Kolpe, Annasaheb

2017-01-01

The antiviral myxovirus resistance protein 1 (MX1) is an interferon-induced GTPase that plays an important role in the defense of mammalian cells against influenza A viruses. Mouse MX1 interacts with the influenza ribonucleoprotein complexes (vRNPs) and can prevent the interaction between polymerase basic 2 (PB2) and the nucleoprotein (NP) of influenza A viruses. However, it is unclear whether mouse MX1 disrupts the PB2-NP interaction in the context of pre-existing vRNPs or prevents the assembly of new vRNP components. Here, we describe a conditionally active mouse MX1 variant that only exerts antiviral activity in the presence of a small molecule drug. Once activated, this MX1 construct phenocopies the antiviral and NP binding activity of wild type MX1. The interaction between PB2 and NP is disrupted within minutes after the addition of the small molecule activator. These findings support a model in which mouse MX1 interacts with the incoming influenza A vRNPs and inhibits their activity by disrupting the PB2-NP interaction. PMID:28011636

Design strategies and functionality of the Visual Interface for Virtual Interaction Development (VIVID) tool

NASA Technical Reports Server (NTRS)

Nguyen, Lac; Kenney, Patrick J.

1993-01-01

Development of interactive virtual environments (VE) has typically consisted of three primary activities: model (object) development, model relationship tree development, and environment behavior definition and coding. The model and relationship tree development activities are accomplished with a variety of well-established graphic library (GL) based programs - most utilizing graphical user interfaces (GUI) with point-and-click interactions. Because of this GUI format, little programming expertise on the part of the developer is necessary to create the 3D graphical models or to establish interrelationships between the models. However, the third VE development activity, environment behavior definition and coding, has generally required the greatest amount of time and programmer expertise. Behaviors, characteristics, and interactions between objects and the user within a VE must be defined via command line C coding prior to rendering the environment scenes. In an effort to simplify this environment behavior definition phase for non-programmers, and to provide easy access to model and tree tools, a graphical interface and development tool has been created. The principal thrust of this research is to effect rapid development and prototyping of virtual environments. This presentation will discuss the 'Visual Interface for Virtual Interaction Development' (VIVID) tool; an X-Windows based system employing drop-down menus for user selection of program access, models, and trees, behavior editing, and code generation. Examples of these selection will be highlighted in this presentation, as will the currently available program interfaces. The functionality of this tool allows non-programming users access to all facets of VE development while providing experienced programmers with a collection of pre-coded behaviors. In conjunction with its existing, interfaces and predefined suite of behaviors, future development plans for VIVID will be described. These include incorporation of dual user virtual environment enhancements, tool expansion, and additional behaviors.

Active control of turbomachine discrete tones

NASA Technical Reports Server (NTRS)

Fleeter, Sanford

1994-01-01

This paper was directed at active control of discrete frequency noise generated by subsonic blade rows through cancellation of the blade row interaction generated propagating acoustic waves. First discrete frequency noise generated by a rotor and stator in a duct was analyzed to determine the propagating acoustic pressure waves. Then a mathematical model was developed to analyze and predict the active control of discrete frequency noise generated by subsonic blade rows through cancellation of the propagating acoustic waves, accomplished by utilizing oscillating airfoil surfaces to generate additional control propagating pressure waves. These control waves interact with the propagating acoustic waves, thereby, in principle, canceling the acoustic waves and thus, the far field discrete frequency tones. This model was then applied to a fan exit guide vane to investigate active airfoil surface techniques for control of the propagating acoustic waves, and thus the far field discrete frequency tones, generated by blade row interactions.

Active control of turbomachine discrete tones

NASA Astrophysics Data System (ADS)

Fleeter, Sanford

This paper was directed at active control of discrete frequency noise generated by subsonic blade rows through cancellation of the blade row interaction generated propagating acoustic waves. First discrete frequency noise generated by a rotor and stator in a duct was analyzed to determine the propagating acoustic pressure waves. Then a mathematical model was developed to analyze and predict the active control of discrete frequency noise generated by subsonic blade rows through cancellation of the propagating acoustic waves, accomplished by utilizing oscillating airfoil surfaces to generate additional control propagating pressure waves. These control waves interact with the propagating acoustic waves, thereby, in principle, canceling the acoustic waves and thus, the far field discrete frequency tones. This model was then applied to a fan exit guide vane to investigate active airfoil surface techniques for control of the propagating acoustic waves, and thus the far field discrete frequency tones, generated by blade row interactions.

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

Dmitriev, Alexander S.; Yemelyanov, Ruslan Yu.; Moscow Institute of Physics and Technology

The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.

Hospital's activity-based financing system and manager-physician [corrected] interaction.

PubMed

Crainich, David; Leleu, Hervé; Mauleon, Ana

2011-10-01

This paper examines the consequences of the introduction of an activity-based reimbursement system on the behavior of physicians and hospital's managers. We consider a private for-profit sector where both hospitals and physicians are initially paid on a fee-for-service basis. We show that the benefit of the introduction of an activity-based system depends on the type of interaction between managers and physicians (simultaneous or sequential decision-making games). It is shown that, under the activity-based system, a sequential interaction with physician leader could be beneficial for both agents in the private sector. We further model an endogenous timing game à la Hamilton and Slutsky (Games Econ Behav 2: 29-46, 1990) in which the type of interaction is determined endogenously. We show that, under the activity-based system, the sequential interaction with physician leader is the unique subgame perfect equilibrium.

[Effects of functional interactions between nonhomologous insulators Wari and Su(Hw)].

PubMed

Erokhin, M M; Georgiev, P G; Chetverina, D A

2010-01-01

Insulators are regulatory DNA elements restricting gene activation by enhancers. Interactions between insulators can lead to both insulation and activation of promoters by enhancers. In this work, we analyzed the effects of interaction of two Drosophila insulators, Wari and Su(Hw). The functional interaction between these insulators was found to enhance the activity of the Su(Hw) insulator only, but not of the Wari insulator. This suggests that the formation of a chromatin loop between interacting insulators is not a key factor for enhancement of insulation, which is in disagreement with the main idea of structural models. In addition, the effect of interaction between Wari and Su(Hw) depends on a distance between them and on the position in the system relative to other regulatory elements.

Simulating an emergency department: the importance of modeling the interactions between physicians and delegates in a discrete event simulation.

PubMed

Lim, Morgan E; Worster, Andrew; Goeree, Ron; Tarride, Jean-Éric

2013-05-22

Computer simulation studies of the emergency department (ED) are often patient driven and consider the physician as a human resource whose primary activity is interacting directly with the patient. In many EDs, physicians supervise delegates such as residents, physician assistants and nurse practitioners each with different skill sets and levels of independence. The purpose of this study is to present an alternative approach where physicians and their delegates in the ED are modeled as interacting pseudo-agents in a discrete event simulation (DES) and to compare it with the traditional approach ignoring such interactions. The new approach models a hierarchy of heterogeneous interacting pseudo-agents in a DES, where pseudo-agents are entities with embedded decision logic. The pseudo-agents represent a physician and delegate, where the physician plays a senior role to the delegate (i.e. treats high acuity patients and acts as a consult for the delegate). A simple model without the complexity of the ED is first created in order to validate the building blocks (programming) used to create the pseudo-agents and their interaction (i.e. consultation). Following validation, the new approach is implemented in an ED model using data from an Ontario hospital. Outputs from this model are compared with outputs from the ED model without the interacting pseudo-agents. They are compared based on physician and delegate utilization, patient waiting time for treatment, and average length of stay. Additionally, we conduct sensitivity analyses on key parameters in the model. In the hospital ED model, comparisons between the approach with interaction and without showed physician utilization increase from 23% to 41% and delegate utilization increase from 56% to 71%. Results show statistically significant mean time differences for low acuity patients between models. Interaction time between physician and delegate results in increased ED length of stay and longer waits for beds. This example shows the importance of accurately modeling physician relationships and the roles in which they treat patients. Neglecting these relationships could lead to inefficient resource allocation due to inaccurate estimates of physician and delegate time spent on patient related activities and length of stay.

Towards a Reconceptualization of Striatal Interactions Between Glutamatergic and Dopaminergic Neurotransmission and Their Contribution to the Production of Movements

PubMed Central

David, Hélène N

2009-01-01

According to the current model of the basal ganglia organization, simultaneous activation of the striato-nigral direct pathway by glutamatergic and dopaminergic neurotransmission should lead to a synergistic facilitatory action on locomotor activity, while in contrast activation of the indirect pathway by these two neurotransmittions should lead to antagonistic effects on locomotor activity. Based on published data, as a break with the current thinking, we propose a reconceptualization of functional interactions between dopaminergic and glutamatergic neurotransmission. In this model, dopaminergic neurotransmission is seen as a motor pacemaker responsible for the basal and primary activation of striatal output neurons and glutamate as a driver providing a multiple combination of tonic, phasic, facilitatory and inhibitory influxes resulting from the processing of environmental, emotional and mnesic stimuli. Thus, in the model, glutamate-coded inputs would allow tuning the intrinsic motor-activating properties of dopamine to adjust the production of locomotor activity into goal-oriented movements. PMID:19949572

Quantitative structure activity relationship studies of mushroom tyrosinase inhibitors

NASA Astrophysics Data System (ADS)

Xue, Chao-Bin; Luo, Wan-Chun; Ding, Qi; Liu, Shou-Zhu; Gao, Xing-Xiang

2008-05-01

Here, we report our results from quantitative structure-activity relationship studies on tyrosinase inhibitors. Interactions between benzoic acid derivatives and tyrosinase active sites were also studied using a molecular docking method. These studies indicated that one possible mechanism for the interaction between benzoic acid derivatives and the tyrosinase active site is the formation of a hydrogen-bond between the hydroxyl (aOH) and carbonyl oxygen atoms of Tyr98, which stabilized the position of Tyr98 and prevented Tyr98 from participating in the interaction between tyrosinase and ORF378. Tyrosinase, also known as phenoloxidase, is a key enzyme in animals, plants and insects that is responsible for catalyzing the hydroxylation of tyrosine into o-diphenols and the oxidation of o-diphenols into o-quinones. In the present study, the bioactivities of 48 derivatives of benzaldehyde, benzoic acid, and cinnamic acid compounds were used to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models using comparative molecular field (CoMFA) and comparative molecular similarity indices (CoMSIA) analyses. After superimposition using common substructure-based alignments, robust and predictive 3D-QSAR models were obtained from CoMFA ( q 2 = 0.855, r 2 = 0.978) and CoMSIA ( q 2 = 0.841, r 2 = 0.946), with 6 optimum components. Chemical descriptors, including electronic (Hammett σ), hydrophobic (π), and steric (MR) parameters, hydrogen bond acceptor (H-acc), and indicator variable ( I), were used to construct a 2D-QSAR model. The results of this QSAR indicated that π, MR, and H-acc account for 34.9, 31.6, and 26.7% of the calculated biological variance, respectively. The molecular interactions between ligand and target were studied using a flexible docking method (FlexX). The best scored candidates were docked flexibly, and the interaction between the benzoic acid derivatives and the tyrosinase active site was elucidated in detail. We believe that the QSAR models built here provide important information necessary for the design of novel tyrosinase inhibitors.

Homology modeling, active site prediction, and targeting the anti hypertension activity through molecular docking on endothelin – B receptor domain

PubMed Central

Rayalu, Daddam Jayasimha; Selvaraj, Chandrabose; Singh, Sanjeev Kumar; Ganeshan, Ramakrishan; Kumar, Nagapatla Udaya; Seshapani, Panthangi

2012-01-01

In cardiovascular system, activation of Endothelin receptors causes vasoconstriction which leads to Pulmonary Arterial Hypertension (PAH). Endothelin receptor antagonism has emerged as an important therapeutic strategy in pulmonary arterial hypertension. Bosentan is intended to affect vasoconstriction, hypertrophic and fibrotic effects by blocking the actions of receptors ETA and ETB. In this study we identified the action of Bosentan on endothelin B receptor using docking studies with homology modeled endothelin B receptor. Through the modeled protein, the flexible Docking study was performed with Bosentan and its derivatives with theoretically predicted active sites. The results indicated that amino acid ARG82, ARG84 and HIS197 present in endothelin B receptor are core important for binding activities and these residues are having strong hydrogen bond interactions with Bosentan. We have investigated the Bosentan and its derivatives interactions and scoring parameters using gold docking package. Among the docked compounds, one of the Bosentan derivatives BD6 shows better interaction than Bosentan with endothelin B receptor. Our results may be helpful for further investigations in both in vivo and in vitro conditions. PMID:22359440

Musculoskeletal Modeling of the Lumbar Spine to Explore Functional Interactions between Back Muscle Loads and Intervertebral Disk Multiphysics

PubMed Central

Toumanidou, Themis; Noailly, Jérôme

2015-01-01

During daily activities, complex biomechanical interactions influence the biophysical regulation of intervertebral disks (IVDs), and transfers of mechanical loads are largely controlled by the stabilizing action of spine muscles. Muscle and other internal forces cannot be easily measured directly in the lumbar spine. Hence, biomechanical models are important tools for the evaluation of the loads in those tissues involved in low-back disorders. Muscle force estimations in most musculoskeletal models mainly rely, however, on inverse calculations and static optimizations that limit the predictive power of the numerical calculations. In order to contribute to the development of predictive systems, we coupled a predictive muscle model with the passive resistance of the spine tissues, in a L3–S1 musculoskeletal finite element model with osmo-poromechanical IVD descriptions. The model included 46 fascicles of the major back muscles that act on the lower spine. The muscle model interacted with activity-related loads imposed to the osteoligamentous structure, as standing position and night rest were simulated through distributed upper body mass and free IVD swelling, respectively. Calculations led to intradiscal pressure values within ranges of values measured in vivo. Disk swelling led to muscle activation and muscle force distributions that seemed particularly appropriate to counterbalance the anterior body mass effect in standing. Our simulations pointed out a likely existence of a functional balance between stretch-induced muscle activation and IVD multiphysics toward improved mechanical stability of the lumbar spine understanding. This balance suggests that proper night rest contributes to mechanically strengthen the spine during day activity. PMID:26301218

Modelling the structure of a ceRNA-theoretical, bipartite microRNA-mRNA interaction network regulating intestinal epithelial cellular pathways using R programming.

PubMed

Robinson, J M; Henderson, W A

2018-01-12

We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.

Interactive Whole Class Teaching in the National Literacy and Numeracy Strategies

ERIC Educational Resources Information Center

Smith, Fay; Hardman, Frank; Wall, Kate; Mroz, Maria

2004-01-01

The study set out to investigate the impact of the official endorsement of 'interactive whole class teaching' on the interaction and discourse styles of primary teachers while teaching the National Literacy and Numeracy Strategies. In both strategies, interactive whole class teaching is seen as an 'active teaching' model promoting high quality…

DFT study of ethyl xanthate interaction with sphalerite (1 1 0) surface in the absence and presence of copper

NASA Astrophysics Data System (ADS)

Liu, Jian; Wen, Shuming; Deng, Jiushuai; Chen, Xiumin; Feng, Qicheng

2014-08-01

The interaction among sphalerite (1 1 0) surface, copper and ethyl xanthate (EX) was simulated using the density functional theory (DFT). The results of DFT indicate that four types of stable interaction models exist among sphalerite surface, copper and EX, i.e., EX interacts with the Cu substituted for Zn, Cu adsorbed on the top site of S, Cu adsorbed on the bridge site of S and Cu(OH)2 adsorbed on the sphalerite surface. The four interaction models can result in the activation flotation of sphalerite. Density of states (DOS) analysis shows that the energy level discrepancy of the Zn 3d orbital in ZnS and the bonding S 3p orbital in EX results in the weak adsorption of EX on un-activated sphalerite surface. However, after copper activation, the Cu 3d orbital peak and bonding S 3p orbital peak are just maximally overlapped nearby the Fermi level. This study provides an insight into the nature that sphalerite responds not well to EX and also a comprehensive understanding on the possible interaction cases existing among sphalerite surface, copper and EX.

Intramolecular hydrophobic interactions are critical mediators of STAT5 dimerization

NASA Astrophysics Data System (ADS)

Fahrenkamp, Dirk; Li, Jinyu; Ernst, Sabrina; Schmitz-van de Leur, Hildegard; Chatain, Nicolas; Küster, Andrea; Koschmieder, Steffen; Lüscher, Bernhard; Rossetti, Giulia; Müller-Newen, Gerhard

2016-10-01

STAT5 is an essential transcription factor in hematopoiesis, which is activated through tyrosine phosphorylation in response to cytokine stimulation. Constitutive activation of STAT5 is a hallmark of myeloid and lymphoblastic leukemia. Using homology modeling and molecular dynamics simulations, a model of the STAT5 phosphotyrosine-SH2 domain interface was generated providing first structural information on the activated STAT5 dimer including a sequence, for which no structural information is available for any of the STAT proteins. We identified a novel intramolecular interaction mediated through F706, adjacent to the phosphotyrosine motif, and a unique hydrophobic interface on the surface of the SH2 domain. Analysis of corresponding STAT5 mutants revealed that this interaction is dispensable for Epo receptor-mediated phosphorylation of STAT5 but essential for dimer formation and subsequent nuclear accumulation. Moreover, the herein presented model clarifies molecular mechanisms of recently discovered leukemic STAT5 mutants and will help to guide future drug development.

Spatial signals link exit from mitosis to spindle position

PubMed Central

Falk, Jill Elaine; Tsuchiya, Dai; Verdaasdonk, Jolien; Lacefield, Soni; Bloom, Kerry; Amon, Angelika

2016-01-01

In budding yeast, if the spindle becomes mispositioned, cells prevent exit from mitosis by inhibiting the mitotic exit network (MEN). The MEN is a signaling cascade that localizes to spindle pole bodies (SPBs) and activates the phosphatase Cdc14. There are two competing models that explain MEN regulation by spindle position. In the 'zone model', exit from mitosis occurs when a MEN-bearing SPB enters the bud. The 'cMT-bud neck model' posits that cytoplasmic microtubule (cMT)-bud neck interactions prevent MEN activity. Here we find that 1) eliminating cMT– bud neck interactions does not trigger exit from mitosis and 2) loss of these interactions does not precede Cdc14 activation. Furthermore, using binucleate cells, we show that exit from mitosis occurs when one SPB enters the bud despite the presence of a mispositioned spindle. We conclude that exit from mitosis is triggered by a correctly positioned spindle rather than inhibited by improper spindle position. DOI: http://dx.doi.org/10.7554/eLife.14036.001 PMID:27166637

Intramolecular hydrophobic interactions are critical mediators of STAT5 dimerization

PubMed Central

Fahrenkamp, Dirk; Li, Jinyu; Ernst, Sabrina; Schmitz-Van de Leur, Hildegard; Chatain, Nicolas; Küster, Andrea; Koschmieder, Steffen; Lüscher, Bernhard; Rossetti, Giulia; Müller-Newen, Gerhard

2016-01-01

STAT5 is an essential transcription factor in hematopoiesis, which is activated through tyrosine phosphorylation in response to cytokine stimulation. Constitutive activation of STAT5 is a hallmark of myeloid and lymphoblastic leukemia. Using homology modeling and molecular dynamics simulations, a model of the STAT5 phosphotyrosine-SH2 domain interface was generated providing first structural information on the activated STAT5 dimer including a sequence, for which no structural information is available for any of the STAT proteins. We identified a novel intramolecular interaction mediated through F706, adjacent to the phosphotyrosine motif, and a unique hydrophobic interface on the surface of the SH2 domain. Analysis of corresponding STAT5 mutants revealed that this interaction is dispensable for Epo receptor-mediated phosphorylation of STAT5 but essential for dimer formation and subsequent nuclear accumulation. Moreover, the herein presented model clarifies molecular mechanisms of recently discovered leukemic STAT5 mutants and will help to guide future drug development. PMID:27752093

Can "CANISO" Activate "CASINO"? Transposed-Letter Similarity Effects with Nonadjacent Letter Positions

ERIC Educational Resources Information Center

Perea, Manuel; Lupker, Stephen J.

2004-01-01

Nonwords created by transposing two "adjacent" letters (i.e., transposed-letter (TL) nonwords like "jugde") are very effective at activating the lexical representation of their base words. This fact poses problems for most computational models of word recognition (e.g., the interactive-activation model and its extensions), which assume that exact…

The electronic-commerce-oriented virtual merchandise model

NASA Astrophysics Data System (ADS)

Fang, Xiaocui; Lu, Dongming

2004-03-01

Electronic commerce has been the trend of commerce activities. Providing with Virtual Reality interface, electronic commerce has better expressing capacity and interaction means. But most of the applications of virtual reality technology in EC, 3D model is only the appearance description of merchandises. There is almost no information concerned with commerce information and interaction information. This resulted in disjunction of virtual model and commerce information. So we present Electronic Commerce oriented Virtual Merchandise Model (ECVMM), which combined a model with commerce information, interaction information and figure information of virtual merchandise. ECVMM with abundant information provides better support to information obtainment and communication in electronic commerce.

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.

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

Data analysis and interpretation related to space system/environment interactions at LEO altitude

NASA Technical Reports Server (NTRS)

Raitt, W. John; Schunk, Robert W.

1991-01-01

Several studies made on the interaction of active systems with the LEO space environment experienced from orbital or suborbital platforms are covered. The issue of high voltage space interaction is covered by theoretical modeling studies of the interaction of charged solar cell arrays with the ionospheric plasma. The theoretical studies were complemented by experimental measurements made in a vacuum chamber. The other active system studied was the emission of effluent from a space platform. In one study the emission of plasma into the LEO environment was studied by using initially a 2-D model, and then extending this model to 3-D to correctly take account of plasma motion parallel to the geomagnetic field. The other effluent studies related to the releases of neutral gas from an orbiting platform. One model which was extended and used determined the density, velocity, and energy of both an effluent gas and the ambient upper atmospheric gases over a large volume around the platform. This model was adapted to study both ambient and contaminant distributions around smaller objects in the orbital frame of reference with scale sizes of 1 m. The other effluent studies related to the interaction of the released neutral gas with the ambient ionospheric plasma. An electrostatic model was used to help understand anomalously high plasma densities measured at times in the vicinity of the space shuttle orbiter.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

PubMed

Santos, Daniel M V; Katzmarzyk, Peter T; Diego, Vincent P; Souza, Michele C; Chaves, Raquel N; Blangero, John; Maia, José A R

2013-01-01

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.

Edible bioactive fatty acid-cellulosic derivative composites used in food-packaging applications.

PubMed

Sebti, Issam; Ham-Pichavant, Frédérique; Coma, Véronique

2002-07-17

To develop biodegradable packaging that both acts as a moisture barrier and as antimicrobial activity, nisin and stearic acid were incorporated into a hydroxy propyl methyl cellulose (HPMC) based film. Fifteen percent (w/w HPMC) of stearic acid improved film moisture barrier. However, film mechanical resistance and film antimicrobial activity on Listeria monocytogenes and Staphylococcus aureus pathogenic strains were both reduced. This lower film inhibitory activity was due to interactions between nisin and stearic acid. The molecular interaction was modeled, and an equation was developed to calculate the nisin concentration needed to be incorporated into the film matrix to obtain a desired residual antimicrobial activity. Because the molecular interactions were pH dependent, the impact of the pH of the film-forming solution on film inhibitory activity was investigated. Adjusting the pH to 3 totally avoided stearic acid and nisin interaction, inducing a high film inhibitory activity.

An Interactive Simulation System for Modeling Stands, Harvests, and Machines

Treesearch

Jingxin Wang; W. Dale Greene

1999-01-01

A interactive computer simulation program models stands, harvest, and machine factors and evaluates their interatcitons while performing felling, skidding, or fowarding activities. A stand generator allows the user to generate either natural or planted stands. Fellings with chainsaw, drive-to-tree feller-bunchers, or harvesters and extraction with grapple skidders or...

A shared-world conceptual model for integrating space station life sciences telescience operations

NASA Technical Reports Server (NTRS)

Johnson, Vicki; Bosley, John

1988-01-01

Mental models of the Space Station and its ancillary facilities will be employed by users of the Space Station as they draw upon past experiences, perform tasks, and collectively plan for future activities. The operational environment of the Space Station will incorporate telescience, a new set of operational modes. To investigate properties of the operational environment, distributed users, and the mental models they employ to manipulate resources while conducting telescience, an integrating shared-world conceptual model of Space Station telescience is proposed. The model comprises distributed users and resources (active elements); agents who mediate interactions among these elements on the basis of intelligent processing of shared information; and telescience protocols which structure the interactions of agents as they engage in cooperative, responsive interactions on behalf of users and resources distributed in space and time. Examples from the life sciences are used to instantiate and refine the model's principles. Implications for transaction management and autonomy are discussed. Experiments employing the model are described which the authors intend to conduct using the Space Station Life Sciences Telescience Testbed currently under development at Ames Research Center.

The Bilingual Language Interaction Network for Comprehension of Speech*

PubMed Central

Marian, Viorica

2013-01-01

During speech comprehension, bilinguals co-activate both of their languages, resulting in cross-linguistic interaction at various levels of processing. This interaction has important consequences for both the structure of the language system and the mechanisms by which the system processes spoken language. Using computational modeling, we can examine how cross-linguistic interaction affects language processing in a controlled, simulated environment. Here we present a connectionist model of bilingual language processing, the Bilingual Language Interaction Network for Comprehension of Speech (BLINCS), wherein interconnected levels of processing are created using dynamic, self-organizing maps. BLINCS can account for a variety of psycholinguistic phenomena, including cross-linguistic interaction at and across multiple levels of processing, cognate facilitation effects, and audio-visual integration during speech comprehension. The model also provides a way to separate two languages without requiring a global language-identification system. We conclude that BLINCS serves as a promising new model of bilingual spoken language comprehension. PMID:24363602

Comparison of a Conceptual Groundwater Model and Physically Based Groundwater Mode

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; Griffiths, J.; Moore, C.; Woods, R. A.

2017-12-01

Groundwater is a vital resource for human activities including agricultural practice and urban water demand. Hydrologic modelling is an important way to study groundwater recharge, movement and discharge, and its response to both human activity and climate change. To understand the groundwater hydrologic processes nationally in New Zealand, we have developed a conceptually based groundwater flow model, which is fully integrated into a national surface-water model (TopNet), and able to simulate groundwater recharge, movement, and interaction with surface water. To demonstrate the capability of this groundwater model (TopNet-GW), we applied the model to an irrigated area with water shortage and pollution problems in the upper Ruamahanga catchment in Great Wellington Region, New Zealand, and compared its performance with a physically-based groundwater model (MODFLOW). The comparison includes river flow at flow gauging sites, and interaction between groundwater and river. Results showed that the TopNet-GW produced similar flow and groundwater interaction patterns as the MODFLOW model, but took less computation time. This shows the conceptually-based groundwater model has the potential to simulate national groundwater process, and could be used as a surrogate for the more physically based model.

Molecular modeling studies of 1,4-dihydro-4-oxoquinoline ribonucleosides with anti-HSV-1 activity

NASA Astrophysics Data System (ADS)

Yoneda, Julliane Diniz; Albuquerque, Magaly Girão; Leal, Kátia Zaccur; Seidl, Peter Rudolf; de Alencastro, Ricardo Bicca

2011-12-01

Eight human herpes viruses ( e.g., herpes simplex, varicella-zoster, Epstein-Barr, cytomegalovirus, Kaposi's sarcoma) are responsible for several diseases from sub-clinic manifestations to fatal infections, mostly in immunocompromised patients. The major limitations of the currently available antiviral drug therapy are drug resistance, host toxicity, and narrow spectrum of activity. However, some non-nucleoside 1,4-dihydro-4-oxoquinoline derivatives ( e.g., PNU-183792) [4] shows broad spectrum antiviral activity. We have developed molecular modeling studies, including molecular docking and molecular dynamics simulations, based on a model proposed by Liu and co-workers [14] in order to understand the mechanism of action of a 6-chloro substituted 1,4-dihydro-4-oxoquinoline ribonucleoside, synthesized by the synthetic group, which showed anti-HSV-1 activity [9]. The molecular docking simulations confirmed the Liu's model showing that the ligand needs to dislocate template residues from the active site in order to interact with the viral DNA polymerase enzyme, reinforcing that the interaction with the Val823 residue is pivotal for the inhibitory activity of non-nucleoside 1,4-dihydro-4-oxoquinoline derivatives, such as PNU-183792, with the HSV-1. The molecular dynamics simulations showed that the 6-chloro-benzyl group of PNU-183792 maintains its interaction with residues of the HSV-1 DNA polymerase hydrophobic pocket, considered important according to the Liu's model, and also showed that the methyl group bounded to the nitrogen atom from PNU-183792 is probably contributing to a push-pull effect with the carbonyl group.

Physiologically-Based Pharmacokinetic Modeling of Macitentan: Prediction of Drug-Drug Interactions.

PubMed

de Kanter, Ruben; Sidharta, Patricia N; Delahaye, Stéphane; Gnerre, Carmela; Segrestaa, Jerome; Buchmann, Stephan; Kohl, Christopher; Treiber, Alexander

2016-03-01

Macitentan is a novel dual endothelin receptor antagonist for the treatment of pulmonary arterial hypertension (PAH). It is metabolized by cytochrome P450 (CYP) enzymes, mainly CYP3A4, to its active metabolite ACT-132577. A physiological-based pharmacokinetic (PBPK) model was developed by combining observations from clinical studies and physicochemical parameters as well as absorption, distribution, metabolism and excretion parameters determined in vitro. The model predicted the observed pharmacokinetics of macitentan and its active metabolite ACT-132577 after single and multiple dosing. It performed well in recovering the observed effect of the CYP3A4 inhibitors ketoconazole and cyclosporine, and the CYP3A4 inducer rifampicin, as well as in predicting interactions with S-warfarin and sildenafil. The model was robust enough to allow prospective predictions of macitentan-drug combinations not studied, including an alternative dosing regimen of ketoconazole and nine other CYP3A4-interacting drugs. Among these were the HIV drugs ritonavir and saquinavir, which were included because HIV infection is a known risk factor for the development of PAH. This example of the application of PBPK modeling to predict drug-drug interactions was used to support the labeling of macitentan (Opsumit).

Collective motion of active Brownian particles with polar alignment.

PubMed

Martín-Gómez, Aitor; Levis, Demian; Díaz-Guilera, Albert; Pagonabarraga, Ignacio

2018-04-04

We present a comprehensive computational study of the collective behavior emerging from the competition between self-propulsion, excluded volume interactions and velocity-alignment in a two-dimensional model of active particles. We consider an extension of the active brownian particles model where the self-propulsion direction of the particles aligns with the one of their neighbors. We analyze the onset of collective motion (flocking) in a low-density regime (10% surface area) and show that it is mainly controlled by the strength of velocity-alignment interactions: the competition between self-propulsion and crowding effects plays a minor role in the emergence of flocking. However, above the flocking threshold, the system presents a richer pattern formation scenario than analogous models without alignment interactions (active brownian particles) or excluded volume effects (Vicsek-like models). Depending on the parameter regime, the structure of the system is characterized by either a broad distribution of finite-sized polar clusters or the presence of an amorphous, highly fluctuating, large-scale traveling structure which can take a lane-like or band-like form (and usually a hybrid structure which is halfway in between both). We establish a phase diagram that summarizes collective behavior of polar active brownian particles and propose a generic mechanism to describe the complexity of the large-scale structures observed in systems of repulsive self-propelled particles.

Infant Smiling during Social Interaction: Arousal Modulation or Activation Indicator?

ERIC Educational Resources Information Center

Ewy, Richard

In a study of infant smiling, 20 mother-infant dyads were videotaped in normal face-to-face interaction when the infants were 9 and 14 weeks of age. Videotapes were used to determine which of two classes of smiling behavior models, either arousal modulation or activation indicator, was most supported by empirical data. Arousal modulation models…

Investigating the Effectiveness of an Active Learning Based-Interactive Conceptual Instruction (ALBICI) on Electric Field Concept

ERIC Educational Resources Information Center

Samsudin, Achmad; Suhandi, Andi; Rusdiana, Dadi; Kaniawati, Ida; Costu, Bayram

2016-01-01

The aim of this study was to develop an Active Learning Based-Interactive Conceptual Instruction (ALBICI) model through PDEODE*E tasks (stands for Predict, Discuss, Explain, Observe, Discuss, Explore, and Explain) for promoting conceptual change and investigating its effectiveness of pre-service physics teachers' understanding on electric field…

Physical activity moderates the association between nicotine dependence and depression among U.S. smokers.

PubMed

Loprinzi, Paul D; Walker, Jerome F; Kane, Christy; Cardinal, Bradley J

2014-01-01

Research demonstrates that nicotine dependence and depression are associated and that physical activity is effective in reducing depression symptoms. However, our understanding of the potential beneficial effects of physical activity on depression in current smokers is more limited. The purpose of this study was to examine whether physical activity moderates the association between nicotine dependence and depression in U.S. smokers. Cross-sectional. National Health and Nutrition Examination Survey 2005-2006. Four hundred forty-one current adult smokers. Participants wore an accelerometer for at least 4 days and completed questionnaires to assess nicotine dependence and depression. Effect modification and statistical interaction models were used. Both models were significant. With regard to the statistical interaction model, and after controlling for age, gender, race/ethnicity, education, comorbidity index, homocysteine, cotinine, total cholesterol, sedentary behavior, and vitamins C, D, and E, objectively measured physical activity moderated the association between nicotine dependence and depression (interaction variable: odds ratio = 3.43; 95% confidence interval: 1.02-11.51; p = .04). In this national sample of current smokers, physical activity moderated the association between nicotine dependence and depression. These results suggest that those individuals with nicotine dependence and who are less physically active are more likely to be depressed than what would be expected on the basis of the individual effects of nicotine and physical inactivity separately.

Cytoskeletal dynamics in fission yeast: a review of models for polarization and division

PubMed Central

Drake, Tyler; Vavylonis, Dimitrios

2010-01-01

We review modeling studies concerning cytoskeletal activity of fission yeast. Recent models vary in length and time scales, describing a range of phenomena from cellular morphogenesis to polymer assembly. The components of cytoskeleton act in concert to mediate cell-scale events and interactions such as polarization. The mathematical models reduce these events and interactions to their essential ingredients, describing the cytoskeleton by its bulk properties. On a smaller scale, models describe cytoskeletal subcomponents and how bulk properties emerge. PMID:21119765

SPARC's Stratospheric Sulfur and its Role in Climate Activity (SSiRC)

NASA Technical Reports Server (NTRS)

Thomason, Larry

2015-01-01

The stratospheric aerosol layer is a key component in the climate system. It affects the radiative balance of the atmosphere directly through interactions with solar and terrestrial radiation, and indirectly through its effect on stratospheric ozone. Because the stratospheric aerosol layer is prescribed in many climate models and Chemistry-Climate Models (CCMs), model simulations of future atmospheric conditions and climate generally do not account for the interaction between the aerosol-sulfur cycle and changes in the climate system. The present understanding of how the stratospheric aerosol layer may be affected by future climate change and how the stratospheric aerosol layer may drive climate change is, therefore, very limited. The purposes of SSiRC (Stratospheric Sulfur and its Role in Climate) include: (i) providing a coordinating structure for the various individual activities already underway in different research centers; (ii) encouraging and supporting new instrumentation and measurements of sulfur containing compounds, such as COS, DMS, and non-volcanic SO2 in the UT/LS globally; and (iii) initiating new model/data inter-comparisons. SSiRC is developing collaborations with a number of other SPARC activities including CCMI and ACAM. This presentation will highlight the scientific goals of this project and on-going activities and propose potential interactions between SSiRC and ACAM.

Molecular modeling and analysis of human and plant endo-β-N-acetyl- glucosaminidases for mutations effects on function

PubMed Central

Choragudi, Shechinah Felice; Veeramachaneni, Ganesh Kumar; Raman, BV; JS, Bondili

2014-01-01

Endo- β-N-acetylgucosaminidases (ENGases) are the enzymes that catalyze both hydrolysis and transglycosylation reactions. It is of interest to study ENGases because of their ability to synthesize glycopeptides. Homology models of Human, Arabidopsis thaliana and Sorghum ENGases were developed and their active sites marked based on information available from Arthrobacter protophormiae (PDB ID: 3FHQ) ENGase. Further, these models were docked with the natural substrate GlcNAc-Asn and the inhibitor Man3GlcNAc-thiazoline. The catalytic triad of Asn, Glu and Tyr (N171, E173 and Y205 of bacteria) were found to be conserved across the phyla. The crucial Y299F mutation showing 3 times higher transglycosylation activity than in wild type Endo-A is known. The hydrolytic activity remained unchanged in bacteria, while the transglycosylation activity increased. This Y to F change is found to be naturally evolved and should be attributing higher transglycosylation rates in human and Arabidopsis thaliana ENGases. Ligand interactions Ligplots revealed the interaction of amino acids with hydrophobic side chains and polar uncharged side chain amino acids. Thus, structure based molecular model-ligand interactions provide insights into the catalytic mechanism of ENGases and assist in the rational engineering of ENGases. PMID:25258486

Molecular modeling and analysis of human and plant endo-β-N-acetyl- glucosaminidases for mutations effects on function.

PubMed

Choragudi, Shechinah Felice; Veeramachaneni, Ganesh Kumar; Raman, Bv; Js, Bondili

2014-01-01

Endo- β-N-acetylgucosaminidases (ENGases) are the enzymes that catalyze both hydrolysis and transglycosylation reactions. It is of interest to study ENGases because of their ability to synthesize glycopeptides. Homology models of Human, Arabidopsis thaliana and Sorghum ENGases were developed and their active sites marked based on information available from Arthrobacter protophormiae (PDB ID: 3FHQ) ENGase. Further, these models were docked with the natural substrate GlcNAc-Asn and the inhibitor Man3GlcNAc-thiazoline. The catalytic triad of Asn, Glu and Tyr (N171, E173 and Y205 of bacteria) were found to be conserved across the phyla. The crucial Y299F mutation showing 3 times higher transglycosylation activity than in wild type Endo-A is known. The hydrolytic activity remained unchanged in bacteria, while the transglycosylation activity increased. This Y to F change is found to be naturally evolved and should be attributing higher transglycosylation rates in human and Arabidopsis thaliana ENGases. Ligand interactions Ligplots revealed the interaction of amino acids with hydrophobic side chains and polar uncharged side chain amino acids. Thus, structure based molecular model-ligand interactions provide insights into the catalytic mechanism of ENGases and assist in the rational engineering of ENGases.

Cyberpsychology: a human-interaction perspective based on cognitive modeling.

PubMed

Emond, Bruno; West, Robert L

2003-10-01

This paper argues for the relevance of cognitive modeling and cognitive architectures to cyberpsychology. From a human-computer interaction point of view, cognitive modeling can have benefits both for theory and model building, and for the design and evaluation of sociotechnical systems usability. Cognitive modeling research applied to human-computer interaction has two complimentary objectives: (1) to develop theories and computational models of human interactive behavior with information and collaborative technologies, and (2) to use the computational models as building blocks for the design, implementation, and evaluation of interactive technologies. From the perspective of building theories and models, cognitive modeling offers the possibility to anchor cyberpsychology theories and models into cognitive architectures. From the perspective of the design and evaluation of socio-technical systems, cognitive models can provide the basis for simulated users, which can play an important role in usability testing. As an example of application of cognitive modeling to technology design, the paper presents a simulation of interactive behavior with five different adaptive menu algorithms: random, fixed, stacked, frequency based, and activation based. Results of the simulation indicate that fixed menu positions seem to offer the best support for classification like tasks such as filing e-mails. This research is part of the Human-Computer Interaction, and the Broadband Visual Communication research programs at the National Research Council of Canada, in collaboration with the Carleton Cognitive Modeling Lab at Carleton University.

Effects of high-frequency activity on latent heat flux of MJO

NASA Astrophysics Data System (ADS)

Gao, Yingxia; Hsu, Pang-Chi; Li, Tim

2018-04-01

The effect of high-frequency (HF) variability on latent heat flux (LHF) associated with the Madden-Julian Oscillation (MJO) during the boreal winter is investigated through diagnosis using two reanalysis datasets and numerical experiments of an atmospheric general circulation model (AGCM). The diagnostic results show that the HF activities exert an impact on the variability of MJO LHF mainly through their interactions with the longer than 90-day low-frequency background state (LFBS). The contribution of intraseasonal LHF induced by the interactions between LFBS and HF activities accounts for more than 20% of the total intraseasonal LHF over active MJO regions. The intraseasonal LHF induced by the LFBS-HF interaction is in phase with the MJO convection, while the total intraseasonal LHF appears at and to the west of the MJO convection center. This suggests that the intraseasonal LHF via the feedback of HF activity interacting with LFBS is conducive to the maintenance and eastward propagation of MJO convection. To confirm the role of HF disturbances in MJO convection activity, we carry out a series of experiments using the AGCM of ECHAM4, which captures well the general features of MJO. We select a number of MJO cases with enhanced convective signals and significant eastward propagation from a 30-year climatological simulation. Once the HF components of surface wind and moisture fields in LHF are excluded in model integration for each MJO case, most of the simulated MJO convection shows weakened activity and a slower propagation speed compared to the simulations containing all time-scale components. The outputs of these sensitivity experiments support the diagnostic results that HF activities contribute to the maintenance and propagation of MJO convection through the intraseasonal LHF induced by the scale interaction of HF activities with lower frequency variability.

Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis.

PubMed

Veinot, Tiffany C; Senteio, Charles R; Hanauer, David; Lowery, Julie C

2018-06-01

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research. We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research. The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process. The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations. The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.

To Build a Brain

ERIC Educational Resources Information Center

Miller, Julie Ann

1977-01-01

Describes use of electronic model to simulate electrical patterns resulting from nerve cell interactions in the brain. Resembles nerve cell activity realistically in that the model produces signals above a set threshold, its firing activity varies, a refractory period is required before second firing, and it displays plasticity. (CS)

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.

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data

PubMed Central

Carty, Mark; Zamparo, Lee; Sahin, Merve; González, Alvaro; Pelossof, Raphael; Elemento, Olivier; Leslie, Christina S.

2017-01-01

Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts—for example, distance-dependent random polymer ligation and GC content and mappability bias—and model zero inflation and overdispersion. Applied to high-resolution Hi-C data in a lymphoblastoid cell line, HiC-DC detects significant interactions at the sub-topologically associating domain level, identifying potential structural and regulatory interactions supported by CTCF binding sites, DNase accessibility, and/or active histone marks. CTCF-associated interactions are most strongly enriched in the middle genomic distance range (∼700 kb–1.5 Mb), while interactions involving actively marked DNase accessible elements are enriched both at short (<500 kb) and longer (>1.5 Mb) genomic distances. There is a striking enrichment of longer-range interactions connecting replication-dependent histone genes on chromosome 6, potentially representing the chromatin architecture at the histone locus body. PMID:28513628

Modeling of active transmembrane transport in a mixture theory framework.

PubMed

Ateshian, Gerard A; Morrison, Barclay; Hung, Clark T

2010-05-01

This study formulates governing equations for active transport across semi-permeable membranes within the framework of the theory of mixtures. In mixture theory, which models the interactions of any number of fluid and solid constituents, a supply term appears in the conservation of linear momentum to describe momentum exchanges among the constituents. In past applications, this momentum supply was used to model frictional interactions only, thereby describing passive transport processes. In this study, it is shown that active transport processes, which impart momentum to solutes or solvent, may also be incorporated in this term. By projecting the equation of conservation of linear momentum along the normal to the membrane, a jump condition is formulated for the mechano-electrochemical potential of fluid constituents which is generally applicable to nonequilibrium processes involving active transport. The resulting relations are simple and easy to use, and address an important need in the membrane transport literature.

Active Brownian rods

NASA Astrophysics Data System (ADS)

Peruani, Fernando

2016-11-01

Bacteria, chemically-driven rods, and motility assays are examples of active (i.e. self-propelled) Brownian rods (ABR). The physics of ABR, despite their ubiquity in experimental systems, remains still poorly understood. Here, we review the large-scale properties of collections of ABR moving in a dissipative medium. We address the problem by presenting three different models, of decreasing complexity, which we refer to as model I, II, and III, respectively. Comparing model I, II, and III, we disentangle the role of activity and interactions. In particular, we learn that in two dimensions by ignoring steric or volume exclusion effects, large-scale nematic order seems to be possible, while steric interactions prevent the formation of orientational order at large scales. The macroscopic behavior of ABR results from the interplay between active stresses and local alignment. ABR exhibit, depending on where we locate ourselves in parameter space, a zoology of macroscopic patterns that ranges from polar and nematic bands to dynamic aggregates.

c-Abl links APP-BACE1 interaction promoting APP amyloidogenic processing in Niemann-Pick type C disease.

PubMed

Yáñez, M J; Belbin, O; Estrada, L D; Leal, N; Contreras, P S; Lleó, A; Burgos, P V; Zanlungo, S; Alvarez, A R

2016-11-01

Niemann-Pick type C (NPC) disease is characterized by lysosomal accumulation of cholesterol. Interestingly, NPC patients' brains also show increased levels of amyloid-β (Aβ) peptide, a key protein in Alzheimer's disease pathogenesis. We previously reported that the c-Abl tyrosine kinase is active in NPC neurons and in AD animal models and that Imatinib, a specific c-Abl inhibitor, decreased the amyloid burden in brains of the AD mouse model. Active c-Abl was shown to interact with the APP cytosolic domain, but the relevance of this interaction to APP processing has yet to be defined. In this work we show that c-Abl inhibition reduces APP amyloidogenic cleavage in NPC cells overexpressing APP. Indeed, we found that levels of the Aβ oligomers and the carboxy-terminal fragment βCTF were decreased when the cells were treated with Imatinib and upon shRNA-mediated c-Abl knockdown. Moreover, Imatinib decreased APP amyloidogenic processing in the brain of an NPC mouse model. In addition, we found decreased levels of βCTF in neuronal cultures from c-Abl null mice. We demonstrate that c-Abl directly interacts with APP, that c-Abl inhibition prevents this interaction, and that Tyr682 in the APP cytoplasmic tail is essential for this interaction. More importantly, we found that c-Abl inhibition by Imatinib significantly inhibits the interaction between APP and BACE1. We conclude that c-Abl activity facilitates the APP-BACE1 interaction, thereby promoting amyloidogenic processing of APP. Thus, inhibition of c-Abl could be a pharmacological target for preventing the injurious effects of increased Aβ levels in NPC disease. Copyright © 2016 Elsevier B.V. All rights reserved.

A review of active learning approaches to experimental design for uncovering biological networks

PubMed Central

2017-01-01

Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature; highlights common themes and notable distinctions among methods; and identifies likely directions of future research and open problems in the area. PMID:28570593

Executive Control Modulates Cross-Language Lexical Activation during L2 Reading: Evidence from Eye Movements

ERIC Educational Resources Information Center

Pivneva, Irina; Mercier, Julie; Titone, Debra

2014-01-01

Models of bilingual reading such as Bilingual Interactive Activation Plus (Dijkstra & van Heuven, 2002) do not predict a central role for domain-general executive control during bilingual reading, in contrast with bilingual models from other domains, such as production (e.g., the Inhibitory Control Model; Green, 1998). We thus investigated…

Co-producing active lifestyles as whole-system-approach: theory, intervention and knowledge-to-action implications.

PubMed

Rütten, Alfred; Frahsa, Annika; Abel, Thomas; Bergmann, Matthias; de Leeuw, Evelyne; Hunter, David; Jansen, Maria; King, Abby; Potvin, Louise

2017-09-08

Population health interventions tend to lack links to the emerging discourse on interactive knowledge production and exchange. This situation may limit both a better understanding of mechanisms that impact health lifestyles and the development of strategies for population level change. This paper introduces an integrated approach based on structure-agency theory in the context of 'social practice'. It investigates the mechanisms of co-production of active lifestyles by population groups, professionals, policymakers and researchers. It combines a whole system approach with an interactive knowledge-to-action strategy for developing and implementing active lifestyle interventions. A system model is outlined to describe and explain how social practices of selected groups co-produce active lifestyles. Four intervention models for promoting the co-production of active lifestyles through an interactive-knowledge-to-action approach are discussed. Examples from case studies of the German research network Capital4Health are used to illustrate, how intervention models might be operationalized in a real-world intervention. Five subprojects develop, implement and evaluate interventions across the life-course. Although subprojects differ with regard to settings and population groups involved, they all focus on the four key components of the system model. The paper contributes new strategies to address the intervention research challenge of sustainable change of inactive lifestyles. The interactive approach presented allows consideration of the specificities of settings and scientific contexts for manifold purposes. Further research remains needed on what a co-produced knowledge-to-action agenda would look like and what impact it might have for whole system change. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evidence for a bimodal distribution in human communication.

PubMed

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-11-02

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.

