Coverage Dependent Assembly of Anthraquinone on Au(111)

NASA Astrophysics Data System (ADS)

Conrad, Brad; Deloach, Andrew; Einstein, Theodore; Dougherty, Daniel

A study of adsorbate-adsorbate and surface state mediated interactions of anthraquinone (AnQ) on Au(111) is presented. We utilize scanning tunneling microscopy (STM) to characterize the coverage dependence of AnQ structure formation. Ordered structures are observed up to a single monolayer (ML) and are found to be strongly dependent on molecular surface density. While the complete ML forms a well-ordered close-packed layer, for a narrow range of sub-ML coverages irregular close-packed islands are observed to coexist with a disordered pore network linking neighboring islands. This network displays a characteristic pore size and at lower coverages, the soliton walls of the herringbone reconstruction are shown to promote formation of distinct pore nanostructures. We will discuss these nanostructure formations in the context of surface mediated and more direct adsorbate interactions.

Structural principles within the human-virus protein-protein interaction network

PubMed Central

Franzosa, Eric A.; Xia, Yu

2011-01-01

General properties of the antagonistic biomolecular interactions between viruses and their hosts (exogenous interactions) remain poorly understood, and may differ significantly from known principles governing the cooperative interactions within the host (endogenous interactions). Systems biology approaches have been applied to study the combined interaction networks of virus and human proteins, but such efforts have so far revealed only low-resolution patterns of host-virus interaction. Here, we layer curated and predicted 3D structural models of human-virus and human-human protein complexes on top of traditional interaction networks to reconstruct the human-virus structural interaction network. This approach reveals atomic resolution, mechanistic patterns of host-virus interaction, and facilitates systematic comparison with the host’s endogenous interactions. We find that exogenous interfaces tend to overlap with and mimic endogenous interfaces, thereby competing with endogenous binding partners. The endogenous interfaces mimicked by viral proteins tend to participate in multiple endogenous interactions which are transient and regulatory in nature. While interface overlap in the endogenous network results largely from gene duplication followed by divergent evolution, viral proteins frequently achieve interface mimicry without any sequence or structural similarity to an endogenous binding partner. Finally, while endogenous interfaces tend to evolve more slowly than the rest of the protein surface, exogenous interfaces—including many sites of endogenous-exogenous overlap—tend to evolve faster, consistent with an evolutionary “arms race” between host and pathogen. These significant biophysical, functional, and evolutionary differences between host-pathogen and within-host protein-protein interactions highlight the distinct consequences of antagonism versus cooperation in biological networks. PMID:21680884

Simulation of a Lunar Surface Base Power Distribution Network for the Constellation Lunar Surface Systems

NASA Technical Reports Server (NTRS)

Mintz, Toby; Maslowski, Edward A.; Colozza, Anthony; McFarland, Willard; Prokopius, Kevin P.; George, Patrick J.; Hussey, Sam W.

2010-01-01

The Lunar Surface Power Distribution Network Study team worked to define, breadboard, build and test an electrical power distribution system consistent with NASA's goal of providing electrical power to sustain life and power equipment used to explore the lunar surface. A testbed was set up to simulate the connection of different power sources and loads together to form a mini-grid and gain an understanding of how the power systems would interact. Within the power distribution scheme, each power source contributes to the grid in an independent manner without communication among the power sources and without a master-slave scenario. The grid consisted of four separate power sources and the accompanying power conditioning equipment. Overall system design and testing was performed. The tests were performed to observe the output and interaction of the different power sources as some sources are added and others are removed from the grid connection. The loads on the system were also varied from no load to maximum load to observe the power source interactions.

Infrared laser ablation of polymeric nanocomposites: A study of surface structure and plume formation

NASA Astrophysics Data System (ADS)

Bartolucci, S. F.; Miller, M. J.; Warrender, J. M.

2016-12-01

The behavior of carbon nanotube composites subjected to laser pulse heating with a 1070 nm variable pulse duration laser has been studied. Previous work has shown that carbon nanotube composites form a protective network on the surface of a composite, which reduces heat input to the underlying polymer and slows mass loss. In this work, we have studied the interaction between the incident laser and the plume formed above the composite. We have correlated these interactions with features observed in the time-resolved mass loss data and confirmed them with observations using high-speed video of the laser irradiations. Beam interactions were studied as a function of laser irradiance and nanotube content. It is shown that beam-plume interactions occur for the carbon nanotube composites and that the interactions occur at shorter pulse durations for increased nanotube content and laser irradiance. When we eliminate beam-plume interaction through alteration of the sample orientation relative to the incident beam, we are able to elucidate the individual contributions of the carbon nanotube surface network and the plume to the observed decrease in mass loss after laser irradiation. We examine the plume content using microscopy and Raman spectroscopy and show that greater beam absorption occurs when there is a higher graphitic content in the plume.