Evidence for a bimodal distribution in human communication

PubMed Central

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-01-01

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc. PMID:20959414

The Bilingual Language Interaction Network for Comprehension of Speech

ERIC Educational Resources Information Center

Shook, Anthony; Marian, Viorica

2013-01-01

During speech comprehension, bilinguals co-activate both of their languages, resulting in cross-linguistic interaction at various levels of processing. This interaction has important consequences for both the structure of the language system and the mechanisms by which the system processes spoken language. Using computational modeling, we can…

Modeling the vegetation-atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient

USDA-ARS?s Scientific Manuscript database

Ecosystem functioning is intimately linked to the physical environment by complex two-way interactions. These two-way interactions arise because vegetation both responds to the external environment and actively regulates its micro-environment. By altering stomatal aperture, for example, plants modif...

Psychological Development and Females' Sport Participation: An Interactional Perspective.

ERIC Educational Resources Information Center

Weiss, Maureen R.; Glenn, Susan D.

1992-01-01

This paper examines the writings of Dorothy Harris and other authors, from a psychosocial perspective of sport involvement. It explores ways self-perceptions, social factors, and cognitive and biological maturity interact to explain females' physical activity participation; it proposes a heuristic model to represent an interactional approach. (SM)

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

Ratchet Effects in Active Matter Systems

NASA Astrophysics Data System (ADS)

Reichhardt, C. J. Olson; Reichhardt, C.

2017-03-01

Ratchet effects can arise for single or collectively interacting Brownian particles on an asymmetric substrate when a net dc transport is produced by an externally applied ac driving force or by periodically flashing the substrate. Recently, a new class of active ratchet systems that do not require the application of external driving has been realized through the use of active matter; they are self-propelled units that can be biological or nonbiological in nature. When active materials such as swimming bacteria interact with an asymmetric substrate, a net dc directed motion can arise even without external driving, opening a wealth of possibilities such as sorting, cargo transport, or micromachine construction. We review the current status of active matter ratchets for swimming bacteria, cells, active colloids, and swarming models, focusing on the role of particle-substrate interactions. We describe ratchet reversals produced by collective effects and the use of active ratchets to transport passive particles. We discuss future directions including deformable substrates or particles, the role of different swimming modes, varied particle-particle interactions, and nondissipative effects.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

Activeness as a key to counter democratic balance

NASA Astrophysics Data System (ADS)

Qian, Shen; Liu, Yijun; Galam, Serge

2015-08-01

According to the classic Galam model of opinion dynamics, each agent participates at each update of an opinion interaction. While the scheme gives everyone the same chance to influence others, in reality, social activity and influence vary considerably from one agent to another. To account for such a feature, we introduce a new individual attribute-"activeness"-which makes some agents more inclined than others at engaging in local discussions. To enhance the corresponding effect, opinion updates are shifted from all-out agent interaction cycles to few agent interaction cycles. Using dynamic analysis and simulations the resulting model is found to exhibit a "Minority Counteroffensive" phenomenon, which under some initial conditions makes the minority to win the opinion competition despite a threshold tipping point at fifty percent. The associated probabilistic phenomenon persists in the case "activeness" is held equal for all agents. The effect of "opinion leaders" is also investigated. Indeed, a leader is an inflexible agent, i.e., an agent who does not change opinion. The results reveal that two opinion leaders with moderate social influence may have a stronger effect than one opinion leader with a strong social influence. The model may shed a new light to the understanding of opinion formation and public voting.

Modeling of the phase equilibria of polystyrene in methylcyclohexane with semi-empirical quantum mechanical methods I.

PubMed

Wilczura-Wachnik, Hanna; Jónsdóttir, Svava Osk

2003-04-01

A method for calculating interaction parameters traditionally used in phase-equilibrium computations in low-molecular systems has been extended for the prediction of solvent activities of aromatic polymer solutions (polystyrene+methylcyclohexane). Using ethylbenzene as a model compound for the repeating unit of the polymer, the intermolecular interaction energies between the solvent molecule and the polymer were simulated. The semiempirical quantum chemical method AM1, and a method for sampling relevant internal orientations for a pair of molecules developed previously were used. Interaction energies are determined for three molecular pairs, the solvent and the model molecule, two solvent molecules and two model molecules, and used to calculated UNIQUAC interaction parameters, a(ij) and a(ji). Using these parameters, the solvent activities of the polystyrene 90,000 amu+methylcyclohexane system, and the total vapor pressures of the methylcyclohexane+ethylbenzene system were calculated. The latter system was compared to experimental data, giving qualitative agreement. Figure Solvent activities for the methylcylcohexane(1)+polystyrene(2) system at 316 K. Parameters aij (blue line) obtained with the AM1 method; parameters aij (pink line) from VLE data for the ethylbenzene+methylcyclohexane system. The abscissa is the polymer weight fraction defined as y2(x1)=(1mx1)M2/[x1M1+(1mx1)M2], where x1 is the solvent mole fraction and Mi are the molecular weights of the components.

Intracochlear Scala Media Pressure Measurement: Implications for Models of Cochlear Mechanics.

PubMed

Kale, Sushrut S; Olson, Elizabeth S

2015-12-15

Models of the active cochlea build upon the underlying passive mechanics. Passive cochlear mechanics is based on physical and geometrical properties of the cochlea and the fluid-tissue interaction between the cochlear partition and the surrounding fluid. Although the fluid-tissue interaction between the basilar membrane and the fluid in scala tympani (ST) has been explored in both active and passive cochleae, there was no experimental data on the fluid-tissue interaction on the scala media (SM) side of the partition. To this aim, we measured sound-evoked intracochlear pressure in SM close to the partition using micropressure sensors. All the SM pressure data are from passive cochleae, likely because the SM cochleostomy led to loss of endocochlear potential. Thus, these experiments are studies of passive cochlear mechanics. SM pressure close to the tissue showed a pattern of peaks and notches, which could be explained as an interaction between fast and slow (i.e., traveling wave) pressure modes. In several animals SM and ST pressure were measured in the same cochlea. Similar to previous studies, ST-pressure was dominated by a slow, traveling wave mode at stimulus frequencies in the vicinity of the best frequency of the measurement location, and by a fast mode above best frequency. Antisymmetric pressure between SM and ST supported the classic single-partition cochlear models, or a dual-partition model with tight coupling between partitions. From the SM and ST pressure we calculated slow and fast modes, and from active ST pressure we extrapolated the passive findings to the active case. The passive slow mode estimated from SM and ST data was low-pass in nature, as predicted by cochlear models. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Intracochlear Scala Media Pressure Measurement: Implications for Models of Cochlear Mechanics

PubMed Central

Kale, Sushrut S.; Olson, Elizabeth S.

2015-01-01

Models of the active cochlea build upon the underlying passive mechanics. Passive cochlear mechanics is based on physical and geometrical properties of the cochlea and the fluid-tissue interaction between the cochlear partition and the surrounding fluid. Although the fluid-tissue interaction between the basilar membrane and the fluid in scala tympani (ST) has been explored in both active and passive cochleae, there was no experimental data on the fluid-tissue interaction on the scala media (SM) side of the partition. To this aim, we measured sound-evoked intracochlear pressure in SM close to the partition using micropressure sensors. All the SM pressure data are from passive cochleae, likely because the SM cochleostomy led to loss of endocochlear potential. Thus, these experiments are studies of passive cochlear mechanics. SM pressure close to the tissue showed a pattern of peaks and notches, which could be explained as an interaction between fast and slow (i.e., traveling wave) pressure modes. In several animals SM and ST pressure were measured in the same cochlea. Similar to previous studies, ST-pressure was dominated by a slow, traveling wave mode at stimulus frequencies in the vicinity of the best frequency of the measurement location, and by a fast mode above best frequency. Antisymmetric pressure between SM and ST supported the classic single-partition cochlear models, or a dual-partition model with tight coupling between partitions. From the SM and ST pressure we calculated slow and fast modes, and from active ST pressure we extrapolated the passive findings to the active case. The passive slow mode estimated from SM and ST data was low-pass in nature, as predicted by cochlear models. PMID:26682824

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

Efficacy of Synaptic Inhibition Depends on Multiple, Dynamically Interacting Mechanisms Implicated in Chloride Homeostasis

PubMed Central

Doyon, Nicolas; Prescott, Steven A.; Castonguay, Annie; Godin, Antoine G.; Kröger, Helmut; De Koninck, Yves

2011-01-01

Chloride homeostasis is a critical determinant of the strength and robustness of inhibition mediated by GABAA receptors (GABAARs). The impact of changes in steady state Cl− gradient is relatively straightforward to understand, but how dynamic interplay between Cl− influx, diffusion, extrusion and interaction with other ion species affects synaptic signaling remains uncertain. Here we used electrodiffusion modeling to investigate the nonlinear interactions between these processes. Results demonstrate that diffusion is crucial for redistributing intracellular Cl− load on a fast time scale, whereas Cl−extrusion controls steady state levels. Interaction between diffusion and extrusion can result in a somato-dendritic Cl− gradient even when KCC2 is distributed uniformly across the cell. Reducing KCC2 activity led to decreased efficacy of GABAAR-mediated inhibition, but increasing GABAAR input failed to fully compensate for this form of disinhibition because of activity-dependent accumulation of Cl−. Furthermore, if spiking persisted despite the presence of GABAAR input, Cl− accumulation became accelerated because of the large Cl− driving force that occurs during spikes. The resulting positive feedback loop caused catastrophic failure of inhibition. Simulations also revealed other feedback loops, such as competition between Cl− and pH regulation. Several model predictions were tested and confirmed by [Cl−]i imaging experiments. Our study has thus uncovered how Cl− regulation depends on a multiplicity of dynamically interacting mechanisms. Furthermore, the model revealed that enhancing KCC2 activity beyond normal levels did not negatively impact firing frequency or cause overt extracellular K− accumulation, demonstrating that enhancing KCC2 activity is a valid strategy for therapeutic intervention. PMID:21931544

Evaluation for the design of experience in virtual environments: modeling breakdown of interaction and illusion.

PubMed

Marsh, T; Wright, P; Smith, S

2001-04-01

New and emerging media technologies have the potential to induce a variety of experiences in users. In this paper, it is argued that the inducement of experience presupposes that users are absorbed in the illusion created by these media. Looking to another successful visual medium, film, this paper borrows from the techniques used in "shaping experience" to hold spectators' attention in the illusion of film, and identifies what breaks the illusion/experience for spectators. This paper focuses on one medium, virtual reality (VR), and advocates a transparent or "invisible style" of interaction. We argue that transparency keeps users in the "flow" of their activities and consequently enhances experience in users. Breakdown in activities breaks the experience and subsequently provides opportunities to identify and analyze potential causes of usability problems. Adopting activity theory, we devise a model of interaction with VR--through consciousness and activity--and introduce the concept of breakdown in illusion. From this, a model of effective interaction with VR is devised and the occurrence of breakdown in interaction and illusion is identified along a continuum of engagement. Evaluation guidelines for the design of experience are proposed and applied to usability problems detected in an empirical study of a head-mounted display (HMD) VR system. This study shows that the guidelines are effective in the evaluation of VR. Finally, we look at the potential experiences that may be induced in users and propose a way to evaluate user experience in virtual environments (VEs) and other new and emerging media.

Interactions between psychosocial and built environment factors in explaining older adults' physical activity.

PubMed

Carlson, Jordan A; Sallis, James F; Conway, Terry L; Saelens, Brian E; Frank, Lawrence D; Kerr, Jacqueline; Cain, Kelli L; King, Abby C

2012-01-01

To evaluate ecological model predictions of cross-level interactions among psychosocial and environmental correlates of physical activity in 719 community-dwelling older adults in the Baltimore, Maryland and Seattle, Washington areas during 2005-2008. Walkability, access to parks and recreation facilities and moderate-to-vigorous physical activity (MVPA) minutes per week (min/week) were measured objectively. Neighborhood aesthetics, walking facilities, social support, self-efficacy, barriers and transportation and leisure walking min/week were self-reported. Walkability interacted with social support in explaining total MVPA (B=13.71) and with social support (B=7.90), self-efficacy (B=7.66) and barriers (B=-8.26) in explaining walking for transportation. Aesthetics interacted with barriers in explaining total MVPA (B=-12.20) and walking facilities interacted with self-efficacy in explaining walking for leisure (B=-10.88; Ps<.05). Summarizing across the interactions, living in a supportive environment (vs. unsupportive) was related to 30-59 more min/week of physical activity for participants with more positive psychosocial attributes, but only 0-28 more min/week for participants with less positive psychosocial attributes. Results supported synergistic interactions between built environment and psychosocial factors in explaining physical activity among older adults. Findings suggest multilevel interventions may be most effective in increasing physical activity. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Genetic and environmental (physical fitness and sedentary activity) interaction effects on cardiometabolic risk factors in Mexican American children and adolescents.

PubMed

Arya, Rector; Farook, Vidya S; Fowler, Sharon P; Puppala, Sobha; Chittoor, Geetha; Resendez, Roy G; Mummidi, Srinivas; Vanamala, Jairam; Almasy, Laura; Curran, Joanne E; Comuzzie, Anthony G; Lehman, Donna M; Jenkinson, Christopher P; Lynch, Jane L; DeFronzo, Ralph A; Blangero, John; Hale, Daniel E; Duggirala, Ravindranath; Diego, Vincent P

2018-06-01

Knowledge on genetic and environmental (G × E) interaction effects on cardiometabolic risk factors (CMRFs) in children is limited.  The purpose of this study was to examine the impact of G × E interaction effects on CMRFs in Mexican American (MA) children (n = 617, ages 6-17 years). The environments examined were sedentary activity (SA), assessed by recalls from "yesterday" (SAy) and "usually" (SAu) and physical fitness (PF) assessed by Harvard PF scores (HPFS). CMRF data included body mass index (BMI), waist circumference (WC), fat mass (FM), fasting insulin (FI), homeostasis model of assessment-insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), systolic (SBP) and diastolic (DBP) blood pressure, and number of metabolic syndrome components (MSC). We examined potential G × E interaction in the phenotypic expression of CMRFs using variance component models and likelihood-based statistical inference. Significant G × SA interactions were identified for six CMRFs: BMI, WC, FI, HOMA-IR, MSC, and HDL, and significant G × HPFS interactions were observed for four CMRFs: BMI, WC, FM, and HOMA-IR. However, after correcting for multiple hypothesis testing, only WC × SAy, FM × SAy, and FI × SAu interactions became marginally significant. After correcting for multiple testing, most of CMRFs exhibited significant G × E interactions (Reduced G × E model vs. Constrained model). These findings provide evidence that genetic factors interact with SA and PF to influence variation in CMRFs, and underscore the need for better understanding of these relationships to develop strategies and interventions to effectively reduce or prevent cardiometabolic risk in children. © 2018 WILEY PERIODICALS, INC.

Interactions among roots, mycorrhizas and free-living microbial communities differentially impact soil carbon processes

DOE PAGES

Moore, Jessica A. M.; Jiang, Jiang; Patterson, Courtney M.; ...

2015-10-20

Plant roots, their associated microbial community and free-living soil microbes interact to regulate the movement of carbon from the soil to the atmosphere, one of the most important and least understood fluxes of terrestrial carbon. Our inadequate understanding of how plant-microbial interactions alter soil carbon decomposition may lead to poor model predictions of terrestrial carbon feedbacks to the atmosphere. Roots, mycorrhizal fungi and free-living soil microbes can alter soil carbon decomposition through exudation of carbon into soil. Exudates of simple carbon compounds can increase microbial activity because microbes are typically carbon limited. When both roots and mycorrhizal fungi are presentmore » in the soil, they may additively increase carbon decomposition. However, when mycorrhizas are isolated from roots, they may limit soil carbon decomposition by competing with free-living decomposers for resources. We manipulated the access of roots and mycorrhizal fungi to soil insitu in a temperate mixed deciduous forest. We added 13C-labelled substrate to trace metabolized carbon in respiration and measured carbon-degrading microbial extracellular enzyme activity and soil carbon pools. We used our data in a mechanistic soil carbon decomposition model to simulate and compare the effects of root and mycorrhizal fungal presence on soil carbon dynamics over longer time periods. Contrary to what we predicted, root and mycorrhizal biomass did not interact to additively increase microbial activity and soil carbon degradation. The metabolism of 13C-labelled starch was highest when root biomass was high and mycorrhizal biomass was low. These results suggest that mycorrhizas may negatively interact with the free-living microbial community to influence soil carbon dynamics, a hypothesis supported by our enzyme results. Our steady-state model simulations suggested that root presence increased mineral-associated and particulate organic carbon pools, while mycorrhizal fungal presence had a greater influence on particulate than mineral-associated organic carbon pools.Synthesis. Our results suggest that the activity of enzymes involved in organic matter decomposition was contingent upon root-mycorrhizal-microbial interactions. Using our experimental data in a decomposition simulation model, we show that root-mycorrhizal-microbial interactions may have longer-term legacy effects on soil carbon sequestration. Lastly, our study suggests that roots stimulate microbial activity in the short term, but contribute to soil carbon storage over longer periods of time.« less

Interactions among roots, mycorrhizas and free-living microbial communities differentially impact soil carbon processes

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

Moore, Jessica A. M.; Jiang, Jiang; Patterson, Courtney M.

Plant roots, their associated microbial community and free-living soil microbes interact to regulate the movement of carbon from the soil to the atmosphere, one of the most important and least understood fluxes of terrestrial carbon. Our inadequate understanding of how plant-microbial interactions alter soil carbon decomposition may lead to poor model predictions of terrestrial carbon feedbacks to the atmosphere. Roots, mycorrhizal fungi and free-living soil microbes can alter soil carbon decomposition through exudation of carbon into soil. Exudates of simple carbon compounds can increase microbial activity because microbes are typically carbon limited. When both roots and mycorrhizal fungi are presentmore » in the soil, they may additively increase carbon decomposition. However, when mycorrhizas are isolated from roots, they may limit soil carbon decomposition by competing with free-living decomposers for resources. We manipulated the access of roots and mycorrhizal fungi to soil insitu in a temperate mixed deciduous forest. We added 13C-labelled substrate to trace metabolized carbon in respiration and measured carbon-degrading microbial extracellular enzyme activity and soil carbon pools. We used our data in a mechanistic soil carbon decomposition model to simulate and compare the effects of root and mycorrhizal fungal presence on soil carbon dynamics over longer time periods. Contrary to what we predicted, root and mycorrhizal biomass did not interact to additively increase microbial activity and soil carbon degradation. The metabolism of 13C-labelled starch was highest when root biomass was high and mycorrhizal biomass was low. These results suggest that mycorrhizas may negatively interact with the free-living microbial community to influence soil carbon dynamics, a hypothesis supported by our enzyme results. Our steady-state model simulations suggested that root presence increased mineral-associated and particulate organic carbon pools, while mycorrhizal fungal presence had a greater influence on particulate than mineral-associated organic carbon pools.Synthesis. Our results suggest that the activity of enzymes involved in organic matter decomposition was contingent upon root-mycorrhizal-microbial interactions. Using our experimental data in a decomposition simulation model, we show that root-mycorrhizal-microbial interactions may have longer-term legacy effects on soil carbon sequestration. Lastly, our study suggests that roots stimulate microbial activity in the short term, but contribute to soil carbon storage over longer periods of time.« less

Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities.

PubMed

Sawyer, Alexia D M; Jones, Russell; Ucci, Marcella; Smith, Lee; Kearns, Ade; Fisher, Abi

2017-01-01

Understanding the environmental determinants of physical activity in populations at high risk of inactivity could contribute to the development of effective interventions. Socioecological models of activity propose that environmental factors have independent and interactive effects of physical activity but there is a lack of research into interactive effects. This study aimed to explore independent and interactive effects of social and physical environmental factors on self-reported physical activity in income-deprived communities. Participants were 5,923 adults in Glasgow, United Kingdom. Features of the social environment were self-reported. Quality of the physical environment was objectively-measured. Neighbourhood walking and participation in moderate physical activity [MPA] on ≥5 days/week was self-reported. Multilevel multivariate logistic regression models tested independent and interactive effects of environmental factors on activity. 'Social support' (walking: OR:1.22,95%CI = 1.06-1.41,p<0.01; MPA: OR:0.79,95%CI = 0.67-0.94,p<0.01), 'social interaction' (walking: OR:1.25,95%CI = 1.10-1.42,p<0.01; MPA: OR:6.16,95%CI = 5.14-7.37,p<0.001) and 'cohesion and safety' (walking: OR:1.78,95%CI = 1.56-2.03,p<0.001; MPA: OR:1.93,95%CI = 1.65-2.27,p<0.001), but not 'trust and empowerment', had independent effects on physical activity. 'Aesthetics of built form' (OR:1.47,95%CI = 1.22-1.77,p<0.001) and 'aesthetics and maintenance of open space' (OR:1.32, 95%CI = 1.13-1.54,p<0.01) were related to walking. 'Physical disorder' (OR:1.63,95%CI = 1.31-2.03,p<0.001) had an independent effect on MPA. Interactive effects of social and physical factors on walking and MPA were revealed. Findings suggest that intervening to create activity-supportive environments in deprived communities may be most effective when simultaneously targeting the social and physical neighbourhood environment.

Model of transcriptional activation by MarA in Escherichia coli.

PubMed

Wall, Michael E; Markowitz, David A; Rosner, Judah L; Martin, Robert G

2009-12-01

The AraC family transcription factor MarA activates approximately 40 genes (the marA/soxS/rob regulon) of the Escherichia coli chromosome resulting in different levels of resistance to a wide array of antibiotics and to superoxides. Activation of marA/soxS/rob regulon promoters occurs in a well-defined order with respect to the level of MarA; however, the order of activation does not parallel the strength of MarA binding to promoter sequences. To understand this lack of correspondence, we developed a computational model of transcriptional activation in which a transcription factor either increases or decreases RNA polymerase binding, and either accelerates or retards post-binding events associated with transcription initiation. We used the model to analyze data characterizing MarA regulation of promoter activity. The model clearly explains the lack of correspondence between the order of activation and the MarA-DNA affinity and indicates that the order of activation can only be predicted using information about the strength of the full MarA-polymerase-DNA interaction. The analysis further suggests that MarA can activate without increasing polymerase binding and that activation can even involve a decrease in polymerase binding, which is opposite to the textbook model of activation by recruitment. These findings are consistent with published chromatin immunoprecipitation assays of interactions between polymerase and the E. coli chromosome. We find that activation involving decreased polymerase binding yields lower latency in gene regulation and therefore might confer a competitive advantage to cells. Our model yields insights into requirements for predicting the order of activation of a regulon and enables us to suggest that activation might involve a decrease in polymerase binding which we expect to be an important theme of gene regulation in E. coli and beyond.

Modeling activity recognition of multi resident using label combination of multi label classification in smart home

NASA Astrophysics Data System (ADS)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.

Dynamic conformational switching in the chemokine ligand is essential for G-protein-coupled receptor activation

PubMed Central

Joseph, Prem Raj B.; Sawant, Kirti V.; Isley, Angela; Pedroza, Mesias; Garofalo, Roberto P.; Richardson, Ricardo M.; Rajarathnam, Krishna

2014-01-01

Chemokines mediate diverse functions from organogenesis to mobilizing leucocytes, and are unusual agonists for class-A GPCRs (G-protein-coupled receptors) because of their large size and multi-domain structure. The current model for receptor activation, which involves interactions between chemokine N-loop and receptor N-terminal residues (Site-I) and between chemokine N-terminal and receptor extracellular loop/transmembrane residues (Site-II), fails to describe differences in ligand/receptor selectivity and the activation of multiple signalling pathways. In the present study, we show in neutrophil-activating chemokine CXCL8 that the highly conserved GP (glycine-proline) motif located distal to both N-terminal and N-loop residues couples Site-I and Site-II interactions. Mutations in the GP motif caused various differences from native-like function to complete loss of activity that could not be correlated with the specific mutation, receptor affinity or subtype, or a specific signalling pathway. NMR studies indicated that the GP motif does not influence Site-I interactions, but molecular dynamics simulations suggested that this motif dictates substates of the CXCL8 conformational ensemble. We conclude that the GP motif enables diverse receptor functions by controlling cross-talk between Site-I and Site-II, and further propose that the repertoire of chemokine functions is best described by a conformational ensemble model in which a network of long-range coupled indirect interactions mediate receptor activity. PMID:24032673

Objectively-Measured Physical Activity and Cognitive Functioning in Breast Cancer Survivors

PubMed Central

Marinac, Catherine R.; Godbole, Suneeta; Kerr, Jacqueline; Natarajan, Loki; Patterson, Ruth E.; Hartman, Sheri J.

2015-01-01

Purpose To explore the relationship between objectively measured physical activity and cognitive functioning in breast cancer survivors. Methods Participants were 136 postmenopausal breast cancer survivors. Cognitive functioning was assessed using a comprehensive computerized neuropsychological test. 7-day physical activity was assessed using hip-worn accelerometers. Linear regression models examined associations of minutes per day of physical activity at various intensities on individual cognitive functioning domains. The partially adjusted model controlled for primary confounders (model 1), and subsequent adjustments were made for chemotherapy history (model 2), and BMI (model 3). Interaction and stratified models examined BMI as an effect modifier. Results Moderate-to-vigorous physical activity (MVPA) was associated with Information Processing Speed. Specifically, ten minutes of MVPA was associated with a 1.35-point higher score (out of 100) on the Information Processing Speed domain in the partially adjusted model, and a 1.29-point higher score when chemotherapy was added to the model (both p<.05). There was a significant BMI x MVPA interaction (p=.051). In models stratified by BMI (<25 vs. ≥25 kg/m2), the favorable association between MVPA and Information Processing Speed was stronger in the subsample of overweight and obese women (p<.05), but not statistically significant in the leaner subsample. Light-intensity physical activity was not significantly associated with any of the measured domains of cognitive function. Conclusions MVPA may have favorable effects on Information Processing Speed in breast cancer survivors, particularly among overweight or obese women. Implications for Cancer Survivors Interventions targeting increased physical activity may enhance aspects of cognitive function among breast cancer survivors. PMID:25304986

Control Surface Interaction Effects of the Active Aeroelastic Wing Wind Tunnel Model

NASA Technical Reports Server (NTRS)

Heeg, Jennifer

2006-01-01

This paper presents results from testing the Active Aeroelastic Wing wind tunnel model in NASA Langley s Transonic Dynamics Tunnel. The wind tunnel test provided an opportunity to study aeroelastic system behavior under combined control surface deflections, testing for control surface interaction effects. Control surface interactions were observed in both static control surface actuation testing and dynamic control surface oscillation testing. The primary method of evaluating interactions was examination of the goodness of the linear superposition assumptions. Responses produced by independently actuating single control surfaces were combined and compared with those produced by simultaneously actuating and oscillating multiple control surfaces. Adjustments to the data were required to isolate the control surface influences. Using dynamic data, the task increases, as both the amplitude and phase have to be considered in the data corrections. The goodness of static linear superposition was examined and analysis of variance was used to evaluate significant factors influencing that goodness. The dynamic data showed interaction effects in both the aerodynamic measurements and the structural measurements.

Interactive Activation Model of Speech Perception.

DTIC Science & Technology

1984-11-01

contract. 0 Elar, .l... & .McC’lelland .1.1. Speech perception a, a cognitive proces,: The interactive act ia- %e., tion model of speech perception. In...attempts to provide a machine solution to the problem of speech perception. A second kind of model, growing out of Cognitive Psychology, attempts to...architectures to cognitive and perceptual problems. We also owe a debt to what we might call the computational connectionists -- those who have applied highly

Numerical simulation of interaction between chemically active exhaust and a jet blast deflector

NASA Astrophysics Data System (ADS)

Korotaeva, T. A.; Turchinovich, A. O.

2017-10-01

The interaction of chemically active exhausts of aircraft engines with jet blast deflector (JBD) of various configurations has been considered at the stage of ground run procedure. The problem is modeled in the 3-D approximation in the framework of the numerical solution of the Navier-Stokes equations taking into account the kinetic model of the interaction of between the components of engine exhaust and air. A complex field of gasdynamic flow that is realized when jets emerge from nozzles and interact with each other, with air, with a gas deflector has been studied. The main purpose of the study is to prove the concept that it is possible to generate a vortex flow that can not only change the direction of the jets, but also contribute to the lifting of the mass of pollutants and their dispersion in the atmosphere using a gas deflector shape.

Interactive autonomy and robotic skills

NASA Technical Reports Server (NTRS)

Kellner, A.; Maediger, B.

1994-01-01

Current concepts of robot-supported operations for space laboratories (payload servicing, inspection, repair, and ORU exchange) are mainly based on the concept of 'interactive autonomy' which implies autonomous behavior of the robot according to predefined timelines, predefined sequences of elementary robot operations and within predefined world models supplying geometrical and other information for parameter instantiation on the one hand, and the ability to override and change the predefined course of activities by human intervention on the other hand. Although in principle a very powerful and useful concept, in practice the confinement of the robot to the abstract world models and predefined activities appears to reduce the robot's stability within real world uncertainties and its applicability to non-predefined parts of the world, calling for frequent corrective interaction by the operator, which in itself may be tedious and time-consuming. Methods are presented to improve this situation by incorporating 'robotic skills' into the concept of interactive autonomy.

Recent Developments in Smart Adaptive Structures for Solar Sailcraft

NASA Technical Reports Server (NTRS)

Whorton, M. S.; Kim, Y. K.; Oakley, J.; Adetona, O.; Keel, L. H.

2007-01-01

The "Smart Adaptive Structures for Solar Sailcraft" development activity at MSFC has investigated issues associated with understanding how to model and scale the subsystem and multi-body system dynamics of a gossamer solar sailcraft with the objective of designing sailcraft attitude control systems. This research and development activity addressed three key tasks that leveraged existing facilities and core competencies of MSFC to investigate dynamics and control issues of solar sails. Key aspects of this effort included modeling and testing of a 30 m deployable boom; modeling of the multi-body system dynamics of a gossamer sailcraft; investigation of control-structures interaction for gossamer sailcraft; and development and experimental demonstration of adaptive control technologies to mitigate control-structures interaction.

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

Reichhardt, Cynthia Jane; Reichhardt, Charles

Ratchet effects can arise for single or collectively interacting Brownian particles on an asymmetric substrate when a net dc transport is produced by an externally applied ac driving force or by periodically flashing the substrate. Recently, a new class of active ratchet systems that do not require the application of external driving has been realized through the use of active matter; they are self-propelled units that can be biological or nonbiological in nature. When active materials such as swimming bacteria interact with an asymmetric substrate, a net dc directed motion can arise even without external driving, opening a wealth ofmore » possibilities such as sorting, cargo transport, or micromachine construction. We review the current status of active matter ratchets for swimming bacteria, cells, active colloids, and swarming models, focusing on the role of particle-substrate interactions. Here, we describe ratchet reversals produced by collective effects and the use of active ratchets to transport passive particles. We discuss future directions including deformable substrates or particles, the role of different swimming modes, varied particle–particle interactions, and nondissipative effects.« less

Active Exploration of Large 3D Model Repositories.

PubMed

Gao, Lin; Cao, Yan-Pei; Lai, Yu-Kun; Huang, Hao-Zhi; Kobbelt, Leif; Hu, Shi-Min

2015-12-01

With broader availability of large-scale 3D model repositories, the need for efficient and effective exploration becomes more and more urgent. Existing model retrieval techniques do not scale well with the size of the database since often a large number of very similar objects are returned for a query, and the possibilities to refine the search are quite limited. We propose an interactive approach where the user feeds an active learning procedure by labeling either entire models or parts of them as "like" or "dislike" such that the system can automatically update an active set of recommended models. To provide an intuitive user interface, candidate models are presented based on their estimated relevance for the current query. From the methodological point of view, our main contribution is to exploit not only the similarity between a query and the database models but also the similarities among the database models themselves. We achieve this by an offline pre-processing stage, where global and local shape descriptors are computed for each model and a sparse distance metric is derived that can be evaluated efficiently even for very large databases. We demonstrate the effectiveness of our method by interactively exploring a repository containing over 100 K models.

Photophysical investigations of squaraine and cyanine dyes and their interaction with bovine serum albumin

NASA Astrophysics Data System (ADS)

Saikiran, M.; Sato, D.; Pandey, S. S.; Kato, T.

2016-04-01

A model far-red sensitive symmetrical squaraine dye (SQ-3) and unsymmetrical near infra-red sensitive cyanine dye (UCD-1) bearing direct-COOH functionalized indole ring were synthesized, characterized and subjected to photophysical investigations including their interaction with bovine serum albumin (BSA) as a model protein in phosphate buffer solution (PBS). Both of the dyes exhibit strong interaction with BSA in phosphate buffer with high apparent binding constant. A judicious tuning of hydrophobic main backbone with reactive functionality for associative interaction with active site of BSA has been found to be necessary for BSA detection in PBS.

Searching for collective behavior in a large network of sensory neurons.

PubMed

Tkačik, Gašper; Marre, Olivier; Amodei, Dario; Schneidman, Elad; Bialek, William; Berry, Michael J

2014-01-01

Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such "K-pairwise" models--being systematic extensions of the previously used pairwise Ising models--provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population's capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction.

Thermal activation of dislocations in large scale obstacle bypass

NASA Astrophysics Data System (ADS)

Sobie, Cameron; Capolungo, Laurent; McDowell, David L.; Martinez, Enrique

2017-08-01

Dislocation dynamics simulations have been used extensively to predict hardening caused by dislocation-obstacle interactions, including irradiation defect hardening in the athermal case. Incorporating the role of thermal energy on these interactions is possible with a framework provided by harmonic transition state theory (HTST) enabling direct access to thermally activated reaction rates using the Arrhenius equation, including rates of dislocation-obstacle bypass processes. Moving beyond unit dislocation-defect reactions to a representative environment containing a large number of defects requires coarse-graining the activation energy barriers of a population of obstacles into an effective energy barrier that accurately represents the large scale collective process. The work presented here investigates the relationship between unit dislocation-defect bypass processes and the distribution of activation energy barriers calculated for ensemble bypass processes. A significant difference between these cases is observed, which is attributed to the inherent cooperative nature of dislocation bypass processes. In addition to the dislocation-defect interaction, the morphology of the dislocation segments pinned to the defects play an important role on the activation energies for bypass. A phenomenological model for activation energy stress dependence is shown to describe well the effect of a distribution of activation energies, and a probabilistic activation energy model incorporating the stress distribution in a material is presented.

The Individual, Joint, and Additive Interaction Associations of Aerobic-Based Physical Activity and Muscle Strengthening Activities on Metabolic Syndrome.

PubMed

Dankel, Scott J; Loenneke, Jeremy P; Loprinzi, Paul D

2016-12-01

Previous research has demonstrated that physical activity and muscle strengthening activities are independently and inversely associated with metabolic syndrome. Despite a number of studies examining the individual associations, only a few studies have examined the joint associations, and to our knowledge, no previous studies have examined the potential additive interaction of performing muscle strengthening activities and aerobic-based physical activity and their association with metabolic syndrome. Using data from the 2003 to 2006 National Health and Nutrition Examination Survey (NHANES), we computed three separate multivariable logistic regression models to examine the individual, combined, and additive interaction of meeting guidelines for accelerometer-assessed physical activity and self-reported muscle strengthening activities, and their association with metabolic syndrome. We found that individuals meeting physical activity and muscle strengthening activity guidelines, respectively, were at 61 and 25 % lower odds of having metabolic syndrome. Furthermore, individuals meeting both guidelines had the lowest odds of having metabolic syndrome (70 %), in part due to the additive interaction of performing both modes of exercise. In this national sample, accelerometer-assessed physical activity and muscle strengthening activities were synergistically associated with metabolic syndrome.

Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells.

PubMed

Macfarlane, Fiona R; Lorenzi, Tommaso; Chaplain, Mark A J

2018-06-01

A growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour-immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells.

Interaction model between capsule robot and intestine based on nonlinear viscoelasticity.

PubMed

Zhang, Cheng; Liu, Hao; Tan, Renjia; Li, Hongyi

2014-03-01

Active capsule endoscope could also be called capsule robot, has been developed from laboratory research to clinical application. However, the system still has defects, such as poor controllability and failing to realize automatic checks. The imperfection of the interaction model between capsule robot and intestine is one of the dominating reasons causing the above problems. A model is hoped to be established for the control method of the capsule robot in this article. It is established based on nonlinear viscoelasticity. The interaction force of the model consists of environmental resistance, viscous resistance and Coulomb friction. The parameters of the model are identified by experimental investigation. Different methods are used in the experiment to obtain different values of the same parameter at different velocities. The model is proved to be valid by experimental verification. The achievement in this article is the attempted perfection of an interaction model. It is hoped that the model can optimize the control method of the capsule robot in the future.

RESEARCH NOTE: Slow-ridge/hotspot interactions from global gravity, seismic tomography and 87Sr/86Sr isotope data

NASA Astrophysics Data System (ADS)

Goslin, Jean; Thirot, Jean-Louis; Noël, Olivier; Francheteau, Jean

1998-11-01

Among the mantle hotspots present under oceanic areas, a large number are located on-or close to-active oceanic ridges. This is especially true in the slow-spreading Atlantic and Indian oceans. The recent availability of worldwide gravity grids and the increasing coverage of geochemical data sets along active spreading centres allow a fruitful comparison of these data with global geoid and seismic tomography models, and allow one to study interactions between mantle plumes and active slow-spreading ridges. The observed correlations allow us to draw preliminary conclusions on the general links between surficial processes, which shape the detailed morphology of the ridge axes, and deeper processes, active in the upper mantle below the ridge axial domains as a whole. The interactions are first studied at the scale of the Atlantic (the Mid-Atlantic Ridge from Iceland to Bouvet Island) from the correlation between the zero-age free-air gravity anomaly, which reflects the zero-age depth of the ridge axis, and Sr isotopic ratios of ridge axis basalts. The study is then extended to a more global scale (the slow ridges from Iceland to the Gulf of Aden) by including geoid and upper-mantle tomography models. The interactions appear complex, ranging from the effect of large and very productive plumes, almost totally overprinting the long-wavelength segmentation pattern of the ridge, to that of weaker hotspots, barely marking some of the observables in the ridge axial domain. Intermediate cases are observed, in which hotspots of medium activity (or whose activity has gradually decreased) located at some distance from the ridge axis produce geophysical or geochemical signals whose variation along the axis can be correlated with the geometry of the plume head in the upper mantle. Such observations tend to preclude the use of a single hotspot/ridge interaction model and stress the need for additional observations in various plume/ridge configurations.

Effect of Interactions between Harvester Ants on Forager Decisions

PubMed Central

Davidson, Jacob D.; Arauco-Aliaga, Roxana P.; Crow, Sam; Gordon, Deborah M.; Goldman, Mark S.

2017-01-01

Harvester ant colonies adjust their foraging activity to day-to-day changes in food availability and hour-to-hour changes in environmental conditions. This collective behavior is regulated through interactions, in the form of brief antennal contacts, between outgoing foragers and returning foragers with food. Here we consider how an ant, waiting in the entrance chamber just inside the nest entrance, uses its accumulated experience of interactions to decide whether to leave the nest to forage. Using videos of field observations, we tracked the interactions and foraging decisions of ants in the entrance chamber. Outgoing foragers tended to interact with returning foragers at higher rates than ants that returned to the deeper nest and did not forage. To provide a mechanistic framework for interpreting these results, we develop a decision model in which ants make decisions based upon a noisy accumulation of individual contacts with returning foragers. The model can reproduce core trends and realistic distributions for individual ant interaction statistics, and suggests possible mechanisms by which foraging activity may be regulated at an individual ant level. PMID:28758093

Understanding Physical Activity through Interactions Between the Built Environment and Social Cognition: A Systematic Review.

PubMed

Rhodes, Ryan E; Saelens, Brian E; Sauvage-Mar, Claire

2018-05-16

Few people in most developed nations engage in regular physical activity (PA), despite its well-established health benefits. Socioecological models highlight the potential interaction of multiple factors from policy and the built environment to individual social cognition in explaining PA. The purpose of this review was to appraise this interaction tenet of the socioecological model between the built environment and social cognition to predict PA. Eligible studies had to have been published in peer-reviewed journals in the English language, and included any tests of interaction between social cognition and the built environment with PA. Literature searches, concluded in October 2017, used five common databases. Findings were grouped by type of PA outcomes (leisure, transportation, total PA and total moderate-vigorous PA [MVPA]), then grouped by the type of interactions between social cognitive and built environment constructs. The initial search yielded 308 hits, which was reduced to 22 independent studies of primarily high- to medium-quality after screening for eligibility criteria. The interaction tenet of the socioecological model was not supported for overall MVPA and total PA. By contrast, while there was heterogeneity of findings for leisure-time PA, environmental accessibility/convenience interacted with intention, and environmental aesthetics interacted with affective judgments, to predict leisure-time PA. Interactions between the built environment and social cognition in PA for transport are limited, with current results failing to support an effect. The results provide some support for interactive aspects of the built environment and social cognition in leisure-time PA, and thus highlight potential areas for integrated intervention of individual and environmental change.

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

Linear summation of outputs in a balanced network model of motor cortex.

PubMed

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

Predicting adsorption isotherms for aqueous organic micropollutants from activated carbon and pollutant properties.

PubMed

Li, Lei; Quinlivan, Patricia A; Knappe, Detlef R U

2005-05-01

A method based on the Polanyi-Dubinin-Manes (PDM) model is presented to predict adsorption isotherms of aqueous organic contaminants on activated carbons. It was assumed that trace organic compound adsorption from aqueous solution is primarily controlled by nonspecific dispersive interactions while water adsorption is controlled by specific interactions with oxygen-containing functional groups on the activated carbon surface. Coefficients describing the affinity of water for the activated carbon surface were derived from aqueous-phase methyl tertiary-butyl ether (MTBE) and trichloroethene (TCE) adsorption isotherm data that were collected with 12 well-characterized activated carbons. Over the range of oxygen contents covered by the adsorbents (approximately 0.8-10 mmol O/g dry, ash-free activated carbon), a linear relationship between water affinity coefficients and adsorbent oxygen content was obtained. Incorporating water affinity coefficients calculated from the developed relationship into the PDM model, isotherm predictions resulted that agreed well with experimental data for three adsorbents and two adsorbates [tetrachloroethene (PCE), cis-1,2-dichloroethene (DCE)] that were not used to calibrate the model.

The Flipped Classroom: An active teaching and learning strategy for making the sessions more interactive and challenging.

PubMed

Sultan, Amber Shamim

2018-04-01

Flipping the classroom is a pedagogical model that employs easy to use, readily accessible technology based resources such as video lectures, reading handouts, and practice problems outside the classroom, whereas interactive group-based, problem-solving activities conducted in the classroom. This strategy permits for an extended range of learning activities during the session. Using class time for active learning provides greater opportunity for mentoring and peer to peer collaboration. Instead of spending too much time on delivering lectures, class time can best be utilized by interacting with students, discussing their concerns related to the particular topic to be taught, providing real life examples relevant to the course content, challenging students to think in a broader aspect about complex process and encouraging different team based learning activities.

Thermodynamics-Based Models of Transcriptional Regulation by Enhancers: The Roles of Synergistic Activation, Cooperative Binding and Short-Range Repression

PubMed Central

He, Xin; Samee, Md. Abul Hassan; Blatti, Charles; Sinha, Saurabh

2010-01-01

Quantitative models of cis-regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled, or heuristic approximations of the underlying regulatory mechanisms. We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Using this model on segmentation-related enhancers in Drosophila, we find that transcriptional synergy due to simultaneous action of multiple activators helps explain the data beyond what can be explained by cooperative DNA-binding alone. We find clear support for the phenomenon of short-range repression, where repressors do not directly interact with the basal transcriptional machinery. We also find that the binding sites contributing to an enhancer's function may not be conserved during evolution, and a noticeable fraction of these undergo lineage-specific changes. Our implementation of the model, called GEMSTAT, is the first publicly available program for simultaneously modeling the regulatory activities of a given set of sequences. PMID:20862354

The role of perceived interactivity in virtual communities: building trust and increasing stickiness

NASA Astrophysics Data System (ADS)

Wang, Hongwei; Meng, Yuan; Wang, Wei

2013-03-01

Although previous research has explored factors affecting trust building in websites, little research has been analysed from the perceived interactivity perspective in virtual communities (VCs). A research model for verifying interactivity antecedents to trust and its impact on member stickiness behaviour is presented. Two social interactivity components and two system interactivity components are, respectively, theorised as process-based antecedents and institution-based antecedents to trust in the model. Data were collected from 310 members of VCs to test the model. The results show that connectedness and reciprocity are important antecedents to trust in members, while responsiveness and active control are important antecedents to trust in systems. The results also indicate that trust has significant influence on the members' duration and retention, which are two dimensions of member stickiness measured in this research. These findings have theoretical implications for online interaction-related literature and critical business implications for practitioners of VCs.

Improving Learning with the Critical Thinking Paradigm: MIBOLC Modules A and B

DTIC Science & Technology

2009-02-06

Model encourages more active learning by requiring much of the learning material to be read prior to classroom instruction, and allotting more time to...for mental interaction with content Rote memorization Multiple Choice exams/quizzes Lower level of intensity in course work Active ... Learning Engaged Lecture Requires mental interaction with content Close reading to understand essential ideas Exams/Quizzes reflective of

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

Active and regulatory sites of cytosolic 5'-nucleotidase.

PubMed

Pesi, Rossana; Allegrini, Simone; Careddu, Maria Giovanna; Filoni, Daniela Nicole; Camici, Marcella; Tozzi, Maria Grazia

2010-12-01

Cytosolic 5'-nucleotidase (cN-II), which acts preferentially on 6-hydroxypurine nucleotides, is essential for the survival of several cell types. cN-II catalyses both the hydrolysis of nucleotides and transfer of their phosphate moiety to a nucleoside acceptor through formation of a covalent phospho-intermediate. Both activities are regulated by a number of phosphorylated compounds, such as diadenosine tetraphosphate (Ap₄A), ADP, ATP, 2,3-bisphosphoglycerate (BPG) and phosphate. On the basis of a partial crystal structure of cN-II, we mutated two residues located in the active site, Y55 and T56. We ascertained that the ability to catalyse the transfer of phosphate depends on the presence of a bulky residue in the active site very close to the aspartate residue that forms the covalent phospho-intermediate. The molecular model indicates two possible sites at which adenylic compounds may interact. We mutated three residues that mediate interaction in the first activation site (R144, N154, I152) and three in the second (F127, M436 and H428), and found that Ap₄A and ADP interact with the same site, but the sites for ATP and BPG remain uncertain. The structural model indicates that cN-II is a homotetrameric protein that results from interaction through a specific interface B of two identical dimers that have arisen from interaction of two identical subunits through interface A. Point mutations in the two interfaces and gel-filtration experiments indicated that the dimer is the smallest active oligomerization state. Finally, gel-filtration and light-scattering experiments demonstrated that the native enzyme exists as a tetramer, and no further oligomerization is required for enzyme activation. © 2010 The Authors Journal compilation © 2010 FEBS.

In Vitro Drug Interaction Modeling of Combinations of Azoles with Terbinafine against Clinical Scedosporium prolificans Isolates

PubMed Central

Meletiadis, Joseph; Mouton, Johan W.; Meis, Jacques F. G. M.; Verweij, Paul E.

2003-01-01

The in vitro interaction between terbinafine and the azoles voriconazole, miconazole, and itraconazole against five clinical Scedosporium prolificans isolates after 48 and 72 h of incubation was tested by a microdilution checkerboard (eight-by-twelve) technique. The antifungal effects of the drugs alone and in combination on the fungal biomass as well as on the metabolic activity of fungi were measured using a spectrophotometric method and two colorimetric methods, based on the lowest drug concentrations showed 75 and 50% growth inhibition (MIC-1 and MIC-2, respectively). The nature and the intensity of the interactions were assessed using a nonparametric approach (fractional inhibitory concentration [FIC] index model) and a fully parametric response surface approach (Greco model) of the Loewe additivity (LA) no-interaction theory as well as a nonparametric (Prichard model) and a semiparametric response surface approaches of the Bliss independence (BI) no-interaction theory. Statistically significant synergy was found between each of the three azoles and terbinafine in all cases, although with different intensities. A 27- to 64-fold and 16- to 90-fold reduction of the geometric mean of the azole and terbinafine MICs, respectively, was observed when they were combined, resulting in FIC indices of <1 to 0.02. Using the MIC-1 higher levels of synergy were obtained, , which were more consistent between the two incubation periods than using the MIC-2. The strongest synergy among the azoles was found with miconazole using the BI-based models and with voriconazole using the LA-based models. The synergistic effects both on fungal growth and metabolic activity were more potent after 72 h of incubation. Fully parametric approaches in combination with the modified colorimetric method might prove useful for testing the in vitro interaction of antifungal drugs against filamentous fungi. PMID:12499177

Connectionist Interaction Information Retrieval.

ERIC Educational Resources Information Center

Dominich, Sandor

2003-01-01

Discussion of connectionist views for adaptive clustering in information retrieval focuses on a connectionist clustering technique and activation spreading-based information retrieval model using the interaction information retrieval method. Presents theoretical as well as simulation results as regards computational complexity and includes…

Modification of social withdrawal through symbolic modeling1

PubMed Central

O'Connor, Robert D.