Spontaneous emergence of cataclysmic networks in spatially extended systems

NASA Astrophysics Data System (ADS)

Manrubia, Susanna C.; Poyatos, Juan F.; Pérez-Mercader, Juan

2002-11-01

A system of interacting chemical species able to catalyse each others' production is studied. We consider a two-dimensional surface where single molecules attach, diffuse, catalytically interact, and decay. The population of species molecules and the network of interactions among them are dynamical entities. After a short transient time, robust catalytic cycles emerge and a "stationary" state of high diversity and large population numbers settles down. Population dynamics and physical space select among possible graphs of catalytic interactions. The organization of the system is robust: parasitic invaders are short-lived, their populations are kept at low levels, and are unable to sweep away the emerging catalytic cycles.

A binomial modeling approach for upscaling colloid transport under unfavorable conditions: Emergent prediction of extended tailing

NASA Astrophysics Data System (ADS)

Hilpert, Markus; Rasmuson, Anna; Johnson, William P.

2017-07-01

Colloid transport in saturated porous media is significantly influenced by colloidal interactions with grain surfaces. Near-surface fluid domain colloids experience relatively low fluid drag and relatively strong colloidal forces that slow their downgradient translation relative to colloids in bulk fluid. Near-surface fluid domain colloids may reenter into the bulk fluid via diffusion (nanoparticles) or expulsion at rear flow stagnation zones, they may immobilize (attach) via primary minimum interactions, or they may move along a grain-to-grain contact to the near-surface fluid domain of an adjacent grain. We introduce a simple model that accounts for all possible permutations of mass transfer within a dual pore and grain network. The primary phenomena thereby represented in the model are mass transfer of colloids between the bulk and near-surface fluid domains and immobilization. Colloid movement is described by a Markov chain, i.e., a sequence of trials in a 1-D network of unit cells, which contain a pore and a grain. Using combinatorial analysis, which utilizes the binomial coefficient, we derive the residence time distribution, i.e., an inventory of the discrete colloid travel times through the network and of their probabilities to occur. To parameterize the network model, we performed mechanistic pore-scale simulations in a single unit cell that determined the likelihoods and timescales associated with the above colloid mass transfer processes. We found that intergrain transport of colloids in the near-surface fluid domain can cause extended tailing, which has traditionally been attributed to hydrodynamic dispersion emanating from flow tortuosity of solute trajectories.

Large-scale investigation of Leishmania interaction networks with host extracellular matrix by surface plasmon resonance imaging.

PubMed

Fatoux-Ardore, Marie; Peysselon, Franck; Weiss, Anthony; Bastien, Patrick; Pratlong, Francine; Ricard-Blum, Sylvie

2014-02-01

We have set up an assay to study the interactions of live pathogens with their hosts by using protein and glycosaminoglycan arrays probed by surface plasmon resonance imaging. We have used this assay to characterize the interactions of Leishmania promastigotes with ~70 mammalian host biomolecules (extracellular proteins, glycosaminoglycans, growth factors, cell surface receptors). We have identified, in total, 27 new partners (23 proteins, 4 glycosaminoglycans) of procyclic promastigotes of six Leishmania species and 18 partners (15 proteins, 3 glycosaminoglycans) of three species of stationary-phase promastigotes for all the strains tested. The diversity of the interaction repertoires of Leishmania parasites reflects their dynamic and complex interplay with their mammalian hosts, which depends mostly on the species and strains of Leishmania. Stationary-phase Leishmania parasites target extracellular matrix proteins and glycosaminoglycans, which are highly connected in the extracellular interaction network. Heparin and heparan sulfate bind to most Leishmania strains tested, and 6-O-sulfate groups play a crucial role in these interactions. Numerous Leishmania strains bind to tropoelastin, and some strains are even able to degrade it. Several strains interact with collagen VI, which is expressed by macrophages. Most Leishmania promastigotes interact with several regulators of angiogenesis, including antiangiogenic factors (endostatin, anastellin) and proangiogenic factors (ECM-1, VEGF, and TEM8 [also known as anthrax toxin receptor 1]), which are regulated by hypoxia. Since hypoxia modulates the infection of macrophages by the parasites, these interactions might influence the infection of host cells by Leishmania.

Large-Scale Investigation of Leishmania Interaction Networks with Host Extracellular Matrix by Surface Plasmon Resonance Imaging

PubMed Central

Fatoux-Ardore, Marie; Peysselon, Franck; Weiss, Anthony; Bastien, Patrick; Pratlong, Francine

2014-01-01

We have set up an assay to study the interactions of live pathogens with their hosts by using protein and glycosaminoglycan arrays probed by surface plasmon resonance imaging. We have used this assay to characterize the interactions of Leishmania promastigotes with ∼70 mammalian host biomolecules (extracellular proteins, glycosaminoglycans, growth factors, cell surface receptors). We have identified, in total, 27 new partners (23 proteins, 4 glycosaminoglycans) of procyclic promastigotes of six Leishmania species and 18 partners (15 proteins, 3 glycosaminoglycans) of three species of stationary-phase promastigotes for all the strains tested. The diversity of the interaction repertoires of Leishmania parasites reflects their dynamic and complex interplay with their mammalian hosts, which depends mostly on the species and strains of Leishmania. Stationary-phase Leishmania parasites target extracellular matrix proteins and glycosaminoglycans, which are highly connected in the extracellular interaction network. Heparin and heparan sulfate bind to most Leishmania strains tested, and 6-O-sulfate groups play a crucial role in these interactions. Numerous Leishmania strains bind to tropoelastin, and some strains are even able to degrade it. Several strains interact with collagen VI, which is expressed by macrophages. Most Leishmania promastigotes interact with several regulators of angiogenesis, including antiangiogenic factors (endostatin, anastellin) and proangiogenic factors (ECM-1, VEGF, and TEM8 [also known as anthrax toxin receptor 1]), which are regulated by hypoxia. Since hypoxia modulates the infection of macrophages by the parasites, these interactions might influence the infection of host cells by Leishmania. PMID:24478075

A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115

CH-π Interaction Driven Macroscopic Property Transition on Smart Polymer Surface

NASA Astrophysics Data System (ADS)

Li, Minmin; Qing, Guangyan; Xiong, Yuting; Lai, Yuekun; Sun, Taolei

2015-10-01

Life systems have evolved to utilize weak noncovalent interactions, particularly CH-π interaction, to achieve various biofunctions, for example cellular communication, immune response, and protein folding. However, for artificial materials, it remains a great challenge to recognize such weak interaction, further transform it into tunable macroscopic properties and realize special functions. Here we integrate monosaccharide-based CH-π receptor capable of recognizing aromatic peptides into a smart polymer with three-component “Recognition-Mediating-Function” design, and report the CH-π interaction driven surface property switching on smart polymer film, including wettability, adhesion, viscoelasticity and stiffness. Detailed studies indicate that, the CH-π interaction induces the complexation between saccharide unit and aromatic peptide, which breaks the initial amphiphilic balance of the polymer network, resulting in contraction-swelling conformational transition for polymer chains and subsequent dramatic switching in surface properties. This work not only presents a new approach to control the surface property of materials, but also points to a broader research prospect on CH-π interaction at a macroscopic level.

CH-π Interaction Driven Macroscopic Property Transition on Smart Polymer Surface.

PubMed

Li, Minmin; Qing, Guangyan; Xiong, Yuting; Lai, Yuekun; Sun, Taolei

2015-10-29

Life systems have evolved to utilize weak noncovalent interactions, particularly CH-π interaction, to achieve various biofunctions, for example cellular communication, immune response, and protein folding. However, for artificial materials, it remains a great challenge to recognize such weak interaction, further transform it into tunable macroscopic properties and realize special functions. Here we integrate monosaccharide-based CH-π receptor capable of recognizing aromatic peptides into a smart polymer with three-component "Recognition-Mediating-Function" design, and report the CH-π interaction driven surface property switching on smart polymer film, including wettability, adhesion, viscoelasticity and stiffness. Detailed studies indicate that, the CH-π interaction induces the complexation between saccharide unit and aromatic peptide, which breaks the initial amphiphilic balance of the polymer network, resulting in contraction-swelling conformational transition for polymer chains and subsequent dramatic switching in surface properties. This work not only presents a new approach to control the surface property of materials, but also points to a broader research prospect on CH-π interaction at a macroscopic level.