1969-01-01

The present experiment was designed to test the efficacy of symbolic modeling as a treatment to enhance social behavior in preschool isolates. Nursery school children who displayed marked social withdrawal were assigned to one of two conditions. One group observed a film depicting increasingly more active social interactions between children with positive consequences ensuing in each scene, while a narrative soundtrack emphasized the appropriate behavior of the models. A control group observed a film that contained no social interaction. Control children displayed no change in withdrawal behavior, whereas those who had the benefit of symbolic modeling increased their level of social interaction to that of non-isolate nursery school children. PMID:16795196

Exploring the interaction of patient activation and message design variables: message frame and presentation mode influence on the walking behavior of patients with type 2 diabetes.

PubMed

Ledford, Christy J W

2012-10-01

Examining interpersonal (physician-patient) communication strategies for promoting walking exercise to patients with type 2 diabetes assigned to primary care clinics, the study evaluated two message design variables--frame and presentation mode--as influencers of communication and adoption success. The single-site, four-week, prospective intervention study followed a 2×3 factorial, non-equivalent comparison group quasi-experimental design. Results showed frame was significantly related to steps walked; however, when including patient activation as an interaction, frame was non-significant. The model including patient activation interactions, however, detected significant mode effects on behavior. Results provide evidence that statistics are most effectively used with activated patients.

Confirmation of high-throughput screening data and novel mechanistic insights into VDR-xenobiotic interactions by orthogonal assays.

PubMed

Mahapatra, Debabrata; Franzosa, Jill A; Roell, Kyle; Kuenemann, Melaine Agnes; Houck, Keith A; Reif, David M; Fourches, Denis; Kullman, Seth W

2018-06-11

High throughput screening (HTS) programs have demonstrated that the Vitamin D receptor (VDR) is activated and/or antagonized by a wide range of structurally diverse chemicals. In this study, we examined the Tox21 qHTS data set generated against VDR for reproducibility and concordance and elucidated functional insights into VDR-xenobiotic interactions. Twenty-one potential VDR agonists and 19 VDR antagonists were identified from a subset of >400 compounds with putative VDR activity and examined for VDR functionality utilizing select orthogonal assays. Transient transactivation assay (TT) using a human VDR plasmid and Cyp24 luciferase reporter construct revealed 20/21 active VDR agonists and 18/19 active VDR antagonists. Mammalian-2-hybrid assay (M2H) was then used to evaluate VDR interactions with co-activators and co-regulators. With the exception of a select few compounds, VDR agonists exhibited significant recruitment of co-regulators and co-activators whereas antagonists exhibited considerable attenuation of recruitment by VDR. A unique set of compounds exhibiting synergistic activity in antagonist mode and no activity in agonist mode was identified. Cheminformatics modeling of VDR-ligand interactions were conducted and revealed selective ligand VDR interaction. Overall, data emphasizes the molecular complexity of ligand-mediated interactions with VDR and suggest that VDR transactivation may be a target site of action for diverse xenobiotics.

Task Analytic Models to Guide Analysis and Design: Use of the Operator Function Model to Represent Pilot-Autoflight System Mode Problems

NASA Technical Reports Server (NTRS)

Degani, Asaf; Mitchell, Christine M.; Chappell, Alan R.; Shafto, Mike (Technical Monitor)

1995-01-01

Task-analytic models structure essential information about operator interaction with complex systems, in this case pilot interaction with the autoflight system. Such models serve two purposes: (1) they allow researchers and practitioners to understand pilots' actions; and (2) they provide a compact, computational representation needed to design 'intelligent' aids, e.g., displays, assistants, and training systems. This paper demonstrates the use of the operator function model to trace the process of mode engagements while a pilot is controlling an aircraft via the, autoflight system. The operator function model is a normative and nondeterministic model of how a well-trained, well-motivated operator manages multiple concurrent activities for effective real-time control. For each function, the model links the pilot's actions with the required information. Using the operator function model, this paper describes several mode engagement scenarios. These scenarios were observed and documented during a field study that focused on mode engagements and mode transitions during normal line operations. Data including time, ATC clearances, altitude, system states, and active modes and sub-modes, engagement of modes, were recorded during sixty-six flights. Using these data, seven prototypical mode engagement scenarios were extracted. One scenario details the decision of the crew to disengage a fully automatic mode in favor of a semi-automatic mode, and the consequences of this action. Another describes a mode error involving updating aircraft speed following the engagement of a speed submode. Other scenarios detail mode confusion at various phases of the flight. This analysis uses the operator function model to identify three aspects of mode engagement: (1) the progress of pilot-aircraft-autoflight system interaction; (2) control/display information required to perform mode management activities; and (3) the potential cause(s) of mode confusion. The goal of this paper is twofold: (1) to demonstrate the use of the operator functio model methodology to describe pilot-system interaction while engaging modes And monitoring the system, and (2) to initiate a discussion of how task-analytic models might inform design processes. While the operator function model is only one type of task-analytic representation, the hypothesis of this paper is that some type of task analytic structure is a prerequisite for the design of effective human-automation interaction.

Physicochemical modeling of reactive violet 5 dye adsorption on home-made cocoa shell and commercial activated carbons using the statistical physics theory

NASA Astrophysics Data System (ADS)

Sellaoui, Lotfi; Lima, Éder Cláudio; Dotto, Guilherme Luiz; Dias, Silvio L. P.; Ben Lamine, Abdelmottaleb

Two equilibrium models based on statistical physics, i.e., monolayer model with single energy and multilayer model with saturation, were developed and employed to access the steric and energetic aspects in the adsorption of reactive violet 5 dye (RV-5) on cocoa shell activated carbon (AC) and commercial activated carbon (CAC), at different temperatures (from 298 to 323 K). The results showed that the multilayer model with saturation was able to represent the adsorption system. This model assumes that the adsorption occurs by a formation of certain number of layers. The n values ranged from 1.10 to 2.98, indicating that the adsorbate molecules interacted in an inclined position on the adsorbent surface and aggregate in solution. The study of the total number of the formed layers (1 + L2) showed that the steric hindrance is the dominant factor. The description of the adsorbate-adsorbent interactions by calculation of the adsorption energy indicated that the process occurred by physisorption in nature, since the values were lower than 40 kJ mol-1.

Toward a complex system understanding of bipolar disorder: A chaotic model of abnormal circadian activity rhythms in euthymic bipolar disorder.

PubMed

Hadaeghi, Fatemeh; Hashemi Golpayegani, Mohammad Reza; Jafari, Sajad; Murray, Greg

2016-08-01

In the absence of a comprehensive neural model to explain the underlying mechanisms of disturbed circadian function in bipolar disorder, mathematical modeling is a helpful tool. Here, circadian activity as a response to exogenous daily cycles is proposed to be the product of interactions between neuronal networks in cortical (cognitive processing) and subcortical (pacemaker) areas of the brain. To investigate the dynamical aspects of the link between disturbed circadian activity rhythms and abnormalities of neurotransmitter functioning in frontal areas of the brain, we developed a novel mathematical model of a chaotic system which represents fluctuations in circadian activity in bipolar disorder as changes in the model's parameters. A novel map-based chaotic system was developed to capture disturbances in circadian activity across the two extreme mood states of bipolar disorder. The model uses chaos theory to characterize interplay between neurotransmitter functions and rhythm generation; it aims to illuminate key activity phenomenology in bipolar disorder, including prolonged sleep intervals, decreased total activity and attenuated amplitude of the diurnal activity rhythm. To test our new cortical-circadian mathematical model of bipolar disorder, we utilized previously collected locomotor activity data recorded from normal subjects and bipolar patients by wrist-worn actigraphs. All control parameters in the proposed model have an important role in replicating the different aspects of circadian activity rhythm generation in the brain. The model can successfully replicate deviations in sleep/wake time intervals corresponding to manic and depressive episodes of bipolar disorder, in which one of the excitatory or inhibitory pathways is abnormally dominant. Although neuroimaging research has strongly implicated a reciprocal interaction between cortical and subcortical regions as pathogenic in bipolar disorder, this is the first model to mathematically represent this multilevel explanation of the phenomena of bipolar disorder. © The Royal Australian and New Zealand College of Psychiatrists 2016.

Modeling the inhibition of quadruple mutant Plasmodium falciparum dihydrofolate reductase by pyrimethamine derivatives

NASA Astrophysics Data System (ADS)

Fogel, Gary B.; Cheung, Mars; Pittman, Eric; Hecht, David

2008-01-01

Modeling studies were performed on known inhibitors of the quadruple mutant Plasmodium falciparum dihydrofolate reductase (DHFR). GOLD was used to dock 32 pyrimethamine derivatives into the active site of DHFR obtained from the x-ray crystal structure 1J3K.pdb. Several scoring functions were evaluated and the Molegro Protein-Ligand Interaction Score was determined to have one of the best correlation to experimental p K i . In conjunction with Protein-Ligand Interaction scores, predicted binding modes and key protein-ligand interactions were evaluated and analyzed in order to develop criteria for selecting compounds having a greater chance of activity versus resistant strains of Plasmodium falciparum. This methodology will be used in future studies for selection of compounds for focused screening libraries.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

PubMed Central

Gerstner, Wulfram

2017-01-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

Cookie-Ases: Interactive Models for Teaching Genotype-Phenotype Relationships

ERIC Educational Resources Information Center

Seipelt, Rebecca L.

2006-01-01

Several hands-on and wet laboratory activities have been proposed to model the genetic concepts of genotypes and phenotypes and their relationship. The exercise presented in this article is a novel, time effective, student-centered, role-playing activity in which students learn about the intricate connection between genotype and phenotype by…

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…

Meet the Molecules in Chocolate: Informal Opportunities for Building Thematic Molecular Models with Children

ERIC Educational Resources Information Center

Amey, Jennifer R.; Fletcher, Matthew D.; Fletcher, Rachael V.; Jones, Alison; Roberts, Erica W.; Roberts, Ieuan O.

2008-01-01

We describe the development and use of a molecular model building activity with a chocolate theme, suitable for a public presentation of chemistry through interaction with visitors to science festivals and museums, and as a special classroom activity during science weeks, and so forth. (Contains 3 figures.)

Vodcasts and active-learning exercises in a "flipped classroom" model of a renal pharmacotherapy module.

PubMed

Pierce, Richard; Fox, Jeremy

2012-12-12

To implement a "flipped classroom" model for a renal pharmacotherapy topic module and assess the impact on pharmacy students' performance and attitudes. Students viewed vodcasts (video podcasts) of lectures prior to the scheduled class and then discussed interactive cases of patients with end-stage renal disease in class. A process-oriented guided inquiry learning (POGIL) activity was developed and implemented that complemented, summarized, and allowed for application of the material contained in the previously viewed lectures. Students' performance on the final examination significantly improved compared to performance of students the previous year who completed the same module in a traditional classroom setting. Students' opinions of the POGIL activity and the flipped classroom instructional model were mostly positive. Implementing a flipped classroom model to teach a renal pharmacotherapy module resulted in improved student performance and favorable student perceptions about the instructional approach. Some of the factors that may have contributed to students' improved scores included: student mediated contact with the course material prior to classes, benchmark and formative assessments administered during the module, and the interactive class activities.

Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling.

PubMed

Garcia, Leandro M T; Diez Roux, Ana V; Martins, André C R; Yang, Yong; Florindo, Alex A

2017-08-22

Despite the increasing body of evidences on the factors influencing leisure-time physical activity, our understanding of the mechanisms and interactions that lead to the formation and evolution of population patterns is still limited. Moreover, most frameworks in this field fail to capture dynamic processes. Our aim was to create a dynamic conceptual model depicting the interaction between key psychological attributes of individuals and main aspects of the built and social environments in which they live. This conceptual model will inform and support the development of an agent-based model aimed to explore how population patterns of LTPA in adults may emerge from the dynamic interplay between psychological traits and built and social environments. We integrated existing theories and models as well as available empirical data (both from literature reviews), and expert opinions (based on a systematic expert assessment of an intermediary version of the model). The model explicitly presents intention as the proximal determinant of leisure-time physical activity, a relationship dynamically moderated by the built environment (access, quality, and available activities) - with the strength of the moderation varying as a function of the person's intention- and influenced both by the social environment (proximal network's and community's behavior) and the person's behavior. Our conceptual model is well supported by evidence and experts' opinions and will inform the design of our agent-based model, as well as data collection and analysis of future investigations on population patterns of leisure-time physical activity among adults.

Comparative Molecular Dynamics Simulations of Mitogen-Activated Protein Kinase-Activated Protein Kinase 5

PubMed Central

Lindin, Inger; Wuxiuer, Yimingjiang; Ravna, Aina Westrheim; Moens, Ugo; Sylte, Ingebrigt

2014-01-01

The mitogen-activated protein kinase-activated protein kinase MK5 is a substrate of the mitogen-activated protein kinases p38, ERK3 and ERK4. Cell culture and animal studies have demonstrated that MK5 is involved in tumour suppression and promotion, embryogenesis, anxiety, cell motility and cell cycle regulation. In the present study, homology models of MK5 were used for molecular dynamics (MD) simulations of: (1) MK5 alone; (2) MK5 in complex with an inhibitor; and (3) MK5 in complex with the interaction partner p38α. The calculations showed that the inhibitor occupied the active site and disrupted the intramolecular network of amino acids. However, intramolecular interactions consistent with an inactive protein kinase fold were not formed. MD with p38α showed that not only the p38 docking region, but also amino acids in the activation segment, αH helix, P-loop, regulatory phosphorylation region and the C-terminal of MK5 may be involved in forming a very stable MK5-p38α complex, and that p38α binding decreases the residual fluctuation of the MK5 model. Electrostatic Potential Surface (EPS) calculations of MK5 and p38α showed that electrostatic interactions are important for recognition and binding. PMID:24651460

Requirements for psychological models to support design: Towards ecological task analysis

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Cognitive engineering is largely concerned with creating environmental designs to support skillful and effective human activity. A set of necessary conditions are proposed for psychological models capable of supporting this enterprise. An analysis of the psychological nature of the design product is used to identify a set of constraints that models must meet if they can usefully guide design. It is concluded that cognitive engineering requires models with resources for describing the integrated human-environment system, and that these models must be capable of describing the activities underlying fluent and effective interaction. These features are required in order to be able to predict the cognitive activity that will be required given various design concepts, and to design systems that promote the acquisition of fluent, skilled behavior. These necessary conditions suggest that an ecological approach can provide valuable resources for psychological modeling to support design. Relying heavily on concepts from Brunswik's and Gibson's ecological theories, ecological task analysis is proposed as a framework in which to predict the types of cognitive activity required to achieve productive behavior, and to suggest how interfaces can be manipulated to alleviate certain types of cognitive demands. The framework is described in terms, and illustrated with an example from the previous research on modeling skilled human-environment interaction.

Electromechanical modelling and design for phase control of locked modes in the DIII-D tokamak

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

Olofsson, K. E. J.; Choi, W.; Humphreys, D. A.

A basic nonlinear electromechanical model is developed for the interaction between a pre-existing near-saturated tearing-mode, a conducting wall, active coils internal to the wall, and active coils external to the wall. The tearing-mode is represented by a perturbed helical surface current and its island has a small but finite moment of inertia. The model is shown to have several properties that are qualitatively consistent with the experimental observations of mode-wall and mode-coil interactions. The main purpose of the model is to guide the design of a phase control system for locked modes (LMs) in tokamaks. Such a phase controller maymore » become an important component in integrated disruption avoidance systems. A realistic feedback controller for the LM phase is designed and tested for the electromechanical model. The results indicate that a simple fixed-gain controller can perform phase control of LMs with a range of sizes, and at arbitrary misalignment relative to a realistically dimensioned background error field. Finally, the basic model is expected to be a useful minimal dynamical system representation also for other aspects of mode-wall-coil interactions.« less

Electromechanical modelling and design for phase control of locked modes in the DIII-D tokamak

DOE PAGES

Olofsson, K. E. J.; Choi, W.; Humphreys, D. A.; ...

2016-02-05

A basic nonlinear electromechanical model is developed for the interaction between a pre-existing near-saturated tearing-mode, a conducting wall, active coils internal to the wall, and active coils external to the wall. The tearing-mode is represented by a perturbed helical surface current and its island has a small but finite moment of inertia. The model is shown to have several properties that are qualitatively consistent with the experimental observations of mode-wall and mode-coil interactions. The main purpose of the model is to guide the design of a phase control system for locked modes (LMs) in tokamaks. Such a phase controller maymore » become an important component in integrated disruption avoidance systems. A realistic feedback controller for the LM phase is designed and tested for the electromechanical model. The results indicate that a simple fixed-gain controller can perform phase control of LMs with a range of sizes, and at arbitrary misalignment relative to a realistically dimensioned background error field. Finally, the basic model is expected to be a useful minimal dynamical system representation also for other aspects of mode-wall-coil interactions.« less

In vivo pharmacological interactions between a type II positive allosteric modulator of α7 nicotinic ACh receptors and nicotinic agonists in a murine tonic pain model

PubMed Central

Freitas, K; Negus, SS; Carroll, FI; Damaj, MI

2013-01-01

Background and Purpose The α7 nicotinic ACh receptor subtype is abundantly expressed in the CNS and in the periphery. Recent evidence suggests that α7 nicotinic ACh receptor (nAChR) subtypes, which can be activated by an endogenous cholinergic tone comprising ACh and the α7 agonist choline, play an important role in chronic pain and inflammation. In this study, we evaluated whether type II α7 positive allosteric modulator PNU-120596 induces antinociception on its own and in combination with choline in the formalin pain model. Experimental Approach We assessed the effects of PNU-120596 and choline and the nature of their interactions in the formalin test using an isobolographic analysis. In addition, we evaluated the interaction of PNU-120596 with PHA-54613, an exogenous selective α7 nAChR agonist, in the formalin test. Finally, we assessed the interaction between PNU-120596 and nicotine using acute thermal pain, locomotor activity, body temperature and convulsing activity tests in mice. Key Results We found that PNU-120596 dose-dependently attenuated nociceptive behaviour in the formalin test after systemic administration in mice. In addition, mixtures of PNU-120596 and choline synergistically reduced formalin-induced pain. PNU-120596 enhanced the effects of nicotine and α7 agonist PHA-543613 in the same test. In contrast, PNU-120596 failed to enhance nicotine-induced convulsions, hypomotility and antinociception in acute pain models. Surprisingly, it enhanced nicotine-induced hypothermia via activation of α7 nAChRs. Conclusions and Implications Our results demonstrate that type II α7 positive allosteric modulators produce antinociceptive effects in the formalin test through a synergistic interaction with the endogenous α7 agonist choline. PMID:23004024

Brief Report: Effects of Video-Based Group Instruction on Spontaneous Social Interaction of Adolescents with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Plavnick, Joshua B.; Dueñas, Ana D.

2018-01-01

Four adolescents with autism spectrum disorder (ASD) were taught to interact with peers by asking social questions or commenting about others during game play or group activities. Participants were shown a video model and then given an opportunity to perform the social behavior depicted in the model when playing a game with one another. All…

Simulating forest landscape disturbances as coupled human and natural systems

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Liu, Zhihua; Lamsal, Aashis

2015-01-01

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

Ratchet Effects in Active Matter Systems

DOE PAGES

Reichhardt, Cynthia Jane; Reichhardt, Charles

2016-12-21

Ratchet effects can arise for single or collectively interacting Brownian particles on an asymmetric substrate when a net dc transport is produced by an externally applied ac driving force or by periodically flashing the substrate. Recently, a new class of active ratchet systems that do not require the application of external driving has been realized through the use of active matter; they are self-propelled units that can be biological or nonbiological in nature. When active materials such as swimming bacteria interact with an asymmetric substrate, a net dc directed motion can arise even without external driving, opening a wealth ofmore » possibilities such as sorting, cargo transport, or micromachine construction. We review the current status of active matter ratchets for swimming bacteria, cells, active colloids, and swarming models, focusing on the role of particle-substrate interactions. Here, we describe ratchet reversals produced by collective effects and the use of active ratchets to transport passive particles. We discuss future directions including deformable substrates or particles, the role of different swimming modes, varied particle–particle interactions, and nondissipative effects.« less

Activation of basolateral amygdala in juvenile C57BL/6J mice during social approach behavior.

PubMed

Ferri, Sarah L; Kreibich, Arati S; Torre, Matthew; Piccoli, Cara T; Dow, Holly; Pallathra, Ashley A; Li, Hongzhe; Bilker, Warren B; Gur, Ruben C; Abel, Ted; Brodkin, Edward S

2016-10-29

There is a strong need to better understand the neurobiology of juvenile sociability (tendency to seek social interaction), a phenotype of central relevance to autism spectrum disorders (ASD). Although numerous genetic mouse models of ASD showing reduced sociability have been reported, and certain brain regions, such as the amygdala, have been implicated in sociability, there has been little emphasis on delineating brain structures and circuits activated during social interactions in the critical juvenile period of the mouse strain that serves as the most common genetic background for these models-the highly sociable C57BL/6J (B6) strain. We measured expression of the immediate early genes Fos and Egr-1 to map activation of brain regions following the Social Approach Test (SAT) in juvenile male B6 mice. We hypothesized that juvenile B6 mice would show activation of the amygdala during social interactions. The basolateral amygdala (BLA) was activated by social exposure in highly sociable, 4-week-old B6 mice. In light of these data, and the many lines of evidence indicating alteration of amygdala circuits in human ASD, future studies are warranted to assess structural and functional alterations in the BLA, particularly at BLA synapses, in various mouse models of ASD. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

PubMed Central

Melo, Manuel N.; Ferre, Rafael; Feliu, Lídia; Bardají, Eduard; Planas, Marta; Castanho, Miguel A. R. B.

2011-01-01

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations. PMID:22194847

Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates

Treesearch

Rachel A. Loehman; Robert E. Keane; Lisa M. Holsinger; Zhiwei Wu

2017-01-01

Context: Interactions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs. Objectives We used the mechanistic...

An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

PubMed

Kittelmann, Jörg; Lang, Katharina M H; Ottens, Marcel; Hubbuch, Jürgen

2017-01-27

Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases. Copyright © 2016 Elsevier B.V. All rights reserved.

HETEROTYPIC INTERACTIONS ENABLED BY POLARIZED NEUTROPHIL MICRODOMAINS MEDIATE THROMBO-INFLAMMATORY INJURY

PubMed Central

Hidalgo, Andrés; Chang, Jungshan; Jang, Jung-Eun; Peired, Anna J.; Chiang, Elaine Y.; Frenette, Paul S.

2009-01-01

Selectins and their ligands mediate leukocyte rolling allowing interactions with chemokines that lead to integrin activation and arrest. Here, we demonstrate that E-selectin is critical to induce a secondary wave of activating signals transduced specifically by E-selectin ligand-1, that induces polarized, activated αMβ2 integrin clusters at the leading edge of crawling neutrophils, allowing the capture of circulating erythrocytes or platelets. In a humanized model of sickle cell disease (SCD), the capture of erythrocytes by αMβ2 microdomains leads to acute lethal vascular occlusions. In a model of transfusion-related acute lung injury, polarized neutrophils capture circulating platelets, resulting in the generation of oxidative species that produces vascular damage and lung injury. Inactivation of E-selectin or αMβ2 prevented tissue injury in both inflammatory models, suggesting broad implications of this paradigm in thrombo-inflammatory diseases. These results indicate that endothelial selectins can influence neutrophil behavior beyond its canonical rolling step through delayed, organ-damaging, polarized activation. PMID:19305412

Chitosan derivatives targeting lipid bilayers: Synthesis, biological activity and interaction with model membranes.

PubMed

Martins, Danubia Batista; Nasário, Fábio Domingues; Silva-Gonçalves, Laiz Costa; de Oliveira Tiera, Vera Aparecida; Arcisio-Miranda, Manoel; Tiera, Marcio José; Dos Santos Cabrera, Marcia Perez

2018-02-01

The antimicrobial activity of chitosan and derivatives to human and plant pathogens represents a high-valued prospective market. Presently, two low molecular weight derivatives, endowed with hydrophobic and cationic character at different ratios were synthesized and characterized. They exhibit antimicrobial activity and increased performance in relation to the intermediate and starting compounds. However, just the derivative with higher cationic character showed cytotoxicity towards human cervical carcinoma cells. Considering cell membranes as targets, the mode of action was investigated through the interaction with model lipid vesicles mimicking bacterial, tumoral and erythrocyte membranes. Intense lytic activity and binding are demonstrated for both derivatives in anionic bilayers. The less charged compound exhibits slightly improved selectivity towards bacterial model membranes, suggesting that balancing its hydrophobic/hydrophilic character may improve efficiency. Observing the aggregation of vesicles, we hypothesize that the "charge cluster mechanism", ascribed to some antimicrobial peptides, could be applied to these chitosan derivatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cross-stream migration of active particles

NASA Astrophysics Data System (ADS)

Uspal, William; Katuri, Jaideep; Simmchen, Juliane; Miguel-Lopez, Albert; Sanchez, Samuel

For natural microswimmers, the interplay of swimming activity and external flow can promote robust directed motion, e.g. propulsion against (upstream rheotaxis) or perpendicular to the direction of flow. These effects are generally attributed to their complex body shapes and flagellar beat patterns. Here, using catalytic Janus particles as a model system, we report on a strong directional response that naturally emerges for spherical active particles in a channel flow. The particles align their propulsion axis to be perpendicular to both the direction of flow and the normal vector of a nearby bounding surface. We develop a deterministic theoretical model that captures this spontaneous transverse orientational order. We show how the directional response emerges from the interplay of external shear flow and swimmer/surface interactions (e.g., hydrodynamic interactions) that originate in swimming activity. Finally, adding the effect of thermal noise, we obtain probability distributions for the swimmer orientation that show good agreement with the experimental probability distributions. Our findings show that the qualitative response of microswimmers to flow is sensitive to the detailed interaction between individual microswimmers and bounding surfaces.

Brownian microhydrodynamics of active filaments.

PubMed

Laskar, Abhrajit; Adhikari, R

2015-12-21

Slender bodies capable of spontaneous motion in the absence of external actuation in an otherwise quiescent fluid are common in biological, physical and technological contexts. The interplay between the spontaneous fluid flow, Brownian motion, and the elasticity of the body presents a challenging fluid-structure interaction problem. Here, we model this problem by approximating the slender body as an elastic filament that can impose non-equilibrium velocities or stresses at the fluid-structure interface. We derive equations of motion for such an active filament by enforcing momentum conservation in the fluid-structure interaction and assuming slow viscous flow in the fluid. The fluid-structure interaction is obtained, to any desired degree of accuracy, through the solution of an integral equation. A simplified form of the equations of motion, which allows for efficient numerical solutions, is obtained by applying the Kirkwood-Riseman superposition approximation to the integral equation. We use this form of equation of motion to study dynamical steady states in free and hinged minimally active filaments. Our model provides the foundation to study collective phenomena in momentum-conserving, Brownian, active filament suspensions.

Biochemistry students' ideas about how an enzyme interacts with a substrate.

PubMed

Linenberger, Kimberly J; Bretz, Stacey Lowery

2015-01-01

Enzyme-substrate interactions are a fundamental concept of biochemistry that is built upon throughout multiple biochemistry courses. Central to understanding enzyme-substrate interactions is specific knowledge of exactly how an enzyme and substrate interact. Within this narrower topic, students must understand the various binding sites on an enzyme and be able to reason from simplistic lock and key or induced fit models to the more complex energetics model of transition state theory. Learning to understand these many facets of enzyme-substrate interactions and reasoning from multiple models present challenges where students incorrectly make connections between concepts or make no connection at all. This study investigated biochemistry students' understanding of enzyme-substrate interactions through the use of clinical interviews and a national administration (N = 707) of the Enzyme-Substrate Interactions Concept Inventory. Findings include misconceptions regarding the nature of enzyme-substrate interactions, naïve ideas about the active site, a lack of energetically driven interactions, and an incomplete understanding of the specificity pocket. © 2015 by the International Union of Biochemistry and Molecular Biology.

Hydrodynamic interaction of a self-propelling particle with a wall : Comparison between an active Janus particle and a squirmer model.

PubMed

Shen, Zaiyi; Würger, Alois; Lintuvuori, Juho S

2018-03-27

Using lattice Boltzmann simulations we study the hydrodynamics of an active spherical particle near a no-slip wall. We develop a computational model for an active Janus particle, by considering different and independent mobilities on the two hemispheres and compare the behaviour to a standard squirmer model. We show that the topology of the far-field hydrodynamic nature of the active Janus particle is similar to the standard squirmer model, but in the near-field the hydrodynamics differ. In order to study how the near-field effects affect the interaction between the particle and a flat wall, we compare the behaviour of a Janus swimmer and a squirmer near a no-slip surface via extensive numerical simulations. Our results show generally a good agreement between these two models, but they reveal some key differences especially with low magnitudes of the squirming parameter [Formula: see text]. Notably the affinity of the particles to be trapped at a surface is increased for the active Janus particles when compared to standard squirmers. Finally, we find that when the particle is trapped on the surface, the velocity parallel to the surface exceeds the bulk swimming speed and scales linearly with [Formula: see text].

Gene–Physical Activity Interactions: Overview of Human Studies

PubMed Central

Rankinen, Tuomo; Bouchard, Claude

2009-01-01

Physical activity level is an important component of the total daily energy expenditure and as such contributes to body weight regulation. A body of data indicates that the level of physical activity plays a role in the risk of excessive weight gain, in weight loss programs, and particularly in the prevention of weight regain. Most studies dealing with potential gene–physical activity interaction effects use an exercise and fitness or performance paradigm as opposed to an obesity-driven model. From these studies, it is clear that there are considerable individual differences in the response to an exercise regimen and that there is a substantial familial aggregation component to the observed heterogeneity. Few studies have focused on the role of specific genes in accounting for the highly prevalent gene–exercise interaction effects. Results for specific genes have been inconsistent with few exceptions. Progress is likely to come when studies will be designed to truly address gene–exercise or physical activity interaction issues and with sample sizes that will provide adequate statistical power. PMID:19037212

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

Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

PubMed

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

PubMed Central

Putz, Mihai V.; Duda-Seiman, Corina; Duda-Seiman, Daniel; Putz, Ana-Maria; Alexandrescu, Iulia; Mernea, Maria; Avram, Speranta

2016-01-01

Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions. PMID:27399692

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.

Paired and interacting galaxies: Conference summary

NASA Technical Reports Server (NTRS)

Norman, Colin A.

1990-01-01

The author gives a summary of the conference proceedings. The conference began with the presentation of the basic data sets on pairs, groups, and interacting galaxies with the latter being further discussed with respect to both global properties and properties of the galactic nuclei. Then followed the theory, modelling and interpretation using analytic techniques, simulations and general modelling for spirals and ellipticals, starbursts and active galactic nuclei. Before the conference the author wrote down the three questions concerning pairs, groups and interacting galaxies that he hoped would be answered at the meeting: (1) How do they form, including the role of initial conditions, the importance of subclustering, the evolution of groups to compact groups, and the fate of compact groups; (2) How do they evolve, including issues such as relevant timescales, the role of halos and the problem of overmerging, the triggering and enhancement of star formation and activity in the galactic nuclei, and the relative importance of dwarf versus giant encounters; and (3) Are they important, including the frequency of pairs and interactions, whether merging and interactions are very important aspects of the life of a normal galaxy at formation, during its evolution, in forming bars, shells, rings, bulges, etc., and in the formation and evolution of active galaxies? Where possible he focuses on these three central issues in the summary.

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

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

Genetic Susceptibility, Change in Physical Activity, and Long-term Weight Gain.

PubMed

Wang, Tiange; Huang, Tao; Heianza, Yoriko; Sun, Dianjianyi; Zheng, Yan; Ma, Wenjie; Jensen, Majken K; Kang, Jae H; Wiggs, Janey L; Pasquale, Louis R; Rimm, Eric B; Manson, JoAnn E; Hu, Frank B; Willett, Walter C; Qi, Lu

2017-10-01

Whether change in physical activity over time modifies the genetic susceptibility to long-term weight gain is unknown. We calculated a BMI-genetic risk score (GRS) based on 77 BMI-associated single nucleotide polymorphisms (SNPs) and a body fat percentage (BF%)-GRS based on 12 BF%-associated SNPs in 9,390 women from the Nurses' Health Study (NHS) and 5,291 men from the Health Professionals Follow-Up Study (HPFS). We analyzed the interactions between each GRS and change in physical activity on BMI/body weight change within five 4-year intervals from 1986 to 2006 using multivariable generalized linear models with repeated-measures analyses. Both the BMI-GRS and the BF%-GRS were associated with long-term increases in BMI/weight, and change in physical activity consistently interacted with the BF%-GRS on BMI change in the NHS ( P for interaction = 0.025) and HPFS ( P for interaction = 0.001). In the combined cohorts, 4-year BMI change per 10-risk allele increment was -0.02 kg/m 2 among participants with greatest increase in physical activity and 0.24 kg/m 2 among those with greatest decrease in physical activity ( P for interaction < 0.001), corresponding to 0.01 kg versus 0.63 kg weight changes every 4 years ( P for interaction = 0.001). Similar but marginal interactions were observed for the BMI-GRS ( P for interaction = 0.045). Our data indicate that the genetic susceptibility to weight gain may be diminished by increasing physical activity. © 2017 by the American Diabetes Association.

Shear Forces during Blast, Not Abrupt Changes in Pressure Alone, Generate Calcium Activity in Human Brain Cells

DTIC Science & Technology

2012-06-29

the tissue-force interaction(s) and the cellular damage properties remain unresolved. Studies on a mechanical head model demonstrated high transient...that pressure transient. In vitro models of primary blast injury [5,18,19] are likewise limited by an absence of real-time, high spatial and temporal... models , as well as with human injuries in which expression of bTBI symptoms among different individuals that are exposed to the same blast is

A Mathematical Model of the Olfactory Bulb for the Selective Adaptation Mechanism in the Rodent Olfactory System.

PubMed

Soh, Zu; Nishikawa, Shinya; Kurita, Yuichi; Takiguchi, Noboru; Tsuji, Toshio

2016-01-01

To predict the odor quality of an odorant mixture, the interaction between odorants must be taken into account. Previously, an experiment in which mice discriminated between odorant mixtures identified a selective adaptation mechanism in the olfactory system. This paper proposes an olfactory model for odorant mixtures that can account for selective adaptation in terms of neural activity. The proposed model uses the spatial activity pattern of the mitral layer obtained from model simulations to predict the perceptual similarity between odors. Measured glomerular activity patterns are used as input to the model. The neural interaction between mitral cells and granular cells is then simulated, and a dissimilarity index between odors is defined using the activity patterns of the mitral layer. An odor set composed of three odorants is used to test the ability of the model. Simulations are performed based on the odor discrimination experiment on mice. As a result, we observe that part of the neural activity in the glomerular layer is enhanced in the mitral layer, whereas another part is suppressed. We find that the dissimilarity index strongly correlates with the odor discrimination rate of mice: r = 0.88 (p = 0.019). We conclude that our model has the ability to predict the perceptual similarity of odorant mixtures. In addition, the model also accounts for selective adaptation via the odor discrimination rate, and the enhancement and inhibition in the mitral layer may be related to this selective adaptation.

Nonlinear Directed Interactions Between HRV and EEG Activity in Children With TLE.

PubMed

Schiecke, Karin; Pester, Britta; Piper, Diana; Benninger, Franz; Feucht, Martha; Leistritz, Lutz; Witte, Herbert

2016-12-01

Epileptic seizure activity influences the autonomic nervous system (ANS) in different ways. Heart rate variability (HRV) is used as indicator for alterations of the ANS. It was shown that linear, nondirected interactions between HRV and EEG activity before, during, and after epileptic seizure occur. Accordingly, investigations of directed nonlinear interactions are logical steps to provide, e.g., deeper insight into the development of seizure onsets. Convergent cross mapping (CCM) investigates nonlinear, directed interactions between time series by using nonlinear state space reconstruction. CCM is applied to simulated and clinically relevant data, i.e., interactions between HRV and specific EEG components of children with temporal lobe epilepsy (TLE). In addition, time-variant multivariate Autoregressive model (AR)-based estimation of partial directed coherence (PDC) was performed for the same data. Influence of estimation parameters and time-varying behavior of CCM estimation could be demonstrated by means of simulated data. AR-based estimation of PDC failed for the investigation of our clinical data. Time-varying interval-based application of CCM on these data revealed directed interactions between HRV and delta-related EEG activity. Interactions between HRV and alpha-related EEG activity were visible but less pronounced. EEG components mainly drive HRV. The interaction pattern and directionality clearly changed with onset of seizure. Statistical relevant interactions were quantified by bootstrapping and surrogate data approach. In contrast to AR-based estimation of PDC CCM was able to reveal time-courses and frequency-selective views of nonlinear interactions for the further understanding of complex interactions between the epileptic network and the ANS in children with TLE.

Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities

PubMed Central

2017-01-01

Background Understanding the environmental determinants of physical activity in populations at high risk of inactivity could contribute to the development of effective interventions. Socioecological models of activity propose that environmental factors have independent and interactive effects of physical activity but there is a lack of research into interactive effects. Objectives This study aimed to explore independent and interactive effects of social and physical environmental factors on self-reported physical activity in income-deprived communities. Methods Participants were 5,923 adults in Glasgow, United Kingdom. Features of the social environment were self-reported. Quality of the physical environment was objectively-measured. Neighbourhood walking and participation in moderate physical activity [MPA] on ≥5 days/week was self-reported. Multilevel multivariate logistic regression models tested independent and interactive effects of environmental factors on activity. Results ‘Social support’ (walking: OR:1.22,95%CI = 1.06–1.41,p<0.01; MPA: OR:0.79,95%CI = 0.67–0.94,p<0.01), ‘social interaction’ (walking: OR:1.25,95%CI = 1.10–1.42,p<0.01; MPA: OR:6.16,95%CI = 5.14–7.37,p<0.001) and ‘cohesion and safety’ (walking: OR:1.78,95%CI = 1.56–2.03,p<0.001; MPA: OR:1.93,95%CI = 1.65–2.27,p<0.001), but not ‘trust and empowerment’, had independent effects on physical activity. ‘Aesthetics of built form’ (OR:1.47,95%CI = 1.22–1.77,p<0.001) and ‘aesthetics and maintenance of open space’ (OR:1.32, 95%CI = 1.13–1.54,p<0.01) were related to walking. ‘Physical disorder’ (OR:1.63,95%CI = 1.31–2.03,p<0.001) had an independent effect on MPA. Interactive effects of social and physical factors on walking and MPA were revealed. Conclusions Findings suggest that intervening to create activity-supportive environments in deprived communities may be most effective when simultaneously targeting the social and physical neighbourhood environment. PMID:29240791

After-School Activities, Misbehavior in School, and Delinquency from the End of Elementary School through the Beginning of High School: A Test of Social Development Model Hypotheses

ERIC Educational Resources Information Center

Fleming, Charles B.; Catalano, Richard F.; Mazza, James J.; Brown, Eric C.; Haggerty, Kevin P.; Harachi, Tracy W.

2008-01-01

Annual survey data on 776 students from sixth through ninth grade were used to examine the relationships among after-school activities, misbehavior in school, and delinquency. The social development model hypothesizes that antisocial behavior in one developmental time period leads to less involvement in activities and interactions that have…

Identifying and modeling the structural discontinuities of human interactions

NASA Astrophysics Data System (ADS)

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Identifying and modeling the structural discontinuities of human interactions

PubMed Central

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-01-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales. PMID:28443647

Identifying and modeling the structural discontinuities of human interactions.

PubMed

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-26

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Hydrodynamic Equations for Flocking Models without Velocity Alignment

NASA Astrophysics Data System (ADS)

Peruani, Fernando

2017-10-01

The spontaneous emergence of collective motion patterns is usually associated with the presence of a velocity alignment mechanism that mediates the interactions among the moving individuals. Despite of this widespread view, it has been shown recently that several flocking behaviors can emerge in the absence of velocity alignment and as a result of short-range, position-based, attractive forces that act inside a vision cone. Here, we derive the corresponding hydrodynamic equations of a microscopic position-based flocking model, reviewing and extending previous reported results. In particular, we show that three distinct macroscopic collective behaviors can be observed: i) the coarsening of aggregates with no orientational order, ii) the emergence of static, elongated nematic bands, and iii) the formation of moving, locally polar structures, which we call worms. The derived hydrodynamic equations indicate that active particles interacting via position-based interactions belong to a distinct class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems.

A template-based approach for responsibility management in executable business processes

NASA Astrophysics Data System (ADS)

Cabanillas, Cristina; Resinas, Manuel; Ruiz-Cortés, Antonio

2018-05-01

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

Sensitivity of predicted scaling and permeability in Enhanced Geothermal Systems to Thermodynamic Data and Activity Models

NASA Astrophysics Data System (ADS)

Hingerl, Ferdinand F.; Wagner, Thomas; Kulik, Dmitrii A.; Kosakowski, Georg; Driesner, Thomas; Thomsen, Kaj

2010-05-01

A consortium of research groups from ETH Zurich, EPF Lausanne, the Paul Scherrer Institut and the University of Bonn collaborates in a comprehensive program of basic research on key aspects of the Enhanced Geothermal Systems (EGSs). As part of this GEOTHERM project (www.geotherm.ethz.ch), we concentrate on the fundamental investigation of thermodynamic models suitable for describing fluid-rock interactions at geothermal conditions. Predictions of the fluid-rock interaction in EGS still face several major challenges. Slight variations in the input thermodynamic and kinetic parameters may result in significant differences in the predicted mineral solubilities and stable assemblage. Realistic modeling of mineral precipitation in turn has implications onto our understanding of the permeability evolution of the geothermal reservoir, as well as the scaling in technical installations. In order to reasonably model an EGS, thermodynamic databases and activity models must be tailored to geothermal conditions. We therefore implemented in GEMS code the Pitzer formalism, which is the standard model used for computing thermodynamic excess properties of brines at elevated temperatures and pressures. This model, however, depends on a vast amount of interaction parameters, which are to a substantial extend unknown. Furthermore, a high order polynomial temperature interpolation makes extrapolation unreliable if not impossible. As an alternative we additionally implemented the EUNIQUAC activity model. EUNIQUAC requires fewer empirical fit parameters (only binary interaction parameters needed) and uses simpler and more stable temperature and pressure extrapolations. This results in an increase in computation speed, which is of crucial importance when performing coupled long term simulations of geothermal reservoirs. To achieve better performance under geothermal conditions, we are currently partly reformulating EUNIQUAC and refitting the existing parameter set. First results of the Pitzer-EUNIQUAC benchmark applied to relevant aqueous solutions at elevated temperature, pressure and ionic strength will be presented.

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

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

Linear summation of outputs in a balanced network model of motor cortex

PubMed Central

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis. PMID:26097452

Analysis of psychological factors for quality assessment of interactive multimodal service

NASA Astrophysics Data System (ADS)

Yamagishi, Kazuhisa; Hayashi, Takanori

2005-03-01

We proposed a subjective quality assessment model for interactive multimodal services. First, psychological factors of an audiovisual communication service were extracted by using the semantic differential (SD) technique and factor analysis. Forty subjects participated in subjective tests and performed point-to-point conversational tasks on a PC-based TV phone that exhibits various network qualities. The subjects assessed those qualities on the basis of 25 pairs of adjectives. Two psychological factors, i.e., an aesthetic feeling and a feeling of activity, were extracted from the results. Then, quality impairment factors affecting these two psychological factors were analyzed. We found that the aesthetic feeling is mainly affected by IP packet loss and video coding bit rate, and the feeling of activity depends on delay time and video frame rate. We then proposed an opinion model derived from the relationships among quality impairment factors, psychological factors, and overall quality. The results indicated that the estimation error of the proposed model is almost equivalent to the statistical reliability of the subjective score. Finally, using the proposed model, we discuss guidelines for quality design of interactive audiovisual communication services.

A model for the electronic support of practice-based research networks.

PubMed

Peterson, Kevin A; Delaney, Brendan C; Arvanitis, Theodoros N; Taweel, Adel; Sandberg, Elisabeth A; Speedie, Stuart; Richard Hobbs, F D

2012-01-01

The principal goal of the electronic Primary Care Research Network (ePCRN) is to enable the development of an electronic infrastructure to support clinical research activities in primary care practice-based research networks (PBRNs). We describe the model that the ePCRN developed to enhance the growth and to expand the reach of PBRN research. Use cases and activity diagrams were developed from interviews with key informants from 11 PBRNs from the United States and United Kingdom. Discrete functions were identified and aggregated into logical components. Interaction diagrams were created, and an overall composite diagram was constructed describing the proposed software behavior. Software for each component was written and aggregated, and the resulting prototype application was pilot tested for feasibility. A practical model was then created by separating application activities into distinct software packages based on existing PBRN business rules, hardware requirements, network requirements, and security concerns. We present an information architecture that provides for essential interactions, activities, data flows, and structural elements necessary for providing support for PBRN translational research activities. The model describes research information exchange between investigators and clusters of independent data sites supported by a contracted research director. The model was designed to support recruitment for clinical trials, collection of aggregated anonymous data, and retrieval of identifiable data from previously consented patients across hundreds of practices. The proposed model advances our understanding of the fundamental roles and activities of PBRNs and defines the information exchange commonly used by PBRNs to successfully engage community health care clinicians in translational research activities. By describing the network architecture in a language familiar to that used by software developers, the model provides an important foundation for the development of electronic support for essential PBRN research activities.

An artificial network model for estimating the network structure underlying partially observed neuronal signals.

PubMed

Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

2014-01-01

Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Designing and Applying Web Assisted Activities to Be Used in Flipped Classroom Model

ERIC Educational Resources Information Center

Çetinkaya, Murat

2017-01-01

The purpose of this study is to develop personalized web assisted activities for the flipped classroom model applied in the "Human and Environment Interactions" unit of science lesson and to research its effect on students' achievement. The study was conducted with the 74 participation of 7th grade science lesson students within a period…

Probing interaction of a fluorescent ligand with HIV TAR RNA

NASA Astrophysics Data System (ADS)

Qi, Liang; Zhang, Jing; He, Tian; Huo, Yuan; Zhang, Zhi-Qi

2017-02-01

Trans-activator of Transcription (Tat) antagonists could block the interaction between Tat protein and its target, trans-activation responsive region (TAR) RNA, to inhibit Tat function and prevent human immunodeficiency virus type 1 (HIV-1) replication. For the first time, a small fluorescence ligand, ICR 191, was found to interact with TAR RNA at the Tat binding site and compete with Tat. It was also observed that the fluorescence of ICR 191 could be quenched when binding to TAR RNA and recovered when discharged via competition with Tat peptide or a well-known Tat inhibitor, neomycin B. The binding parameters of ICR 191 to TAR RNA were determined through theoretical calculations. Mass spectrometry, circular dichroism and molecular docking were used to further confirm the interaction of ICR 191 with TAR RNA. Inspired by these discoveries, a primary fluorescence model for the discovery of Tat antagonists was built using ICR 191 as a fluorescence indicator and the feasibility of this model was evaluated. This ligand-RNA interaction could provide a new strategy for research aimed at discovering Tat antagonists.

Innovation diffusion on time-varying activity driven networks

NASA Astrophysics Data System (ADS)

Rizzo, Alessandro; Porfiri, Maurizio

2016-01-01

Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

Global structure–activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors

PubMed Central

Cunningham, Albert R.; Trent, John O.

2012-01-01

Structure–activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby’s structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity. PMID:22678118

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

A model of mechanical interactions between heart and lungs.

PubMed

Fontecave Jallon, Julie; Abdulhay, Enas; Calabrese, Pascale; Baconnier, Pierre; Gumery, Pierre-Yves

2009-12-13

To study the mechanical interactions between heart, lungs and thorax, we propose a mathematical model combining a ventilatory neuromuscular model and a model of the cardiovascular system, as described by Smith et al. (Smith, Chase, Nokes, Shaw & Wake 2004 Med. Eng. Phys.26, 131-139. (doi:10.1016/j.medengphy.2003.10.001)). The respiratory model has been adapted from Thibault et al. (Thibault, Heyer, Benchetrit & Baconnier 2002 Acta Biotheor. 50, 269-279. (doi:10.1023/A:1022616701863)); using a Liénard oscillator, it allows the activity of the respiratory centres, the respiratory muscles and rib cage internal mechanics to be simulated. The minimal haemodynamic system model of Smith includes the heart, as well as the pulmonary and systemic circulation systems. These two modules interact mechanically by means of the pleural pressure, calculated in the mechanical respiratory system, and the intrathoracic blood volume, calculated in the cardiovascular model. The simulation by the proposed model provides results, first, close to experimental data, second, in agreement with the literature results and, finally, highlighting the presence of mechanical cardiorespiratory interactions.

Mechanisms underlying rhythmic locomotion: interactions between activation, tension and body curvature waves

PubMed Central

Chen, Jun; Friesen, W. Otto; Iwasaki, Tetsuya

2012-01-01

SUMMARY Undulatory animal locomotion arises from three closely related propagating waves that sweep rostrocaudally along the body: activation of segmental muscles by motoneurons (MNs), strain of the body wall, and muscle tension induced by activation and strain. Neuromechanical models that predict the relative propagation speeds of neural/muscle activation, muscle tension and body curvature can reveal crucial underlying control features of the central nervous system and the power-generating mechanisms of the muscle. We provide an analytical explanation of the relative speeds of these three waves based on a model of neuromuscular activation and a model of the body–fluid interactions for leech anguilliform-like swimming. First, we deduced the motoneuron spike frequencies that activate the muscle and the resulting muscle tension during swimming in intact leeches from muscle bending moments. Muscle bending moments were derived from our video-recorded kinematic motion data by our body–fluid interaction model. The phase relationships of neural activation and muscle tension in the strain cycle were then calculated. Our study predicts that the MN activation and body curvature waves have roughly the same speed (the ratio of curvature to MN activation speed ≈0.84), whereas the tension wave travels about twice as fast. The high speed of the tension wave resulting from slow MN activation is explained by the multiplicative effects of MN activation and muscle strain on tension development. That is, the product of two slower waves (activation and strain) with appropriate amplitude, bias and phase can generate a tension wave with twice the propagation speed of the factors. Our study predicts that (1) the bending moment required for swimming is achieved by minimal MN spike frequency, rather than by minimal muscle tension; (2) MN activity is greater in the mid-body than in the head and tail regions; (3) inhibitory MNs not only accelerate the muscle relaxation but also reduce the intrinsic tonus tension during one sector of the swim cycle; and (4) movements of the caudal end are passive during swimming. These predictions await verification or rejection through further experiments on swimming animals. PMID:22189764

Mechanisms underlying rhythmic locomotion: interactions between activation, tension and body curvature waves.

PubMed

Chen, Jun; Friesen, W Otto; Iwasaki, Tetsuya

2012-01-15

Undulatory animal locomotion arises from three closely related propagating waves that sweep rostrocaudally along the body: activation of segmental muscles by motoneurons (MNs), strain of the body wall, and muscle tension induced by activation and strain. Neuromechanical models that predict the relative propagation speeds of neural/muscle activation, muscle tension and body curvature can reveal crucial underlying control features of the central nervous system and the power-generating mechanisms of the muscle. We provide an analytical explanation of the relative speeds of these three waves based on a model of neuromuscular activation and a model of the body-fluid interactions for leech anguilliform-like swimming. First, we deduced the motoneuron spike frequencies that activate the muscle and the resulting muscle tension during swimming in intact leeches from muscle bending moments. Muscle bending moments were derived from our video-recorded kinematic motion data by our body-fluid interaction model. The phase relationships of neural activation and muscle tension in the strain cycle were then calculated. Our study predicts that the MN activation and body curvature waves have roughly the same speed (the ratio of curvature to MN activation speed ≈0.84), whereas the tension wave travels about twice as fast. The high speed of the tension wave resulting from slow MN activation is explained by the multiplicative effects of MN activation and muscle strain on tension development. That is, the product of two slower waves (activation and strain) with appropriate amplitude, bias and phase can generate a tension wave with twice the propagation speed of the factors. Our study predicts that (1) the bending moment required for swimming is achieved by minimal MN spike frequency, rather than by minimal muscle tension; (2) MN activity is greater in the mid-body than in the head and tail regions; (3) inhibitory MNs not only accelerate the muscle relaxation but also reduce the intrinsic tonus tension during one sector of the swim cycle; and (4) movements of the caudal end are passive during swimming. These predictions await verification or rejection through further experiments on swimming animals.

Dynamic Transcription Factor Networks in Epithelial-Mesenchymal Transition in Breast Cancer Models

PubMed Central

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J.; Shin, Seungjin; Jeruss, Jacqueline S.; Shea, Lonnie D.

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy. PMID:23593114

Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

PubMed

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J; Shin, Seungjin; Jeruss, Jacqueline S; Shea, Lonnie D

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

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.

Toward construction of the unified lepton-nucleus interaction model from a few hundred MeV to GeV region

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

Nakamura, S. X.; Hayato, Y.; Hirai, M.

2015-05-15

Next generation neutrino oscillation experiments will need a quantitative understanding of neutrino-nucleus interaction far better than ever. Kinematics covered by the relevant neutrino-nucleus interaction spans wide region, from the quasi-elastic, through the resonance region, to the deeply inelastic scattering region. The neutrino-nucleus interaction in each region has quite different characteristics. Obviously, it is essential to combine different expertise to construct a unified model that covers all the kinematical region of the neutrino-nucleus interaction. Recently, several experimentalists and theorists got together to form a collaboration to tackle this problem. In this contribution, we report the collaboration’s recent activity and a goalmore » in near future.« less

Structure and Dynamics of Antifreeze Protein--Model Membrane Interactions: A Combined Spectroscopic and Molecular Dynamics Study.

PubMed

Kar, Rajiv K; Mroue, Kamal H; Kumar, Dinesh; Tejo, Bimo A; Bhunia, Anirban

2016-02-11

Antifreeze proteins (AFPs) are the key biomolecules that enable species to survive under subzero temperature conditions. The physiologically relevant activities of AFPs are based on the adsorption to ice crystals, followed by the inhibition of subsequent crystal layer growth of ice, routed with depression in freezing point in a noncolligative manner. The functional attributes governing the mechanism by which AFPs inhibit freezing of body fluids in bacteria, fungi, plants, and fishes are mainly attributed to their adsorption onto the surface of ice within the physiological system. Importantly, AFPs are also known for their application in cryopreservation of biological samples that might be related to membrane interaction. To date, there is a paucity of information detailing the interaction of AFPs with membrane structures. Here, we focus on elucidating the biophysical properties of the interactions between AFPs and micelle models that mimic the membrane system. Micelle model systems of zwitterionic DPC and negatively charged SDS were utilized in this study, against which a significant interaction is experienced by two AFP molecules, namely, Peptide 1m and wfAFP (the popular AFP sourced from winter flounder). Using low- and high-resolution biophysical characterization techniques, such as circular dichroism (CD) and NMR spectroscopy, a strong evidence for the interactions of these AFPs with the membrane models is revealed in detail and is corroborated by in-depth residue-specific information derived from molecular dynamics simulation. Altogether, these results not only strengthen the fact that AFPs interact actively with membrane systems, but also demonstrate that membrane-associated AFPs are dynamic and capable of adopting a number of conformations rendering fluidity to the system.

Voluntary exercise enhances activity rhythms and ameliorates anxiety- and depression-like behaviors in the sand rat model of circadian rhythm-related mood changes.

PubMed

Tal-Krivisky, Katy; Kronfeld-Schor, Noga; Einat, Haim

2015-11-01

Physical exercise is a non-pharmacological treatment for affective disorders. The mechanisms of its effects are unknown although some suggest a relationship to synchronization of circadian rhythms. One way to explore mechanisms is to utilize animal models. We previously demonstrated that the diurnal fat sand rat is an advantageous model for studying the interactions between photoperiods and mood. The current study was designed to evaluate the effects of voluntary exercise on activity rhythms and anxiety and depression-like behaviors in sand rats as a step towards better understanding of the underlying mechanisms. Male sand rats were housed in short photoperiod (SP; 5h light/19 h dark) or neutral light (NP; 12h light/12h dark) regimens for 3 weeks and divided into subgroups with or without running wheels. Activity was monitored for 3 additional weeks and then animals were tested in the elevated plus-maze, the forced swim test and the social interaction test. Activity rhythms were enhanced by the running wheels. As hypothesized, voluntary exercise had significant effects on SP animals' anxiety- and depression-like behaviors but not on NP animals. Results are discussed in the context of interactions between physical exercise, circadian rhythms and mood. We suggest that the sand rat model can be used to explore the underlying mechanism of the effects of physical exercise for mood disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

Histamine-releasing factor has a proinflammatory role in mouse models of asthma and allergy

PubMed Central

Kashiwakura, Jun-ichi; Ando, Tomoaki; Matsumoto, Kenji; Kimura, Miho; Kitaura, Jiro; Matho, Michael H.; Zajonc, Dirk M.; Ozeki, Tomomitsu; Ra, Chisei; MacDonald, Susan M.; Siraganian, Reuben P.; Broide, David H.; Kawakami, Yuko; Kawakami, Toshiaki

2011-01-01

IgE-mediated activation of mast cells and basophils underlies allergic diseases such as asthma. Histamine-releasing factor (HRF; also known as translationally controlled tumor protein [TCTP] and fortilin) has been implicated in late-phase allergic reactions (LPRs) and chronic allergic inflammation, but its functions during asthma are not well understood. Here, we identified a subset of IgE and IgG antibodies as HRF-interacting molecules in vitro. HRF was able to dimerize and bind to Igs via interactions of its N-terminal and internal regions with the Fab region of Igs. Therefore, HRF together with HRF-reactive IgE was able to activate mast cells in vitro. In mouse models of asthma and allergy, Ig-interacting HRF peptides that were shown to block HRF/Ig interactions in vitro inhibited IgE/HRF-induced mast cell activation and in vivo cutaneous anaphylaxis and airway inflammation. Intranasally administered HRF recruited inflammatory immune cells to the lung in naive mice in a mast cell– and Fc receptor–dependent manner. These results indicate that HRF has a proinflammatory role in asthma and skin immediate hypersensitivity, leading us to suggest HRF as a potential therapeutic target. PMID:22133880

Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions.

PubMed

Sedykh, Alexander; Fourches, Denis; Duan, Jianmin; Hucke, Oliver; Garneau, Michel; Zhu, Hao; Bonneau, Pierre; Tropsha, Alexander

2013-04-01

Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71-100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles.

Attentional control of associative learning--a possible role of the central cholinergic system.

PubMed

Pauli, Wolfgang M; O'Reilly, Randall C

2008-04-02

How does attention interact with learning? Kruschke [Kruschke, J.K. (2001). Toward a unified Model of Attention in Associative Learning. J. Math. Psychol. 45, 812-863.] proposed a model (EXIT) that captures Mackintosh's [Mackintosh, N.J. (1975). A theory of attention: Variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276-298.] framework for attentional modulation of associative learning. We developed a computational model that showed analogous interactions between selective attention and associative learning, but is significantly simplified and, in contrast to EXIT, is motivated by neurophysiological findings. Competition among input representations in the internal representation layer, which increases the contrast between stimuli, is critical for simulating these interactions in human behavior. Furthermore, this competition is modulated in a way that might be consistent with the phasic activation of the central cholinergic system, which modulates activity in sensory cortices. Specifically, phasic increases in acetylcholine can cause increased excitability of both pyramidal excitatory neurons in cortical layers II/III and cortical GABAergic inhibitory interneurons targeting the same pyramidal neurons. These effects result in increased attentional contrast in our model. This model thus represents an initial attempt to link human attentional learning data with underlying neural substrates.

Attentional control of associative learning—A possible role of the central cholinergic system

PubMed Central

Pauli, Wolfgang M.; O'Reilly, Randall C.

2010-01-01

How does attention interact with learning? Kruschke [Kruschke, J.K. (2001). Toward a unified Model of Attention in Associative Learning. J. Math. Psychol. 45, 812–863.] proposed a model (EXIT) that captures Mackintosh's [Mackintosh, N.J. (1975). A theory of attention: Variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276–298.] framework for attentional modulation of associative learning. We developed a computational model that showed analogous interactions between selective attention and associative learning, but is significantly simplified and, in contrast to EXIT, is motivated by neurophysiological findings. Competition among input representations in the internal representation layer, which increases the contrast between stimuli, is critical for simulating these interactions in human behavior. Furthermore, this competition is modulated in a way that might be consistent with the phasic activation of the central cholinergic system, which modulates activity in sensory cortices. Specifically, phasic increases in acetylcholine can cause increased excitability of both pyramidal excitatory neurons in cortical layers II/III and cortical GABAergic inhibitory interneurons targeting the same pyramidal neurons. These effects result in increased attentional contrast in our model. This model thus represents an initial attempt to link human attentional learning data with underlying neural substrates. PMID:17870060

HYDRAULIC ANALYSIS ON STREAM-AQUIFER INTERACTION BY STORAGE FUNCTION MODELS

EPA Science Inventory

In the natural hydrologic cycle, surface and subsurface water in a watershed are closely related and interact with each other. However, their relatrionships are affected by human activities. For instance, as the impervious area of a basin spreads due to urbanization, rainfall r...

Agent Technologies Designed to Facilitate Interactive Knowledge Construction

ERIC Educational Resources Information Center

Graesser, Arthur C.; Jeon, Moongee; Dufty, David

2008-01-01

During the last decade, interdisciplinary researchers have developed technologies with animated pedagogical agents that interact with the student in language and other communication channels (such as facial expressions and gestures). These pedagogical agents model good learning strategies and coach the students in actively constructing knowledge…

Versatile Molecular Functionalization for Inhibiting Concentration Quenching of Thermally Activated Delayed Fluorescence.

PubMed

Lee, Jiyoung; Aizawa, Naoya; Numata, Masaki; Adachi, Chihaya; Yasuda, Takuma

2017-01-01

Concentration quenching of thermally activated delayed fluorescence is found to be dominated by electron-exchange interactions, as described by the Dexter energy-transfer model. Owing to the short-range nature of the electron-exchange interactions, even a small modulation in the molecular geometric structure drastically affects the concentration-quenching, leading to enhanced solid-state photoluminescence and electroluminescence quantum efficiencies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

PubMed

Yan, Luchun; Liu, Jiemin; Qu, Chen; Gu, Xingye; Zhao, Xia

2015-01-28

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

Enhanced adsorptive removal of methyl orange and methylene blue from aqueous solution by alkali-activated multiwalled carbon nanotubes.

PubMed

Ma, Jie; Yu, Fei; Zhou, Lu; Jin, Lu; Yang, Mingxuan; Luan, Jingshuai; Tang, Yuhang; Fan, Haibo; Yuan, Zhiwen; Chen, Junhong

2012-11-01

An alkali-acitvated method was explored to synthesize activated carbon nanotubes (CNTs-A) with a high specific surface area (SSA), and a large number of mesopores. The resulting CNTs-A were used as an adsorbent material for removal of anionic and cationic dyes in aqueous solutions. Experimental results indicated that CNTs-A have excellent adsorption capacity for methyl orange (149 mg/g) and methylene blue (399 mg/g). Alkali-activation treatment of CNTs increased the SSA and pore volume (PV), and introduced oxygen-containing functional groups on the surface of CNTs-A, which would be beneficial to improving the adsorption affinity of CNTs-A for removal of dyes. Kinetic regression results shown that the adsorption kinetic was more accurately represented by a pseudo second-order model. The overall adsorption process was jointly controlled by external mass transfer and intra-particle diffusion, and intra-particle diffusion played a dominant role. Freundlich isotherm model showed a better fit with adsorption data than Langmuir isotherm model. Adsorption interactions of dyes onto CNTs-A from aqueous solutions were investigated using Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) method. The remarkable adsorption capacity of dye onto CNTs-A can be attributed to the multiple adsorption interaction mechanisms (hydrogen bonding, π-π electron-donor-acceptor interactions, electrostatic interactions, mesopore filling) on the CNTs-A. Results of this work are of great significance for environmental applications of activated CNTs as a promising adsorbent nanomaterial for organic pollutants from aqueous solutions.

Toxicodynamic analysis of the combined cholinesterase inhibition by paraoxon and methamidophos in human whole blood

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

Bosgra, Sieto; Eijkeren, Jan C.H. van; Schans, Marcel J. van der

2009-04-01

Theoretical work has shown that the isobole method is not generally valid as a method for testing the absence or presence of interaction (in the biochemical sense) between chemicals. The present study illustrates how interaction can be tested by fitting a toxicodynamic model to the results of a mixture experiment. The inhibition of cholinesterases (ChE) in human whole blood by various dose combinations of paraoxon and methamidophos was measured in vitro. A toxicodynamic model describing the processes related to both OPs in inhibiting AChE activity was developed, and fit to the observed activities. This model, not containing any interaction betweenmore » the two OPs, described the results from the mixture experiment well, and it was concluded that the OPs did not interact in the whole blood samples. While this approach of toxicodynamic modeling is the most appropriate method for predicting combined effects, it is not rapidly applicable. Therefore, we illustrate how toxicodynamic modeling can be used to explore under which conditions dose addition would give an acceptable approximation of the combined effects from various chemicals. In the specific case of paraoxon and methamidophos in whole blood samples, it was found that dose addition gave a reasonably accurate prediction of the combined effects, despite considerable difference in some of their rate constants, and mildly non-parallel dose-response curves. Other possibilities of validating dose-addition using toxicodynamic modeling are briefly discussed.« less

Interaction with Machine Improvisation

NASA Astrophysics Data System (ADS)

Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

Study of the functional hyperconnectivity between couples of pilots during flight simulation: an EEG hyperscanning study.

PubMed

Astolfi, L; Toppi, J; Borghini, G; Vecchiato, G; Isabella, R; De Vico Fallani, F; Cincotti, F; Salinari, S; Mattia, D; He, B; Caltagirone, C; Babiloni, F

2011-01-01

Brain Hyperscanning, i.e. the simultaneous recording of the cerebral activity of different human subjects involved in interaction tasks, is a very recent field of Neuroscience aiming at understanding the cerebral processes generating and generated by social interactions. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects, and, even more interestingly, of the functional links existing between the activities in the brains of the subjects interacting together. In this EEG hyperscanning study we explored the functional hyperconnectivity between the activity in different scalp sites of couples of Civil Aviation Pilots during different phases of a flight reproduced in a flight simulator. Results shown a dense network of connections between the two brains in the takeoff and landing phases, when the cooperation between them is maximal, in contrast with phases during which the activity of the two pilots was independent, when no or quite few links were shown. These results confirms that the study of the brain connectivity between the activity simultaneously acquired in human brains during interaction tasks can provide important information about the neural basis of the "spirit of the group".

Year of Tropical Convection (YOTC): Status and Research Agenda

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.; Waliser, D. E.

2009-12-01

The realistic representation of tropical convection in global models is a long-standing challenge for numerical weather prediction and an emerging grand challenge for climate prediction in respect to its physical basis. Insufficient knowledge and practical capabilities in this area disadvantage the modeling and prediction of prominent multi-scale phenomena such as the ITCZ, ENSO, monsoons and their active/break periods, the MJO, subtropical stratus decks, near-surface ocean properties, and tropical cyclones. Science elements include the diurnal cycle of precipitation, multi-scale convective organization, the global energy and water cycle, and interaction between the tropics and extra-tropics which interact strongly on timescales of weeks-to-months: the intersection of weather and climate. To address such challenges, the WCRP and WWRP/THORPEX are conducting a joint international research project, the Year of Tropical Convection (YOTC) which is a coordinated observing, modeling and forecasting project. The focus-year and integrated framework is intended to exploit the vast observational datasets, the modern high-resolution modeling frameworks, and theoretical insights. The over-arching objective is to advance the characterization, diagnosis, modeling, parameterization and prediction of multi-scale organized tropical phenomena and their interaction with the global circulation. The “Year” (May 2008 - April 2010) is intended to leverage recent major investments in Earth Science infrastructure and overlapping observational activities, e.g., Asian Monsoon Years (AMY) and the THORPEX Pacific Asian Regional Campaign (T-PARC). The research agenda involves phenomena and scale-interactions that are problematic for prediction models and have important socio-economic implications: MJO and convectively coupled equatorial waves; easterly waves and tropical cyclones; the monsoons including their intraseasonal variability; the diurnal cycle of precipitation; and two-way tropical-extratropical interaction. This presentation will summarize the status of the above.

Effect of glycyrrhetinic acid on lipid raft model at the air/water interface.

PubMed

Sakamoto, Seiichi; Uto, Takuhiro; Shoyama, Yukihiro

2015-02-01

To investigate an interfacial behavior of the aglycon of glycyrrhizin (GC), glycyrrhetinic acid (GA), with a lipid raft model consisting of equimolar ternary mixtures of N-palmitoyl sphingomyelin (PSM), dioleoylphosphatidylcholine (DOPC), and cholesterol (CHOL), Langmuir monolayer techniques were systematically conducted. Surface pressure (π)-molecular area (A) and surface potential (ΔV)-A isotherms showed that the adsorbed GA at the air/water interface was desorbed into the bulk upon compression of the lipid monolayer. In situ morphological analysis by Brewster angle microscopy and fluorescence microscopy revealed that the raft domains became smaller as the concentrations of GA in the subphase (CGA) increased, suggesting that GA promotes the formation of fluid networks related to various cellular processes via lipid rafts. In addition, ex situ morphological analysis by atomic force microscopy revealed that GA interacts with lipid raft by lying down at the surface. Interestingly, the distinctive striped regions were formed at CGA=5.0 μM. This phenomenon was observed to be induced by the interaction of CHOL with adsorbed GA and is involved in the membrane-disrupting activity of saponin and its aglycon. A quantitative comparison of GA with GC (Sakamoto et al., 2013) revealed that GA interacts more strongly with the raft model than GC in the monolayer state. Various biological activities of GA are known to be stronger than those of GC. This fact allows us to hypothesize that differences in the interactions of GA/GC with the model monolayer correlate to their degree of exertion for numerous activities. Copyright © 2014 Elsevier B.V. All rights reserved.

Human Cancer and Platelet Interaction, a Potential Therapeutic Target.

PubMed

Wang, Shike; Li, Zhenyu; Xu, Ren

2018-04-20

Cancer patients experience a four-fold increase in thrombosis risk, indicating that cancer development and progression are associated with platelet activation. Xenograft experiments and transgenic mouse models further demonstrate that platelet activation and platelet-cancer cell interaction are crucial for cancer metastasis. Direct or indirect interaction of platelets induces cancer cell plasticity and enhances survival and extravasation of circulating cancer cells during dissemination. In vivo and in vitro experiments also demonstrate that cancer cells induce platelet aggregation, suggesting that platelet-cancer interaction is bidirectional. Therefore, understanding how platelets crosstalk with cancer cells may identify potential strategies to inhibit cancer metastasis and to reduce cancer-related thrombosis. Here, we discuss the potential function of platelets in regulating cancer progression and summarize the factors and signaling pathways that mediate the cancer cell-platelet interaction.

Active subnetwork recovery with a mechanism-dependent scoring function; with application to angiogenesis and organogenesis studies

PubMed Central

2013-01-01

Background The learning active subnetworks problem involves finding subnetworks of a bio-molecular network that are active in a particular condition. Many approaches integrate observation data (e.g., gene expression) with the network topology to find candidate subnetworks. Increasingly, pathway databases contain additional annotation information that can be mined to improve prediction accuracy, e.g., interaction mechanism (e.g., transcription, microRNA, cleavage) annotations. We introduce a mechanism-based approach to active subnetwork recovery which exploits such annotations. We suggest that neighboring interactions in a network tend to be co-activated in a way that depends on the “correlation” of their mechanism annotations. e.g., neighboring phosphorylation and de-phosphorylation interactions may be more likely to be co-activated than neighboring phosphorylation and covalent bonding interactions. Results Our method iteratively learns the mechanism correlations and finds the most likely active subnetwork. We use a probabilistic graphical model with a Markov Random Field component which creates dependencies between the states (active or non-active) of neighboring interactions, that incorporates a mechanism-based component to the function. We apply a heuristic-based EM-based algorithm suitable for the problem. We validated our method’s performance using simulated data in networks downloaded from GeneGO against the same approach without the mechanism-based component, and two other existing methods. We validated our methods performance in correctly recovering (1) the true interaction states, and (2) global network properties of the original network against these other methods. We applied our method to networks generated from time-course gene expression studies in angiogenesis and lung organogenesis and validated the findings from a biological perspective against current literature. Conclusions The advantage of our mechanism-based approach is best seen in networks composed of connected regions with a large number of interactions annotated with a subset of mechanisms, e.g., a regulatory region of transcription interactions, or a cleavage cascade region. When applied to real datasets, our method recovered novel and biologically meaningful putative interactions, e.g., interactions from an integrin signaling pathway using the angiogenesis dataset, and a group of regulatory microRNA interactions in an organogenesis network. PMID:23432934

Physical activity attenuates genetic effects on BMI: Results from a study of Chinese adult twins.

PubMed

Wang, Biqi; Gao, Wenjing; Lv, Jun; Yu, Canqing; Wang, Shengfeng; Pang, Zengchang; Cong, Liming; Dong, Zhong; Wu, Fan; Wang, Hua; Wu, Xianping; Jiang, Guohong; Wang, Xiaojie; Wang, Binyou; Cao, Weihua; Li, Liming

2016-03-01

This study aimed to examine the gene-environment interaction of physical activity and body mass index (BMI) using the Chinese National Twin Registry (CNTR). A total of 19,308 same-sex adult twins from CNTR were included in the analysis. Twin zygosity was determined by self-reported questionnaire. Height and weight were measured using self-reported questionnaire. The vigorous physical activity was defined as greater or equal to five times a week of at least 30 min moderate- or high-intensity physical activity. A twin structural equation model was used to analyze the gene-environment interaction of vigorous exercise with BMI among 13,506 monozygotic twins and 5,802 dizygotic twins. A structural equation model adjusting for age and sex found vigorous exercise significantly moderated the additive genetic effects (P < 0.001) and shared environmental effects (P < 0.001) on BMI. The genetic contributions to BMI were significantly lower for people who adopted a physically active lifestyle [h(2) = 40%, 95% confidence interval (CI): 35%-46%] than those who were relative sedentary (h(2) = 59%, 95% CI: 52%-66%). The observed gene-physical activity interaction was more pronounced in men than women. Our results suggested that adopting a physically active lifestyle may help to reduce the genetic influence on BMI among the Chinese population. © 2016 The Obesity Society.

An interactive activation and competition model of person knowledge, suggested by proactive interference by traits spontaneously inferred from behaviours.

PubMed

Wang, Yuanbo E; Higgins, Nancy C; Uleman, James S; Michaux, Aaron; Vipond, Douglas

2016-03-01

People unconsciously and unintentionally make inferences about others' personality traits based on their behaviours. In this study, a classic memory phenomenon--proactive interference (PI)--is for the first time used to detect spontaneous trait inferences. PI should occur when lists of behaviour descriptions, all implying the same trait, are to be remembered. Switching to a new trait should produce 'release' from proactive interference (or RPI). Results from two experiments supported these predictions. PI and RPI effects are consistent with an interactive activation and competition model of person perception (e.g., McNeill & Burton, 2002, J. Exp. Psychol., 55A, 1141), which predicts categorical organization of social behaviours based on personality traits. Advantages of this model are discussed. © 2015 The British Psychological Society.

Modeling of Relation between Transaction Network and Production Activity for Firms

NASA Astrophysics Data System (ADS)

Iino, T.; Iyetomi, H.

Bak et al. [Ricerche Economiche 47 (1993), 3] proposed a self-organizing model for production activity of interacting firms to illustrate how large fluctuations can be triggered by small independent shocks in aggregate economy. This paper develops the original transaction model based on a regular network with layered order flow to accommodate more realistic networks. Simulations in the generalized model so obtained are then carried out for various networks to examine the influence caused by change of the network structure.

Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study.

PubMed

Saleh, Soha; Yarossi, Mathew; Manuweera, Thushini; Adamovich, Sergei; Tunik, Eugene

2017-01-01

Mirror visual feedback (MVF) is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical) or opposite (mirror) hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional) action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with non-invasive brain stimulation as a means of potentiating the effects of mirror training.

NATURE OF BINDING INTERACTION OF SELECTED CHEMICALS WITH RAT ESTROGEN RECEPTORS

EPA Science Inventory

The US EPA is currently validating a rat uterine estrogen receptor (ER) binding assay as part of the Tier 1 Screening Battery for the Endocrine Disruptor Program. An eventual goal is to use interactive data to create computerized structure-activity models. However, more informati...

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.

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.

Dynamical Consequences of Bandpass Feedback Loops in a Bacterial Phosphorelay

PubMed Central

Sen, Shaunak; Garcia-Ojalvo, Jordi; Elowitz, Michael B.

2011-01-01

Under conditions of nutrient limitation, Bacillus subtilis cells terminally differentiate into a dormant spore state. Progression to sporulation is controlled by a genetic circuit consisting of a phosphorelay embedded in multiple transcriptional feedback loops, which is used to activate the master regulator Spo0A by phosphorylation. These transcriptional regulatory interactions are “bandpass”-like, in the sense that activation occurs within a limited band of Spo0A∼P concentrations. Additionally, recent results show that the phosphorelay activation occurs in pulses, in a cell-cycle dependent fashion. However, the impact of these pulsed bandpass interactions on the circuit dynamics preceding sporulation remains unclear. In order to address this question, we measured key features of the bandpass interactions at the single-cell level and analyzed them in the context of a simple mathematical model. The model predicted the emergence of a delayed phase shift between the pulsing activity of the different sporulation genes, as well as the existence of a stable state, with elevated Spo0A activity but no sporulation, embedded within the dynamical structure of the system. To test the model, we used time-lapse fluorescence microscopy to measure dynamics of single cells initiating sporulation. We observed the delayed phase shift emerging during the progression to sporulation, while a re-engineering of the sporulation circuit revealed behavior resembling the predicted additional state. These results show that periodically-driven bandpass feedback loops can give rise to complex dynamics in the progression towards sporulation. PMID:21980382

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 physically-based approach of treating dust-water cloud interactions in climate models

NASA Astrophysics Data System (ADS)

Kumar, P.; Karydis, V.; Barahona, D.; Sokolik, I. N.; Nenes, A.

2011-12-01

All aerosol-cloud-climate assessment studies to date assume that the ability of dust (and other insoluble species) to act as a Cloud Condensation Nuclei (CCN) is determined solely by their dry size and amount of soluble material. Recent evidence however clearly shows that dust can act as efficient CCN (even if lacking appreciable amounts of soluble material) through adsorption of water vapor onto the surface of the particle. This "inherent" CCN activity is augmented as the dust accumulates soluble material through atmospheric aging. A comprehensive treatment of dust-cloud interactions therefore requires including both of these sources of CCN activity in atmospheric models. This study presents a "unified" theory of CCN activity that considers both effects of adsorption and solute. The theory is corroborated and constrained with experiments of CCN activity of mineral aerosols generated from clays, calcite, quartz, dry lake beds and desert soil samples from Northern Africa, East Asia/China, and Northern America. The unified activation theory then is included within the mechanistic droplet activation parameterization of Kumar et al. (2009) (including the giant CCN correction of Barahona et al., 2010), for a comprehensive treatment of dust impacts on global CCN and cloud droplet number. The parameterization is demonstrated with the NASA Global Modeling Initiative (GMI) Chemical Transport Model using wind fields computed with the Goddard Institute for Space Studies (GISS) general circulation model. References Barahona, D. et al. (2010) Comprehensively Accounting for the Effect of Giant CCN in Cloud Activation Parameterizations, Atmos.Chem.Phys., 10, 2467-2473 Kumar, P., I.N. Sokolik, and A. Nenes (2009), Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos.Chem.Phys., 9, 2517- 2532

Interactive, process-oriented climate modeling with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2016-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

Vodcasts and Active-Learning Exercises in a “Flipped Classroom” Model of a Renal Pharmacotherapy Module

PubMed Central

Fox, Jeremy

2012-01-01

Objective. To implement a “flipped classroom” model for a renal pharmacotherapy topic module and assess the impact on pharmacy students’ performance and attitudes. Design. Students viewed vodcasts (video podcasts) of lectures prior to the scheduled class and then discussed interactive cases of patients with end-stage renal disease in class. A process-oriented guided inquiry learning (POGIL) activity was developed and implemented that complemented, summarized, and allowed for application of the material contained in the previously viewed lectures. Assessment. Students’ performance on the final examination significantly improved compared to performance of students the previous year who completed the same module in a traditional classroom setting. Students’ opinions of the POGIL activity and the flipped classroom instructional model were mostly positive. Conclusion. Implementing a flipped classroom model to teach a renal pharmacotherapy module resulted in improved student performance and favorable student perceptions about the instructional approach. Some of the factors that may have contributed to students’ improved scores included: student mediated contact with the course material prior to classes, benchmark and formative assessments administered during the module, and the interactive class activities. PMID:23275661

Brief Report: Effects of Video-Based Group Instruction on Spontaneous Social Interaction of Adolescents with Autism Spectrum Disorders.

PubMed

Plavnick, Joshua B; Dueñas, Ana D

2018-06-01

Four adolescents with autism spectrum disorder (ASD) were taught to interact with peers by asking social questions or commenting about others during game play or group activities. Participants were shown a video model and then given an opportunity to perform the social behavior depicted in the model when playing a game with one another. All participants demonstrated an increase in both social interaction skills, replicating previous research on video-based group instruction for adolescents with ASD. The results suggest the procedure may be useful for teaching social skills that occur under natural conditions.

Transport properties in the atmosphere of Jupiter

NASA Technical Reports Server (NTRS)

Biolsi, L., Jr.

1979-01-01

Activities reported include: (1) testing of the computer program used to obtain transport properties for the Hulburt-Hirschfelder potential; (2) calculation of transport properties for the C2-C interaction; (3) preliminary calculations for the C2-C2 interaction; (4) calculation of transport properties for the C2H-He interaction; (5) consideration of the effect of inelastic collisions on the transport properties; and (6) the use of the Hulburt-Hirschfelder potential to model ion-atom interactions.

Stability and activity of lactate dehydrogenase on biofunctional layers deposited by activated vapor silanization (AVS) and immersion silanization (IS)

NASA Astrophysics Data System (ADS)

Calvo, Jorge Nieto-Márquez; Elices, Manuel; Guinea, Gustavo V.; Pérez-Rigueiro, José; Arroyo-Hernández, María

2017-09-01

The interaction between surfaces and biological elements, in particular, proteins is critical for the performance of biomaterials and biosensors. This interaction can be controlled by modifying the surface in a process known as biofunctionalization. In this work, the enzyme lactate dehydrogenase (LDH) is used to study the stability of the interaction between a functional protein and amine-functionalized surfaces. Two different functionalization procedures were compared: Activated Vapor Silanization (AVS) and Immersion Silanization (IS). Adsorption kinetics is shown to follow the Langmuir model for AVS-functionalized samples, while IS-functionalized samples show a certain instability if immersed in an aqueous medium for several hours. In turn, the enzymatic activity of LDH is preserved for longer times by using glutaraldehyde as crosslinker between the AVS biofunctional surface and the enzyme.

Population reversal driven by unrestrained interactions in molecular dynamics simulations: A dialanine model

NASA Astrophysics Data System (ADS)

Pullara, Filippo; Ignacio, J., General

2015-10-01

Standard Molecular Dynamics simulations (MD) are usually performed under periodic boundary conditions using the well-established "Ewald summation". This implies that the distance among each element in a given lattice cell and its corresponding element in another cell, as well as their relative orientations, are constant. Consequently, protein-protein interactions between proteins in different cells—important in many biological activities, such as protein cooperativity and physiological/pathological aggregation—are severely restricted, and features driven by protein-protein interactions are lost. The consequences of these restrictions, although conceptually understood and mentioned in the literature, have not been quantitatively studied before. The effect of protein-protein interactions on the free energy landscape of a model system, dialanine, is presented. This simple system features a free energy diagram with well-separated minima. It is found that, in the case of absence of peptide-peptide (p-p) interactions, the ψ = 150° dihedral angle determines the most energetically favored conformation (global free-energy minimum). When strong p-p interactions are induced, the global minimum switches to the ψ = 0° conformation. This shows that the free-energy landscape of an individual molecule is dramatically affected by the presence of other freely interacting molecules of its same type. Results of the study suggest how taking into account p-p interactions in MD allows having a more realistic picture of system activity and functional conformations.

Biotic Interactions in Microbial Communities as Modulators of Biogeochemical Processes: Methanotrophy as a Model System

PubMed Central

Ho, Adrian; Angel, Roey; Veraart, Annelies J.; Daebeler, Anne; Jia, Zhongjun; Kim, Sang Yoon; Kerckhof, Frederiek-Maarten; Boon, Nico; Bodelier, Paul L. E.

2016-01-01

Microbial interaction is an integral component of microbial ecology studies, yet the role, extent, and relevance of microbial interaction in community functioning remains unclear, particularly in the context of global biogeochemical cycles. While many studies have shed light on the physico-chemical cues affecting specific processes, (micro)biotic controls and interactions potentially steering microbial communities leading to altered functioning are less known. Yet, recent accumulating evidence suggests that the concerted actions of a community can be significantly different from the combined effects of individual microorganisms, giving rise to emergent properties. Here, we exemplify the importance of microbial interaction for ecosystem processes by analysis of a reasonably well-understood microbial guild, namely, aerobic methane-oxidizing bacteria (MOB). We reviewed the literature which provided compelling evidence for the relevance of microbial interaction in modulating methane oxidation. Support for microbial associations within methane-fed communities is sought by a re-analysis of literature data derived from stable isotope probing studies of various complex environmental settings. Putative positive interactions between active MOB and other microbes were assessed by a correlation network-based analysis with datasets covering diverse environments where closely interacting members of a consortium can potentially alter the methane oxidation activity. Although, methanotrophy is used as a model system, the fundamentals of our postulations may be applicable to other microbial guilds mediating other biogeochemical processes. PMID:27602021

Emergent organization in a model market

NASA Astrophysics Data System (ADS)

Yadav, Avinash Chand; Manchanda, Kaustubh; Ramaswamy, Ramakrishna

2017-09-01

We study the collective behaviour of interacting agents in a simple model of market economics that was originally introduced by Nørrelykke and Bak. A general theoretical framework for interacting traders on an arbitrary network is presented, with the interaction consisting of buying (namely consumption) and selling (namely production) of commodities. Extremal dynamics is introduced by having the agent with least profit in the market readjust prices, causing the market to self-organize. In addition to examining this model market on regular lattices in two-dimensions, we also study the cases of random complex networks both with and without community structures. Fluctuations in an activity signal exhibit properties that are characteristic of avalanches observed in models of self-organized criticality, and these can be described by power-law distributions when the system is in the critical state.

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

Takahashi, Takuya, E-mail: takahashi@kwasan.kyoto-u.ac.jp

Flare-associated coronal shock waves sometimes interact with solar prominences, leading to large-amplitude prominence oscillations (LAPOs). Such prominence activation gives us a unique opportunity to track the time evolution of shock–cloud interaction in cosmic plasmas. Although the dynamics of interstellar shock–cloud interaction has been extensively studied, coronal shock–solar prominence interaction is rarely studied in the context of shock–cloud interaction. Associated with the X5.4 class solar flare that occurred on 2012 March 7, a globally propagated coronal shock wave interacted with a polar prominence, leading to LAPO. In this paper, we studied bulk acceleration and excitation of the internal flow of themore » shocked prominence using three-dimensional magnetohydrodynamic (MHD) simulations. We studied eight MHD simulation runs, each with different mass density structure of the prominence, and one hydrodynamic simulation run, and we compared the result. In order to compare the observed motion of activated prominence with the corresponding simulation, we also studied prominence activation by injection of a triangular-shaped coronal shock. We found that the prominence is first accelerated mainly by magnetic tension force as well as direct transmission of the shock, and later decelerated mainly by magnetic tension force. The internal flow, on the other hand, is excited during the shock front sweeps through the prominence and damps almost exponentially. We construct a phenomenological model of bulk momentum transfer from the shock to the prominence, which agreed quantitatively with all the simulation results. Based on the phenomenological prominence activation model, we diagnosed physical parameters of the coronal shock wave. The estimated energy of the coronal shock is several percent of the total energy released during the X5.4 flare.« less

Noah's Ark-Red Cross Foundation: a Swedish model.

PubMed

Florence, M E

1993-01-01

During the Spring of 1991, the author spent many weeks at the Noah's Ark-Red Cross Foundation, a support service for HIV infected persons, and their families and friends, located in Stockholm, Sweden. The purpose was to study, through interviews, observation and participation, the foundation's interactive model in order to discover what makes it work and share that knowledge with other professionals. The Noah's Ark Model consists of three spheres of activity: service, including reception services and the volunteer programme; information and education, including the Hot Line and the Newsletter; and counselling and support, including the guest house. Staff from each area interact freely with and participate in the activities of other areas. The foundation also utilizes the services of carefully trained volunteers. This use of volunteers makes it unique in Sweden. It is the dedication and flexibility of the staff and volunteers that make this model work. The report of the study follows.

The role of idiotypic interactions in the adaptive immune system: a belief-propagation approach

NASA Astrophysics Data System (ADS)

Bartolucci, Silvia; Mozeika, Alexander; Annibale, Alessia

2016-08-01

In this work we use belief-propagation techniques to study the equilibrium behaviour of a minimal model for the immune system comprising interacting T and B clones. We investigate the effect of the so-called idiotypic interactions among complementary B clones on the system’s activation. Our results show that B-B interactions increase the system’s resilience to noise, making clonal activation more stable, while increasing the cross-talk between different clones. We derive analytically the noise level at which a B clone gets activated, in the absence of cross-talk, and find that this increases with the strength of idiotypic interactions and with the number of T cells sending signals to the B clones. We also derive, analytically and numerically, via population dynamics, the critical line where clonal cross-talk arises. Our approach allows us to derive the B clone size distribution, which can be experimentally measured and gives important information about the adaptive immune system response to antigens and vaccination.

The Research and Training Activities for the Joint Institute for Aeronautics and Acoustics

NASA Technical Reports Server (NTRS)

Cantwell, Brian

1995-01-01

This proposal requests continued support for the program of activities to be undertaken by the Ames-Stanford Joint Institute for Aeronautics and Acoustics during the period 1 Oct. 1995 - 30 Sept. 1996. The emphasis in this program is on training and research in experimental and computational methods with application to aerodynamics, acoustics and the important interactions between them. The program comprises activities in active flow control, Large Eddy Simulation of jet noise, flap aerodynamics and acoustics and high lift modeling studies. During the proposed period there will be a continued emphasis on the interaction between NASA Ames, Stanford University and Industry, particularly in connection with the high lift activities.

Cohesion-decohesion asymmetry in geckos

NASA Astrophysics Data System (ADS)

Puglisi, G.; Truskinovsky, L.

2013-03-01

Lizards and insects can strongly attach to walls and then detach applying negligible additional forces. We propose a simple mechanical model of this phenomenon which implies active muscle control. We show that the detachment force may depend not only on the properties of the adhesive units, but also on the elastic interaction among these units. By regulating the scale of such cooperative interaction, the organism can actively switch between two modes of adhesion: delocalized (pull off) and localized (peeling).

Local and systemic tumor immune dynamics

NASA Astrophysics Data System (ADS)

Enderling, Heiko

Tumor-associated antigens, stress proteins, and danger-associated molecular patterns are endogenous immune adjuvants that can both initiate and continually stimulate an immune response against a tumor. In retaliation, tumors can hijack intrinsic immune regulatory programs that are intended to prevent autoimmune disease, thereby facilitating continued growth despite the activated antitumor immune response. In metastatic disease, this ongoing tumor-immune battle occurs at each site. Adding an additional layer of complexity, T cells activated at one tumor site can cycle through the blood circulation system and extravasate in a different anatomic location to surveil a distant metastasis. We propose a mathematical modeling framework that incorporates the trafficking of activated T cells between metastatic sites. We extend an ordinary differential equation model of tumor-immune system interactions to multiple metastatic sites. Immune cells are activated in response to tumor burden and tumor cell death, and are recruited from tumor sites elsewhere in the body. A model of T cell trafficking throughout the circulatory system can inform the tumor-immune interaction model about the systemic distribution and arrival of T cells at specific tumor sites. Model simulations suggest that metastases not only contribute to immune surveillance, but also that this contribution varies between metastatic sites. Such information may ultimately help harness the synergy of focal therapy with the immune system to control metastatic disease.

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

PubMed Central

Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

Recent advances in plasma modeling for space applications

NASA Astrophysics Data System (ADS)

Srinivasan, Bhuvana; Scales, Wayne; Cagas, Petr; Glesner, Colin

2017-02-01

This paper presents a brief overview of the application of advanced plasma modeling techniques to several space science and engineering problems currently of significant interest. Recent advances in both kinetic and fluid modeling provide the ability to study a wide variety of problems that may be important to space plasmas including spacecraft-environment interactions, plasma-material interactions for propulsion systems such as Hall thrusters, ionospheric plasma instabilities, plasma separation from magnetic nozzles, active space experiments, and a host of additional problems. Some of the key findings are summarized here.

A copper-methionine interaction controls the pH-dependent activation of peptidylglycine monooxygenase.

PubMed

Bauman, Andrew T; Broers, Brenda A; Kline, Chelsey D; Blackburn, Ninian J

2011-12-20

The pH dependence of native peptidylglycine monooxygenase (PHM) and its M314H variant has been studied in detail. For wild-type (WT) PHM, the intensity of the Cu-S interaction visible in the Cu(I) extended X-ray absorption fine structure (EXAFS) data is inversely proportional to catalytic activity over the pH range of 3-8. A previous model based on more limited data was interpreted in terms of two protein conformations involving an inactive Met-on form and an active flexible Met-off form [Bauman, A. T., et al. (2006) Biochemistry 45, 11140-11150] that derived its catalytic activity from the ability to couple into vibrational modes critical for proton tunneling. The new studies comparing the WT and M314H variant have led to the evolution of this model, in which the Met-on form has been found to be derived from coordination of an additional Met residue, rather than a more rigid conformer of M314 as previously proposed. The catalytic activity of the mutant decreased by 96% because of effects on both k(cat) and K(M), but it displayed the same activity-pH profile with a maximum around pH 6. At pH 8, the reduced Cu(I) form gave spectra that could be simulated by replacement of the Cu(M) Cu-S(Met) interaction with a Cu-N/O interaction, but the data did not unambiguously assign the ligand to the imidazole side chain of H314. At pH 3.5, the EXAFS still showed the presence of a strong Cu-S interaction, establishing that the Met-on form observed at low pH in WT cannot be due to a strengthening of the Cu(M)-methionine interaction but must arise from a different Cu-S interaction. Therefore, lowering the pH causes a conformational change at one of the Cu centers that brings a new S donor residue into a favorable orientation for coordination to copper and generates an inactive form. Cys coordination is unlikely because all Cys residues in PHM are engaged in disulfide cross-links. Sequence comparison with the PHM homologues tyramine β-monooxygenase and dopamine β-monooxygenase suggests that M109 (adjacent to H site ligands H107 and H108) is the most likely candidate. A model is presented in which H108 is protonated with a pK(a) of 4.6 to generate the inactive low-pH form with Cu(H) coordinated by M109, H107, and H172.

CPI motif interaction is necessary for capping protein function in cells

PubMed Central

Edwards, Marc; McConnell, Patrick; Schafer, Dorothy A.; Cooper, John A.

2015-01-01

Capping protein (CP) has critical roles in actin assembly in vivo and in vitro. CP binds with high affinity to the barbed end of actin filaments, blocking the addition and loss of actin subunits. Heretofore, models for actin assembly in cells generally assumed that CP is constitutively active, diffusing freely to find and cap barbed ends. However, CP can be regulated by binding of the ‘capping protein interaction' (CPI) motif, found in a diverse and otherwise unrelated set of proteins that decreases, but does not abolish, the actin-capping activity of CP and promotes uncapping in biochemical experiments. Here, we report that CP localization and the ability of CP to function in cells requires interaction with a CPI-motif-containing protein. Our discovery shows that cells target and/or modulate the capping activity of CP via CPI motif interactions in order for CP to localize and function in cells. PMID:26412145

Interaction of gold nanoparticles with free radicals and their role in enhancing the scavenging activity of ascorbic acid.

PubMed

Razzaq, Humaira; Saira, Farhat; Yaqub, Azra; Qureshi, Rumana; Mumtaz, Misbah; Saleemi, Samia

2016-08-01

The present study investigates the interaction of citrate stabilized gold nanoparticles (12±1.5nm) (GNPs) with free radicals; 1,1-diphenyl-2-picrylhydrazyl (DPPH) stable and electrochemically generated superoxide, O2(-). Different experiments were designed to understand the interaction between GNPs and DPPH by employing cyclic voltammetry, UV-vis spectroscopy and computational chemistry using 6-311G basis set. The increase in heterogeneous rate constant, ksh, of DPPH upon addition of GNPs pointed towards possible complex formation, DPPH-GNPs which were further explained by a model assuming surface adsorption of DPPH on GNPs. Further, the model was validated by studying interaction of GNPs with a biologically important free radical, O2(-). Exciting result in terms of disappearance of anodic peak after GNPs addition confirmed that gold nanoparticles interacted with stable as well as unstable free radicals. Also, the stoichiometry of the most stable complex GNP-DPPH was determined from UV-vis spectroscopy by applying Job's method. The GNP-DPPH complex was found to be active with 46.0% reduction of the IC50 value of standard antioxidant, ascorbic acid (AA), indicating its role in enhancing antioxidant activity. Hence, this study presents a simple and potential approach to enhance the efficiency of natural antioxidants without modifying their structure, or involving the complex functionalization of GNPs with antioxidants. Copyright © 2016. Published by Elsevier B.V.

Saponin Interactions with Model Membrane Systems - Langmuir Monolayer Studies, Hemolysis and Formation of ISCOMs.