Two-dimensional honeycomb network through sequence-controlled self-assembly of oligopeptides.

PubMed

Abb, Sabine; Harnau, Ludger; Gutzler, Rico; Rauschenbach, Stephan; Kern, Klaus

2016-01-12

The sequence of a peptide programs its self-assembly and hence the expression of specific properties through non-covalent interactions. A large variety of peptide nanostructures has been designed employing different aspects of these non-covalent interactions, such as dispersive interactions, hydrogen bonding or ionic interactions. Here we demonstrate the sequence-controlled fabrication of molecular nanostructures using peptides as bio-organic building blocks for two-dimensional (2D) self-assembly. Scanning tunnelling microscopy reveals changes from compact or linear assemblies (angiotensin I) to long-range ordered, chiral honeycomb networks (angiotensin II) as a result of removal of steric hindrance by sequence modification. Guided by our observations, molecular dynamic simulations yield atomistic models for the elucidation of interpeptide-binding motifs. This new approach to 2D self-assembly on surfaces grants insight at the atomic level that will enable the use of oligo- and polypeptides as large, multi-functional bio-organic building blocks, and opens a new route towards rationally designed, bio-inspired surfaces.

Towards a Comprehensive Computational Simulation System for Turbomachinery

NASA Technical Reports Server (NTRS)

Shih, Ming-Hsin

1994-01-01

The objective of this work is to develop algorithms associated with a comprehensive computational simulation system for turbomachinery flow fields. This development is accomplished in a modular fashion. These modules includes grid generation, visualization, network, simulation, toolbox, and flow modules. An interactive grid generation module is customized to facilitate the grid generation process associated with complicated turbomachinery configurations. With its user-friendly graphical user interface, the user may interactively manipulate the default settings to obtain a quality grid within a fraction of time that is usually required for building a grid about the same geometry with a general-purpose grid generation code. Non-Uniform Rational B-Spline formulations are utilized in the algorithm to maintain geometry fidelity while redistributing grid points on the solid surfaces. Bezier curve formulation is used to allow interactive construction of inner boundaries. It is also utilized to allow interactive point distribution. Cascade surfaces are transformed from three-dimensional surfaces of revolution into two-dimensional parametric planes for easy manipulation. Such a transformation allows these manipulated plane grids to be mapped to surfaces of revolution by any generatrix definition. A sophisticated visualization module is developed to al-low visualization for both grid and flow solution, steady or unsteady. A network module is built to allow data transferring in the heterogeneous environment. A flow module is integrated into this system, using an existing turbomachinery flow code. A simulation module is developed to combine the network, flow, and visualization module to achieve near real-time flow simulation about turbomachinery geometries. A toolbox module is developed to support the overall task. A batch version of the grid generation module is developed to allow portability and has been extended to allow dynamic grid generation for pitch changing turbomachinery configurations. Various applications with different characteristics are presented to demonstrate the success of this system.

Network organization of the human autophagy system.

PubMed

Behrends, Christian; Sowa, Mathew E; Gygi, Steven P; Harper, J Wade

2010-07-01

Autophagy, the process by which proteins and organelles are sequestered in autophagosomal vesicles and delivered to the lysosome/vacuole for degradation, provides a primary route for turnover of stable and defective cellular proteins. Defects in this system are linked with numerous human diseases. Although conserved protein kinase, lipid kinase and ubiquitin-like protein conjugation subnetworks controlling autophagosome formation and cargo recruitment have been defined, our understanding of the global organization of this system is limited. Here we report a proteomic analysis of the autophagy interaction network in human cells under conditions of ongoing (basal) autophagy, revealing a network of 751 interactions among 409 candidate interacting proteins with extensive connectivity among subnetworks. Many new autophagy interaction network components have roles in vesicle trafficking, protein or lipid phosphorylation and protein ubiquitination, and affect autophagosome number or flux when depleted by RNA interference. The six ATG8 orthologues in humans (MAP1LC3/GABARAP proteins) interact with a cohort of 67 proteins, with extensive binding partner overlap between family members, and frequent involvement of a conserved surface on ATG8 proteins known to interact with LC3-interacting regions in partner proteins. These studies provide a global view of the mammalian autophagy interaction landscape and a resource for mechanistic analysis of this critical protein homeostasis pathway.