PubMed

de Groot, Carolin; Müller-Goymann, Christel C

2016-12-01

Saponins are used in medicine due to their pharmacological and immunological effects. To better understand interactions of saponins with model membranes and natural membranes of, for example, erythrocytes, Langmuir film balance experiments are well established. For most saponins, a strong interaction with cholesterol was demonstrated in dependence of both the aglycone part and the sugar moieties and is suggested to be correlated with a strong hemolytic activity, high toxicity, and high surface activity, as was demonstrated for the steroid saponin digitonin. In general, changes in the sugar chain or in substituents of the aglycone result in a modification of the saponin properties. A promising saponin with regard to fairly low hemolytic activity and high adjuvant effect is α -tomatine, which still shows a high affinity for cholesterol. An interaction with cholesterol and lipids has also been proven for the Quillaja saponin from the bark of Quillaja saponaria Molina. This triterpene saponin was approved in marketed vaccines as an adjuvant due to the formation of immunostimulating complexes. Immunostimulating complexes consist of a Quillaja saponin, cholesterol, phospholipids, and a corresponding antigen. Recently, another saponin from Quillaja brasiliensis was successfully tested in immunostimulating complexes, too. Based on the results of interaction studies, the formation of drug delivery systems such as immunostimulating complexes or similar self-assembled colloids is postulated for a variety of saponins. Georg Thieme Verlag KG Stuttgart · New York.

Interaction vs. observation: distinctive modes of social cognition in human brain and behavior? A combined fMRI and eye-tracking study.

PubMed

Tylén, Kristian; Allen, Micah; Hunter, Bjørk K; Roepstorff, Andreas

2012-01-01

Human cognition has usually been approached on the level of individual minds and brains, but social interaction is a challenging case. Is it best thought of as a self-contained individual cognitive process aiming at an "understanding of the other," or should it rather be approached as an collective, inter-personal process where individual cognitive components interact on a moment-to-moment basis to form coupled dynamics? In a combined fMRI and eye-tracking study we directly contrasted these models of social cognition. We found that the perception of situations affording social contingent responsiveness (e.g., someone offering or showing you an object) elicited activations in regions of the right posterior temporal sulcus and yielded greater pupil dilation corresponding to a model of coupled dynamics (joint action). In contrast, the social-cognitive perception of someone "privately" manipulating an object elicited activation in medial prefrontal cortex, the right inferior frontal gyrus and right inferior parietal lobus, regions normally associated with Theory of Mind and with the mirror neuron system. Our findings support a distinction in social cognition between social observation and social interaction, and demonstrate that simple ostensive cues may shift participants' experience, behavior, and brain activity between these modes. The identification of a distinct, interactive mode has implications for research on social cognition, both in everyday life and in clinical conditions.

Isolation and characterisation of sericin antifreeze peptides and molecular dynamics modelling of their ice-binding interaction.

PubMed

Wu, Jinhong; Rong, Yuzhi; Wang, Zhengwu; Zhou, Yanfu; Wang, Shaoyun; Zhao, Bo

2015-05-01

This study aimed to isolate and characterise a novel sericin antifreeze peptide and investigate its ice-binding molecular mechanism. The thermal hysteresis activity of ice-binding sericin peptides (I-SP) was measured and their activity reached as high as 0.94 °C. A P4 fraction, with high hypothermia protective activity and inhibition activity of ice recrystallisation, was obtained from I-SP, and a purified sericin peptide, named SM-AFP, with the sequence of TTSPTNVSTT and a molecular weight of 1009.50 Da was then isolated from the P4 fraction. Treatment of Lactobacillus delbrueckii Subsp. bulgaricus LB340 LYO with 100 μg/ml synthetic SM-AFP led to 1.4-fold increased survival (p < 0.05). Finally, an SM-AFP/ice binding model was constructed and results of molecular dynamics simulation suggested that the binding of SM-AFP with ice and prevention of ice crystal growth could be attributed to hydrogen bond formation, hydrophobic interaction and non-bond interactions. Sericin peptides could be developed into beneficial cryoprotectants and used in frozen food processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ceruloplasmin: Macromolecular Assemblies with Iron-Containing Acute Phase Proteins

PubMed Central

Samygina, Valeriya R.; Sokolov, Alexey V.; Bourenkov, Gleb; Petoukhov, Maxim V.; Pulina, Maria O.; Zakharova, Elena T.; Vasilyev, Vadim B.; Bartunik, Hans; Svergun, Dmitri I.

2013-01-01

Copper-containing ferroxidase ceruloplasmin (Cp) forms binary and ternary complexes with cationic proteins lactoferrin (Lf) and myeloperoxidase (Mpo) during inflammation. We present an X-ray crystal structure of a 2Cp-Mpo complex at 4.7 Å resolution. This structure allows one to identify major protein–protein interaction areas and provides an explanation for a competitive inhibition of Mpo by Cp and for the activation of p-phenylenediamine oxidation by Mpo. Small angle X-ray scattering was employed to construct low-resolution models of the Cp-Lf complex and, for the first time, of the ternary 2Cp-2Lf-Mpo complex in solution. The SAXS-based model of Cp-Lf supports the predicted 1∶1 stoichiometry of the complex and demonstrates that both lobes of Lf contact domains 1 and 6 of Cp. The 2Cp-2Lf-Mpo SAXS model reveals the absence of interaction between Mpo and Lf in the ternary complex, so Cp can serve as a mediator of protein interactions in complex architecture. Mpo protects antioxidant properties of Cp by isolating its sensitive loop from proteases. The latter is important for incorporation of Fe3+ into Lf, which activates ferroxidase activity of Cp and precludes oxidation of Cp substrates. Our models provide the structural basis for possible regulatory role of these complexes in preventing iron-induced oxidative damage. PMID:23843990

Direct Interactions with the Integrin β1 Cytoplasmic Tail Activate the Abl2/Arg Kinase*

PubMed Central

Simpson, Mark A.; Bradley, William D.; Harburger, David; Parsons, Maddy; Calderwood, David A.; Koleske, Anthony J.

2015-01-01

Integrins are heterodimeric α/β extracellular matrix adhesion receptors that couple physically to the actin cytoskeleton and regulate kinase signaling pathways to control cytoskeletal remodeling and adhesion complex formation and disassembly. β1 integrins signal through the Abl2/Arg (Abl-related gene) nonreceptor tyrosine kinase to control fibroblast cell motility, neuronal dendrite morphogenesis and stability, and cancer cell invasiveness, but the molecular mechanisms by which integrin β1 activates Arg are unknown. We report here that the Arg kinase domain interacts directly with a lysine-rich membrane-proximal segment in the integrin β1 cytoplasmic tail, that Arg phosphorylates the membrane-proximal Tyr-783 in the β1 tail, and that the Arg Src homology domain then engages this phosphorylated region in the tail. We show that these interactions mediate direct binding between integrin β1 and Arg in vitro and in cells and activate Arg kinase activity. These findings provide a model for understanding how β1-containing integrins interact with and activate Abl family kinases. PMID:25694433

Psychosocial Precursors and Correlates of Migraine Headache.

ERIC Educational Resources Information Center

Levor, Robert M.; And Others

1986-01-01

Tested the interactions of migraine headache cycles and sufferers' daily experiences of stressful events, emotional arousal, and physical activity. Results support a model of migraine characterized by parallel physiological and psychosocial instability during a 4-day cycle and by an interaction of personality and behavioral (self-reported stress)…

The Impact of Interactive Engagement Methods on Students' Academic Achievement

ERIC Educational Resources Information Center

Tlhoaele, Malefyane; Hofman, Adriaan; Winnips, Koos; Beetsma, Yta

2014-01-01

Interactive engagement (IE) is a process that promotes students' conceptual understanding through activities, combined with immediate feedback from peers and/or instructors. The present study investigates the impact of IE on students' academic performance, using the comprehensive model of educational effectiveness. Engineering students (n?=?158),…

The Early Childhood Interactive Technology Literacy Curriculum Project: A Final Report.

ERIC Educational Resources Information Center

Hutinger, Patricia; Robinsosn, Linda; Schneider, Carol; Johanson, Joyce

This final report describes the activities and outcomes of the Interactive Technology Literacy Curriculum (ITLC) project. This federally funded 5-year model demonstration project was designed to advance the availability, quality, use and effectiveness of computer technology in addressing the acquisition of emergent literacy among young children…

Activation of Basolateral Amygdala in Juvenile C57BL/6J Mice During Social Approach Behavior

PubMed Central

Ferri, Sarah L.; Kreibich, Arati S.; Torre, Matthew; Piccoli, Cara T.; Dow, Holly; Pallathra, Ashley A.; Li, Hongzhe; Bilker, Warren B.; Gur, Ruben C.; Abel, Ted; Brodkin, Edward S.

2016-01-01

There is a strong need to better understand the neurobiology of juvenile sociability (tendency to seek social interaction), a phenotype of central relevance to autism spectrum disorders (ASD). Although numerous genetic mouse models of ASD showing reduced sociability have been reported, and certain brain regions, such as the amygdala, have been implicated in sociability, there has been little emphasis on delineating brain structures and circuits activated during social interactions in the critical juvenile period of the mouse strain that serves as the most common genetic background for these models—the highly sociable C57BL/6J (B6) strain. We measured expression of the immediate early genes Fos and Egr-1 to map activation of brain regions following the Social Approach Test (SAT) in juvenile male B6 mice. We hypothesized that juvenile B6 mice would show activation of the amygdala during social interactions. The basoloateral amygdala (BLA) was activated by social exposure in highly sociable, 4-week-old B6 mice. In light of these data, and the many lines of evidence indicating alteration of amygdala circuits in human ASD, future studies are warranted to assess structural and functional alterations in the BLA, particularly at BLA synapses, in various mouse models of ASD. PMID:27520082

Theoretical study of the Raman active CDW gap mode in manganites.

PubMed

Rout, G C; Panda, Saswati; Behera, S N

2010-09-22

We report here the microscopic theory of the Raman spectra of the colossal magnetoresistive (CMR) manganite systems. The system is described by a model Hamiltonian consisting of the double exchange interaction in addition to the charge ordering interaction in the e(g) band and spin-spin interaction among the t(2g) core electrons. Further the phonon coupling to the conduction electron density is incorporated in the model for phonons in the harmonic approximation. The spectral density function for the Raman spectra is calculated from the imaginary part of the phonon Green's function. The calculated spectra display the Raman active bare phonon peak along with the charge ordering peak. The magnetic field and temperature dependence of the charge ordering peak agrees with the 480 cm(-1) JT mode observed in the experiments. The evolution of this mode is investigated in the report.

Modelling engagement in dementia through behaviour. Contribution for socially interactive robotics.

PubMed

Perugia, Giulia; Diaz Doladeras, Marta; Mallofre, Andreu Catala; Rauterberg, Matthias; Barakova, Emilia

2017-07-01

In this paper, we present a novel tool to measure engagement in people with dementia playing board games and interacting with a social robot, Pleo. We carried out two studies to reach a comprehensive inventory of behaviours accounting for engagement in dementia. The first one is an exploratory study aimed at modelling engagement in cognitive board games. The second one is a longitudinal study to investigate how people with dementia express engagement in cognitive games and in interactions with social robots. We adopted a technique coming from Ethology to mould behaviour, the ethogram. Ethogram is founded on low level behaviours, and allows hierarchical structuring. Herein, we present preliminary results consisting in the description of two ethograms and in their structuring obtained through thematic analysis. Such results show that an underlying structure of engagement exists across activities, and that different activities trigger different behavioural displays of engagement that adhere to such a structure.

Insights into structure and activity of natural compound inhibitors of pneumolysin

PubMed Central

Li, Hongen; Zhao, Xiaoran; Deng, Xuming; Wang, Jianfeng; Song, Meng; Niu, Xiaodi; Peng, Liping

2017-01-01

Pneumolysin is the one of the major virulence factor of the bacterium Streptococcus pneumoniae. In previous report, it is shown that β-sitosterol, a natural compound without antimicrobial activity, is a potent antagonist of pneumolysin. Here, two new pneumolysin natural compound inhibitors, with differential activity, were discovered via haemolysis assay. To explore the key factor of the conformation for the inhibition activity, the interactions between five natural compound inhibitors with differential activity and pneumolysin were reported using molecular modelling, the potential of mean force profiles. Interestingly, it is found that incorporation of the single bond (C22-C23-C24-C25) to replace the double bond (hydrocarbon sidechain) improved the anti-haemolytic activity. In view of the molecular modelling, binding of the five inhibitors to the conserved loop region (Val372, Leu460, and Tyr461) of the cholesterol binding sites led to stable complex systems, which was consistent with the result of β-sitosterol. Owing to the single bond (C22-C23-C24-C25), campesterol and brassicasterol could form strong interactions with Val372 and show higher anti-haemolytic activity, which indicated that the single bond (C22-C23-C24-C25) in inhibitors was required for the anti-haemolytic activity. Overall, the current molecular modelling work provides a starting point for the development of rational design and higher activity pneumolysin inhibitors. PMID:28165051

Linguistic Ambiguity in a Connectionist Model for Grammatical Studies.

ERIC Educational Resources Information Center

Angelica, Julia; Ney, James W.

1995-01-01

Discusses the evolution of the connectionist model of language processing, focusing on the parallel distributed processing (PDP) model proposed by Rumelhart and others (1986) that explains the microstructure of cognition in terms of interactive activation between elementary input, output, and intermediate processing units linked by weighted…

Mealtime Interactions and Life Satisfaction Among Older Adults in Shanghai.

PubMed

Ye, Minzhi; Chen, Lin; Kahana, Eva

2017-06-01

We examined the association between older adults' mealtime interactions at senior centers in Shanghai and their life satisfaction. Competing hypotheses, derived from socioemotional selectivity theory and activity theory, were tested. Data were obtained from the 2011 Shanghai senior center service utilization survey ( N = 320). Relationships between respondents' mealtime interactions and life satisfaction were tested using multilevel regression modeling. After adjusting for demographics, interactions with tablemates (companionship, self-disclosure, and instrumental support) were positively associated with respondents' life satisfaction. These associations varied by senior centers. However, the number of tablemates was not significantly associated with respondents' life satisfaction. Findings support the activity-theory-based hypothesis that mealtime interactions are related to older adults' life satisfaction independent of the number of tablemates. This study illuminates the value of social interactions in the context of community dining programs for the rapidly increasing older population in urban China.

The Overlap Model: A Model of Letter Position Coding

ERIC Educational Resources Information Center

Gomez, Pablo; Ratcliff, Roger; Perea, Manuel

2008-01-01

Recent research has shown that letter identity and letter position are not integral perceptual dimensions (e.g., jugde primes judge in word-recognition experiments). Most comprehensive computational models of visual word recognition (e.g., the interactive activation model, J. L. McClelland & D. E. Rumelhart, 1981, and its successors) assume that…

A study of the antibacterial activity of L-phenylalanine and L-tyrosine esters in relation to their CMCs and their interactions with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine, DPPC as model membrane.

PubMed

Joondan, Nausheen; Jhaumeer-Laulloo, Sabina; Caumul, Prakashanand

2014-01-01

Cationic amino acid-based surfactants are known to interact with the lipid bilayer of cell membranes resulting in depolarization, lysis and cell death through a disruption of the membrane topology. A range of cationic surfactant analogues derived from L-Phenylalanine (C1-C20) and L-Tyrosine (C8-C14) esters have been synthesized and screened for their antibacterial activity. The esters were more active against gram positive than gram negative bacteria. The activity increased with increasing chain length, exhibiting a cut-off effect at C12 for gram positive and C8/C10 for gram negative bacteria. The cut-off effect for gram negative bacteria was observed at a lower alkyl chain length. The CMC was correlated with the MIC, inferring that micellar activity contribute to the cut-off effect in antibacterial activity. The interaction of the cationic surfactants with the phospholipid vesicles (1,2-dipalmitoyl-sn-glycero-3-phosphocholine, DPPC) in the presence of 1-anilino-8-naphthalene sulfonate (ANS) and 1,6-diphenyl-1,3,5-hexatriene (DPH) as fluorescence probes showed that an increase in ionic interaction causes an increase in antibacterial activity. Increase in hydrophobic interaction increases the antibacterial activity only to a certain chain length, attributing to the cut-off effect. Therefore, both electrostatic and hydrophobic interactions, involving the polar and nonpolar moieties are of paramount importance for the bactericidal properties. Copyright © 2014 Elsevier GmbH. All rights reserved.

New insights into the interaction between pyrrolyl diketoacids and HIV-1 integrase active site and comparison with RNase H.

PubMed

Corona, Angela; di Leva, Francesco Saverio; Rigogliuso, Giuseppe; Pescatori, Luca; Madia, Valentina Noemi; Subra, Frederic; Delelis, Olivier; Esposito, Francesca; Cadeddu, Marta; Costi, Roberta; Cosconati, Sandro; Novellino, Ettore; di Santo, Roberto; Tramontano, Enzo

2016-10-01

HIV-1 integrase (IN) inhibitors are one of the most recent innovations in the treatment of HIV infection. The selection of drug resistance viral strains is however a still open issue requiring constant efforts to identify new anti-HIV-1 drugs. Pyrrolyl diketo acid (DKA) derivatives inhibit HIV-1 replication by interacting with the Mg 2+ cofactors within the HIV-1 IN active site or within the HIV-1 reverse-transcriptase associated ribonuclease H (RNase H) active site. While the interaction mode of pyrrolyl DKAs with the RNase H active site has been recently reported and substantiated by mutagenesis experiments, their interaction within the IN active site still lacks a detailed understanding. In this study, we investigated the binding mode of four pyrrolyl DKAs to the HIV-1 IN active site by molecular modeling coupled with site-directed mutagenesis studies showing that the DKA pyrrolyl scaffold primarily interacts with the IN amino residues P145, Q146 and Q148. Importantly, the tested DKAs demonstrated good effectiveness against HIV-1 Raltegravir resistant Y143A and N155H INs, thus showing an interaction pattern with relevant differences if compared with the first generation IN inhibitors. These data provide precious insights for the design of new HIV inhibitors active on clinically selected Raltegravir resistant variants. Furthermore, this study provides new structural information to modulate IN and RNase H inhibitory activities for development of dual-acting anti-HIV agents. Copyright © 2016 Elsevier B.V. All rights reserved.

Model of brain activation predicts the neural collective influence map of the brain

PubMed Central

Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.

2017-01-01

Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973

Formation of readiness for future physics teachers by using interactive learning tools

NASA Astrophysics Data System (ADS)

Kulikova, N. U.; Danilchuk, E. V.; Zhidkova, A. V.

2017-01-01

In this article we give the reviewing of approaches to the preparedness of future physics teachers for the usage of interactive means of education as an important part of their professional activity. We discuss the key concepts such as interactivity, an interactive dialogue, and interactive means of education. The conception of interactive means of education as a tool of teachers' professional activity, which provides a way for the students to intensify their learning in class by using interactive tools and electronic educational resources, is validated. Furthermore, it is proved that interactive means of education allow the students to intensify their learning in the course of an interactive dialogue by means of organization different types of feedback in electronic educational resources (the program behavior depending on a user actions in the form of comments, prompts, elements of arrangement of objects, etc, the control and correction of students' actions by the program, providing with recommendations for further learning, carrying out constant access to reference information, etc), involving in different types of educational activity (modeling, investigation, etc), self-selection of time, speed, content of learning, complexity and priority of the usage of educational information on the screen, etc. By training students - future teachers of physics authors consider technological aspects, methodical features and examples of creation of these resources for physics lesson.

A general consumer-resource population model

USGS Publications Warehouse

Lafferty, Kevin D.; DeLeo, Giulio; Briggs, Cheryl J.; Dobson, Andrew P.; Gross, Thilo; Kuris, Armand M.

2015-01-01

Food-web dynamics arise from predator-prey, parasite-host, and herbivore-plant interactions. Models for such interactions include up to three consumer activity states (questing, attacking, consuming) and up to four resource response states (susceptible, exposed, ingested, resistant). Articulating these states into a general model allows for dissecting, comparing, and deriving consumer-resource models. We specify this general model for 11 generic consumer strategies that group mathematically into predators, parasites, and micropredators and then derive conditions for consumer success, including a universal saturating functional response. We further show how to use this framework to create simple models with a common mathematical lineage and transparent assumptions. Underlying assumptions, missing elements, and composite parameters are revealed when classic consumer-resource models are derived from the general model.

Using an academic-community partnership model and blended learning to advance community health nursing pedagogy.

PubMed

Ezeonwu, Mabel; Berkowitz, Bobbie; Vlasses, Frances R

2014-01-01

This article describes a model of teaching community health nursing that evolved from a long-term partnership with a community with limited existing health programs. The partnership supported RN-BSN students' integration in the community and resulted in reciprocal gains for faculty, students and community members. Community clients accessed public health services as a result of the partnership. A blended learning approach that combines face-to-face interactions, service learning and online activities was utilized to enhance students' learning. Following classroom sessions, students actively participated in community-based educational process through comprehensive health needs assessments, planning and implementation of disease prevention and health promotion activities for community clients. Such active involvement in an underserved community deepened students' awareness of the fundamentals of community health practice. Students were challenged to view public health from a broader perspective while analyzing the impacts of social determinants of health on underserved populations. Through asynchronous online interactions, students synthesized classroom and community activities through critical thinking. This paper describes a model for teaching community health nursing that informs students' learning through blended learning, and meets the demands for community health nursing services delivery. © 2013 Wiley Periodicals, Inc.

Monte Carlo calculations of positron emitter yields in proton radiotherapy.

PubMed

Seravalli, E; Robert, C; Bauer, J; Stichelbaut, F; Kurz, C; Smeets, J; Van Ngoc Ty, C; Schaart, D R; Buvat, I; Parodi, K; Verhaegen, F

2012-03-21

Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring. © 2012 Institute of Physics and Engineering in Medicine

Quantitative Modeling of Human-Environment Interactions in Preindustrial Time

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-04-01

Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical environment, e.g., through soil erosion.

Analytical response function for planar Ge detectors

NASA Astrophysics Data System (ADS)

García-Alvarez, Juan A.; Maidana, Nora L.; Vanin, Vito R.; Fernández-Varea, José M.

2016-04-01

We model the response function (RF) of planar HPGe x-ray spectrometers for photon energies between around 10 keV and 100 keV. The RF is based on the proposal of Seltzer [1981. Nucl. Instrum. Methods 188, 133-151] and takes into account the full-energy absorption in the Ge active volume, the escape of Ge Kα and Kβ x-rays and the escape of photons after one Compton interaction. The relativistic impulse approximation is employed instead of the Klein-Nishina formula to describe incoherent photon scattering in the Ge crystal. We also incorporate a simple model for the continuous component of the spectrum produced by the escape of photo-electrons from the active volume. In our calculations we include external interaction contributions to the RF: (i) the incoherent scattering effects caused by the detector's Be window and (ii) the spectrum produced by photo-electrons emitted in the Ge dead layer that reach the active volume. The analytical RF model is compared with pulse-height spectra simulated using the PENELOPE Monte Carlo code.

Lacosamide derivatives with anticonvulsant activity as carbonic anhydrase inhibitors. Molecular modeling, docking and QSAR analysis.

PubMed

Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Duchowicz, Pablo R; Torrens, Francisco; Estrada, Mario R

2014-01-01

Lacosamide is an anticonvulsant drug which presents carbonic anhydrase inhibition. In this paper, we analyzed the apparent relationship between both activities performing a molecular modeling, docking and QSAR studies on 18 lacosamide derivatives with known anticonvulsant activity. Docking results suggested the zinc-binding site of carbonic anhydrase is a possible target of lacosamide and lacosamide derivatives making favorable Van der Waals interactions with Asn67, Gln92, Phe131 and Thr200. The mathematical models revealed a poor relationship between the anticonvulsant activity and molecular descriptors obtained from DFT and docking calculations. However, a QSAR model was developed using Dragon software descriptors. The statistic parameters of the model are: correlation coefficient, R=0.957 and standard deviation, S=0.162. Our results provide new valuable information regarding the relationship between both activities and contribute important insights into the essential molecular requirements for the anticonvulsant activity.

BH3-only proteins trigger cytochrome c release, but how?

PubMed

Häcker, Georg; Weber, Arnim

2007-06-15

The mitochondrial apoptosis pathway has been neatly ordered. Mitochondrial apoptosis is governed by Bcl-2 family proteins, and their respective contributions determine the release of cytochrome c. It is clear that, among the Bcl-2 family, BH3-only proteins are the triggers: activation of BH3-only proteins by apoptotic stimuli initiates the process. BH3-only proteins cause cytochrome c release by activating Bax and/or Bak, and the anti-apoptotic group of Bcl-2-like proteins prevents this. However, it is curiously uncertain how BH3-only proteins activate Bax/Bak. Current models suggest that this is either through direct interaction--although this interaction is not detectable experimentally--or by the neutralisation of Bcl-2-like proteins. Here we discuss the context in which these models are placed and attempt to weigh the evidence.

Comparison of the oxime-induced reactivation of rhesus monkey, swine and guinea pig erythrocyte acetylcholinesterase following inhibition by sarin or paraoxon, using a perfusion model for the real-time determination of membrane-bound acetylcholinesterase activity.

PubMed

Herkert, Nadja M; Lallement, Guy; Clarençon, Didier; Thiermann, Horst; Worek, Franz

2009-04-28

Recently, a dynamically working in vitro model with real-time determination of membrane-bound human acetylcholinesterase (AChE) activity was shown to be a versatile model to investigate oxime-induced reactivation kinetics of organophosphate- (OP) inhibited enzyme. In this assay, AChE was immobilized on particle filters which were perfused with acetylthiocholine, Ellman's reagent and phosphate buffer. Subsequently, AChE activity was continuously analyzed in a flow-through detector. Now, it was an intriguing question whether this model could be used with erythrocyte AChE from other species in order to investigate kinetic interactions in the absence of annoying side reactions. Rhesus monkey, swine and guinea pig erythrocytes were a stable and highly reproducible enzyme source. Then, the model was applied to the reactivation of sarin- and paraoxon-inhibited AChE by obidoxime or HI 6 and it could be shown that the derived reactivation rate constants were in good agreement to previous results obtained from experiments with a static model. Hence, this dynamic model offers the possibility to investigate highly reproducible interactions between AChE, OP and oximes with human and animal AChE.

Engaging Undergraduate Biology Students in Scientific Modeling: Analysis of Group Interactions, Sense-Making, and Justification

PubMed Central

Bierema, Andrea M.-K.; Schwarz, Christina V.; Stoltzfus, Jon R.

2017-01-01

National calls for improving science education (e.g., Vision and Change) emphasize the need to learn disciplinary core ideas through scientific practices. To address this need, we engaged small groups of students in developing diagrammatic models within two (one large-enrollment and one medium-enrollment) undergraduate introductory biology courses. During these activities, students developed scientific models of biological phenomena such as enhanced growth in genetically modified fish. To investigate whether undergraduate students productively engaged in scientific practices during these modeling activities, we recorded groups of students as they developed models and examined three characteristics: how students 1) interacted with one another, 2) made sense of phenomena, and 3) justified their ideas. Our analysis indicates that students spent most of the time on task, developing and evaluating their models. Moreover, they worked cooperatively to make sense of core ideas and justified their ideas to one another throughout the activities. These results demonstrate that, when provided with the opportunity to develop models during class, students in large-enrollment lecture courses can productively engage in scientific practices. We discuss potential reasons for these outcomes and suggest areas of future research to continue advancing knowledge regarding engaging students in scientific practices in large-enrollment lecture courses. PMID:29196429

Additive and synergistic antiandrogenic activities of mixtures of azol fungicides and vinclozolin

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

Christen, Verena; Crettaz, Pierre; Fent, Karl, E-mail: karl.fent@fhnw.ch

Objective: Many pesticides including pyrethroids and azole fungicides are suspected to have an endocrine disrupting property. At present, the joint activity of compound mixtures is only marginally known. Here we tested the hypothesis that the antiandrogenic activity of mixtures of azole fungicides can be predicted by the concentration addition (CA) model. Methods: The antiandrogenic activity was assessed in MDA-kb2 cells. Following assessing single compounds activities mixtures of azole fungicides and vinclozolin were investigated. Interactions were analyzed by direct comparison between experimental and estimated dose–response curves assuming CA, followed by an analysis by the isobole method and the toxic unit approach.more » Results: The antiandrogenic activity of pyrethroids deltamethrin, cypermethrin, fenvalerate and permethrin was weak, while the azole fungicides tebuconazole, propiconazole, epoxiconazole, econazole and vinclozolin exhibited strong antiandrogenic activity. Ten binary and one ternary mixture combinations of five antiandrogenic fungicides were assessed at equi-effective concentrations of EC{sub 25} and EC{sub 50}. Isoboles indicated that about 50% of the binary mixtures were additive and 50% synergistic. Synergism was even more frequently indicated by the toxic unit approach. Conclusion: Our data lead to the conclusion that interactions in mixtures follow the CA model. However, a surprisingly high percentage of synergistic interactions occurred. Therefore, the mixture activity of antiandrogenic azole fungicides is at least additive. Practice: Mixtures should also be considered for additive antiandrogenic activity in hazard and risk assessment. Implications: Our evaluation provides an appropriate “proof of concept”, but whether it equally translates to in vivo effects should further be investigated. - Highlights: • Humans are exposed to pesticide mixtures such as pyrethroids and azole fungicides. • We assessed the antiandrogenicity of pyrethroids and azole fungizides. • Many azole fungicides showed significant antiandrogenic activity . • Many binary mixtures of antiandrogenic azole fungicides showed synergistic interactions. • Concentration addition of pesticides in mixtures should be considered.« less

A physiologically required G protein-coupled receptor (GPCR)-regulator of G protein signaling (RGS) interaction that compartmentalizes RGS activity.

PubMed

Croft, Wayne; Hill, Claire; McCann, Eilish; Bond, Michael; Esparza-Franco, Manuel; Bennett, Jeannette; Rand, David; Davey, John; Ladds, Graham

2013-09-20

G protein-coupled receptors (GPCRs) can interact with regulator of G protein signaling (RGS) proteins. However, the effects of such interactions on signal transduction and their physiological relevance have been largely undetermined. Ligand-bound GPCRs initiate by promoting exchange of GDP for GTP on the Gα subunit of heterotrimeric G proteins. Signaling is terminated by hydrolysis of GTP to GDP through intrinsic GTPase activity of the Gα subunit, a reaction catalyzed by RGS proteins. Using yeast as a tool to study GPCR signaling in isolation, we define an interaction between the cognate GPCR (Mam2) and RGS (Rgs1), mapping the interaction domains. This reaction tethers Rgs1 at the plasma membrane and is essential for physiological signaling response. In vivo quantitative data inform the development of a kinetic model of the GTPase cycle, which extends previous attempts by including GPCR-RGS interactions. In vivo and in silico data confirm that GPCR-RGS interactions can impose an additional layer of regulation through mediating RGS subcellular localization to compartmentalize RGS activity within a cell, thus highlighting their importance as potential targets to modulate GPCR signaling pathways.

Phonological Activation of Category Coordinates during Speech Planning is Observable in Children but Not in Adults: Evidence for Cascaded Processing

ERIC Educational Resources Information Center

Jescheniak, Jorg D.; Hahne, Anja; Hoffmann, Stefanie; Wagner, Valentin

2006-01-01

There is a long-standing debate in the area of speech production on the question of whether only words selected for articulation are phonologically activated (as maintained by serial-discrete models) or whether this is also true for their semantic competitors (as maintained by forward-cascading and interactive models). Past research has addressed…

Real beards and real networks: a spin-glass model for interacting individuals

NASA Astrophysics Data System (ADS)

O'Neale, Dion

''I want to be different, just like all the other different people'' sang the band King Missile. Whether they are the Beatniks of the 1950s, the punks of the 1970s, or the hipsters of today, non-conformists often tend to look the same, seemingly at odds with their goal of non-conformity. The spin-glass model, originally developed to describe the interaction of magnetic spins, and since applied to situations as diverse as the electrical activity of networks of neurons, to trades on a financial market, has recently been used in social science to study populations of interacting individuals comprised of a mix of both conformists and anti-conformists - or hipsters. Including delay effects for the interactions between individuals has been shown to give a system with non-trivial dynamics with a phase transition from stable behaviour to periodic switching between two states (let's call them bushy bearded and clean shaven). Analytic solutions to such a model are possible, but only for particular assumptions about the interaction and delay matrices. In this work we will show what happens when the interactions in the model are based on real-world networks with ''small-world'' effects and clustering.

The Learners' Mental Models of Television in Mathematics.

ERIC Educational Resources Information Center

Sumalee, Chaijaroen

1999-01-01

Examines the learners' mental models of television in actual media classroom activity by which knowledge was constructed. Findings revealed how media capabilities and the instructional designs that employ them interact with the learners and the task characteristics to influence the formation of the learners' mental models and their learning…

Student Modeling Based on Problem Solving Times

ERIC Educational Resources Information Center

Pelánek, Radek; Jarušek, Petr

2015-01-01

Student modeling in intelligent tutoring systems is mostly concerned with modeling correctness of students' answers. As interactive problem solving activities become increasingly common in educational systems, it is useful to focus also on timing information associated with problem solving. We argue that the focus on timing is natural for certain…

Activated PLC-γ1 is Catalytically Induced at LAT but Activated PLC-γ1 is Localized at both LAT- and TCR-Containing Complexes

PubMed Central

Cruz-Orcutt, Noemi; Vacaflores, Aldo; Connolly, Sean F.; Bunnell, Stephen C.; Houtman, Jon C.D.

2014-01-01

Phospholipase C-γ1 (PLC-γ1) is a key regulator of T cell receptor (TCR)-induced signaling. Activation of the TCR enhances PLC-γ1 enzymatic function, resulting in calcium influx and the activation of PKC family members and RasGRP. The current model is that phosphorylation of LAT tyrosine 132 facilitates the recruitment of PLC-γ1, leading to its activation and function at the LAT complex. In this study, we examined the phosphorylation kinetics of LAT and PLC-γ1 and the cellular localization of activated PLC-γ1. We observed that commencement of the phosphorylation of LAT tyrosine 132 and PLC-γ1 tyrosine 783 occurred simultaneously, supporting the current model. However, once begun, PLC-γ1 activation occurred more rapidly than LAT tyrosine 132. The association of LAT and PLC-γ1 was more transient than the interaction of LAT and Grb2 and a pool of activated PLC-γ1 translocated away from LAT to cellular structures containing the TCR. These studies demonstrate that LAT and PLC-γ1 form transient interactions that catalyze the activation of PLC-γ1, but that activated PLC-γ1 resides in both LAT and TCR clusters. Together, this work highlights that our current model is incomplete and the activation and function of PLC-γ1 in T cells is highly complex. PMID:24412752

Isobolographic analysis of the opioid-opioid interactions in a tonic and a phasic mouse model of induced nociceptive pain.

PubMed

Miranda, Hugo F; Noriega, Viviana; Zanetta, Pilar; Prieto, Juan Carlos; Prieto-Rayo, Juan Carlos; Aranda, Nicolás; Sierralta, Fernando

2014-07-15

Opioids have been used for the management of pain and coadministration of two opioids may induce synergism. In a model of tonic pain, the acetic acid writhing test and in a phasic model, the hot plate, the antinociceptive interaction between fentanyl, methadone, morphine, and tramadol was evaluated. The potency of opioids in the writhing test compared to the hot plate assay was from 2.5 (fentanyl) to 15.5 (morphine) times, respectively. The ED50 was used in a fixed ratio for each of the six pairs of opioid combinations, which, resulted in a synergistic antinociception except for methadone/tramadol and fentanyl/tramadol which were additive, in the hot plate. The opioid antagonists naltrexone, naltrindole and nor-binaltorphimine, suggests that the synergism of morphine combinations are due to the activation of MOR subtypes with partially contribution of DOR and KOR, however fentanyl and methadone combinations are partially due to the activation of MOR and DOR subtypes and KOR lack of participation. The antinociceptive effects of tramadol combinations, are partially due to the activation of MOR, DOR and KOR opioid subtypes. These results suggets that effectiveness and magnitude of the interactions between opioids are dependent on pain stimulus intensity.

Isobolographic analysis of the opioid-opioid interactions in a tonic and a phasic mouse model of induced nociceptive pain

PubMed Central

2014-01-01

Background Opioids have been used for the management of pain and coadministration of two opioids may induce synergism. In a model of tonic pain, the acetic acid writhing test and in a phasic model, the hot plate, the antinociceptive interaction between fentanyl, methadone, morphine, and tramadol was evaluated. Results The potency of opioids in the writhing test compared to the hot plate assay was from 2.5 (fentanyl) to 15.5 (morphine) times, respectively. The ED50 was used in a fixed ratio for each of the six pairs of opioid combinations, which, resulted in a synergistic antinociception except for methadone/tramadol and fentanyl/tramadol which were additive, in the hot plate. The opioid antagonists naltrexone, naltrindole and nor-binaltorphimine, suggests that the synergism of morphine combinations are due to the activation of MOR subtypes with partially contribution of DOR and KOR, however fentanyl and methadone combinations are partially due to the activation of MOR and DOR subtypes and KOR lack of participation. The antinociceptive effects of tramadol combinations, are partially due to the activation of MOR, DOR and KOR opioid subtypes. Conclusion These results suggets that effectiveness and magnitude of the interactions between opioids are dependent on pain stimulus intensity. PMID:25017386

Autonomous Optimization of Targeted Stimulation of Neuronal Networks

PubMed Central

Kumar, Sreedhar S.; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin

2016-01-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers. PMID:27509295

Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

PubMed

Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

2016-08-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.

A System for Modelling Cell–Cell Interactions during Plant Morphogenesis

PubMed Central

Dupuy, Lionel; Mackenzie, Jonathan; Rudge, Tim; Haseloff, Jim

2008-01-01

Background and aims During the development of multicellular organisms, cells are capable of interacting with each other through a range of biological and physical mechanisms. A description of these networks of cell–cell interactions is essential for an understanding of how cellular activity is co-ordinated in regionalized functional entities such as tissues or organs. The difficulty of experimenting on living tissues has been a major limitation to describing such systems, and computer modelling appears particularly helpful to characterize the behaviour of multicellular systems. The experimental difficulties inherent to the multitude of parallel interactions that underlie cellular morphogenesis have led to the need for computer models. Methods A new generic model of plant cellular morphogenesis is described that expresses interactions amongst cellular entities explicitly: the plant is described as a multi-scale structure, and interactions between distinct entities is established through a topological neighbourhood. Tissues are represented as 2D biphasic systems where the cell wall responds to turgor pressure through a viscous yielding of the cell wall. Key Results This principle was used in the development of the CellModeller software, a generic tool dedicated to the analysis and modelling of plant morphogenesis. The system was applied to three contrasting study cases illustrating genetic, hormonal and mechanical factors involved in plant morphogenesis. Conclusions Plant morphogenesis is fundamentally a cellular process and the CellModeller software, through its underlying generic model, provides an advanced research tool to analyse coupled physical and biological morphogenetic mechanisms. PMID:17921524

Visible Geology - Interactive online geologic block modelling

NASA Astrophysics Data System (ADS)

Cockett, R.

2012-12-01

Geology is a highly visual science, and many disciplines require spatial awareness and manipulation. For example, interpreting cross-sections, geologic maps, or plotting data on a stereonet all require various levels of spatial abilities. These skills are often not focused on in undergraduate geoscience curricula and many students struggle with spatial relations, manipulations, and penetrative abilities (e.g. Titus & Horsman, 2009). A newly developed program, Visible Geology, allows for students to be introduced to many geologic concepts and spatial skills in a virtual environment. Visible Geology is a web-based, three-dimensional environment where students can create and interrogate their own geologic block models. The program begins with a blank model, users then add geologic beds (with custom thickness and color) and can add geologic deformation events like tilting, folding, and faulting. Additionally, simple intrusive dikes can be modelled, as well as unconformities. Students can also explore the interaction of geology with topography by drawing elevation contours to produce their own topographic models. Students can not only spatially manipulate their model, but can create cross-sections and boreholes to practice their visual penetrative abilities. Visible Geology is easy to access and use, with no downloads required, so it can be incorporated into current, paper-based, lab activities. Sample learning activities are being developed that target introductory and structural geology curricula with learning objectives such as relative geologic history, fault characterization, apparent dip and thickness, interference folding, and stereonet interpretation. Visible Geology provides a richly interactive, and immersive environment for students to explore geologic concepts and practice their spatial skills.; Screenshot of Visible Geology showing folding and faulting interactions on a ridge topography.

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.

Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

PubMed Central

Zhang, Peng; Gao, Chao; Zhang, Na; Slepian, Marvin J.; Deng, Yuefan; Bluestein, Danny

2014-01-01

We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions. PMID:25530818

An Interactive Simulation Program for Exploring Computational Models of Auto-Associative Memory.

PubMed

Fink, Christian G

2017-01-01

While neuroscience students typically learn about activity-dependent plasticity early in their education, they often struggle to conceptually connect modification at the synaptic scale with network-level neuronal dynamics, not to mention with their own everyday experience of recalling a memory. We have developed an interactive simulation program (based on the Hopfield model of auto-associative memory) that enables the user to visualize the connections generated by any pattern of neural activity, as well as to simulate the network dynamics resulting from such connectivity. An accompanying set of student exercises introduces the concepts of pattern completion, pattern separation, and sparse versus distributed neural representations. Results from a conceptual assessment administered before and after students worked through these exercises indicate that the simulation program is a useful pedagogical tool for illustrating fundamental concepts of computational models of memory.

Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

Prediction of Physical Activity Level Using Processes of Change From the Transtheoretical Model: Experiential, Behavioral, or an Interaction Effect?

PubMed

Romain, Ahmed Jérôme; Horwath, Caroline; Bernard, Paquito

2018-01-01

The purpose of the present study was to compare prediction of physical activity (PA) by experiential or behavioral processes of change (POCs) or an interaction between both types of processes. A cross-sectional study. This study was conducted using an online questionnaire. A total of 394 participants (244 women, 150 men), with a mean age of 35.12 ± 12.04 years and a mean body mass index of 22.97 ± 4.25 kg/m 2 were included. Participants completed the Processes of Change, Stages of Change questionnaires, and the International Physical Activity Questionnaire to evaluate self-reported PA level (total, vigorous, and moderate PA). Hierarchical multiple regression models were used to test the prediction of PA level. For both total PA (β = .261; P < .001) and vigorous PA (β = .297; P < .001), only behavioral POCs were a significant predictor. Regarding moderate PA, only the interaction between experiential and behavioral POCs was a significant predictor (β = .123; P = .017). Our results provide confirmation that behavioral processes are most prominent in PA behavior. Nevertheless, it is of interest to note that the interaction between experiential and behavioral POCs was the only element predicting moderate PA level. Experiential processes were not associated with PA level.

Predicting forest insect flight activity: A Bayesian network approach

Treesearch

Stephen M. Pawson; Bruce G. Marcot; Owen G. Woodberry

2017-01-01

Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight...

In silico analysis of Pycnoporus cinnabarinus laccase active site with toxic industrial dyes.

PubMed

Prasad, Nirmal K; Vindal, Vaibhav; Narayana, Siva Lakshmi; Ramakrishna, V; Kunal, Swaraj Priyaranjan; Srinivas, M

2012-05-01

Laccases belong to multicopper oxidases, a widespread class of enzymes implicated in many oxidative functions in various industrial oxidative processes like production of fine chemicals to bioremediation of contaminated soil and water. In order to understand the mechanisms of substrate binding and interaction between substrates and Pycnoporus cinnabarinus laccase, a homology model was generated. The resulted model was further validated and used for docking studies with toxic industrial dyes- acid blue 74, reactive black 5 and reactive blue 19. Interactions of chemical mediators with the laccase was also examined. The docking analysis showed that the active site always cannot accommodate the dye molecules, due to constricted nature of the active site pocket and steric hindrance of the residues whereas mediators are relatively small and can easily be accommodated into the active site pocket, which, thereafter leads to the productive binding. The binding properties of these compounds along with identification of critical active site residues can be used for further site-directed mutagenesis experiments in order to identify their role in activity and substrate specificity, ultimately leading to improved mutants for degradation of these toxic compounds.

HTLV-1 Tax activates HIV-1 transcription in latency models.

PubMed

Geddes, Victor Emmanuel Viana; José, Diego Pandeló; Leal, Fabio E; Nixon, Douglas F; Tanuri, Amilcar; Aguiar, Renato Santana

2017-04-01

HIV-1 latency is a major obstacle to HIV-1 eradication. Coinfection with HTLV-1 has been associated with faster progression to AIDS. HTLV-1 encodes the transactivator Tax which can activate both HTLV-1 and HIV-1 transcription. Here, we demonstrate that Tax activates HIV transcription in latent CD4 + T cells. Tax promotes the activation of P-TEFb, releasing CDK9 and Cyclin T1 from inactive forms, promoting transcription elongation and reactivation of latent HIV-1. Tax mutants lacking interaction with the HIV-1-LTR promoter were not able to activate P-TEFb, with no subsequent activation of latent HIV. In HIV-infected primary resting CD4 + T cells, Tax-1 reactivated HIV-1 transcription up to five fold, confirming these findings in an ex vivo latency model. Finally, our results confirms that HTLV-1/Tax hijacks cellular partners, promoting HIV-1 transcription, and this interaction should be further investigated in HIV-1 latency studies in patients with HIV/HTLV-1 co-infection. Copyright © 2017 Elsevier Inc. All rights reserved.

Computing by physical interaction in neurons.

PubMed

Aur, Dorian; Jog, Mandar; Poznanski, Roman R

2011-12-01

The electrodynamics of action potentials represents the fundamental level where information is integrated and processed in neurons. The Hodgkin-Huxley model cannot explain the non-stereotyped spatial charge density dynamics that occur during action potential propagation. Revealed in experiments as spike directivity, the non-uniform charge density dynamics within neurons carry meaningful information and suggest that fragments of information regarding our memories are endogenously stored in structural patterns at a molecular level and are revealed only during spiking activity. The main conceptual idea is that under the influence of electric fields, efficient computation by interaction occurs between charge densities embedded within molecular structures and the transient developed flow of electrical charges. This process of computation underlying electrical interactions and molecular mechanisms at the subcellular level is dissimilar from spiking neuron models that are completely devoid of physical interactions. Computation by interaction describes a more powerful continuous model of computation than the one that consists of discrete steps as represented in Turing machines.

Nervous kidney. Interaction between renal sympathetic nerves and the renin-angiotensin system in the control of renal function.

PubMed

DiBona, G F

2000-12-01

Increases in renal sympathetic nerve activity regulate the functions of the nephron, the vasculature, and the renin-containing juxtaglomerular granular cells. Because increased activity of the renin-angiotensin system can also influence nephron and vascular function, it is important to understand the interactions between the renal sympathetic nerves and the renin-angiotensin system in the control of renal function. These interactions can be intrarenal, for example, the direct (by specific innervation) and indirect (by angiotensin II) contributions of increased renal sympathetic nerve activity to the regulation of renal function. The effects of increased renal sympathetic nerve activity on renal function are attenuated when the activity of the renin-angiotensin system is suppressed or antagonized with ACE inhibitors or angiotensin II-type AT(1)-receptor antagonists. The effects of intrarenal administration of angiotensin II are attenuated after renal denervation. These interactions can also be extrarenal, for example, in the central nervous system, wherein renal sympathetic nerve activity and its arterial baroreflex control are modulated by changes in activity of the renin-angiotensin system. In addition to the circumventricular organs, whose permeable blood-brain barrier permits interactions with circulating angiotensin II, there are interactions at sites behind the blood-brain barrier that depend on the influence of local angiotensin II. The responses to central administration of angiotensin II-type AT(1)-receptor antagonists into the ventricular system or microinjected into the rostral ventrolateral medulla are modulated by changes in activity of the renin-angiotensin system produced by physiological changes in dietary sodium intake. Similar modulation is observed in pathophysiological models wherein activity of both the renin-angiotensin and sympathetic nervous systems is increased (eg, congestive heart failure). Thus, both renal and extrarenal sites of interaction between the renin-angiotensin system and renal sympathetic nerve activity are involved in influencing the neural control of renal function.

Interaction of oscillations, and their suppression via deep brain stimulation, in a model of the cortico-basal ganglia network.

PubMed

Kang, Guiyeom; Lowery, Madeleine M

2013-03-01

Growing evidence suggests that synchronized neural oscillations in the cortico-basal ganglia network may play a critical role in the pathophysiology of Parkinson's disease. In this study, a new model of the closed loop network is used to explore the generation and interaction of network oscillations and their suppression through deep brain stimulation (DBS). Under simulated dopamine depletion conditions, increased gain through the hyperdirect pathway resulted in the interaction of neural oscillations at different frequencies in the cortex and subthalamic nucleus (STN), leading to the emergence of synchronized oscillations at a new intermediate frequency. Further increases in synaptic gain resulted in the cortex driving synchronous oscillatory activity throughout the network. When DBS was added to the model a progressive reduction in STN power at the tremor and beta frequencies was observed as the frequency of stimulation was increased, with resonance effects occurring for low frequency DBS (40 Hz) in agreement with experimental observations. The results provide new insights into the mechanisms by which synchronous oscillations can arise within the network and how DBS may suppress unwanted oscillatory activity.

Activated Tissue-Resident Mesenchymal Stromal Cells Regulate Natural Killer Cell Immune and Tissue-Regenerative Function.

PubMed

Petri, Robert Michael; Hackel, Alexander; Hahnel, Katrin; Dumitru, Claudia Alexandra; Bruderek, Kirsten; Flohe, Stefanie B; Paschen, Annette; Lang, Stephan; Brandau, Sven

2017-09-12

The interaction of mesenchymal stromal cells (MSCs) with natural killer (NK) cells is traditionally thought of as a static inhibitory model, whereby resting MSCs inhibit NK cell effector function. Here, we use a dynamic in vitro system of poly(I:C) stimulation to model the interaction of NK cells and tissue-resident MSCs in the context of infection or tissue injury. The experiments suggest a time-dependent system of regulation and feedback, where, at early time points, activated MSCs secrete type I interferon to enhance NK cell effector function, while at later time points TGF-β and IL-6 limit NK cell effector function and terminate inflammatory responses by induction of a regulatory senescent-like NK cell phenotype. Importantly, feedback of these regulatory NK cells to MSCs promotes survival, proliferation, and pro-angiogenic properties. Our data provide additional insight into the interaction of stromal cells and innate immune cells and suggest a model of time-dependent MSC polarization and licensing. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Parents and friends both matter: simultaneous and interactive influences of parents and friends on European schoolchildren's energy balance-related behaviours - the ENERGY cross-sectional study.

PubMed

te Velde, Saskia J; ChinAPaw, Mai J M; De Bourdeaudhuij, Ilse; Bere, Elling; Maes, Lea; Moreno, Luis; Jan, Nataša; Kovacs, Eva; Manios, Yannis; Brug, Johannes

2014-07-08

The family, and parents in particular, are considered the most important influencers regarding children's energy-balance related behaviours (EBRBs). When children become older and gain more behavioural autonomy regarding different behaviours, the parental influences may become less important and peer influences may gain importance. Therefore the current study aims to investigate simultaneous and interactive associations of family rules, parent and friend norms and modelling with soft drink intake, TV viewing, daily breakfast consumption and sport participation among schoolchildren across Europe. A school-based cross-sectional survey in eight countries across Europe among 10-12 year old schoolchildren. Child questionnaires were used to assess EBRBs (soft drink intake, TV viewing, breakfast consumption, sport participation), and potential determinants of these behaviours as perceived by the child, including family rules, parental and friend norms and modelling. Linear and logistic regression analyses (n = 7811) were applied to study the association of parental (norms, modelling and rules) and friend influences (norm and modelling) with the EBRBs. In addition, potential moderating effects of parental influences on the associations of friend influences with the EBRBs were studied by including interaction terms. Children reported more unfavourable friend norms and modelling regarding soft drink intake and TV viewing, while they reported more favourable friend and parental norms and modelling for breakfast consumption and physical activity. Perceived friend and parental norms and modelling were significantly positively associated with soft drink intake, breakfast consumption, physical activity (only modelling) and TV time. Across the different behaviours, ten significant interactions between parental and friend influencing variables were found and suggested a weaker association of friend norms and modelling when rules were in place. Parental and friends norm and modelling are associated with schoolchildren's energy balance-related behaviours. Having family rules or showing favourable parental modelling and norms seems to reduce the potential unfavourable associations of friends' norms and modelling with the EBRBs.

A Spatially Detailed Model of Isometric Contraction Based on Competitive Binding of Troponin I Explains Cooperative Interactions between Tropomyosin and Crossbridges

PubMed Central

Land, Sander; Niederer, Steven A.

2015-01-01

Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB), tropomyosin and troponin within a contractile regulatory unit (RU) to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU), between crossbridges (XB-XB), as well more complex interactions between crossbridges and regulatory units (XB-RU interactions). For the steady-state force-calcium relationship, our framework predicts that: (1) XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca2+], but have only small effects on cooperativity. (2) XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3) RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RU’s unblocking. (4) Myosin affinity for short (1–4 RU) unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca2+] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment ktr is explained by transient blocking of RU’s by a temporary decrease in XB-RU effects. PMID:26262582

Pollinators, pests, and predators: Recognizing ecological trade-offs in agroecosystems.

PubMed

Saunders, Manu E; Peisley, Rebecca K; Rader, Romina; Luck, Gary W

2016-02-01

Ecological interactions between crops and wild animals frequently result in increases or declines in crop yield. Yet, positive and negative interactions have mostly been treated independently, owing partly to disciplinary silos in ecological and agricultural sciences. We advocate a new integrated research paradigm that explicitly recognizes cost-benefit trade-offs among animal activities and acknowledges that these activities occur within social-ecological contexts. Support for this paradigm is presented in an evidence-based conceptual model structured around five evidence statements highlighting emerging trends applicable to sustainable agriculture. The full range of benefits and costs associated with animal activities in agroecosystems cannot be quantified by focusing on single species groups, crops, or systems. Management of productive agroecosystems should sustain cycles of ecological interactions between crops and wild animals, not isolate these cycles from the system. Advancing this paradigm will therefore require integrated studies that determine net returns of animal activity in agroecosystems.

Exploring Molecular Mechanisms of Paradoxical Activation in the BRAF Kinase Dimers: Atomistic Simulations of Conformational Dynamics and Modeling of Allosteric Communication Networks and Signaling Pathways

PubMed Central

Tse, Amanda; Verkhivker, Gennady M.

2016-01-01

The recent studies have revealed that most BRAF inhibitors can paradoxically induce kinase activation by promoting dimerization and enzyme transactivation. Despite rapidly growing number of structural and functional studies about the BRAF dimer complexes, the molecular basis of paradoxical activation phenomenon is poorly understood and remains largely hypothetical. In this work, we have explored the relationships between inhibitor binding, protein dynamics and allosteric signaling in the BRAF dimers using a network-centric approach. Using this theoretical framework, we have combined molecular dynamics simulations with coevolutionary analysis and modeling of the residue interaction networks to determine molecular determinants of paradoxical activation. We have investigated functional effects produced by paradox inducer inhibitors PLX4720, Dabrafenib, Vemurafenib and a paradox breaker inhibitor PLX7904. Functional dynamics and binding free energy analyses of the BRAF dimer complexes have suggested that negative cooperativity effect and dimer-promoting potential of the inhibitors could be important drivers of paradoxical activation. We have introduced a protein structure network model in which coevolutionary residue dependencies and dynamic maps of residue correlations are integrated in the construction and analysis of the residue interaction networks. The results have shown that coevolutionary residues in the BRAF structures could assemble into independent structural modules and form a global interaction network that may promote dimerization. We have also found that BRAF inhibitors could modulate centrality and communication propensities of global mediating centers in the residue interaction networks. By simulating allosteric communication pathways in the BRAF structures, we have determined that paradox inducer and breaker inhibitors may activate specific signaling routes that correlate with the extent of paradoxical activation. While paradox inducer inhibitors may facilitate a rapid and efficient communication via an optimal single pathway, the paradox breaker may induce a broader ensemble of suboptimal and less efficient communication routes. The central finding of our study is that paradox breaker PLX7904 could mimic structural, dynamic and network features of the inactive BRAF-WT monomer that may be required for evading paradoxical activation. The results of this study rationalize the existing structure-functional experiments by offering a network-centric rationale of the paradoxical activation phenomenon. We argue that BRAF inhibitors that amplify dynamic features of the inactive BRAF-WT monomer and intervene with the allosteric interaction networks may serve as effective paradox breakers in cellular environment. PMID:27861609

Interactions of dendrimers with biological drug targets: reality or mystery - a gap in drug delivery and development research.

PubMed

Ahmed, Shaimaa; Vepuri, Suresh B; Kalhapure, Rahul S; Govender, Thirumala

2016-07-21

Dendrimers have emerged as novel and efficient materials that can be used as therapeutic agents/drugs or as drug delivery carriers to enhance therapeutic outcomes. Molecular dendrimer interactions are central to their applications and realising their potential. The molecular interactions of dendrimers with drugs or other materials in drug delivery systems or drug conjugates have been extensively reported in the literature. However, despite the growing application of dendrimers as biologically active materials, research focusing on the mechanistic analysis of dendrimer interactions with therapeutic biological targets is currently lacking in the literature. This comprehensive review on dendrimers over the last 15 years therefore attempts to identify the reasons behind the apparent lack of dendrimer-receptor research and proposes approaches to address this issue. The structure, hierarchy and applications of dendrimers are briefly highlighted, followed by a review of their various applications, specifically as biologically active materials, with a focus on their interactions at the target site. It concludes with a technical guide to assist researchers on how to employ various molecular modelling and computational approaches for research on dendrimer interactions with biological targets at a molecular level. This review highlights the impact of a mechanistic analysis of dendrimer interactions on a molecular level, serves to guide and optimise their discovery as medicinal agents, and hopes to stimulate multidisciplinary research between scientific, experimental and molecular modelling research teams.

Models of physician-patient relationships in pharmaceutical direct-to-consumer advertising and consumer interviews.

PubMed

Arney, Jennifer; Lewin, Benjamin

2013-07-01

The rise of direct-to-consumer advertising (DTCA) has mirrored, if not facilitated, the shift toward more active health care consumers. We used content analysis to identify models of physician-patient interaction in DTCA from the 1997 to 2006 issues of a broad sample of women's, men's, and common readership magazines. We also conducted 36 in-depth interviews to examine the ways consumers receive and regard advertising messages, and to explore their preferences for clinical communication and decision making. We identified four models of physician-patient relationships that vary in their locus of control (physician, patient, or shared) and the form of support sought or obtained in the relationship (emotional or instrumental). Whereas consumer interviews reflected references to all four models of interaction, only two appeared in DTCA. The limited range of interactions seen in these advertisements creates a lack of congruity between interaction styles found in advertisements vs. styles reported by actual consumers.

Discrete model of the olivo-cerebellar system: structure and dynamics

NASA Astrophysics Data System (ADS)

Maslennikov, O. V.; Nekorkin, V. I.

2012-08-01

We propose a discrete model of the olivo-cerebellar system. The model consists of three layers of interacting elements, namely, inferior olive neurons, Purkinje cells, and deep cerebellar nuclear neurons combined into a structure by axonal connections. Each element of the structure is described by a two-dimensional map with an individual set of parameters for each type of neurons. Dynamic properties of different types of neurons are described and spontaneous and stimulusinduced dynamics of the system is explored. Unlike the previously proposed models, this study takes into account the axonal interaction of neurons of different layers, as well as the interaction of the inferior olive neurons through electrical synapses with the property of plasticity. It is shown that the inclusion of these factors plays a significant role in the formation of spatio-temporal activity of the inferior olive neurons.

Aggregation models on hypergraphs

NASA Astrophysics Data System (ADS)

Alberici, Diego; Contucci, Pierluigi; Mingione, Emanuele; Molari, Marco

2017-01-01

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer-dimer case. After translating those relations into structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.

3D-quantitative structure-activity relationship study for the design of novel enterovirus A71 3C protease inhibitors.

PubMed

Nie, Quandeng; Xu, Xiaoyi; Zhang, Qi; Ma, Yuying; Yin, Zheng; Shang, Luqing

2018-06-07

A three-dimensional quantitative structure-activity relationships model of enterovirus A71 3C protease inhibitors was constructed in this study. The protein-ligand interaction fingerprint was analyzed to generate a pharmacophore model. A predictive and reliable three-dimensional quantitative structure-activity relationships model was built based on the Flexible Alignment of AutoGPA. Moreover, three novel compounds (I-III) were designed and evaluated for their biochemical activity against 3C protease and anti-enterovirus A71 activity in vitro. III exhibited excellent inhibitory activity (IC 50 =0.031 ± 0.005 μM, EC 50 =0.036 ± 0.007 μM). Thus, this study provides a useful quantitative structure-activity relationships model to develop potent inhibitors for enterovirus A71 3C protease. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

20180129 - Computational Embryology: Translational Tools for Modeling in vitro Data (Toxicology Forum)

EPA Science Inventory

Integrative models are needed to "decode the toxicological blueprint of active substances that interact with living systems" (Systems toxicology). Computational biology is uniquely positioned to capture this connectivity and help shift decision-making to mechanistic pre...

F15063, a compound with D2/D3 antagonist, 5-HT1A agonist and D4 partial agonist properties: (III) Activity in models of cognition and negative symptoms

PubMed Central

Depoortère, R; Auclair, A L; Bardin, L; Slot, L Bruins; Kleven, M S; Colpaert, F; Vacher, B; Newman-Tancredi, A

2007-01-01

Background and purpose: The D2/D3 receptor antagonist, D4 receptor partial agonist, and high efficacy 5-HT1A receptor agonist F15063 was shown to be highly efficacious and potent in rodent models of activity against positive symptoms of schizophrenia. However F15063 induced neither catalepsy nor the ‘serotonin syndrome'. Here, we evaluated its profile in rat models predictive of efficacy against negative symptoms/cognitive deficits of schizophrenia. Experimental approach: F15063, given i.p., was assessed in models of behavioural deficits induced by interference with the NMDA/glutamatergic (phencyclidine: PCP) or cholinergic (scopolamine) systems. Key results: Through 5-HT1A activation, F15063 partially alleviated (MED: 0.04 mg kg−1) PCP-induced social interaction deficit between two adult rats, without effect by itself, underlining its potential to combat negative symptoms. At doses above 0.16 mg kg−1, F15063 reduced interaction by itself. F15063 (0.16 mg kg−1) selectively re-established PCP-impaired ‘cognitive flexibility' in a reversal learning task, suggesting potential against adaptability deficits. F15063 (0.04–0.63 mg kg−1) also reversed scopolamine-induced amnesia in a juvenile-adult rat social recognition test, indicative of a pro-cholinergic influence. Activity in this latter test is consistent with its D4 partial agonism, as it was blocked by the D4 antagonist L745,870. Finally, F15063 up to 40 mg kg−1 did not disrupt basal prepulse inhibition of startle reflex in rats, a marker of sensorimotor gating. Conclusions and implications: The balance of D2/D3, D4 and 5-HT1A receptor interactions of F15063 yields a promising profile of activity in models of cognitive deficits and negative symptoms of schizophrenia. PMID:17375085

The shape of things to come: Examining the interplay of elasticity, activity and geometry in soft matter

NASA Astrophysics Data System (ADS)

Evans, Arthur A.

This dissertation contains within an exploration of the interactions between various soft matter systems and an environmental stimulus. The natural case studies for examining soft matter using the language of thermodynamics and phase transitions are biological constituents, from slender filaments to entire collections of organisms. We first present a brief overview of soft condensed matter, couching the thesis in terms of states of matter and preparing the stage for using continuum mechanics to examine the sensitive balance between competing physical forces in determining the final state of the systems of interest. Following this we present analysis of long-range interactions in a ubiquitous soft matter system, flexible filaments. Adhesion events that occur between attractive filaments can be understood in terms of phase transitions, and herein we present a methodology for describing physical regimes where such transitions take place. Following this we present analyses of slender filaments and flexible membranes interacting with viscous fluids; of primary concern is the transduction of undulatory motion of the surface into propulsive thrust, as a model of microorganism locomotion. We show that slender filaments near walls can be shown to exhibit non-intuitive force characteristics as a fundamental consequence of the flexibility and geometry of the system, for several models of passively actuated and internally active model flagella. We then present two different active models for propulsion using a flexible membrane: the first simplifies the geometry in order to elucidate the direct consequences of internal forcing on macroscopic propulsive thrust, while the second is a proof of principle model for a microscopic vesicular swimmer. Finally, we study collective locomotion of microorganisms and active colloidal dispersions by performing a robust hydrodynamics simulation of a concentrated suspension of microswimmers. We find that global polar order persists throughout the system as a function of various microscopic swimming/activity parameters, as well as the volume fraction.

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

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

Cook, Kristin A.; Cramer, Nicholas O.; Israel, David

2015-12-07

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying modelsmore » of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.« less

Additive and synergistic antiandrogenic activities of mixtures of azol fungicides and vinclozolin.

PubMed

Christen, Verena; Crettaz, Pierre; Fent, Karl

2014-09-15

Many pesticides including pyrethroids and azole fungicides are suspected to have an endocrine disrupting property. At present, the joint activity of compound mixtures is only marginally known. Here we tested the hypothesis that the antiandrogenic activity of mixtures of azole fungicides can be predicted by the concentration addition (CA) model. The antiandrogenic activity was assessed in MDA-kb2 cells. Following assessing single compounds activities mixtures of azole fungicides and vinclozolin were investigated. Interactions were analyzed by direct comparison between experimental and estimated dose-response curves assuming CA, followed by an analysis by the isobole method and the toxic unit approach. The antiandrogenic activity of pyrethroids deltamethrin, cypermethrin, fenvalerate and permethrin was weak, while the azole fungicides tebuconazole, propiconazole, epoxiconazole, econazole and vinclozolin exhibited strong antiandrogenic activity. Ten binary and one ternary mixture combinations of five antiandrogenic fungicides were assessed at equi-effective concentrations of EC25 and EC50. Isoboles indicated that about 50% of the binary mixtures were additive and 50% synergistic. Synergism was even more frequently indicated by the toxic unit approach. Our data lead to the conclusion that interactions in mixtures follow the CA model. However, a surprisingly high percentage of synergistic interactions occurred. Therefore, the mixture activity of antiandrogenic azole fungicides is at least additive. Mixtures should also be considered for additive antiandrogenic activity in hazard and risk assessment. Our evaluation provides an appropriate "proof of concept", but whether it equally translates to in vivo effects should further be investigated. Copyright © 2014 Elsevier Inc. All rights reserved.

Solution structure of Apaf-1 CARD and its interaction with caspase-9 CARD: a structural basis for specific adaptor/caspase interaction.

PubMed

Zhou, P; Chou, J; Olea, R S; Yuan, J; Wagner, G

1999-09-28

Direct recruitment and activation of caspase-9 by Apaf-1 through the homophilic CARD/CARD (Caspase Recruitment Domain) interaction is critical for the activation of caspases downstream of mitochondrial damage in apoptosis. Here we report the solution structure of the Apaf-1 CARD domain and its surface of interaction with caspase-9 CARD. Apaf-1 CARD consists of six tightly packed amphipathic alpha-helices and is topologically similar to the RAIDD CARD, with the exception of a kink observed in the middle of the N-terminal helix. By using chemical shift perturbation data, the homophilic interaction was mapped to the acidic surface of Apaf-1 CARD centered around helices 2 and 3. Interestingly, a significant portion of the chemically perturbed residues are hydrophobic, indicating that in addition to the electrostatic interactions predicted previously, hydrophobic interaction is also an important driving force underlying the CARD/CARD interaction. On the basis of the identified functional residues of Apaf-1 CARD and the surface charge complementarity, we propose a model of CARD/CARD interaction between Apaf-1 and caspase-9.

A Semantic Basis for Meaning Construction in Constructivist Interactions

ERIC Educational Resources Information Center

Badie, Farshad

2015-01-01

Regarding constructivism as a learning philosophy and/or a model of knowing, a person (learner or mentor) based on her/his preconceptions and on personal knowings could actively participate in an interaction with another person (learner or mentor) in order to construct her/his personal knowledge. In this research I will analyse "meaning…

Poly(propyleneimine) glycodendrimers non-covalently bind ATP in a pH- and salt-dependent manner - model studies for adenosine analogue drug delivery.

PubMed

Gorzkiewicz, Michał; Buczkowski, Adam; Appelhans, Dietmar; Voit, Brigitte; Pułaski, Łukasz; Pałecz, Bartłomiej; Klajnert-Maculewicz, Barbara

2018-06-10

Adenosine analogue drugs (such as fludarabine or cladribine) require transporter-mediated uptake into cells and subsequent phosphorylation for anticancer activity. Therefore, application of nanocarrier systems for direct delivery of active triphosphate forms has been proposed. Here, we applied isothermal titration calorimetry and zeta potential titration to determine the stoichiometry and thermodynamic parameters of interactions between 4th generation poly(propyleneimine) dendrimers (unmodified or sugar-modified for increased biocompatibility) and ATP as a model adenosine nucleotide. We showed that glycodendrimers have the ability to efficiently interact with nucleoside triphosphates and to form stable complexes via electrostatic interactions between the ionized phosphate and amino groups on the nucleotide and the dendrimer, respectively. The complexation process is spontaneous, enthalpy-driven and depends on buffer composition (strongest interactions in organic buffer) and pH (more binding sites in acidic pH). These properties allow us to consider maltose-modified dendrimers as especially promising carriers for adenosine analogues. Copyright © 2018 Elsevier B.V. All rights reserved.

Suramin blocks interaction between human FGF1 and FGFR2 D2 domain and reduces downstream signaling activity

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

Wu, Zong-Sian, E-mail: gary810426@hotmail.com; Liu, Che Fu, E-mail: s9823002@m98.nthu.edu.tw; Fu, Brian, E-mail: brianfu9@gmail.com

2016-09-02

The extracellular portion of the human fibroblast growth factor receptor2 D2 domain (FGFR2 D2) interacts with human fibroblast growth factor 1 (hFGF1) to activate a downstream signaling cascade that ultimately affects mitosis and differentiation. Suramin is an antiparasiticdrug and a potent inhibitor of FGF-induced angiogenesis. Suramin has been shown to bind to hFGF1, and might block the interaction between hFGF1 and FGFR2 D2. Here, we titrated hFGF1 with FGFR2 D2 and suramin to elucidate their interactions using the detection of NMR. The docking results of both hFGF1-FGFR2 D2 domain and hFGF1-suramin complex were superimposed. The results indicate that suramin blocksmore » the interaction between hFGF1 and FGFR2 D2. We used the PyMOL software to show the hydrophobic interaction of hFGF1-suramin. In addition, we used a Water-soluble Tetrazolium salts assay (WST1) to assess hFGF1 bioactivity. The results will be useful for the development of new antimitogenic activity drugs. - Highlights: • The interfacial residues on hFGF1-FGFR2 D2 and hFGF1-Suramin contact surface were mapped by {sup 1}H-{sup 15}N HSQC experiments. • hFGF1-FGFR2 D2 and hFGF1-Suramin complex models were generated from NMR restraints by using HADDOCK program. • We analyzed hFGF1-Suramin complex models and found the interaction between hFGF1-Suramin is hydrophobic. • The bioactivity of the hFGF1-FGFR2 D2 and hFGF1-Suramin complex was studied by using WST1 assay.« less

The Prospective Joint Effects of Self-Regulation and Impulsive Processes on Early Adolescence Alcohol Use

PubMed Central

O’Connor, Roisin M.; Colder, Craig R.

2015-01-01

Objective: Dual-process models propose that behavior is influenced by the interactive effect of impulsive (automatic) and selfregulatory (controlled) processes. Elaborations of this model posit that the effect of impulsive processes on alcohol use is influenced by capacity and motivation to self-regulate. The interactive effect of these three processes on drinking has not previously been tested. The goal of this study was to provide a developmental extension of this model to early adolescent alcohol use and to test the three-way interaction between impulsive processes (implicit alcohol cognition), self-regulatory capacity (inhibitory and activation control), and self-regulatory motivation (negative alcohol outcome expectancies [AOE]) in a 1-year prospective prediction of adolescent alcohol use. Method: Adolescents (N = 325; 54% girls, mean age = 13.6 years at baseline) completed the Single Category Implicit Association Test and self-reports of alcohol expectancies and use. Inhibitory and activation control were based on parental report. Results: Negative AOE and inhibitory/activation control were supported as moderators of the effect of implicit alcohol cognition on 1-year prospective alcohol use. As expected, weak implicit negative alcohol cognition was associated with elevated alcohol use when both negative AOE and inhibitory control were low. Contrary to hypothesis, when activation control was high, weak implicit negative alcohol cognition was unrelated to alcohol use if negative AOE were high (p = .72) (vs. low, p < .01).Activation control may reflect the ability to plan ahead and act pro-socially. Conclusions: Our study supports current theory suggesting alcohol use is influenced by a complex interplay of impulsive and self-regulatory processes. PMID:26562596

Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.

PubMed

Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea

2018-06-01

The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

A pilot study assessing the value of 3D printed molecular modelling tools for pharmacy student education.

PubMed

Hall, Susan; Grant, Gary; Arora, Devinder; Karaksha, Abdullah; McFarland, Amelia; Lohning, Anna; Anoopkumar-Dukie, Shailendra

2017-07-01

Medicinal chemistry and pharmacology are difficult topics to both teach and learn given the complex nature of drug mechanisms and drug-receptor interactions. This highlights the need for innovative teaching methods to deliver this information to students. One such method is through three-dimensional (3D) printing of enzymes and ligands in the teaching of molecular modelling concepts relating to drug-receptor and enzyme interactions be ligands. This type of printing has been shown to be beneficial in several educational settings; however, to our knowledge, its effectiveness in pharmacy, medicinal chemistry and pharmacology learning and teaching is largely unknown. Therefore, the aim of this study was to evaluate pharmacy student perceptions and the educational benefits of 3D printed molecules in molecular modelling with regards to engagement and learning outcomes when used in a drug-target interaction topic. This aim was achieved through administering students a short questionnaire designed to evaluate their engagement and learning outcomes with students also free to provide comments. This study found that nearly all (>90%) students found the activity was useful in improving both student engagement and learning outcomes. In conclusion, 3D printing may provide an alternative learning activity to help pharmacy students understand the drug-target interaction. Copyright © 2017 Elsevier Inc. All rights reserved.

Abnormal Strain Rate Sensitivity Driven by a Unit Dislocation-Obstacle Interaction in bcc Fe

NASA Astrophysics Data System (ADS)

Bai, Zhitong; Fan, Yue

2018-03-01

The interaction between an edge dislocation and a sessile vacancy cluster in bcc Fe is investigated over a wide range of strain rates from 108 down to 103 s-1 , which is enabled by employing an energy landscape-based atomistic modeling algorithm. It is observed that, at low strain rates regime less than 105 s-1 , such interaction leads to a surprising negative strain rate sensitivity behavior because of the different intermediate microstructures emerged under the complex interplays between thermal activation and applied strain rate. Implications of our findings regarding the previously established global diffusion model are also discussed.

Information for Successful Interaction with Autonomous Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Johnson, Kathy A.

2003-01-01

Interaction in heterogeneous mission operations teams is not well matched to classical models of coordination with autonomous systems. We describe methods of loose coordination and information management in mission operations. We describe an information agent and information management tool suite for managing information from many sources, including autonomous agents. We present an integrated model of levels of complexity of agent and human behavior, which shows types of information processing and points of potential error in agent activities. We discuss the types of information needed for diagnosing problems and planning interactions with an autonomous system. We discuss types of coordination for which designs are needed for autonomous system functions.

An Interactive Activation Model of the Effect of Context in Perception. Part 2

DTIC Science & Technology

1980-07-15

nonword strings are often seen with letters transposed if the transposition will produce legal strings (Estes, 1975a; c.f. experiment by Stevens reported...Activation Model Rumelhart & McClelland Part II 90 References Anderson, J. A. Neural models with cognitive implications. In D. LaBerge & S. J. Samuels...Washington, DC 20372 Coe391 Dr. Gory PoockNavy Personnel R&D Center Operations Research Department LT Steven D. Harris. MSC, USN San Diego, CA 92152 Code

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Interactions of 1A2 insulator with promoter of hsp 70 gene in Drosophila melanogaster].

PubMed

Chetverina, D A; Elizar'ev, P V; Georgiev, P G; Erokhin, M M

2013-04-01

Insulators are regulatory DNA elements that participate in the modulation of the interactions between enhancers and promoters. Depending on the situation, insulators can either stabilize or destroy the contacts between enhancers and promoters. A possible explanation for the activity of insulators is their ability to directly interact with gene promoters. In the present study, it was demonstrated that, in model systems, a 1A2 insulator could interact with the core sequence of an hsp70 promoter. In this case, the insulator protein CP190 is found on the hsp70 promoter, which depends on the presence of an insulator in the transgene. The data obtained are consistent with the model, which implies that direct contacts between insulators and promoters make a considerable contribution to the modulation of the interactions between insulators and promoters.

Molecular Docking, Molecular Dynamics, and Structure–Activity Relationship Explorations of 14-Oxygenated N-Methylmorphinan-6-ones as Potent μ-Opioid Receptor Agonists

PubMed Central

2017-01-01

Among opioids, morphinans are of major importance as the most effective analgesic drugs acting primarily via μ-opioid receptor (μ-OR) activation. Our long-standing efforts in the field of opioid analgesics from the class of morphinans led to N-methylmorphinan-6-ones differently substituted at positions 5 and 14 as μ-OR agonists inducing potent analgesia and fewer undesirable effects. Herein we present the first thorough molecular modeling study and structure–activity relationship (SAR) explorations aided by docking and molecular dynamics (MD) simulations of 14-oxygenated N-methylmorphinan-6-ones to gain insights into their mode of binding to the μ-OR and interaction mechanisms. The structure of activated μ-OR provides an essential model for how ligand/μ-OR binding is encoded within small chemical differences in otherwise structurally similar morphinans. We reveal important molecular interactions that these μ-agonists share and distinguish them. The molecular docking outcomes indicate the crucial role of the relative orientation of the ligand in the μ-OR binding site, influencing the propensity of critical non-covalent interactions that are required to facilitate ligand/μ-OR interactions and receptor activation. The MD simulations point out minor differences in the tendency to form hydrogen bonds by the 4,5α-epoxy group, along with the tendency to affect the 3–7 lock switch. The emerged SARs reveal the subtle interplay between the substituents at positions 5 and 14 in the morphinan scaffold by enabling the identification of key structural elements that determine the distinct pharmacological profiles. This study provides a significant structural basis for understanding ligand binding and μ-OR activation by the 14-oxygenated N-methylmorphinan-6-ones, which should be useful for guiding drug design. PMID:28125215

Molecular Docking, Molecular Dynamics, and Structure-Activity Relationship Explorations of 14-Oxygenated N-Methylmorphinan-6-ones as Potent μ-Opioid Receptor Agonists.

PubMed

Noha, Stefan M; Schmidhammer, Helmut; Spetea, Mariana

2017-06-21

Among opioids, morphinans are of major importance as the most effective analgesic drugs acting primarily via μ-opioid receptor (μ-OR) activation. Our long-standing efforts in the field of opioid analgesics from the class of morphinans led to N-methylmorphinan-6-ones differently substituted at positions 5 and 14 as μ-OR agonists inducing potent analgesia and fewer undesirable effects. Herein we present the first thorough molecular modeling study and structure-activity relationship (SAR) explorations aided by docking and molecular dynamics (MD) simulations of 14-oxygenated N-methylmorphinan-6-ones to gain insights into their mode of binding to the μ-OR and interaction mechanisms. The structure of activated μ-OR provides an essential model for how ligand/μ-OR binding is encoded within small chemical differences in otherwise structurally similar morphinans. We reveal important molecular interactions that these μ-agonists share and distinguish them. The molecular docking outcomes indicate the crucial role of the relative orientation of the ligand in the μ-OR binding site, influencing the propensity of critical non-covalent interactions that are required to facilitate ligand/μ-OR interactions and receptor activation. The MD simulations point out minor differences in the tendency to form hydrogen bonds by the 4,5α-epoxy group, along with the tendency to affect the 3-7 lock switch. The emerged SARs reveal the subtle interplay between the substituents at positions 5 and 14 in the morphinan scaffold by enabling the identification of key structural elements that determine the distinct pharmacological profiles. This study provides a significant structural basis for understanding ligand binding and μ-OR activation by the 14-oxygenated N-methylmorphinan-6-ones, which should be useful for guiding drug design.

Designing for sustained adoption: A model of developing educational innovations for successful propagation

NASA Astrophysics Data System (ADS)

Khatri, Raina; Henderson, Charles; Cole, Renée; Froyd, Jeffrey E.; Friedrichsen, Debra; Stanford, Courtney

2016-06-01

[This paper is part of the Focused Collection on Preparing and Supporting University Physics Educators.] The physics education research community has produced a wealth of knowledge about effective teaching and learning of college level physics. Based on this knowledge, many research-proven instructional strategies and teaching materials have been developed and are currently available to instructors. Unfortunately, these intensive research and development activities have failed to influence the teaching practices of many physics instructors. This paper describes interim results of a larger study to develop a model of designing materials for successful propagation. The larger study includes three phases, the first two of which are reported here. The goal of the first phase was to characterize typical propagation practices of education developers, using data from a survey of 1284 National Science Foundation (NSF) principal investigators and focus group data from eight disciplinary groups of NSF program directors. The goal of the second phase was to develop an understanding of successful practice by studying three instructional strategies that have been well propagated. The result of the first two phases is a tentative model of designing for successful propagation, which will be further validated in the third phase through purposeful sampling of additional well-propagated instructional strategies along with typical education development projects. We found that interaction with potential adopters was one of the key missing ingredients in typical education development activities. Education developers often develop a polished product before getting feedback, rely on mass-market communication channels for dissemination, and do not plan for supporting adopters during implementation. The tentative model resulting from this study identifies three key propagation activities: interactive development, interactive dissemination, and support of adopters. Interactive development uses significant feedback from potential adopters to develop a strong product suitable for use in many settings. Interactive dissemination uses personal interactions to reach and motivate potential users. Support of adopters is missing from typical propagation practice and is important to reduce the burden of implementation and increases the likelihood of successful adoption.

Phase Transitions in a Model for Social Learning via the Internet

NASA Astrophysics Data System (ADS)

Bordogna, Clelia M.; Albano, Ezequiel V.

Based on the concepts of educational psychology, sociology and statistical physics, a mathematical model for a new type of social learning process that takes place when individuals interact via the Internet is proposed and studied. The noise of the interaction (misunderstandings, lack of well organized participative activities, etc.) dramatically restricts the number of individuals that can be efficiently in mutual contact and drives phase transitions between ``ordered states'' such as the achievements of the individuals are satisfactory and ``disordered states'' with negligible achievements.

Molecular modeling of human neutral sphingomyelinase provides insight into its molecular interactions.

PubMed

Dinesh; Goswami, Angshumala; Suresh, Panneer Selvam; Thirunavukkarasu, Chinnasamy; Weiergräber, Oliver H; Kumar, Muthuvel Suresh

2011-01-01

The neutral sphingomyelinase (N-SMase) is considered a major candidate for mediating the stress-induced production of ceramide, and it plays an important role in cell-cycle arrest, apoptosis, inflammation, and eukaryotic stress responses. Recent studies have identified a small region at the very N-terminus of the 55 kDa tumour necrosis factor receptor (TNF-R55), designated the neutral sphingomyelinase activating domain (NSD) that is responsible for the TNF-induced activation of N-SMase. There is no direct association between TNF-R55 NSD and N-SMase; instead, a protein named factor associated with N-SMase activation (FAN) has been reported to couple the TNF-R55 NSD to N-SMase. Since the three-dimensional fold of N-SMase is still unknown, we have modeled the structure using the protein fold recognition and threading method. Moreover, we propose models for the TNF-R55 NSD as well as the FAN protein in order to study the structural basis of N-SMase activation and regulation. Protein-protein interaction studies suggest that FAN is crucially involved in mediating TNF-induced activation of the N-SMase pathway, which in turn regulates mitogenic and proinflammatory responses. Inhibition of N-SMase may lead to reduction of ceramide levels and hence may provide a novel therapeutic strategy for inflammation and autoimmune diseases. Molecular dynamics (MD) simulations were performed to check the stability of the predicted model and protein-protein complex; indeed, stable RMS deviations were obtained throughout the simulation. Furthermore, in silico docking of low molecular mass ligands into the active site of N-SMase suggests that His135, Glu48, Asp177, and Asn179 residues play crucial roles in this interaction. Based on our results, these ligands are proposed to be potent and selective N-SMase inhibitors, which may ultimately prove useful as lead compounds for drug development.

Ising model of cardiac thin filament activation with nearest-neighbor cooperative interactions

NASA Technical Reports Server (NTRS)

Rice, John Jeremy; Stolovitzky, Gustavo; Tu, Yuhai; de Tombe, Pieter P.; Bers, D. M. (Principal Investigator)

2003-01-01

We have developed a model of cardiac thin filament activation using an Ising model approach from equilibrium statistical physics. This model explicitly represents nearest-neighbor interactions between 26 troponin/tropomyosin units along a one-dimensional array that represents the cardiac thin filament. With transition rates chosen to match experimental data, the results show that the resulting force-pCa (F-pCa) relations are similar to Hill functions with asymmetries, as seen in experimental data. Specifically, Hill plots showing (log(F/(1-F)) vs. log [Ca]) reveal a steeper slope below the half activation point (Ca(50)) compared with above. Parameter variation studies show interplay of parameters that affect the apparent cooperativity and asymmetry in the F-pCa relations. The model also predicts that Ca binding is uncooperative for low [Ca], becomes steeper near Ca(50), and becomes uncooperative again at higher [Ca]. The steepness near Ca(50) mirrors the steep F-pCa as a result of thermodynamic considerations. The model also predicts that the correlation between troponin/tropomyosin units along the one-dimensional array quickly decays at high and low [Ca], but near Ca(50), high correlation occurs across the whole array. This work provides a simple model that can account for the steepness and shape of F-pCa relations that other models fail to reproduce.

The CD44-initiated pathway of T-cell extravasation uses VLA-4 but not LFA-1 for firm adhesion

PubMed Central

Siegelman, Mark H.; Stanescu, Diana; Estess, Pila

2000-01-01

Leukocytes extravasate from the blood in response to physiologic or pathologic demands by means of complementary ligand interactions between leukocytes and endothelial cells. The multistep model of leukocyte extravasation involves an initial transient interaction (“rolling” adhesion), followed by secondary (firm) adhesion. We recently showed that binding of CD44 on activated T lymphocytes to endothelial hyaluronan (HA) mediates a primary adhesive interaction under shear stress, permitting extravasation at sites of inflammation. The mechanism for subsequent firm adhesion has not been elucidated. Here we demonstrate that the integrin VLA-4 is used in secondary adhesion after CD44-mediated primary adhesion of human and mouse T cells in vitro, and by mouse T cells in an in vivo model. We show that clonal cell lines and polyclonally activated normal T cells roll under physiologic shear forces on hyaluronate and require VCAM-1, but not ICAM-1, as ligand for subsequent firm adhesion. This firm adhesion is also VLA-4 dependent, as shown by antibody inhibition. Moreover, in vivo short-term homing experiments in a model dependent on CD44 and HA demonstrate that superantigen-activated T cells require VLA-4, but not LFA-1, for entry into an inflamed peritoneal site. Thus, extravasation of activated T cells initiated by CD44 binding to HA depends upon VLA-4–mediated firm adhesion, which may explain the frequent association of these adhesion receptors with diverse chronic inflammatory processes. PMID:10712440

ECOLOGICAL THEORY. A general consumer-resource population model.

PubMed

Lafferty, Kevin D; DeLeo, Giulio; Briggs, Cheryl J; Dobson, Andrew P; Gross, Thilo; Kuris, Armand M

2015-08-21

Food-web dynamics arise from predator-prey, parasite-host, and herbivore-plant interactions. Models for such interactions include up to three consumer activity states (questing, attacking, consuming) and up to four resource response states (susceptible, exposed, ingested, resistant). Articulating these states into a general model allows for dissecting, comparing, and deriving consumer-resource models. We specify this general model for 11 generic consumer strategies that group mathematically into predators, parasites, and micropredators and then derive conditions for consumer success, including a universal saturating functional response. We further show how to use this framework to create simple models with a common mathematical lineage and transparent assumptions. Underlying assumptions, missing elements, and composite parameters are revealed when classic consumer-resource models are derived from the general model. Copyright © 2015, American Association for the Advancement of Science.

Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors

NASA Astrophysics Data System (ADS)

Wang, Fangfang; Zhou, Bo

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R2cv = 0.600, R2pred = 0.6760) and CoMSIA (R2cv = 0.624, R2pred = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors.

Collective dynamics of soft active particles

NASA Astrophysics Data System (ADS)

van Drongelen, Ruben; Pal, Anshuman; Goodrich, Carl P.; Idema, Timon

2015-03-01

We present a model of soft active particles that leads to a rich array of collective behavior found also in dense biological swarms of bacteria and other unicellular organisms. Our model uses only local interactions, such as Vicsek-type nearest-neighbor alignment, short-range repulsion, and a local boundary term. Changing the relative strength of these interactions leads to migrating swarms, rotating swarms, and jammed swarms, as well as swarms that exhibit run-and-tumble motion, alternating between migration and either rotating or jammed states. Interestingly, although a migrating swarm moves slower than an individual particle, the diffusion constant can be up to three orders of magnitude larger, suggesting that collective motion can be highly advantageous, for example, when searching for food.

Modeling Interactions between Transposable Elements and the Plant Epigenetic Response: A Surprising Reliance on Element Retention.

PubMed

Roessler, Kyria; Bousios, Alexandros; Meca, Esteban; Gaut, Brandon S

2018-03-01

Transposable elements (TEs) compose the majority of angiosperm DNA. Plants counteract TE activity by silencing them epigenetically. One form of epigenetic silencing requires 21-22 nt small interfering RNAs that act to degrade TE mRNA and may also trigger DNA methylation. DNA methylation is reinforced by a second mechanism, the RNA-dependent DNA methylation (RdDM) pathway. RdDM relies on 24 nt small interfering RNAs and ultimately establishes TEs in a quiescent state. These host factors interact at a systems level, but there have been no system level analyses of their interactions. Here, we define a deterministic model that represents the propagation of active TEs, aspects of the host response and the accumulation of silenced TEs. We describe general properties of the model and also fit it to biological data in order to explore two questions. The first is why two overlapping pathways are maintained, given that both are likely energetically expensive. Under our model, RdDM silenced TEs effectively even when the initiation of silencing was weak. This relationship implies that only a small amount of RNAi is needed to initiate TE silencing, but reinforcement by RdDM is necessary to efficiently counter TE propagation. Second, we investigated the reliance of the host response on rates of TE deletion. The model predicted that low levels of deletion lead to few active TEs, suggesting that silencing is most efficient when methylated TEs are retained in the genome, thereby providing one explanation for the large size of plant genomes.

Neurotoxicological and statistical analyses of a mixture of five organophosphorus pesticides using a ray design.

PubMed

Moser, V C; Casey, M; Hamm, A; Carter, W H; Simmons, J E; Gennings, C

2005-07-01

Environmental exposures generally involve chemical mixtures instead of single chemicals. Statistical models such as the fixed-ratio ray design, wherein the mixing ratio (proportions) of the chemicals is fixed across increasing mixture doses, allows for the detection and characterization of interactions among the chemicals. In this study, we tested for interaction(s) in a mixture of five organophosphorus (OP) pesticides (chlorpyrifos, diazinon, dimethoate, acephate, and malathion). The ratio of the five pesticides (full ray) reflected the relative dietary exposure estimates of the general population as projected by the US EPA Dietary Exposure Evaluation Model (DEEM). A second mixture was tested using the same dose levels of all pesticides, but excluding malathion (reduced ray). The experimental approach first required characterization of dose-response curves for the individual OPs to build a dose-additivity model. A series of behavioral measures were evaluated in adult male Long-Evans rats at the time of peak effect following a single oral dose, and then tissues were collected for measurement of cholinesterase (ChE) activity. Neurochemical (blood and brain cholinesterase [ChE] activity) and behavioral (motor activity, gait score, tail-pinch response score) endpoints were evaluated statistically for evidence of additivity. The additivity model constructed from the single chemical data was used to predict the effects of the pesticide mixture along the full ray (10-450 mg/kg) and the reduced ray (1.75-78.8 mg/kg). The experimental mixture data were also modeled and statistically compared to the additivity models. Analysis of the 5-OP mixture (the full ray) revealed significant deviation from additivity for all endpoints except tail-pinch response. Greater-than-additive responses (synergism) were observed at the lower doses of the 5-OP mixture, which contained non-effective dose levels of each of the components. The predicted effective doses (ED20, ED50) were about half that predicted by additivity, and for brain ChE and motor activity, there was a threshold shift in the dose-response curves. For the brain ChE and motor activity, there was no difference between the full (5-OP mixture) and reduced (4-OP mixture) rays, indicating that malathion did not influence the non-additivity. While the reduced ray for blood ChE showed greater deviation from additivity without malathion in the mixture, the non-additivity observed for the gait score was reversed when malathion was removed. Thus, greater-than-additive interactions were detected for both the full and reduced ray mixtures, and the role of malathion in the interactions varied depending on the endpoint. In all cases, the deviations from additivity occurred at the lower end of the dose-response curves.

Mechanisms and models of REM sleep control.

PubMed

McCarley, R W

2004-07-01

The first sections of this paper survey the history and recent developments relevant to the major neurotransmitters and neuromodulators involved in REM sleep control. The last portion of this paper proposes a structural model of cellular interaction that produces the REM sleep cycle, and constitutes a further revision of the reciprocal interaction model This paper proposes seven criteria to define a causal role in REM sleep control for putative neuro-transmitters/modulators. The principal criteria are measurements during behavioral state changes of the extracellular concentrations of the putative substances, and electrophysiological recording of their neuronal source. A cautionary note is that, while pharmacological manipulations are suggestive, they alone do not provide definitive causal evidence. The extensive body of in vivo and in vitro evidence supporting cholinergic promotion of REM sleep via LDT/PPT neuronal activity is surveyed. An interesting question raised by some studies is whether cholinergic influences in rat are less puissant than in cat. At least some of the apparent lesser REM-inducing effect of carbachol in the rat may be due to incomplete control of circadian influences; almost all experiments have been run only in the daytime, inactive period, when REM sleep is more prominent, rather than in the REM-sparse nighttime inactive period. Monoaminergic inhibition of cholinergic neurons, once thought to be the most shaky proposal of the reciprocal interaction model, now enjoys considerable support from both in vivo and in vitro data. However, the observed time course of monoaminergic neurons, their "turning off" discharge activity as REM sleep is approached and entered would seem to be difficult to produce from feedback inhibition, as originally postulated by the reciprocal interaction model. New data suggest the possibility that GABAergic inhibition of Locus Coeruleus and Dorsal Raphe monoaminergic neurons may account for the "REM-off" neurons turning off. However, the source(s) of GABAergic influences suggested by anatomical studies has yet to be definitively identified by electrophysiological recordings of GABAergic neurons that show the requisite inverse time course of activity relative to monoaminergic neurons. New and still preliminary microdialysis data suggest that reticular formation neurons, the effector neurons for REM sleep phenomena, might be disinhibited during REM sleep by decreased GABAergic influence, perhaps stemming from REM-on cholinergic neuronal inhibition of reticular formation GABAergic neurons. Whether the postulated cholinergic inhibition of GABAergic neurons is present is testable with in vitro recordings and double labeling. Taking into account the observed data on neuro-modulators/transmitters, a structural model incorporating interaction of REM-on and REM-off neurons and GABAergic influences is proposed. Finally, with respect to orexin and REM sleep, it is hypothesized that orexinergic activity may be a principal factor controlling REM sleep's absence from the active period in strongly circadian animals such as rat and man.

μ Opioid receptor: novel antagonists and structural modeling

NASA Astrophysics Data System (ADS)

Kaserer, Teresa; Lantero, Aquilino; Schmidhammer, Helmut; Spetea, Mariana; Schuster, Daniela

2016-02-01

The μ opioid receptor (MOR) is a prominent member of the G protein-coupled receptor family and the molecular target of morphine and other opioid drugs. Despite the long tradition of MOR-targeting drugs, still little is known about the ligand-receptor interactions and structure-function relationships underlying the distinct biological effects upon receptor activation or inhibition. With the resolved crystal structure of the β-funaltrexamine-MOR complex, we aimed at the discovery of novel agonists and antagonists using virtual screening tools, i.e. docking, pharmacophore- and shape-based modeling. We suggest important molecular interactions, which active molecules share and distinguish agonists and antagonists. These results allowed for the generation of theoretically validated in silico workflows that were employed for prospective virtual screening. Out of 18 virtual hits evaluated in in vitro pharmacological assays, three displayed antagonist activity and the most active compound significantly inhibited morphine-induced antinociception. The new identified chemotypes hold promise for further development into neurochemical tools for studying the MOR or as potential therapeutic lead candidates.

Models for the mechanism for activating copper-zinc superoxide dismutase in the absence of the CCS Cu chaperone in Arabidopsis.

PubMed

Huang, Chien-Hsun; Kuo, Wen-Yu; Jinn, Tsung-Luo

2012-03-01

Copper-zinc superoxide dismutase (CuZnSOD; CSD) is an important antioxidant enzyme for oxidative stress protection. To date, two activation pathways have been identified in many species. One requiring the CCS, Cu chaperone for SOD, to insert Cu and activate CSD (referred to as CCS-dependent pathway), and the other works independently of CCS (referred to as CCS-independent pathway). In our previous study, we suggest an unidentified factor will work with glutathione (GSH) for CSD activation in the absence of the CCS. Here, two models of the CCS-independent mechanism are proposed. The role of the unidentified factor may work as a scaffold protein, which provides a platform for the CSD protein and Cu-GSH to interact, or as a Cu carrier, which itself can bind Cu and interact with CSD proteins. We also suggest that the CSD protein conformation at C-terminal is important in providing a docking site for unidentified factor to access.

Enalapril enhances the anticonvulsant activity of lamotrigine in the test of maximal electroshock.