Tree Resin Composition, Collection Behavior and Selective Filters Shape Chemical Profiles of Tropical Bees (Apidae: Meliponini)

PubMed Central

Leonhardt, Sara D.; Schmitt, Thomas; Blüthgen, Nico

2011-01-01

The diversity of species is striking, but can be far exceeded by the chemical diversity of compounds collected, produced or used by them. Here, we relate the specificity of plant-consumer interactions to chemical diversity applying a comparative network analysis to both levels. Chemical diversity was explored for interactions between tropical stingless bees and plant resins, which bees collect for nest construction and to deter predators and microbes. Resins also function as an environmental source for terpenes that serve as appeasement allomones and protection against predators when accumulated on the bees' body surfaces. To unravel the origin of the bees' complex chemical profiles, we investigated resin collection and the processing of resin-derived terpenes. We therefore analyzed chemical networks of tree resins, foraging networks of resin collecting bees, and their acquired chemical networks. We revealed that 113 terpenes in nests of six bee species and 83 on their body surfaces comprised a subset of the 1,117 compounds found in resins from seven tree species. Sesquiterpenes were the most variable class of terpenes. Albeit widely present in tree resins, they were only found on the body surface of some species, but entirely lacking in others. Moreover, whereas the nest profile of Tetragonula melanocephala contained sesquiterpenes, its surface profile did not. Stingless bees showed a generalized collecting behavior among resin sources, and only a hitherto undescribed species-specific “filtering” of resin-derived terpenes can explain the variation in chemical profiles of nests and body surfaces from different species. The tight relationship between bees and tree resins of a large variety of species elucidates why the bees' surfaces contain a much higher chemodiversity than other hymenopterans. PMID:21858119

Temporal Information Partitioning Networks (TIPNets): A process network approach to infer ecohydrologic shifts

NASA Astrophysics Data System (ADS)

Goodwell, Allison E.; Kumar, Praveen

2017-07-01

In an ecohydrologic system, components of atmospheric, vegetation, and root-soil subsystems participate in forcing and feedback interactions at varying time scales and intensities. The structure of this network of complex interactions varies in terms of connectivity, strength, and time scale due to perturbations or changing conditions such as rainfall, drought, or land use. However, characterization of these interactions is difficult due to multivariate and weak dependencies in the presence of noise, nonlinearities, and limited data. We introduce a framework for Temporal Information Partitioning Networks (TIPNets), in which time-series variables are viewed as nodes, and lagged multivariate mutual information measures are links. These links are partitioned into synergistic, unique, and redundant information components, where synergy is information provided only jointly, unique information is only provided by a single source, and redundancy is overlapping information. We construct TIPNets from 1 min weather station data over several hour time windows. From a comparison of dry, wet, and rainy conditions, we find that information strengths increase when solar radiation and surface moisture are present, and surface moisture and wind variability are redundant and synergistic influences, respectively. Over a growing season, network trends reveal patterns that vary with vegetation and rainfall patterns. The framework presented here enables us to interpret process connectivity in a multivariate context, which can lead to better inference of behavioral shifts due to perturbations in ecohydrologic systems. This work contributes to more holistic characterizations of system behavior, and can benefit a wide variety of studies of complex systems.

A feedback model of figure-ground assignment.

PubMed

Domijan, Drazen; Setić, Mia

2008-05-30

A computational model is proposed in order to explain how bottom-up and top-down signals are combined into a unified perception of figure and background. The model is based on the interaction between the ventral and the dorsal stream. The dorsal stream computes saliency based on boundary signals provided by the simple and the complex cortical cells. Output from the dorsal stream is projected to the surface network which serves as a blackboard on which the surface representation is formed. The surface network is a recurrent network which segregates different surfaces by assigning different firing rates to them. The figure is labeled by the maximal firing rate. Computer simulations showed that the model correctly assigns figural status to the surface with a smaller size, a greater contrast, convexity, surroundedness, horizontal-vertical orientation and a higher spatial frequency content. The simple gradient of activity in the dorsal stream enables the simulation of the new principles of the lower region and the top-bottom polarity. The model also explains how the exogenous attention and the endogenous attention may reverse the figural assignment. Due to the local excitation in the surface network, neural activity at the cued region will spread over the whole surface representation. Therefore, the model implements the object-based attentional selection.