PubMed

Łukawski, Krzysztof; Jakubus, Tomasz; Janowska, Agnieszka; Raszewski, Grzegorz; Czuczwar, Stanisław J

2013-01-01

The aim of this study was to find out whether angiotensin-converting enzyme (ACE) inhibitors, enalapril and cilazapril, affect the anticonvulsant action of some second-generation antiepileptics, lamotrigine (LTG), topiramate (TPM) and oxcarbazepine (OXC). The effects of ACE inhibitors on antiepileptic drugs were examined in the mouse model of maximal electroshock. Enalapril (30 mg/kg ip) potentiated the anticonvulsant action of LTG, decreasing its ED50 value from 5.3 to 3.6 mg/kg (p < 0.01). The anticonvulsant activity of TPM or OXC was not modified by enalapril. Cilazapril did not affect the protective activity of the studied antiepileptics. The interaction between enalapril and LTG could be pharmacodynamic in nature because enalapril did not change plasma and total brain concentrations of LTG. This study shows that there are no negative interactions between the studied antiepileptic drugs and enalapril or cilazapril. Enalapril even enhanced the anticonvulsant activity of LTG in the MES test in mice that is thought to be a predictive model of human generalized tonic-clonic seizures.

Designing a highly active soluble PQQ-glucose dehydrogenase for efficient glucose biosensors and biofuel cells

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

Durand, Fabien; Stines-Chaumeil, Claire; Flexer, Victoria

2010-11-26

Research highlights: {yields} A new mutant of PQQ-GDH designed for glucose biosensors application. {yields} First mutant of PQQ-GDH with higher activity for D-glucose than the Wild type. {yields} Position N428 is a key point to increase the enzyme activity. {yields} Molecular modeling shows that the N428 C mutant displays a better interaction for PQQ than the WT. -- Abstract: We report for the first time a soluble PQQ-glucose dehydrogenase that is twice more active than the wild type for glucose oxidation and was obtained by combining site directed mutagenesis, modelling and steady-state kinetics. The observed enhancement is attributed to amore » better interaction between the cofactor and the enzyme leading to a better electron transfer. Electrochemical experiments also demonstrate the superiority of the new mutant for glucose oxidation and make it a promising enzyme for the development of high-performance glucose biosensors and biofuel cells.« less

Impact of two different saponins on the organization of model lipid membranes.

PubMed

Korchowiec, Beata; Gorczyca, Marcelina; Wojszko, Kamila; Janikowska, Maria; Henry, Max; Rogalska, Ewa

2015-10-01

Saponins, naturally occurring plant compounds are known for their biological and pharmacological activity. This activity is strongly related to the amphiphilic character of saponins that allows them to aggregate in aqueous solution and interact with membrane components. In this work, Langmuir monolayer techniques combined with polarization modulation infrared reflection-absorption spectroscopy (PM-IRRAS) and Brewster angle microscopy were used to study the interaction of selected saponins with lipid model membranes. Two structurally different saponins were used: digitonin and a commercial Merck Saponin. Membranes of different composition, namely, cholesterol, 1,2-dipalmitoyl-sn-glycero-3-phosphocholine or 1,2-dipalmitoyl-sn-glycero-3-phospho-rac-(1-glycerol) were formed at the air/water and air/saponin solution interfaces. The saponin-lipid interaction was characterized by changes in surface pressure, surface potential, surface morphology and PM-IRRAS signal. Both saponins interact with model membranes and change the physical state of membranes by perturbing the lipid acyl chain orientation. The changes in membrane fluidity were more significant upon the interaction with Merck Saponin. A higher affinity of saponins for cholesterol than phosphatidylglycerols was observed. Moreover, our results indicate that digitonin interacts strongly with cholesterol and solubilize the cholesterol monolayer at higher surface pressures. It was shown, that digitonin easily penetrate to the cholesterol monolayer and forms a hydrogen bond with the hydroxyl groups. These findings might be useful in further understanding of the saponin action at the membrane interface and of the mechanism of membrane lysis. Copyright © 2015 Elsevier B.V. All rights reserved.

Solubility Prediction of Active Pharmaceutical Compounds with the UNIFAC Model

NASA Astrophysics Data System (ADS)

Nouar, Abderrahim; Benmessaoud, Ibtissem; Koutchoukali, Ouahiba; Koutchoukali, Mohamed Salah

2016-03-01

The crystallization from solution of an active pharmaceutical ingredient requires the knowledge of the solubility in the entire temperature range investigated during the process. However, during the development of a new active ingredient, these data are missing. Its experimental determination is possible, but tedious. UNIFAC Group contribution method Fredenslund et al. (Vapor-liquid equilibria using UNIFAC: a group contribution method, 1977; AIChE J 21:1086, 1975) can be used to predict this physical property. Several modifications on this model have been proposed since its development in 1977, modified UNIFAC of Dortmund Weidlich et al. (Ind Eng Chem Res 26:1372, 1987), Gmehling et al. (Ind Eng Chem Res 32:178, 1993), Pharma-modified UNIFAC Diedrichs et al. (Evaluation und Erweiterung thermodynamischer Modelle zur Vorhersage von Wirkstofflöslichkeiten, PhD Thesis, 2010), KT-UNIFAC Kang et al. (Ind Eng Chem Res 41:3260, 2002), ldots In this study, we used UNIFAC model by considering the linear temperature dependence of interaction parameters as in Pharma-modified UNIFAC and structural groups as defined by KT-UNIFAC first-order model. More than 100 binary datasets were involved in the estimation of interaction parameters. These new parameters were then used to calculate activity coefficient and solubility of some molecules in various solvents at different temperatures. The model gives better results than those from the original UNIFAC and shows good agreement between the experimental solubility and the calculated one.

Emotional persistence in online chatting communities

NASA Astrophysics Data System (ADS)

Garas, Antonios; Garcia, David; Skowron, Marcin; Schweitzer, Frank

2012-05-01

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional ``tone'' of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.

Emotional persistence in online chatting communities

PubMed Central

Garas, Antonios; Garcia, David; Skowron, Marcin; Schweitzer, Frank

2012-01-01

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional “tone” of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication. PMID:22577512

Interaction vs. observation: distinctive modes of social cognition in human brain and behavior? A combined fMRI and eye-tracking study

PubMed Central

Tylén, Kristian; Allen, Micah; Hunter, Bjørk K.; Roepstorff, Andreas

2012-01-01

Human cognition has usually been approached on the level of individual minds and brains, but social interaction is a challenging case. Is it best thought of as a self-contained individual cognitive process aiming at an “understanding of the other,” or should it rather be approached as an collective, inter-personal process where individual cognitive components interact on a moment-to-moment basis to form coupled dynamics? In a combined fMRI and eye-tracking study we directly contrasted these models of social cognition. We found that the perception of situations affording social contingent responsiveness (e.g., someone offering or showing you an object) elicited activations in regions of the right posterior temporal sulcus and yielded greater pupil dilation corresponding to a model of coupled dynamics (joint action). In contrast, the social-cognitive perception of someone “privately” manipulating an object elicited activation in medial prefrontal cortex, the right inferior frontal gyrus and right inferior parietal lobus, regions normally associated with Theory of Mind and with the mirror neuron system. Our findings support a distinction in social cognition between social observation and social interaction, and demonstrate that simple ostensive cues may shift participants' experience, behavior, and brain activity between these modes. The identification of a distinct, interactive mode has implications for research on social cognition, both in everyday life and in clinical conditions. PMID:23267322

GP0.4 from bacteriophage T7: in silico characterisation of its structure and interaction with E. coli FtsZ.

PubMed

Simpkin, Adam J; Rigden, Daniel J

2016-07-13

Proteins produced by bacteriophages can have potent antimicrobial activity. The study of phage-host interactions can therefore inform small molecule drug discovery by revealing and characterising new drug targets. Here we characterise in silico the predicted interaction of gene protein 0.4 (GP0.4) from the Escherichia coli (E. coli) phage T7 with E. coli filamenting temperature-sensitive mutant Z division protein (FtsZ). FtsZ is a tubulin homolog which plays a key role in bacterial cell division and that has been proposed as a drug target. Using ab initio, fragment assembly structure modelling, we predicted the structure of GP0.4 with two programs. A structure similarity-based network was used to identify a U-shaped helix-turn-helix candidate fold as being favoured. ClusPro was used to dock this structure prediction to a homology model of E. coli FtsZ resulting in a favourable predicted interaction mode. Alternative docking methods supported the proposed mode which offered an immediate explanation for the anti-filamenting activity of GP0.4. Importantly, further strong support derived from a previously characterised insertion mutation, known to abolish GP0.4 activity, that is positioned in close proximity to the proposed GP0.4/FtsZ interface. The mode of interaction predicted by bioinformatics techniques strongly suggests a mechanism through which GP0.4 inhibits FtsZ and further establishes the latter's druggable intrafilament interface as a potential drug target.

Manipulating 3D-Printed and Paper Models Enhances Student Understanding of Viral Replication

ERIC Educational Resources Information Center

Couper, Lisa; Johannes, Kristen; Powers, Jackie; Silberglitt, Matt; Davenport, Jodi

2016-01-01

Understanding key concepts in molecular biology requires reasoning about molecular processes that are not directly observable and, as such, presents a challenge to students and teachers. We ask whether novel interactive physical models and activities can help students understand key processes in viral replication. Our 3D tangible models are…

SAMM: a prototype southeast Alaska multiresource model.

Treesearch

Roger D. Fight; Lawrence D. Garrett; Dale L. Weyermann

1990-01-01

The adaptive environmental assessment method was used by an interdisciplinary team of forest specialists to gain an understanding of resource interactions and tradeoffs resulting from forest management activities in southeast Alaska. A forest multiresource projection model was developed in the process. The multiresource model, “SAMM,” is capable of characterizing and...

Multiperson visual focus of attention from head pose and meeting contextual cues.

PubMed

Ba, Sileye O; Odobez, Jean-Marc

2011-01-01

This paper introduces a novel contextual model for the recognition of people's visual focus of attention (VFOA) in meetings from audio-visual perceptual cues. More specifically, instead of independently recognizing the VFOA of each meeting participant from his own head pose, we propose to jointly recognize the participants' visual attention in order to introduce context-dependent interaction models that relate to group activity and the social dynamics of communication. Meeting contextual information is represented by the location of people, conversational events identifying floor holding patterns, and a presentation activity variable. By modeling the interactions between the different contexts and their combined and sometimes contradictory impact on the gazing behavior, our model allows us to handle VFOA recognition in difficult task-based meetings involving artifacts, presentations, and moving people. We validated our model through rigorous evaluation on a publicly available and challenging data set of 12 real meetings (5 hours of data). The results demonstrated that the integration of the presentation and conversation dynamical context using our model can lead to significant performance improvements.

A simplistic model for identifying prominent web users in directed multiplex social networks: a case study using Twitter networks

NASA Astrophysics Data System (ADS)

Loucif, Hemza; Boubetra, Abdelhak; Akrouf, Samir

2016-10-01

This paper aims to describe a new simplistic model dedicated to gauge the online influence of Twitter users based on a mixture of structural and interactional features. The model is an additive mathematical formulation which involves two main parts. The first part serves to measure the influence of the Twitter user on just his neighbourhood covering his followers. However, the second part evaluates the potential influence of the Twitter user beyond the circle of his followers. Particularly, it measures the likelihood that the tweets of the Twitter user will spread further within the social graph through the retweeting process. The model is tested on a data set involving four kinds of real-world egocentric networks. The empirical results reveal that an active ordinary user is more prominent than a non-active celebrity one. A simple comparison is conducted between the proposed model and two existing simplistic approaches. The results show that our model generates the most realistic influence scores due to its dealing with both explicit (structural and interactional) and implicit features.

Multiphysics modeling of non-linear laser-matter interactions for optically active semiconductors

NASA Astrophysics Data System (ADS)

Kraczek, Brent; Kanp, Jaroslaw

Development of photonic devices for sensors and communications devices has been significantly enhanced by computational modeling. We present a new computational method for modelling laser propagation in optically-active semiconductors within the paraxial wave approximation (PWA). Light propagation is modeled using the Streamline-upwind/Petrov-Galerkin finite element method (FEM). Material response enters through the non-linear polarization, which serves as the right-hand side of the FEM calculation. Maxwell's equations for classical light propagation within the PWA can be written solely in terms of the electric field, producing a wave equation that is a form of the advection-diffusion-reaction equations (ADREs). This allows adaptation of the computational machinery developed for solving ADREs in fluid dynamics to light-propagation modeling. The non-linear polarization is incorporated using a flexible framework to enable the use of multiple methods for carrier-carrier interactions (e.g. relaxation-time-based or Monte Carlo) to enter through the non-linear polarization, as appropriate to the material type. We demonstrate using a simple carrier-carrier model approximating the response of GaN. Supported by ARL Materials Enterprise.

Molecular design of two sterol 14α-demethylase homology models and their interactions with the azole antifungals ketoconazole and bifonazole

NASA Astrophysics Data System (ADS)

Rupp, Bernd; Raub, Stephan; Marian, Christel; Höltje, Hans-Dieter

2005-03-01

Sterol 14α-demethylase (CYP51) is one of the known major targets for azole antifungals. Therapeutic side effects of these antifungals are based on interactions of the azoles with the human analogue enzyme. This study describes for the first time a comparison of a human CYP51 (HU-CYP51) homology model with a homology model of the fungal CYP51 of Candida albicans (CA-CYP51). Both models are constructed by using the crystal structure of Mycobacterium tuberculosis MT-CYP51 (PDB code: 1EA1). The binding mode of the azole ketoconazole is investigated in molecular dynamics simulations with the GROMACS force field. The usage of special parameters for the iron azole complex binding is necessary to obtain the correct complex geometry in the active site of the enzyme models. Based on the dynamics simulations it is possible to explain the enantioselectivity of the human enzyme and also to predict the binding mode of the isomers of ketoconazole in the active site of the fungal model.

Structure-affinity relationship of the interaction between phenolic acids and their derivatives and β-lactoglobulin and effect on antioxidant activity.

PubMed

Wu, Simin; Zhang, Yunyue; Ren, Fazheng; Qin, Yinghui; Liu, Jiaxin; Liu, Jingwen; Wang, Qingyu; Zhang, Hao

2018-04-15

In this study, 71 phenolic acids and their derivatives were used to investigate the structure-affinity relationship of β-lactoglobulin binding, and the effect of this interaction on antioxidant activity. Based on a fluorescence quenching method, an improved mathematical model was adopted to calculate the binding constants, with a correction for the inner-filter effect. Hydroxylation at the 3-position increased the affinity of the phenolic acids for β-lactoglobulin, while hydroxylation at the 2- or 4-positions had a negative effect. Complete methylation of all hydroxy groups, except at the 3-position, enhanced the binding affinity. Replacing the hydroxy groups with methyl groups at the 2-position also had a positive effect. Hydrogen bonding was one of the binding forces for the interaction. The antioxidant activity of phenolic acid-β-lactoglobulin complexes was higher than that of phenolic acids alone. These findings provide an understanding of the structure-activity relationship of the interaction between β-lactoglobulin and phenolic acids. Copyright © 2017 Elsevier Ltd. All rights reserved.

A conserved role for the ESCRT membrane budding complex in LINE retrotransposition

PubMed Central

Dong, Chun; Han, Jeffrey S.

2017-01-01

Long interspersed nuclear element-1s (LINE-1s, or L1s) are an active family of retrotransposable elements that continue to mutate mammalian genomes. Despite the large contribution of L1 to mammalian genome evolution, we do not know where active L1 particles (particles in the process of retrotransposition) are located in the cell, or how they move towards the nucleus, the site of L1 reverse transcription. Using a yeast model of LINE retrotransposition, we identified ESCRT (endosomal sorting complex required for transport) as a critical complex for LINE retrotransposition, and verified that this interaction is conserved for human L1. ESCRT interacts with L1 via a late domain motif, and this interaction facilitates L1 replication. Loss of the L1/ESCRT interaction does not impair RNP formation or enzymatic activity, but leads to loss of retrotransposition and reduced L1 endonuclease activity in the nucleus. This study highlights the importance of the ESCRT complex in the L1 life cycle and suggests an unusual mode for L1 RNP trafficking. PMID:28586350

Quantitative assessment of the contribution of sodium-dependent taurocholate co-transporting polypeptide (NTCP) to the hepatic uptake of rosuvastatin, pitavastatin and fluvastatin.

PubMed

Bi, Yi-an; Qiu, Xi; Rotter, Charles J; Kimoto, Emi; Piotrowski, Mary; Varma, Manthena V; Ei-Kattan, Ayman F; Lai, Yurong

2013-11-01

Hepatic uptake transport is often the rate-determining step in the systemic clearance of drugs. The ability to predict uptake clearance and to determine the contribution of individual transporters to overall hepatic uptake is therefore critical in assessing the potential pharmacokinetic and pharmacodynamic variability associated with drug-drug interactions and pharmacogenetics. The present study revisited the interaction of statin drugs, including pitavastatin, fluvastatin and rosuvastatin, with the sodium-dependent taurocholate co-transporting polypeptide (NTCP) using gene transfected cell models. In addition, the uptake clearance and the contribution of NTCP to the overall hepatic uptake were assessed using in vitro hepatocyte models. Then NTCP protein expression was measured by a targeted proteomics transporter quantification method to confirm the presence and stability of NTCP expression in suspended and cultured hepatocyte models. It was concluded that NTCP-mediated uptake contributed significantly to active hepatic uptake in hepatocyte models for all three statins. However, the contribution of NTCP-mediated uptake to the overall active hepatic uptake was compound-dependent and varied from about 24% to 45%. Understanding the contribution of individual transporter proteins to the overall hepatic uptake and its functional variability when other active hepatic uptake pathways are interrupted could improve the current prediction practice used to assess the pharmacokinetic variability due to drug-drug interactions, pharmacogenetics and physiopathological conditions in humans. Copyright © 2013 John Wiley & Sons, Ltd.

Development of feedforward receptive field structure of a simple cell and its contribution to the orientation selectivity: a modeling study.

PubMed

Garg, Akhil R; Obermayer, Klaus; Bhaumik, Basabi

2005-01-01

Recent experimental studies of hetero-synaptic interactions in various systems have shown the role of signaling in the plasticity, challenging the conventional understanding of Hebb's rule. It has also been found that activity plays a major role in plasticity, with neurotrophins acting as molecular signals translating activity into structural changes. Furthermore, role of synaptic efficacy in biasing the outcome of competition has also been revealed recently. Motivated by these experimental findings we present a model for the development of simple cell receptive field structure based on the competitive hetero-synaptic interactions for neurotrophins combined with cooperative hetero-synaptic interactions in the spatial domain. We find that with proper balance in competition and cooperation, the inputs from two populations (ON/OFF) of LGN cells segregate starting from the homogeneous state. We obtain segregated ON and OFF regions in simple cell receptive field. Our modeling study supports the experimental findings, suggesting the role of synaptic efficacy and the role of spatial signaling. We find that using this model we obtain simple cell RF, even for positively correlated activity of ON/OFF cells. We also compare different mechanism of finding the response of cortical cell and study their possible role in the sharpening of orientation selectivity. We find that degree of selectivity improvement in individual cells varies from case to case depending upon the structure of RF field and type of sharpening mechanism.

AST: Activity-Security-Trust driven modeling of time varying networks.

PubMed

Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

2016-02-18

Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

Dynamics of two interacting active Janus particles.

PubMed

Bayati, Parvin; Najafi, Ali

2016-04-07

Starting from a microscopic model for a spherically symmetric active Janus particle, we study the interactions between two such active motors. The ambient fluid mediates a long range hydrodynamic interaction between two motors. This interaction has both direct and indirect hydrodynamic contributions. The direct contribution is due to the propagation of fluid flow that originated from a moving motor and affects the motion of the other motor. The indirect contribution emerges from the re-distribution of the ionic concentrations in the presence of both motors. Electric force exerted on the fluid from this ionic solution enhances the flow pattern and subsequently changes the motion of both motors. By formulating a perturbation method for very far separated motors, we derive analytic results for the translation and rotational dynamics of the motors. We show that the overall interaction at the leading order modifies the translational and rotational speeds of motors which scale as O[1/D](3) and O[1/D](4) with their separation, respectively. Our findings open up the way for studying the collective dynamics of synthetic micro-motors.

Mean ionic activity coefficients in aqueous NaCl solutions from molecular dynamics simulations

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

Mester, Zoltan; Panagiotopoulos, Athanassios Z., E-mail: azp@princeton.edu

The mean ionic activity coefficients of aqueous NaCl solutions of varying concentrations at 298.15 K and 1 bar have been obtained from molecular dynamics simulations by gradually turning on the interactions of an ion pair inserted into the solution. Several common non-polarizable water and ion models have been used in the simulations. Gibbs-Duhem equation calculations of the thermodynamic activity of water are used to confirm the thermodynamic consistency of the mean ionic activity coefficients. While the majority of model combinations predict the correct trends in mean ionic activity coefficients, they overestimate their values at high salt concentrations. The solubility predictionsmore » also suffer from inaccuracies, with all models underpredicting the experimental values, some by large factors. These results point to the need for further ion and water model development.« less

Evaluation of the Science Enrichment Activities (SEA) Program: A Decision Oriented Model.

ERIC Educational Resources Information Center

Linn, Marcia C.

1978-01-01

Three questions guided an evaluation of sixth and eighth grade science enrichment activities: (1) Does a free choice interactive program affect cognitive abilities? (2) Do students in a free choice program make predictable selections of activities based on their age, sex, or ability level? and (3) Are specific student choices associated with…

Computational active site analysis of molecular pathways to improve functional classification of enzymes.

PubMed

Ozyurt, A Sinem; Selby, Thomas L

2008-07-01

This study describes a method to computationally assess the function of homologous enzymes through small molecule binding interaction energy. Three experimentally determined X-ray structures and four enzyme models from ornithine cyclo-deaminase, alanine dehydrogenase, and mu-crystallin were used in combination with nine small molecules to derive a function score (FS) for each enzyme-model combination. While energy values varied for a single molecule-enzyme combination due to differences in the active sites, we observe that the binding energies for the entire pathway were proportional for each set of small molecules investigated. This proportionality of energies for a reaction pathway appears to be dependent on the amino acids in the active site and their direct interactions with the small molecules, which allows a function score (FS) to be calculated to assess the specificity of each enzyme. Potential of mean force (PMF) calculations were used to obtain the energies, and the resulting FS values demonstrate that a measurement of function may be obtained using differences between these PMF values. Additionally, limitations of this method are discussed based on: (a) larger substrates with significant conformational flexibility; (b) low homology enzymes; and (c) open active sites. This method should be useful in accurately predicting specificity for single enzymes that have multiple steps in their reactions and in high throughput computational methods to accurately annotate uncharacterized proteins based on active site interaction analysis. 2008 Wiley-Liss, Inc.

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.

On the representation of aerosol activation and its influence on model-derived estimates of the aerosol indirect effect

NASA Astrophysics Data System (ADS)

Rothenberg, Daniel; Avramov, Alexander; Wang, Chien

2018-06-01

Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNCs). However, different activation schemes can exhibit different sensitivities to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC (two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC) coupled with the National Center for Atmospheric Research's (NCAR) Community Earth System Model (CESM; version 1.2)). Although the model produces a reasonable present-day CDNC climatology when compared with observations regardless of the scheme used, ΔCDNCs between the present and preindustrial era regionally increase by over 100 % in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity may lead to a different evolution of the model meteorology, and ultimately to a spread of over 0.8 W m-2 in global average shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom intercomparison. Model-derived AIE strongly scales with the simulated preindustrial CDNC burden, and those models with the greatest preindustrial CDNC tend to have the smallest AIE, regardless of their ΔCDNC. This suggests that present-day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of the AIE, which will arise from differences in model estimates of the preindustrial aerosol and cloud climatology.

Adult wheel access interaction with activity and boldness personality in Siberian dwarf hamsters (Phodopus sungorus).

PubMed

Kanda, L Leann; Abdulhay, Amir; Erickson, Caitlin

2017-05-01

Individual animal personalities interact with environmental conditions to generate differences in behavior, a phenomenon of growing interest for understanding the effects of environmental enrichment on captive animals. Wheels are common environmental enrichment for laboratory rodents, but studies conflict on how this influences behavior, and interaction of wheels with individual personalities has rarely been examined. We examined whether wheel access altered personality profiles in adult Siberian dwarf hamsters. We assayed animals in a tunnel maze twice for baseline personality, then again at two and at seven weeks after the experimental group was provisioned with wheels in their home cages. Linear mixed model selection was used to assess changes in behavior over time and across environmental gradient of wheel exposure. While animals showed consistent inter-individual differences in activity, activity personality did not change upon exposure to a wheel. Boldness also varies among individuals, and there is evidence for female boldness scores converging after wheel exposure, that is, opposite shifts in behavior by high and low boldness individuals, although sample size is too small for the mixed model results to be robust. In general, Siberian dwarf hamsters appear to show low behavioral plasticity, particularly in general activity, in response to running wheels. Copyright © 2017 Elsevier B.V. All rights reserved.

Complex regulation of Hsf1-Skn7 activities by the catalytic subunits of PKA in Saccharomyces cerevisiae: experimental and computational evidences.

PubMed

Pérez-Landero, Sergio; Sandoval-Motta, Santiago; Martínez-Anaya, Claudia; Yang, Runying; Folch-Mallol, Jorge Luis; Martínez, Luz María; Ventura, Larissa; Guillén-Navarro, Karina; Aldana-González, Maximino; Nieto-Sotelo, Jorge

2015-07-27

The cAMP-dependent protein kinase regulatory network (PKA-RN) regulates metabolism, memory, learning, development, and response to stress. Previous models of this network considered the catalytic subunits (CS) as a single entity, overlooking their functional individualities. Furthermore, PKA-RN dynamics are often measured through cAMP levels in nutrient-depleted cells shortly after being fed with glucose, dismissing downstream physiological processes. Here we show that temperature stress, along with deletion of PKA-RN genes, significantly affected HSE-dependent gene expression and the dynamics of the PKA-RN in cells growing in exponential phase. Our genetic analysis revealed complex regulatory interactions between the CS that influenced the inhibition of Hsf1/Skn7 transcription factors. Accordingly, we found new roles in growth control and stress response for Hsf1/Skn7 when PKA activity was low (cdc25Δ cells). Experimental results were used to propose an interaction scheme for the PKA-RN and to build an extension of a classic synchronous discrete modeling framework. Our computational model reproduced the experimental data and predicted complex interactions between the CS and the existence of a repressor of Hsf1/Skn7 that is activated by the CS. Additional genetic analysis identified Ssa1 and Ssa2 chaperones as such repressors. Further modeling of the new data foresaw a third repressor of Hsf1/Skn7, active only in the absence of Tpk2. By averaging the network state over all its attractors, a good quantitative agreement between computational and experimental results was obtained, as the averages reflected more accurately the population measurements. The assumption of PKA being one molecular entity has hindered the study of a wide range of behaviors. Additionally, the dynamics of HSE-dependent gene expression cannot be simulated accurately by considering the activity of single PKA-RN components (i.e., cAMP, individual CS, Bcy1, etc.). We show that the differential roles of the CS are essential to understand the dynamics of the PKA-RN and its targets. Our systems level approach, which combined experimental results with theoretical modeling, unveils the relevance of the interaction scheme for the CS and offers quantitative predictions for several scenarios (WT vs. mutants in PKA-RN genes and growth at optimal temperature vs. heat shock).

Interaction between leptin and leisure-time physical activity and development of hypertension.

PubMed

Asferg, Camilla; Møgelvang, Rasmus; Flyvbjerg, Allan; Frystyk, Jan; Jensen, Jan S; Marott, Jacob L; Appleyard, Merete; Schnohr, Peter; Jensen, Gorm B; Jeppesen, J Rgen

2011-12-01

OBJECTIVE. The mechanisms by which overweight and physical inactivity lead to hypertension are complex. Leptin, an adipocyte-derived hormone, has been linked with hypertension. We wanted to investigate the relationship between leptin, physical activity and new-onset hypertension. METHODS. The study was a prospective cohort study of 744 women and 367 men, who were normotensive in the third Copenhagen City Heart Study (CCHS) examination, performed 1991−94. Based on questionnaire items, the participants were divided into two groups with low (n = 674) and high (n = 437) levels of leisure-time physical activity, respectively. RESULTS. Between the third and the fourth CCHS examination, performed 2001?03, 304 had developed hypertension, defined as systolic blood pressure (SBP) ≥140 mmHg or diastolic blood pressure (DBP) ≥90 mmHg or use of antihypertensive medication. In a logistic regression model, including age, sex, body mass index, SBP, DBP, level of physical activity and leptin, we found a significant interaction between leptin and level of physical activity with new-onset hypertension as outcome variable (p = 0.012). When we entered the interaction variables, effect of leptin with low level of physical activity and with high level of physical activity, respectively, in the original model, leptin predicted new-onset hypertension in participants with low level of physical activity [odds ratio (95% confidence interval): 1.16 (1.01−1.33) for one unit increase in log-transformed leptin levels, p = 0.038], but not in participants with high level of physical activity [0.88 (0.74−1.05), p = 0.15]. CONCLUSION. We found that leptin predicted new-onset hypertension but only in participants with low level of physical activity.

Effect of Field Spread on Resting-State Magneto Encephalography Functional Network Analysis: A Computational Modeling Study.

PubMed

Silva Pereira, Silvana; Hindriks, Rikkert; Mühlberg, Stefanie; Maris, Eric; van Ede, Freek; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo

2017-11-01

A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.

Unique binding behavior of the recently approved angiotensin II receptor blocker azilsartan compared with that of candesartan

PubMed Central

Miura, Shin-ichiro; Okabe, Atsutoshi; Matsuo, Yoshino; Karnik, Sadashiva S; Saku, Keijiro

2014-01-01

The angiotensin II type 1 (AT1) receptor blocker (ARB) candesartan strongly reduces blood pressure (BP) in patients with hypertension and has been shown to have cardioprotective effects. A new ARB, azilsartan, was recently approved and has been shown to provide a more potent 24-h sustained antihypertensive effect than candesartan. However, the molecular interactions of azilsartan with the AT1 receptor that could explain its strong BP-lowering activity are not yet clear. To address this issue, we examined the binding affinities of ARBs for the AT1 receptor and their inverse agonist activity toward the production of inositol phosphate (IP), and we constructed docking models for the interactions between ARBs and the receptor. Azilsartan, unlike candesartan, has a unique moiety, a 5-oxo-1,2,4-oxadiazole, in place of a tetrazole ring. Although the results regarding the binding affinities of azilsartan and candesartan demonstrated that these ARBs interact with the same sites in the AT1 receptor (Tyr113, Lys199 and Gln257), the hydrogen bonding between the oxadiazole of azilsartan-Gln257 is stronger than that between the tetrazole of candesartan-Gln257, according to molecular docking models. An examination of the inhibition of IP production by ARBs using constitutively active mutant receptors indicated that inverse agonist activity required azilsartan–Gln257 interaction and that azilsartan had a stronger interaction with Gln257 than candesartan. Thus, we speculate that azilsartan has a unique binding behavior to the AT1 receptor due to its 5-oxo-1,2,4-oxadiazole moiety and induces stronger inverse agonism. This property of azilsartan may underlie its previously demonstrated superior BP-lowering efficacy compared with candesartan and other ARBs. PMID:23034464

Unique binding behavior of the recently approved angiotensin II receptor blocker azilsartan compared with that of candesartan.

PubMed

Miura, Shin-ichiro; Okabe, Atsutoshi; Matsuo, Yoshino; Karnik, Sadashiva S; Saku, Keijiro

2013-02-01

The angiotensin II type 1 (AT(1)) receptor blocker (ARB) candesartan strongly reduces blood pressure (BP) in patients with hypertension and has been shown to have cardioprotective effects. A new ARB, azilsartan, was recently approved and has been shown to provide a more potent 24-h sustained antihypertensive effect than candesartan. However, the molecular interactions of azilsartan with the AT(1) receptor that could explain its strong BP-lowering activity are not yet clear. To address this issue, we examined the binding affinities of ARBs for the AT(1) receptor and their inverse agonist activity toward the production of inositol phosphate (IP), and we constructed docking models for the interactions between ARBs and the receptor. Azilsartan, unlike candesartan, has a unique moiety, a 5-oxo-1,2,4-oxadiazole, in place of a tetrazole ring. Although the results regarding the binding affinities of azilsartan and candesartan demonstrated that these ARBs interact with the same sites in the AT(1) receptor (Tyr(113), Lys(199) and Gln(257)), the hydrogen bonding between the oxadiazole of azilsartan-Gln(257) is stronger than that between the tetrazole of candesartan-Gln(257), according to molecular docking models. An examination of the inhibition of IP production by ARBs using constitutively active mutant receptors indicated that inverse agonist activity required azilsartan-Gln(257) interaction and that azilsartan had a stronger interaction with Gln(257) than candesartan. Thus, we speculate that azilsartan has a unique binding behavior to the AT(1) receptor due to its 5-oxo-1,2,4-oxadiazole moiety and induces stronger inverse agonism. This property of azilsartan may underlie its previously demonstrated superior BP-lowering efficacy compared with candesartan and other ARBs.

Interaction between synaptic inhibition and glial-potassium dynamics leads to diverse seizure transition modes in biophysical models of human focal seizures.

PubMed

Y Ho, E C; Truccolo, Wilson

2016-10-01

How focal seizures initiate and evolve in human neocortex remains a fundamental problem in neuroscience. Here, we use biophysical neuronal network models of neocortical patches to study how the interaction between inhibition and extracellular potassium ([K (+)] o ) dynamics may contribute to different types of focal seizures. Three main types of propagated focal seizures observed in recent intracortical microelectrode recordings in humans were modelled: seizures characterized by sustained (∼30-60 Hz) gamma local field potential (LFP) oscillations; seizures where the onset in the propagated site consisted of LFP spikes that later evolved into rhythmic (∼2-3 Hz) spike-wave complexes (SWCs); and seizures where a brief stage of low-amplitude fast-oscillation (∼10-20 Hz) LFPs preceded the SWC activity. Our findings are fourfold: (1) The interaction between elevated [K (+)] o (due to abnormal potassium buffering by glial cells) and the strength of synaptic inhibition plays a predominant role in shaping these three types of seizures. (2) Strengthening of inhibition leads to the onset of sustained narrowband gamma seizures. (3) Transition into SWC seizures is obtained either by the weakening of inhibitory synapses, or by a transient strengthening followed by an inhibitory breakdown (e.g. GABA depletion). This reduction or breakdown of inhibition among fast-spiking (FS) inhibitory interneurons increases their spiking activity and leads them eventually into depolarization block. Ictal spike-wave discharges in the model are then sustained solely by pyramidal neurons. (4) FS cell dynamics are also critical for seizures where the evolution into SWC activity is preceded by low-amplitude fast oscillations. Different levels of elevated [K (+)] o were important for transitions into and maintenance of sustained gamma oscillations and SWC discharges. Overall, our modelling study predicts that the interaction between inhibitory interneurons and [K (+)] o glial buffering under abnormal conditions may explain different types of ictal transitions and dynamics during propagated seizures in human focal epilepsy.

Interactions between THC and cannabidiol in mouse models of cannabinoid activity.

PubMed

Varvel, S A; Wiley, J L; Yang, R; Bridgen, D T; Long, K; Lichtman, A H; Martin, B R

2006-06-01

Interest persists in characterizing potential interactions between Delta(9)-tetrahydocannabinol (THC) and other marijuana constituents such as cannabidiol (CBD). Such interactions may have important implications for understanding the long-term health consequences of chronic marijuana use as well as for attempts to develop therapeutic uses for THC and other CB(1) agonists. We investigated whether CBD may modulate the pharmacological effects of intravenously administered THC or inhaled marijuana smoke on hypoactivity, antinociception, catalepsy, and hypothermia, the well characterized models of cannabinoid activity. Intravenously administered CBD possessed very little activity on its own and, at a dose equal to a maximally effective dose of THC (3 mg/kg), failed to alter THC's effects on any measure. However, higher doses of CBD (ED(50)=7.4 mg/kg) dose-dependently potentiated the antinociceptive effects of a low dose of THC (0.3 mg/kg). Pretreatment with 30 mg/kg CBD, but not 3 mg/kg, significantly elevated THC blood and brain levels. No interactions between THC and CBD were observed in several variations of a marijuana smoke exposure model. Either quantities of CBD were applied directly to marijuana, CBD and THC were both applied to placebo plant material, or mice were pretreated intravenously with 30 mg/kg CBD before being exposed to marijuana smoke. As the amount of CBD found in most marijuana strains in the US is considerably less than that of THC, these results suggest that CBD concentrations relevant to what is normally found in marijuana exert very little, if any, modulatory effects on CB(1)-receptor-mediated pharmacological effects of marijuana smoke.

Active vibration control activities at the LaRC - Present and future

NASA Technical Reports Server (NTRS)

Newsom, J. R.

1990-01-01

The NASA Controls-Structures-Interaction (CSI) program is presented with a description of the ground testing element objectives and approach. The goal of the CSI program is to develop and validate the technology required to design, verify and operate space systems in which the structure and the controls interact beneficially to meet the needs of future NASA missions. The operational Mini-Mast ground testbed and some sample active vibration control experimental results are discussed along with a description of the CSI Evolutionary Model testbed presently under development. Initial results indicate that embedded sensors and actuators are effective in controlling a large truss/reflector structure.

Application of Molecular Interaction Volume Model for Phase Equilibrium of Sn-Based Binary System in Vacuum Distillation

NASA Astrophysics Data System (ADS)

Kong, Lingxin; Yang, Bin; Xu, Baoqiang; Li, Yifu

2014-09-01

Based on the molecular interaction volume model (MIVM), the activities of components of Sn-Sb, Sb-Bi, Sn-Zn, Sn-Cu, and Sn-Ag alloys were predicted. The predicted values are in good agreement with the experimental data, which indicate that the MIVM is of better stability and reliability due to its good physical basis. A significant advantage of the MIVM lies in its ability to predict the thermodynamic properties of liquid alloys using only two parameters. The phase equilibria of Sn-Sb and Sn-Bi alloys were calculated based on the properties of pure components and the activity coefficients, which indicates that Sn-Sb and Sn-Bi alloys can be separated thoroughly by vacuum distillation. This study extends previous investigations and provides an effective and convenient model on which to base refining simulations for Sn-based alloys.

The examination of headache activity using time-series research designs.

PubMed

Houle, Timothy T; Remble, Thomas A; Houle, Thomas A

2005-05-01

The majority of research conducted on headache has utilized cross-sectional designs which preclude the examination of dynamic factors and principally rely on group-level effects. The present article describes the application of an individual-oriented process model using time-series analytical techniques. The blending of a time-series approach with an interactive process model allows consideration of the relationships of intra-individual dynamic processes, while not precluding the researcher to examine inter-individual differences. The authors explore the nature of time-series data and present two necessary assumptions underlying the time-series approach. The concept of shock and its contribution to headache activity is also presented. The time-series approach is not without its problems and two such problems are specifically reported: autocorrelation and the distribution of daily observations. The article concludes with the presentation of several analytical techniques suited to examine the time-series interactive process model.

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

Using DFT methodology for more reliable predictive models: Design of inhibitors of Golgi α-Mannosidase II.

PubMed

Bobovská, Adela; Tvaroška, Igor; Kóňa, Juraj

2016-05-01

Human Golgi α-mannosidase II (GMII), a zinc ion co-factor dependent glycoside hydrolase (E.C.3.2.1.114), is a pharmaceutical target for the design of inhibitors with anti-cancer activity. The discovery of an effective inhibitor is complicated by the fact that all known potent inhibitors of GMII are involved in unwanted co-inhibition with lysosomal α-mannosidase (LMan, E.C.3.2.1.24), a relative to GMII. Routine empirical QSAR models for both GMII and LMan did not work with a required accuracy. Therefore, we have developed a fast computational protocol to build predictive models combining interaction energy descriptors from an empirical docking scoring function (Glide-Schrödinger), Linear Interaction Energy (LIE) method, and quantum mechanical density functional theory (QM-DFT) calculations. The QSAR models were built and validated with a library of structurally diverse GMII and LMan inhibitors and non-active compounds. A critical role of QM-DFT descriptors for the more accurate prediction abilities of the models is demonstrated. The predictive ability of the models was significantly improved when going from the empirical docking scoring function to mixed empirical-QM-DFT QSAR models (Q(2)=0.78-0.86 when cross-validation procedures were carried out; and R(2)=0.81-0.83 for a testing set). The average error for the predicted ΔGbind decreased to 0.8-1.1kcalmol(-1). Also, 76-80% of non-active compounds were successfully filtered out from GMII and LMan inhibitors. The QSAR models with the fragmented QM-DFT descriptors may find a useful application in structure-based drug design where pure empirical and force field methods reached their limits and where quantum mechanics effects are critical for ligand-receptor interactions. The optimized models will apply in lead optimization processes for GMII drug developments. Copyright © 2016 Elsevier Inc. All rights reserved.

Activating transcription factor 6 derepression mediates neuroprotection in Huntington disease

PubMed Central

Naranjo, José R.; Zhang, Hongyu; Villar, Diego; González, Paz; Dopazo, Xose M.; Morón-Oset, Javier; Higueras, Elena; Oliveros, Juan C.; Arrabal, María D.; Prieto, Angela; Cercós, Pilar; González, Teresa; De la Cruz, Alicia; Casado-Vela, Juan; Rábano, Alberto; Valenzuela, Carmen; Gutierrez-Rodriguez, Marta; Li, Jia-Yi; Mellström, Britt

2016-01-01

Deregulated protein and Ca2+ homeostasis underlie synaptic dysfunction and neurodegeneration in Huntington disease (HD); however, the factors that disrupt homeostasis are not fully understood. Here, we determined that expression of downstream regulatory element antagonist modulator (DREAM), a multifunctional Ca2+-binding protein, is reduced in murine in vivo and in vitro HD models and in HD patients. DREAM downregulation was observed early after birth and was associated with endogenous neuroprotection. In the R6/2 mouse HD model, induced DREAM haplodeficiency or blockade of DREAM activity by chronic administration of the drug repaglinide delayed onset of motor dysfunction, reduced striatal atrophy, and prolonged life span. DREAM-related neuroprotection was linked to an interaction between DREAM and the unfolded protein response (UPR) sensor activating transcription factor 6 (ATF6). Repaglinide blocked this interaction and enhanced ATF6 processing and nuclear accumulation of transcriptionally active ATF6, improving prosurvival UPR function in striatal neurons. Together, our results identify a role for DREAM silencing in the activation of ATF6 signaling, which promotes early neuroprotection in HD. PMID:26752648

Modeling interactions of agriculture and groundwater nitrate contaminants: application of The STICS-Eau-Dyssée coupled models over the Seine River Basin

NASA Astrophysics Data System (ADS)

Tavakoly, A. A.; Habets, F.; Saleh, F.; Yang, Z. L.

2017-12-01

Human activities such as the cultivation of N-fixing crops, burning of fossil fuels, discharging of industrial and domestic effluents, and extensive usage of fertilizers have recently accelerated the nitrogen loading to watersheds worldwide. Increasing nitrate concentration in surface water and groundwater is a major concern in watersheds with extensive agricultural activities. Nutrient enrichment is one of the major environmental problems in the French coastal zone. To understand and predict interactions between agriculture, surface water and groundwater nitrate contaminants, this study presents a modeling framework that couples the agronomic STICS model with Eau-Dyssée, a distributed hydrologic modeling system to simulate groundwater-surface water interaction. The coupled system is implemented on the Seine River Basin with an area of 88,000 km2 to compute daily nitrate contaminants. Representing a sophisticated hydrosystem with several aquifers and including the megalopolis of Paris, the Seine River Basin is well-known as one of the most productive agricultural areas in France. The STICS-EauDyssée framework is evaluated for a long-term simulation covering 39 years (1971-2010). Model results show that the simulated nitrate highly depends on the inflow produced by surface and subsurface waters. Daily simulation shows that the model captures the seasonal variation of observations and that the overall long-term simulation of nitrate contaminant is satisfactory at the regional scale.

The two-brain approach: how can mutually interacting brains teach us something about social interaction?

PubMed Central

Konvalinka, Ivana; Roepstorff, Andreas

2012-01-01

Measuring brain activity simultaneously from two people interacting is intuitively appealing if one is interested in putative neural markers of social interaction. However, given the complex nature of interactions, it has proven difficult to carry out two-person brain imaging experiments in a methodologically feasible and conceptually relevant way. Only a small number of recent studies have put this into practice, using fMRI, EEG, or NIRS. Here, we review two main two-brain methodological approaches, each with two conceptual strategies. The first group has employed two-brain fMRI recordings, studying (1) turn-based interactions on the order of seconds, or (2) pseudo-interactive scenarios, where only one person is scanned at a time, investigating the flow of information between brains. The second group of studies has recorded dual EEG/NIRS from two people interacting, in (1) face-to-face turn-based interactions, investigating functional connectivity between theory-of-mind regions of interacting partners, or in (2) continuous mutual interactions on millisecond timescales, to measure coupling between the activity in one person's brain and the activity in the other's brain. We discuss the questions these approaches have addressed, and consider scenarios when simultaneous two-brain recordings are needed. Furthermore, we suggest that (1) quantification of inter-personal neural effects via measures of emergence, and (2) multivariate decoding models that generalize source-specific features of interaction, may provide novel tools to study brains in interaction. This may allow for a better understanding of social cognition as both representation and participation. PMID:22837744

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.

In Praise of a Model but Not Its Conclusions: Commentary on Cooper, Catmur, and Heyes (2012)

ERIC Educational Resources Information Center

Bertenthal, Bennett I.; Scheutz, Matthias

2013-01-01

Cooper et al. (this issue) develop an interactive activation model of spatial and imitative compatibilities that simulates the key results from Catmur and Heyes (2011) and thus conclude that both compatibilities are mediated by the same processes since their single model can predict all the results. Although the model is impressive, the…

Exploring Affiliation Network Models as a Collaborative Filtering Mechanism in E-Learning

ERIC Educational Resources Information Center

Rodriguez, Daniel; Sicilia, Miguel Angel; Sanchez-Alonso, Salvador; Lezcano, Leonardo; Garcia-Barriocanal, Elena

2011-01-01

The online interaction of learners and tutors in activities with concrete objectives provides a valuable source of data that can be analyzed for different purposes. One of these purposes is the use of the information extracted from that interaction to aid tutors and learners in decision making about either the configuration of further learning…

The Teaching and the Learning Brain: A Cortical Hemodynamic Marker of Teacher-Student Interactions in the Socratic Dialog

ERIC Educational Resources Information Center

Holper, Lisa; Goldin, Andrea P.; Shalom, Diego E.; Battro, Antonio M.; Wolf, Martin; Sigman, Mariano

2013-01-01

The study aimed to step into two-person (teacher-student) educational neuroscience. We describe a physiological marker of cortical hemodynamic correlates involved in teacher-student interactions during performance of a classical teaching model, the Socratic dialog. We recorded prefrontal brain activity during dialog execution simultaneously in…

Visual interaction: models, systems, prototypes. The Pictorial Computing Laboratory at the University of Rome La Sapienza.

PubMed

Bottoni, Paolo; Cinque, Luigi; De Marsico, Maria; Levialdi, Stefano; Panizzi, Emanuele

2006-06-01

This paper reports on the research activities performed by the Pictorial Computing Laboratory at the University of Rome, La Sapienza, during the last 5 years. Such work, essentially is based on the study of humancomputer interaction, spans from metamodels of interaction down to prototypes of interactive systems for both synchronous multimedia communication and groupwork, annotation systems for web pages, also encompassing theoretical and practical issues of visual languages and environments also including pattern recognition algorithms. Some applications are also considered like e-learning and collaborative work.

Annotation-Based Learner's Personality Modeling in Distance Learning Context

ERIC Educational Resources Information Center

Omheni, Nizar; Kalboussi, Anis; Mazhoud, Omar; Kacem, Ahmed Hadj

2016-01-01

Researchers in distance education are interested in observing and modeling learners' personality profiles, and adapting their learning experiences accordingly. When learners read and interact with their reading materials, they do unselfconscious activities like annotation which may be key feature of their personalities. Annotation activity…

Hydrological modeling of upper Indus Basin and assessment of deltaic ecology

USDA-ARS?s Scientific Manuscript database

Managing water resources is mostly required at watershed scale where the complex hydrology processes and interactions linking land surface, climatic factors and human activities can be studied. Geographical Information System based watershed model; Soil and Water Assessment Tool (SWAT) is applied f...

Collaboration for Education with the Apple Learning Interchange

NASA Astrophysics Data System (ADS)

Young, Patrick A.; Zimmerman, T.; Knierman, K. A.

2006-12-01

We present a progressive effort to deliver online education and outreach resources in collaboration with the Apple Learning Interchange, a free community for educators. We have created a resource site with astronomy activities, video training for the activities, and the possibility of interactive training through video chat services. Also in development is an online textbook for graduate and advanced undergraduate courses in stellar evolution, featuring an updatable and annotated text with multimedia content, online lectures, podcasts, and a framework for interactive simulation activities. Both sites will be highly interactive, combining online discussions, the opportunity for live video interaction, and a growing library of student work samples. This effort promises to provide a compelling model for collaboration between science educators and corporations. As scientists, we provide content knowledge and a compelling reason to communicate, while Apple provides technical expertise, a deep knowledge of online education, and a way for us to reach a wide audience of higher education, community outreach, and K-12 educators.