Network based approaches reveal clustering in protein point patterns

NASA Astrophysics Data System (ADS)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Surface pressure affects B-hordein network formation at the air-water interface in relation to gastric digestibility.

PubMed

Yang, Jingqi; Huang, Jun; Zeng, Hongbo; Chen, Lingyun

2015-11-01

Protein interfacial network formation under mechanical pressure and its influence on degradation was investigated at molecular level using Langmuir-Blodgett B-hordein monolayer as a 2D model. Surface properties, such as surface pressure, dilatational and shear rheology and the surface pressure--area (π-A) isotherm, of B-hordein at air-water interface were analyzed by tensiometer, rheometer and a Langmuir-Blodgett trough respectively. B-Hordein conformation and orientation under different surface pressures were determined by polarization modulation-infrared reflection absorption spectroscopy (PM-IRRAS). The interfacial network morphology was observed by atomic force microscopy (AFM). B-Hordein could reduce the air-water surface tension rapidly to ∼ 45 mN/m and form a solid-like network with high rheological elasticity and compressibility at interface, which could be a result of interactions developed by intermolecular β-sheets. The results also revealed that B-hordein interfacial network switched from an expanded liquid phase to a solid-like film with increasing compression pressure. The orientation of B-hordein was parallel to the surface when in expended liquid phase, whereas upon compression, the hydrophobic repetitive region tilted away from water phase. When compressed to 30 mN/m, a strong elastic network was formed at the interface, and it was resistant to a harsh gastric-like environment of low pH and pepsin. This work generated fundamental knowledge, which suggested the potential to design B-hordein stabilized emulsions and encapsulations with controllable digestibility for small intestine targeted delivery of bioactive compounds. Copyright © 2015 Elsevier B.V. All rights reserved.

Methane dissociation on Ni(111): A fifteen-dimensional potential energy surface using neural network method

NASA Astrophysics Data System (ADS)

Shen, Xiangjian; Chen, Jun; Zhang, Zhaojun; Shao, Kejie; Zhang, Dong H.

2015-10-01

In the present work, we develop a highly accurate, fifteen-dimensional potential energy surface (PES) of CH4 interacting on a rigid flat Ni(111) surface with the methodology of neural network (NN) fit to a database consisted of about 194 208 ab initio density functional theory (DFT) energy points. Some careful tests of the accuracy of the fitting PES are given through the descriptions of the fitting quality, vibrational spectrum of CH4 in vacuum, transition state (TS) geometries as well as the activation barriers. Using a 25-60-60-1 NN structure, we obtain one of the best PESs with the least root mean square errors: 10.11 meV for the entrance region and 17.00 meV for the interaction and product regions. Our PES can reproduce the DFT results very well in particular for the important TS structures. Furthermore, we present the sticking probability S0 of ground state CH4 at the experimental surface temperature using some sudden approximations by Jackson's group. An in-depth explanation is given for the underestimated sticking probability.

Carbon Nanotube Web with Carboxylated Polythiophene "Assist" for High-Performance Battery Electrodes.

PubMed

Kwon, Yo Han; Park, Jung Jin; Housel, Lisa M; Minnici, Krysten; Zhang, Guoyan; Lee, Sujin R; Lee, Seung Woo; Chen, Zhongming; Noda, Suguru; Takeuchi, Esther S; Takeuchi, Kenneth J; Marschilok, Amy C; Reichmanis, Elsa

2018-04-24

A carbon nanotube (CNT) web electrode comprising magnetite spheres and few-walled carbon nanotubes (FWNTs) linked by the carboxylated conjugated polymer, poly[3-(potassium-4-butanoate) thiophene] (PPBT), was designed to demonstrate benefits derived from the rational consideration of electron/ion transport coupled with the surface chemistry of the electrode materials components. To maximize transport properties, the approach introduces monodispersed spherical Fe 3 O 4 (sFe 3 O 4 ) for uniform Li + diffusion and a FWNT web electrode frame that affords characteristics of long-ranged electronic pathways and porous networks. The sFe 3 O 4 particles were used as a model high-capacity energy active material, owing to their well-defined chemistry with surface hydroxyl (-OH) functionalities that provide for facile detection of molecular interactions. PPBT, having a π-conjugated backbone and alkyl side chains substituted with carboxylate moieties, interacted with the FWNT π-electron-rich and hydroxylated sFe 3 O 4 surfaces, which enabled the formation of effective electrical bridges between the respective components, contributing to efficient electron transport and electrode stability. To further induce interactions between PPBT and the metal hydroxide surface, polyethylene glycol was coated onto the sFe 3 O 4 particles, allowing for facile materials dispersion and connectivity. Additionally, the introduction of carbon particles into the web electrode minimized sFe 3 O 4 aggregation and afforded more porous FWNT networks. As a consequence, the design of composite electrodes with rigorous consideration of specific molecular interactions induced by the surface chemistries favorably influenced electrochemical kinetics and electrode resistance, which afforded high-performance electrodes for battery applications.