Aggregation models on hypergraphs

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

Alberici, Diego, E-mail: diego.alberici2@unibo.it; Contucci, Pierluigi, E-mail: pierluigi.contucci@unibo.it; Mingione, Emanuele, E-mail: emanuele.mingione2@unibo.it

2017-01-15

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer–dimer case. After translating those relations intomore » structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.« less

Brief report: learning via the electronic interactive whiteboard for two students with autism and a student with moderate intellectual disability.

PubMed

Yakubova, Gulnoza; Taber-Doughty, Teresa

2013-06-01

The effects of a multicomponent intervention (a self-operated video modeling and self-monitoring delivered via an electronic interactive whiteboard (IWB) and a system of least prompts) on skill acquisition and interaction behavior of two students with autism and one student with moderate intellectual disability were examined using a multi-probe across students design. Students were taught to operate and view video modeling clips, perform a chain of novel tasks and self-monitor task performance using a SMART Board IWB. Results support the effectiveness of a multicomponent intervention in improving students' skill acquisition. Results also highlight the use of this technology as a self-operated and interactive device rather than a traditional teacher-operated device to enhance students' active participation in learning.

A conative educational model for an intervention program in obese youth.

PubMed

Vanhelst, Jérémy; Béghin, Laurent; Fardy, Paul Stephen; Bui-Xuan, Gilles; Mikulovic, Jacques

2012-06-07

Obesity in children has increased in recent years throughout the world and is associated with adverse health consequences. Early interventions, including appropriate pedagogy strategies, are important for a successful intervention program. The aim of this study was to assess changes in body mass index, the ability to perform sport activities, behavior in the classroom and academic performance following one year of a health-wellness intervention program in obese youth. The CEMHaVi program included 37 obese children (19 girls and 18 boys). Participants received an intervention program consisting of physical activity and health education. Assessment included body mass index, academic performance, classroom performance and ability to perform sport activities. Paired t tests were used to assess the effects of intervention, and chi square was used to assess inter-action between measures. Findings of the study suggest significant decrease in Z scores of Body Mass Index and an improvement of academic performance, classroom behavior and the ability to perform sport activities (p < 0.05). Chi square testing showed significant positive inter-actions between body mass index, classroom behavior and academic performance. Results following year one of CEMHaVi showed that a program of physical activity and health education had positive effects on obesity, behavior in the classroom and the ability to perform sport activities in obese adolescents. Significant inter-action in changes between variables was observed. Findings are important for designing intervention models to improve health in obese youth.

Numerical modeling of water spray suppression of conveyor belt fires in a large-scale tunnel.

PubMed

Yuan, Liming; Smith, Alex C

2015-05-01

Conveyor belt fires in an underground mine pose a serious life threat to miners. Water sprinkler systems are usually used to extinguish underground conveyor belt fires, but because of the complex interaction between conveyor belt fires and mine ventilation airflow, more effective engineering designs are needed for the installation of water sprinkler systems. A computational fluid dynamics (CFD) model was developed to simulate the interaction between the ventilation airflow, the belt flame spread, and the water spray system in a mine entry. The CFD model was calibrated using test results from a large-scale conveyor belt fire suppression experiment. Simulations were conducted using the calibrated CFD model to investigate the effects of sprinkler location, water flow rate, and sprinkler activation temperature on the suppression of conveyor belt fires. The sprinkler location and the activation temperature were found to have a major effect on the suppression of the belt fire, while the water flow rate had a minor effect.

Numerical modeling of water spray suppression of conveyor belt fires in a large-scale tunnel

PubMed Central

Yuan, Liming; Smith, Alex C.

2015-01-01

Conveyor belt fires in an underground mine pose a serious life threat to miners. Water sprinkler systems are usually used to extinguish underground conveyor belt fires, but because of the complex interaction between conveyor belt fires and mine ventilation airflow, more effective engineering designs are needed for the installation of water sprinkler systems. A computational fluid dynamics (CFD) model was developed to simulate the interaction between the ventilation airflow, the belt flame spread, and the water spray system in a mine entry. The CFD model was calibrated using test results from a large-scale conveyor belt fire suppression experiment. Simulations were conducted using the calibrated CFD model to investigate the effects of sprinkler location, water flow rate, and sprinkler activation temperature on the suppression of conveyor belt fires. The sprinkler location and the activation temperature were found to have a major effect on the suppression of the belt fire, while the water flow rate had a minor effect. PMID:26190905

Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel Adrian; Oprisan, Ana

2005-03-01

Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.

Cortical activity and functional hyperconnectivity by simultaneous EEG recordings from interacting couples of professional pilots.

PubMed

Astolfi, L; Toppi, J; Borghini, G; Vecchiato, G; He, E J; Roy, A; Cincotti, F; Salinari, S; Mattia, D; He, B; Babiloni, F

2012-01-01

Controlling an aircraft during a flight is a compelling condition, which requires a strict and well coded interaction between the crew. The interaction level between the Captain and the First Officer changes during the flight, ranging from a maximum (during takeoff and landing, as well as in case of a failure of the instrumentation or other emergency situations) to a minimum during quiet mid-flight. In this study, our aim is to investigate the neural correlates of different kinds and levels of interaction between couples of professional crew members by means of the innovative technique called brain hyperscanning, i.e. the simultaneous recording of the hemodynamic or neuroelectrical activity of different human subjects involved in interaction tasks. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects, and, even more interestingly, of the functional links existing between the brain activities of the subjects interacting together. In this EEG hyperscanning study, different phases of a flight were reproduced in a professional flight simulator, which allowed, on one side, to reproduce the ecological setting of a real flight, and, on the other, to keep under control the different levels of interaction induced in the crew by means of systematic and simulated failures of the aircraft instrumentation. Results of the procedure of linear inverse estimation, together with functional hyperconnectivity estimated by means of Partial Directed Coherence, showed a dense network of connections between the activity in the two brains in the takeoff and landing phases, when the cooperation between the crew is maximal, while conversely no significant links were shown during the phases in which the activity of the two pilots was independent.

Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

NASA Astrophysics Data System (ADS)

Zhou, C.; Zhang, X.; Gong, S.

2015-12-01

A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under CMA chemical weather modeling system GRAPES/CUACE. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) is fed online interactively into a two-moment cloud scheme (WDM6) and a convective parameterization to drive the cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred. The results show that interactive aerosols with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content and cloud droplet number concentrations while decrease the mean diameter of cloud droplets with varying magnitudes of the changes in each case and region. These interactive micro-physical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24% to 48% enhancements of TS scoring for 6-h precipitation in almost all regions. The interactive aerosols with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3°C.

Interaction between p68 RNA helicase and Ca2+-calmodulin promotes cell migration and metastasis

PubMed Central

Wang, Haizhen; Gao, Xueliang; Yang, Jenny J.; Liu, Zhi-Ren

2012-01-01

Summary p68 RNA helicase is a prototypical RNA helicase. Here we present evidence to show that, by interacting with Ca-calmodulin (CaM), p68 plays a role in cancer metastasis and cell migration. A peptide fragment that spans the IQ motif of p68 strongly inhibits cancer metastasis in two different animal models. The peptide interrupts p68 and CaM interaction and inhibits cell migration. Our results demonstrate that the p68-CaM interaction is essential for the formation of lamellipodia and filopodia in migrating cells. p68 interacts with microtubules in the presence of CaM. Our experiments show that interaction with microtubules stimulates p68 ATPase activity. Further, microtubule gliding assays demonstrate that p68, in the presence of CaM, can function as a microtubule motor. This motor activity may allow p68 to transport CaM to the leading edge of migrating cells. PMID:23322042

Revealing interaction mode between HIV-1 protease and mannitol analog inhibitor.

PubMed

Yan, Guan-Wen; Chen, Yue; Li, Yixue; Chen, Hai-Feng

2012-06-01

HIV protease is a key enzyme to play a key role in the HIV-1 replication cycle and control the maturation from HIV viruses to an infectious virion. HIV-1 protease has become an important target for anti-HIV-1 drug development. Here, we used molecular dynamics simulation to study the binding mode between mannitol derivatives and HIV-1 protease. The results suggest that the most active compound (M35) has more stable hydrogen bonds and stable native contacts than the less active one (M17). These mannitol derivatives might have similar interaction mode with HIV-1 protease. Then, 3D-QSAR was used to construct quantitative structure-activity models. The cross-validated q(2) values are found as 0.728 and 0.611 for CoMFA and CoMSIA, respectively. And the non-cross-validated r(2) values are 0.973 and 0.950. Nine test set compounds validate the model. The results show that this model possesses better prediction ability than the previous work. This model can be used to design new chemical entities and make quantitative prediction of the bioactivities for HIV-1 protease inhibitors before resorting to in vitro and in vivo experiment. © 2012 John Wiley & Sons A/S.

Timing Interactions in Social Simulations: The Voter Model

NASA Astrophysics Data System (ADS)

Fernández-Gracia, Juan; Eguíluz, Víctor M.; Miguel, Maxi San

The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.

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

Moore, J. A. M.; Jiang, J.; Post, W. M.

Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential formore » ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.« less

Interaction between organophosphate pesticide exposure and PON1 activity on thyroid function

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

Lacasana, Marina, E-mail: marina.lacasana.easp@juntadeandalucia.e; CIBER de Epidemiologia y Salud Publica; Lopez-Flores, Inmaculada

Organophosphate pesticides are widely used in agricultural purposes. Recently, a few studies have demonstrated the ability of these chemicals to alter the function of the thyroid gland in human. Moreover, the paraoxonase-1 enzyme (PON1) plays an important role in the toxicity of some organophosphate pesticides, with low PON1 activity being associated with higher pesticide sensitivity. This study evaluates the interaction between exposure to organophosphate compounds and PON1 enzyme activity on serum levels of TSH and thyroid hormones in a population of workers occupationally exposed to pesticides. A longitudinal study was conducted on a population of floriculture workers from Mexico, duringmore » two periods of high and low-intensity levels of pesticide application. A structured questionnaire was completed by workers containing questions on sociodemographic characteristics and other variables of interest. Urine and blood samples were taken, and biomarkers of exposure (dialkylphosphates), susceptibility (PON1 polymorphisms and activity) and effect (thyroid hormone levels) were determined. Interaction between dialkylphosphates and PON1 polymorphisms or PON1 activity on hormone levels was evaluated by generalized estimating equation (GEE) models. A significant interaction was found between serum diazoxonase activity and total dialkylphosphates ({Sigma}DAP) on TSH levels. Thus, when PON1 activity was increased we observed a decrease in the percentage of variation of TSH level for each increment in one logarithmic unit of the {Sigma}DAP levels. This interaction was also observed with the PON1{sub 192}RR genotype. These results suggest a stronger association between organophosphate pesticides and thyroid function in individuals with lower PON1 activity.« less

The BioGRID interaction database: 2013 update.

PubMed

Chatr-Aryamontri, Andrew; Breitkreutz, Bobby-Joe; Heinicke, Sven; Boucher, Lorrie; Winter, Andrew; Stark, Chris; Nixon, Julie; Ramage, Lindsay; Kolas, Nadine; O'Donnell, Lara; Reguly, Teresa; Breitkreutz, Ashton; Sellam, Adnane; Chen, Daici; Chang, Christie; Rust, Jennifer; Livstone, Michael; Oughtred, Rose; Dolinski, Kara; Tyers, Mike

2013-01-01

The Biological General Repository for Interaction Datasets (BioGRID: http//thebiogrid.org) is an open access archive of genetic and protein interactions that are curated from the primary biomedical literature for all major model organism species. As of September 2012, BioGRID houses more than 500 000 manually annotated interactions from more than 30 model organisms. BioGRID maintains complete curation coverage of the literature for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe and the model plant Arabidopsis thaliana. A number of themed curation projects in areas of biomedical importance are also supported. BioGRID has established collaborations and/or shares data records for the annotation of interactions and phenotypes with most major model organism databases, including Saccharomyces Genome Database, PomBase, WormBase, FlyBase and The Arabidopsis Information Resource. BioGRID also actively engages with the text-mining community to benchmark and deploy automated tools to expedite curation workflows. BioGRID data are freely accessible through both a user-defined interactive interface and in batch downloads in a wide variety of formats, including PSI-MI2.5 and tab-delimited files. BioGRID records can also be interrogated and analyzed with a series of new bioinformatics tools, which include a post-translational modification viewer, a graphical viewer, a REST service and a Cytoscape plugin.

A Qualitative Model of Human Interaction with Complex Dynamic Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

A qualitative model of human interaction with complex dynamic systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

Memory-induced mechanism for self-sustaining activity in networks

NASA Astrophysics Data System (ADS)

Allahverdyan, A. E.; Steeg, G. Ver; Galstyan, A.

2015-12-01

We study a mechanism of activity sustaining on networks inspired by a well-known model of neuronal dynamics. Our primary focus is the emergence of self-sustaining collective activity patterns, where no single node can stay active by itself, but the activity provided initially is sustained within the collective of interacting agents. In contrast to existing models of self-sustaining activity that are caused by (long) loops present in the network, here we focus on treelike structures and examine activation mechanisms that are due to temporal memory of the nodes. This approach is motivated by applications in social media, where long network loops are rare or absent. Our results suggest that under a weak behavioral noise, the nodes robustly split into several clusters, with partial synchronization of nodes within each cluster. We also study the randomly weighted version of the models where the nodes are allowed to change their connection strength (this can model attention redistribution) and show that it does facilitate the self-sustained activity.

Analysis of the Mechanism of Prolonged Persistence of Drug Interaction between Terbinafine and Amitriptyline or Nortriptyline.

PubMed

Mikami, Akiko; Hori, Satoko; Ohtani, Hisakazu; Sawada, Yasufumi

2017-01-01

The purpose of the study was to quantitatively estimate and predict drug interactions between terbinafine and tricyclic antidepressants (TCAs), amitriptyline or nortriptyline, based on in vitro studies. Inhibition of TCA-metabolizing activity by terbinafine was investigated using human liver microsomes. Based on the unbound K i values obtained in vitro and reported pharmacokinetic parameters, a pharmacokinetic model of drug interaction was fitted to the reported plasma concentration profiles of TCAs administered concomitantly with terbinafine to obtain the drug-drug interaction parameters. Then, the model was used to predict nortriptyline plasma concentration with concomitant administration of terbinafine and changes of area under the curve (AUC) of nortriptyline after cessation of terbinafine. The CYP2D6 inhibitory potency of terbinafine was unaffected by preincubation, so the inhibition seems to be reversible. Terbinafine competitively inhibited amitriptyline or nortriptyline E-10-hydroxylation, with unbound K i values of 13.7 and 12.4 nM, respectively. Observed plasma concentrations of TCAs administered concomitantly with terbinafine were successfully simulated with the drug interaction model using the in vitro parameters. Model-predicted nortriptyline plasma concentration after concomitant nortriptylene/terbinafine administration for two weeks exceeded the toxic level, and drug interaction was predicted to be prolonged; the AUC of nortriptyline was predicted to be increased by 2.5- or 2.0- and 1.5-fold at 0, 3 and 6 months after cessation of terbinafine, respectively. The developed model enables us to quantitatively predict the prolonged drug interaction between terbinafine and TCAs. The model should be helpful for clinical management of terbinafine-CYP2D6 substrate drug interactions, which are difficult to predict due to their time-dependency.

Enantiomeric metabolic interactions and stereoselective human methadone metabolism.

PubMed

Totah, Rheem A; Allen, Kyle E; Sheffels, Pamela; Whittington, Dale; Kharasch, Evan D

2007-04-01

Methadone is administered as a racemate, although opioid activity resides in the R-enantiomer. Methadone disposition is stereoselective, with considerable unexplained variability in clearance and plasma R/S ratios. N-Demethylation of methadone in vitro is predominantly mediated by cytochrome P450 CYP3A4 and CYP2B6 and somewhat by CYP2C19. This investigation evaluated stereoselectivity, models, and kinetic parameters for methadone N-demethylation by recombinant CYP2B6, CYP3A4, and CYP2C19, and the potential for interactions between enantiomers during racemate metabolism. CYP2B6 metabolism was stereoselective. CYP2C19 was less active, and stereoselectivity was opposite that for CYP2B6. CYP3A4 was not stereoselective. With all three isoforms, enantiomer N-dealkylation rates in the racemate were lower than those of (R)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (R-methadone) or (S)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (S-methadone) alone, suggesting an enantiomeric interaction and mutual metabolic inhibition. For CYP2B6, the interaction between enantiomers was stereoselective, with S-methadone as a more potent inhibitor of R-methadone N-demethylation than R-of S-methadone. In contrast, enantiomer interactions were not stereoselective with CYP2C19 or CYP3A4. For all three cytochromes P450, methadone N-demethylation was best described by two-site enzyme models with competitive inhibition. There were minor model differences between cytochromes P450 to account for stereoselectivity of metabolism and enantiomeric interactions. Changes in plasma R/S methadone ratios observed after rifampin or troleandomycin pretreatment in humans in vivo were successfully predicted by CYP2B6- but not CYP3A4-catalyzed methadone N-demethylation. CYP2B6 is a predominant catalyst of stereoselective methadone metabolism in vitro. In vivo, CYP2B6 may be a major determinant of methadone metabolism and disposition, and CYP2B6 activity and stereoselective metabolic interactions may confer variability in methadone disposition.

Experimental Measurement of the Nonlinear Interaction between Counterpropagating Alfv'en Waves in the LaPD

NASA Astrophysics Data System (ADS)

Schroeder, J. W. R.; Drake, D. J.; Howes, G. G.; Skiff, F.; Kletzing, C. A.; Carter, T. A.; Dorfman, S.; Auerbach, D.

2012-10-01

Turbulence plays an important role in the transport of mass and energy in many space and astrophysical plasmas ranging from galaxy clusters to Earth's magnetosphere. One active topic of research is the application of idealized Alfv'enic turbulence models to plasma conditions relevant to space and astrophysical plasmas. Alfv'enic turbulence models based on incompressible magnetohydrodynamics (MHD) contain a nonlinear interaction that drives the cascade of energy to smaller scales. We describe experiments at the Large Plasma Device (LaPD) that focus on the interaction of an Alfv'en wave traveling parallel to the mean magnetic field with a counterpropagating Alfv'en wave. Theory predicts the nonlinear interaction of the two primary waves will produce a secondary daughter Alfv'en wave. In this study, we present the first experimental identification of the daughter wave generated by nonlinear interactions between the primary Alfv'en waves.

Continuous theory of active matter systems with metric-free interactions.

PubMed

Peshkov, Anton; Ngo, Sandrine; Bertin, Eric; Chaté, Hugues; Ginelli, Francesco

2012-08-31

We derive a hydrodynamic description of metric-free active matter: starting from self-propelled particles aligning with neighbors defined by "topological" rules, not metric zones-a situation advocated recently to be relevant for bird flocks, fish schools, and crowds-we use a kinetic approach to obtain well-controlled nonlinear field equations. We show that the density-independent collision rate per particle characteristic of topological interactions suppresses the linear instability of the homogeneous ordered phase and the nonlinear density segregation generically present near threshold in metric models, in agreement with microscopic simulations.

Estimating Likelihood of Fetal In Vivo Interactions Using In ...

EPA Pesticide Factsheets

Tox21/ToxCast efforts provide in vitro concentration-response data for thousands of compounds. Predicting whether chemical-biological interactions observed in vitro will occur in vivo is challenging. We hypothesize that using a modified model from the FDA guidance for drug interaction studies, Cmax/AC50 (i.e., maximal in vivo blood concentration over the half-maximal in in vitro activity concentration), will give a useful approximation for concentrations where in vivo interactions are likely. Further, for doses where maternal blood concentrations are likely to elicit an interaction (Cmax/AC50>0.1), where do the compounds accumulate in fetal tissues? In order to estimate these doses based on Tox21 data, in silico parameters of chemical fraction unbound in plasma and intrinsic hepatic clearance were estimated from ADMET predictor (Simulations-Plus Inc.) and used in the HTTK R-package to obtain Cmax values from a physiologically-based toxicokinetics model. In silico estimated Cmax values predicted in vivo human Cmax with median absolute error of 0.81 for 93 chemicals, giving confidence in the R-package and in silico estimates. A case example evaluating Cmax/AC50 values for peroxisome proliferator-activated receptor gamma (PPARγ) and glucocorticoid receptor revealed known compounds (glitazones and corticosteroids, respectively) highest on the list at pharmacological doses. Doses required to elicit likely interactions across all Tox21/ToxCast assays were compared to

Targeting YAP/TAZ-TEAD protein-protein interactions using fragment-based and computational modeling approaches

PubMed Central

Verma, Chandra

2017-01-01

The Hippo signaling pathway, which is implicated in the regulation of organ size, has emerged as a potential target for the development of cancer therapeutics. YAP, TAZ (transcription co-activators) and TEAD (transcription factor) are the downstream transcriptional machinery and effectors of the pathway. Formation of the YAP/TAZ-TEAD complex leads to transcription of growth-promoting genes. Conversely, disrupting the interactions of the complex decreases cell proliferation. Herein, we screened a 1000-member fragment library using Thermal Shift Assay and identified a hit fragment. We confirmed its binding at the YAP/TAZ-TEAD interface by X-ray crystallography, and showed that it occupies the same hydrophobic pocket as a conserved phenylalanine of YAP/TAZ. This hit fragment serves as a scaffold for the development of compounds that have the potential to disrupt YAP/TAZ-TEAD interactions. Structure-activity relationship studies and computational modeling were also carried out to identify more potent compounds that may bind at this validated druggable binding site. PMID:28570566

Anatomy of a fumarolic system inferred from a multiphysics approach.

PubMed

Gresse, Marceau; Vandemeulebrouck, Jean; Byrdina, Svetlana; Chiodini, Giovanni; Roux, Philippe; Rinaldi, Antonio Pio; Wathelet, Marc; Ricci, Tullio; Letort, Jean; Petrillo, Zaccaria; Tuccimei, Paola; Lucchetti, Carlo; Sciarra, Alessandra

2018-05-15

Fumaroles are a common manifestation of volcanic activity that are associated with large emissions of gases into the atmosphere. These gases originate from the magma, and they can provide indirect and unique insights into magmatic processes. Therefore, they are extensively used to monitor and forecast eruptive activity. During their ascent, the magmatic gases interact with the rock and hydrothermal fluids, which modify their geochemical compositions. These interactions can complicate our understanding of the real volcanic dynamics and remain poorly considered. Here, we present the first complete imagery of a fumarolic plumbing system using three-dimensional electrical resistivity tomography and new acoustic noise localization. We delineate a gas reservoir that feeds the fumaroles through distinct channels. Based on this geometry, a thermodynamic model reveals that near-surface mixing between gas and condensed steam explains the distinct geochemical compositions of fumaroles that originate from the same source. Such modeling of fluid interactions will allow for the simulation of dynamic processes of magmatic degassing, which is crucial to the monitoring of volcanic unrest.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni

2015-09-01

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.

Active bio-based food-packaging: Diffusion and release of active substances through and from cellulose nanofiber coating toward food-packaging design.

PubMed

Lavoine, Nathalie; Guillard, Valérie; Desloges, Isabelle; Gontard, Nathalie; Bras, Julien

2016-09-20

Cellulose nanofibers (CNFs) were recently investigated for the elaboration of new functional food-packaging materials. Their nanoporous network was especially of interest for controlling the release of active species. Qualitative release studies were conducted, but quantification of the diffusion phenomenon observed when the active species are released from and through CNF coating has not yet been studied. Therefore, this work aims to model CNF-coated paper substrates as controlled release system for food-packaging using release data obtained for two model molecules, namely caffeine and chlorhexidine digluconate. The applied mathematical model - derived from Fickian diffusion - was validated for caffeine only. When the active species chemically interacts with the release device, another model is required as a non-predominantly diffusion-controlled release was observed. From caffeine modeling data, a theoretical active food-packaging material was designed. The use of CNFs as barrier coating was proved to be the ideal material configuration that best meets specifications. Copyright © 2016. Published by Elsevier Ltd.

Development of structural model of adaptive training complex in ergatic systems for professional use

NASA Astrophysics Data System (ADS)

Obukhov, A. D.; Dedov, D. L.; Arkhipov, A. E.

2018-03-01

The article considers the structural model of the adaptive training complex (ATC), which reflects the interrelations between the hardware, software and mathematical model of ATC and describes the processes in this subject area. The description of the main components of software and hardware complex, their interaction and functioning within the common system are given. Also the article scrutinizers a brief description of mathematical models of personnel activity, a technical system and influences, the interactions of which formalize the regularities of ATC functioning. The studies of main objects of training complexes and connections between them will make it possible to realize practical implementation of ATC in ergatic systems for professional use.

Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates

USGS Publications Warehouse

Loehman, Rachel A.; Keane, Robert E.; Holsinger, Lisa M.; Wu, Zhiwei

2016-01-01

ContextInteractions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs.ObjectivesWe used the mechanistic ecosystem-fire process model FireBGCv2 to model interactions of wildland fire, mountain pine beetle (Dendroctonus ponderosae), and white pine blister rust (Cronartium ribicola) under current and future climates, across three diverse study areas.MethodsWe assessed changes in tree basal area as a measure of landscape response over a 300-year simulation period for the Crown of the Continent in north-central Montana, East Fork of the Bitterroot River in western Montana, and Yellowstone Central Plateau in western Wyoming, USA.ResultsInteracting disturbances reduced overall basal area via increased tree mortality of host species. Wildfire decreased basal area more than beetles or rust, and disturbance interactions modeled under future climate significantly altered landscape basal area as compared with no-disturbance and current climate scenarios. Responses varied among landscapes depending on species composition, sensitivity to fire, and pathogen and beetle suitability and susceptibility.ConclusionsUnderstanding disturbance interactions is critical for managing landscapes because forest responses to wildfires, pathogens, and beetle attacks may offset or exacerbate climate influences, with consequences for wildlife, carbon, and biodiversity.

Multi-Physics MRI-Based Two-Layer Fluid-Structure Interaction Anisotropic Models of Human Right and Left Ventricles with Different Patch Materials: Cardiac Function Assessment and Mechanical Stress Analysis

PubMed Central

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

2011-01-01

Multi-physics right and left ventricle (RV/LV) fluid-structure interaction (FSI) models were introduced to perform mechanical stress analysis and evaluate the effect of patch materials on RV function. The FSI models included three different patch materials (Dacron scaffold, treated pericardium, and contracting myocardium), two-layer construction, fiber orientation, and active anisotropic material properties. The models were constructed based on cardiac magnetic resonance (CMR) images acquired from a patient with severe RV dilatation and solved by ADINA. Our results indicate that the patch model with contracting myocardium leads to decreased stress level in the patch area, improved RV function and patch area contractility. PMID:21765559

Identification of New Antifungal Compounds Targeting Thioredoxin Reductase of Paracoccidioides Genus

PubMed Central

Abadio, Ana Karina Rodrigues; Kioshima, Erika Seki; Leroux, Vincent; Martins, Natalia Florêncio; Maigret, Bernard; Felipe, Maria Sueli Soares

2015-01-01

The prevalence of invasive fungal infections worldwide has increased in the last decades. The development of specific drugs targeting pathogenic fungi without producing collateral damage to mammalian cells is a daunting pharmacological challenge. Indeed, many of the toxicities and drug interactions observed with contemporary antifungal therapies can be attributed to “nonselective” interactions with enzymes or cell membrane systems found in mammalian host cells. A computer-aided screening strategy against the TRR1 protein of Paracoccidioides lutzii is presented here. Initially, a bank of commercially available compounds from Life Chemicals provider was docked to model by virtual screening simulations. The small molecules that interact with the model were ranked and, among the best hits, twelve compounds out of 3,000 commercially-available candidates were selected. These molecules were synthesized for validation and in vitro antifungal activity assays for Paracoccidioides lutzii and P. brasiliensis were performed. From 12 molecules tested, 3 harbor inhibitory activity in antifungal assays against the two pathogenic fungi. Corroborating these findings, the molecules have inhibitory activity against the purified recombinant enzyme TRR1 in biochemical assays. Therefore, a rational combination of molecular modeling simulations and virtual screening of new drugs has provided a cost-effective solution to an early-stage medicinal challenge. These results provide a promising technique to the development of new and innovative drugs. PMID:26569405

A Computational Model of Major Depression: the Role of Glutamate Dysfunction on Cingulo-Frontal Network Dynamics

PubMed Central

Ramirez-Mahaluf, Juan P.; Roxin, Alexander; Mayberg, Helen S.; Compte, Albert

2017-01-01

Abstract Major depression disease (MDD) is associated with the dysfunction of multinode brain networks. However, converging evidence implicates the reciprocal interaction between midline limbic regions (typified by the ventral anterior cingulate cortex, vACC) and the dorso-lateral prefrontal cortex (dlPFC), reflecting interactions between emotions and cognition. Furthermore, growing evidence suggests a role for abnormal glutamate metabolism in the vACC, while serotonergic treatments (selective serotonin reuptake inhibitor, SSRI) effective for many patients implicate the serotonin system. Currently, no mechanistic framework describes how network dynamics, glutamate, and serotonin interact to explain MDD symptoms and treatments. Here, we built a biophysical computational model of 2 areas (vACC and dlPFC) that can switch between emotional and cognitive processing. MDD networks were simulated by slowing glutamate decay in vACC and demonstrated sustained vACC activation. This hyperactivity was not suppressed by concurrent dlPFC activation and interfered with expected dlPFC responses to cognitive signals, mimicking cognitive dysfunction seen in MDD. Simulation of clinical treatments (SSRI or deep brain stimulation) counteracted this aberrant vACC activity. Theta and beta/gamma oscillations correlated with network function, representing markers of switch-like operation in the network. The model shows how glutamate dysregulation can cause aberrant brain dynamics, respond to treatments, and be reflected in EEG rhythms as biomarkers of MDD. PMID:26514163

The application of Biological-Hydraulic coupled model for Tubificidae-microorganism interaction system

NASA Astrophysics Data System (ADS)

Zhong, Xiao; Sun, Peide; Song, Yingqi; Wang, Ruyi; Fang, Zhiguo

2010-11-01

Based on the fully coupled activated sludge model (FCASM), the novel model Tubificidae -Fully Coupled Activated Sludge Model-hydraulic (T-FCASM-Hydro), has been developed in our previous work. T-FCASM-Hydro not only describe the interactive system between Tubificidae and functional microorganisms for the sludge reduction and nutrient removal simultaneously, but also considere the interaction between biological and hydraulic field, After calibration and validation of T-FCASM-Hydro at Zhuji Feida-hongyu Wastewater treatment plant (WWTP) in Zhejiang province, T-FCASM-Hydro was applied for determining optimal operating condition in the WWTP. Simulation results showed that nitrogen and phosphorus could be removed efficiently, and the efficiency of NH4+-N removal enhanced with increase of DO concentration. At a certain low level of DO concentration in the aerobic stage, shortcut nitrification-denitrification dominated in the process of denitrification in the novel system. However, overhigh agitation (>6 mgṡL-1) could result in the unfavorable feeding behavior of Tubificidae because of the strong flow disturbance, which might lead to low rate of sludge reduction. High sludge reduction rate and high removal rate of nitrogen and phosphorus could be obtained in the new-style oxidation ditch when DO concentration at the aerobic stage with Tubificidae was maintained at 3.6 gṡm-3.

Docking Analysis and Multidimensional Hybrid QSAR Model of 1,4-Benzodiazepine-2,5-Diones as HDM2 Antagonists

PubMed Central

Dai, Yujie; Chen, Nan; Wang, Qiang; Zheng, Heng; Zhang, Xiuli; Jia, Shiru; Dong, Lilong; Feng, Dacheng

2012-01-01

The inhibitors of p53-HDM2 interaction are attractive molecules for the treatment of wild-type p53 tumors. In order to search more potent HDM2 inhibitors, docking operation with CDOCKER protocol in Discovery Studio 2.1 (DS2.1) and multidimensional hybrid quantitative structure-activity relationship (QSAR) studies through the physiochemical properties obtained from DS2.1 and E-Dragon 1.0 as descriptors, have been performed on 59 1,4-benzodiazepine- 2,5-diones which have p53-HDM2 interaction inhibitory activities. The docking results indicate that π-π interaction between the imidazole group in HIS96 and the aryl ring at 4-N of 1,4-benzodiazepine-2,5-dione may be one of the key factors for the combination of ligands with HDM2. Two QSAR models were obtained using genetic function approximation (GFA) and genetic partial least squares (G/PLS) based on the descriptors obtained from DS2.1 and E-dragon 1.0, respectively. The best model can explain 85.5% of the variance (R 2adj ) while it could predict 81.7% of the variance (R 2 cv ). With this model, the bioactivities of some new compounds were predicted. PMID:24250508

Docking Analysis and Multidimensional Hybrid QSAR Model of 1,4-Benzodiazepine-2,5-Diones as HDM2 Antagonists.

PubMed

Dai, Yujie; Chen, Nan; Wang, Qiang; Zheng, Heng; Zhang, Xiuli; Jia, Shiru; Dong, Lilong; Feng, Dacheng

2012-01-01

The inhibitors of p53-HDM2 interaction are attractive molecules for the treatment of wild-type p53 tumors. In order to search more potent HDM2 inhibitors, docking operation with CDOCKER protocol in Discovery Studio 2.1 (DS2.1) and multidimensional hybrid quantitative structure-activity relationship (QSAR) studies through the physiochemical properties obtained from DS2.1 and E-Dragon 1.0 as descriptors, have been performed on 59 1,4-benzodiazepine- 2,5-diones which have p53-HDM2 interaction inhibitory activities. The docking results indicate that π-π interaction between the imidazole group in HIS96 and the aryl ring at 4-N of 1,4-benzodiazepine-2,5-dione may be one of the key factors for the combination of ligands with HDM2. Two QSAR models were obtained using genetic function approximation (GFA) and genetic partial least squares (G/PLS) based on the descriptors obtained from DS2.1 and E-dragon 1.0, respectively. The best model can explain 85.5% of the variance (R (2) adj ) while it could predict 81.7% of the variance (R (2) cv ). With this model, the bioactivities of some new compounds were predicted.

Targeting the cell wall of Mycobacterium tuberculosis: a molecular modeling investigation of the interaction of imipenem and meropenem with L,D-transpeptidase 2.

PubMed

Silva, José Rogério A; Bishai, William R; Govender, Thavendran; Lamichhane, Gyanu; Maguire, Glenn E M; Kruger, Hendrik G; Lameira, Jeronimo; Alves, Cláudio N

2016-01-01

The single crystal X-ray structure of the extracellular portion of the L,D-transpeptidase (ex-LdtMt2 - residues 120-408) enzyme was recently reported. It was observed that imipenem and meropenem inhibit activity of this enzyme, responsible for generating L,D-transpeptide linkages in the peptidoglycan layer of Mycobacterium tuberculosis. Imipenem is more active and isothermal titration calorimetry experiments revealed that meropenem is subjected to an entropy penalty upon binding to the enzyme. Herein, we report a molecular modeling approach to obtain a molecular view of the inhibitor/enzyme interactions. The average binding free energies for nine commercially available inhibitors were calculated using MM/GBSA and Solvation Interaction Energy (SIE) approaches and the calculated energies corresponded well with the available experimentally observed results. The method reproduces the same order of binding energies as experimentally observed for imipenem and meropenem. We have also demonstrated that SIE is a reasonably accurate and cost-effective free energy method, which can be used to predict carbapenem affinities for this enzyme. A theoretical explanation was offered for the experimental entropy penalty observed for meropenem, creating optimism that this computational model can serve as a potential computational model for other researchers in the field.

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.

Promoting student engagement in science: Interaction rituals and the pursuit of a community of practice

NASA Astrophysics Data System (ADS)

Olitsky, Stacy

2007-01-01

This study explores the relationship between interaction rituals, student engagement with science, and learning environments modeled on communities of practice based on an ethnographic study of an eighth grade urban magnet school classroom. It compares three interactional events in order to examine the classroom conditions and teacher practices that can foster successful interaction rituals (IRs), which are characterized by high levels of emotional energy, feelings of group membership, and sustained interest in the subject. Classroom conditions surrounding the emergence of successful IRs included mutual focus, familiar symbols and activity structures, the permissibility of some side-talk, and opportunities for physical and emotional entrainment. Sustained interest in the topic beyond the duration of the IR and an increase in students' helping each other learn occurred more frequently when the mutual focus consisted of science-related symbols, when there were low levels of risk for participants, when activities involved sufficient challenge and time, and when students were positioned as knowledgeable and competent in science. The results suggest that successful interaction rituals can foster student engagement with topics that may not have previously held interest and can contribute to students' support of peers' learning, thereby moving the classroom toward a community-of-practice model.

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.

A Spectral-SAR Model for the Anionic-Cationic Interaction in Ionic Liquids: Application to Vibrio fischeri Ecotoxicity

PubMed Central

Lacrămă, Ana-Maria; Putz, Mihai V.; Ostafe, Vasile

2007-01-01

Within the recently launched the spectral-structure activity relationship (S-SAR) analysis, the vectorial anionic-cationic model of a generic ionic liquid is proposed, along with the associated algebraic correlation factor in terms of the measured and predicted activity norms. The reliability of the present scheme is tested by assessing the Hansch factors, i.e. lipophylicity, polarizability and total energy, to predict the ecotoxicity endpoints of wide types of ionic liquids with ammonium, pyridinium, phosphonium, choline and imidazolium cations on the aquatic bacteria Vibrio fischeri. The results, while confirming the cationic dominant influence when only lipophylicity is considered, demonstrate that the anionic effect dominates all other more specific interactions. It was also proved that the S-SAR vectorial model predicts considerably higher activity for the ionic liquids than for its anionic and cationic subsystems separately, in all considered cases. Moreover, through applying the least norm-correlation path principle, the complete toxicological hierarchies are presented, unfolding the ecological rules of combined cationic and anionic influences in ionic liquid toxicity.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

PubMed

Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

2015-11-01

Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Giant optical activity of sugar in thin soap films.

PubMed

Emile, Janine; Emile, Olivier; Ghoufi, Aziz; Moréac, Alain; Casanova, Federico; Ding, Minxia; Houizot, Patrick

2013-10-15

We report on enhanced experimental optical activity measurements of thin soap films in the presence of sugar. This unusual optical activity is linked to the intramolecular chiral conformation of the glucose molecules at the air/liquid interface. Choosing sodium dodecylsulfate (SDS) as a model surfactant and glucose as model sugar, favorable interactions between the anionic group -OSO3(-)- and the glucose molecules are highlighted. This induces an interfacial anchoring of glucose molecules leading to a perturbing influence of the asymmetric chiral environment. Copyright © 2013 Elsevier Inc. All rights reserved.

Trails of meaning construction: Symbolic artifacts engage the social brain.

PubMed

Tylén, Kristian; Philipsen, Johanne Stege; Roepstorff, Andreas; Fusaroli, Riccardo

2016-07-01

Symbolic artifacts present a challenge to theories of neurocognitive processing due to their hybrid nature: they are at the same time physical objects and vehicles of intangible social meanings. While their physical properties can be read of their perceptual appearance, the meaning of symbolic artifacts depends on the perceiver's interpretative attitude and embeddedness in cultural practices. In this study, participants built models of LEGO bricks to illustrate their understanding of abstract concepts. They were then scanned with fMRI while presented to photographs of their own and others' models. When participants attended to the meaning of the models in contrast to their bare physical properties, we observed activations in mPFC and TPJ, areas often associated with social cognition, and IFG, possibly related to semantics. When contrasting own and others' models, we also found activations in precuneus, an area associated with autobiographical memory and agency, while looking at one's own collective models yielded interaction effects in rostral ACC, right IFG and left Insula. Interestingly, variability in the insula was predicted by individual differences in participants' feeling of relatedness to their fellow group members during LEGO construction activity. Our findings support a view of symbolic artifacts as neuro-cognitive trails of human social interactions. Copyright © 2016 Elsevier Inc. All rights reserved.

Decomposition by ectomycorrhizal fungi alters soil carbon storage in a simulation model

DOE PAGES

Moore, J. A. M.; Jiang, J.; Post, W. M.; ...

2015-03-06

Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential formore » ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.« less

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.

Squamous metaplasia amplifies pathologic epithelial-mesenchymal interactions in COPD patients

PubMed Central

Araya, Jun; Cambier, Stephanie; Markovics, Jennifer A.; Wolters, Paul; Jablons, David; Hill, Arthur; Finkbeiner, Walter; Jones, Kirk; Broaddus, V. Courtney; Sheppard, Dean; Barzcak, Andrea; Xiao, Yuanyuan; Erle, David J.; Nishimura, Stephen L.

2007-01-01

Squamous metaplasia (SM) is common in smokers and is associated with airway obstruction in chronic obstructive pulmonary disease (COPD). A major mechanism of airway obstruction in COPD is thickening of the small airway walls. We asked whether SM actively contributes to airway wall thickening through alteration of epithelial-mesenchymal interactions in COPD. Using immunohistochemical staining, airway morphometry, and fibroblast culture of lung samples from COPD patients; genome-wide analysis of an in vitro model of SM; and in vitro modeling of human airway epithelial-mesenchymal interactions, we provide evidence that SM, through the increased secretion of IL-1β, induces a fibrotic response in adjacent airway fibroblasts. We identify a pivotal role for integrin-mediated TGF-β activation in amplifying SM and driving IL-1β–dependent profibrotic mesenchymal responses. Finally, we show that SM correlates with increased severity of COPD and that fibroblast expression of the integrin αvβ8, which is the major mediator of airway fibroblast TGF-β activation, correlated with disease severity and small airway wall thickening in COPD. Our findings have identified TGF-β as a potential therapeutic target for COPD. PMID:17965775

Cortical subnetwork dynamics during human language tasks.

PubMed

Collard, Maxwell J; Fifer, Matthew S; Benz, Heather L; McMullen, David P; Wang, Yujing; Milsap, Griffin W; Korzeniewska, Anna; Crone, Nathan E

2016-07-15

Language tasks require the coordinated activation of multiple subnetworks-groups of related cortical interactions involved in specific components of task processing. Although electrocorticography (ECoG) has sufficient temporal and spatial resolution to capture the dynamics of event-related interactions between cortical sites, it is difficult to decompose these complex spatiotemporal patterns into functionally discrete subnetworks without explicit knowledge of each subnetwork's timing. We hypothesized that subnetworks corresponding to distinct components of task-related processing could be identified as groups of interactions with co-varying strengths. In this study, five subjects implanted with ECoG grids over language areas performed word repetition and picture naming. We estimated the interaction strength between each pair of electrodes during each task using a time-varying dynamic Bayesian network (tvDBN) model constructed from the power of high gamma (70-110Hz) activity, a surrogate for population firing rates. We then reduced the dimensionality of this model using principal component analysis (PCA) to identify groups of interactions with co-varying strengths, which we term functional network components (FNCs). This data-driven technique estimates both the weight of each interaction's contribution to a particular subnetwork, and the temporal profile of each subnetwork's activation during the task. We found FNCs with temporal and anatomical features consistent with articulatory preparation in both tasks, and with auditory and visual processing in the word repetition and picture naming tasks, respectively. These FNCs were highly consistent between subjects with similar electrode placement, and were robust enough to be characterized in single trials. Furthermore, the interaction patterns uncovered by FNC analysis correlated well with recent literature suggesting important functional-anatomical distinctions between processing external and self-produced speech. Our results demonstrate that subnetwork decomposition of event-related cortical interactions is a powerful paradigm for interpreting the rich dynamics of large-scale, distributed cortical networks during human cognitive tasks. Copyright © 2016 Elsevier Inc. All rights reserved.

Visualizing the phage T4 activated transcription complex of DNA and E. coli RNA polymerase

PubMed Central

James, Tamara D.; Cardozo, Timothy; Abell, Lauren E.; Hsieh, Meng-Lun; Jenkins, Lisa M. Miller; Jha, Saheli S.; Hinton, Deborah M.

2016-01-01

The ability of RNA polymerase (RNAP) to select the right promoter sequence at the right time is fundamental to the control of gene expression in all organisms. However, there is only one crystallized structure of a complete activator/RNAP/DNA complex. In a process called σ appropriation, bacteriophage T4 activates a class of phage promoters using an activator (MotA) and a co-activator (AsiA), which function through interactions with the σ70 subunit of RNAP. We have developed a holistic, structure-based model for σ appropriation using multiple experimentally determined 3D structures (Escherichia coli RNAP, the Thermus aquaticus RNAP/DNA complex, AsiA /σ70 Region 4, the N-terminal domain of MotA [MotANTD], and the C-terminal domain of MotA [MotACTD]), molecular modeling, and extensive biochemical observations indicating the position of the proteins relative to each other and to the DNA. Our results visualize how AsiA/MotA redirects σ, and therefore RNAP activity, to T4 promoter DNA, and demonstrate at a molecular level how the tactful interaction of transcriptional factors with even small segments of RNAP can alter promoter specificity. Furthermore, our model provides a rational basis for understanding how a mutation within the β subunit of RNAP (G1249D), which is far removed from AsiA or MotA, impairs σ appropriation. PMID:27458207

Modeling low-temperature geochemical processes: Chapter 2

USGS Publications Warehouse

Nordstrom, D. Kirk; Campbell, Kate M.

2014-01-01

This chapter provides an overview of geochemical modeling that applies to water–rock interactions under ambient conditions of temperature and pressure. Topics include modeling definitions, historical background, issues of activity coefficients, popular codes and databases, examples of modeling common types of water–rock interactions, and issues of model reliability. Examples include speciation, microbial redox kinetics and ferrous iron oxidation, calcite dissolution, pyrite oxidation, combined pyrite and calcite dissolution, dedolomitization, seawater–carbonate groundwater mixing, reactive-transport modeling in streams, modeling catchments, and evaporation of seawater. The chapter emphasizes limitations to geochemical modeling: that a proper understanding and ability to communicate model results well are as important as completing a set of useful modeling computations and that greater sophistication in model and code development is not necessarily an advancement. If the goal is to understand how a particular geochemical system behaves, it is better to collect more field data than rely on computer codes.

Analysis of PKR-RNA interactions by sedimentation velocity

PubMed Central

Wong, C. Jason; Launer-Felty, Katherine; Cole, James L.

2010-01-01

PKR is an interferon-induced kinase that plays a pivotal role in the innate immunity pathway for defense against viral infection. PKR is activated to undergo autophosphorylation upon binding to RNAs that contain duplex regions. Some highly structured viral RNAs do not activate and function as PKR inhibitors. In order to define the mechanisms of activation and inhibition of PKR by RNA it is necessary to characterize the stoichiometries, affinities and free energy couplings governing the assembly of the relevant complexes. We have found sedimentation velocity analytical ultracentrifugation to be particularly useful in the study of PKR-RNA interactions. Here, we describe protocols for designing and analyzing sedimentation velocity experiments that are generally applicable to studies of protein-nucleic interactions. Initially, velocity data obtained at multiple protein:RNA ratios are analyzed using the dc/dt method to define the association model and to test whether the system is kinetically limited. The sedimentation velocity data obtained at multiple loading concentrations are then globally fit to this model to determine the relevant association constants. The frictional ratios of the complexes are calculated using the fitted sedimentation coefficients to determine whether the hydrodynamic properties are physically reasonable. We demonstrate the utility of this approach using examples from our studies of PKR interactions with simple dsRNAs, the HIV TAR RNA and the VAI RNA from Adenovirus. PMID:21195224

Interactions between internal forces, body stiffness, and fluid environment in a neuromechanical model of lamprey swimming.

PubMed

Tytell, Eric D; Hsu, Chia-Yu; Williams, Thelma L; Cohen, Avis H; Fauci, Lisa J

2010-11-16

Animal movements result from a complex balance of many different forces. Muscles produce force to move the body; the body has inertial, elastic, and damping properties that may aid or oppose the muscle force; and the environment produces reaction forces back on the body. The actual motion is an emergent property of these interactions. To examine the roles of body stiffness, muscle activation, and fluid environment for swimming animals, a computational model of a lamprey was developed. The model uses an immersed boundary framework that fully couples the Navier-Stokes equations of fluid dynamics with an actuated, elastic body model. This is the first model at a Reynolds number appropriate for a swimming fish that captures the complete fluid-structure interaction, in which the body deforms according to both internal muscular forces and external fluid forces. Results indicate that identical muscle activation patterns can produce different kinematics depending on body stiffness, and the optimal value of stiffness for maximum acceleration is different from that for maximum steady swimming speed. Additionally, negative muscle work, observed in many fishes, emerges at higher tail beat frequencies without sensory input and may contribute to energy efficiency. Swimming fishes that can tune their body stiffness by appropriately timed muscle contractions may therefore be able to optimize the passive dynamics of their bodies to maximize peak acceleration or swimming speed.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors: pharmacological characterization, computational modeling, and pharmacophore development.

PubMed

McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C

2007-05-01

As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.