Effect of Alumina Incorporation on the Surface Mineralization and Degradation of a Bioactive Glass (CaO-MgO-SiO2-Na2O-P2O5-CaF2)-Glycerol Paste

PubMed Central

Abdukayumov, Khasan; Ruzimuradov, Olim; Hojamberdiev, Mirabbos; Riedel, Ralf

2017-01-01

This study investigates the dissolution behavior as well as the surface biomineralization in simulated body fluid (SBF) of a paste composed of glycerol (gly) and a bioactive glass in the system CaO-MgO-SiO2-Na2O-P2O5-CaF2 (BG). The synthesis of the bioactive glass in an alumina crucible has been shown to significantly affect its bioactivity due to the incorporation of aluminum (ca. 1.3–1.4 wt %) into the glass network. Thus, the kinetics of the hydroxyapatite (HA) mineralization on the glass prepared in the alumina crucible was found to be slower than that reported for the same glass composition prepared in a Pt crucible. It is considered that the synthesis conditions lead to the incorporation of small amount of aluminum into the BG network and thus delay the HA mineralization. Interestingly, the BG-gly paste was shown to have significantly higher bioactivity than that of the as-prepared BG. Structural analysis of the paste indicate that glycerol chemically interacts with the glass surface and strongly alter the glass network architecture, thus generating a more depolymerized network, as well as an increased amount of silanol groups at the surface of the glass. In particular, BG-gly paste features early intermediate calcite precipitation during immersion in SBF, followed by hydroxyapatite formation after ca. seven days of SBF exposure; whereas the HA mineralization seems to be suppressed in BG, probably a consequence of the incorporation of aluminum into the glass network. The results obtained within the present study reveal the positive effect of using pastes based on bioactive glasses and organic carriers (here alcohols) which may be of interest not only due to their advantageous visco-elastic properties, but also due to the possibility of enhancing the glass bioactivity upon surface interactions with the organic carrier. PMID:29156541

Walking peptide on Au(110) surface: Origin and nature of interfacial process

NASA Astrophysics Data System (ADS)

Humblot, V.; Tejeda, A.; Landoulsi, J.; Vallée, A.; Naitabdi, A.; Taleb, A.; Pradier, C.-M.

2014-10-01

IGF tri-peptide adsorption on Au(110)-(1 × 2) under Ultra High Vacuum (UHV) conditions has been investigated using surface science techniques such as synchrotron based Angle Resolved X-ray Photoemission Spectroscopy (AR-PES or AR-XPS), Low Energy Electron Diffraction (LEED) and Scanning Tunnelling Microscopy (STM). The behaviour of IGF molecules has been revealed to be coverage dependent; at low coverage, there is formation of islands presenting a chiral self-organised molecular network with a (4 2, - 3 2) symmetry as shown by Low Energy Electron Diffraction (LEED) and Scanning Tunnelling Microscopy (STM) on the unaltered Au(110)-(1 × 2) reconstruction, suggesting significant intermolecular interactions. When the coverage is increased, the islands grow bigger, and one can observe the disappearance of the self-organised network, along with a remarkable destruction of the (1 × 2) substrate reconstruction, as shown by STM. The effect of IGF on the surface gold atoms has been further confirmed by angle-resolved photoemission measurements which suggest a modification of the electronic states with the (1 × 2) symmetry. The resulting molecular organisation, and overall the gold surface disorganisation, prove a strong surface-molecule interaction, which may be probably be explained by a covalent bonding.

An interactive network of elastase, secretases, and PAR-2 protein regulates CXCR1 receptor surface expression on neutrophils.

PubMed

Bakele, Martina; Lotz-Havla, Amelie S; Jakowetz, Anja; Carevic, Melanie; Marcos, Veronica; Muntau, Ania C; Gersting, Soeren W; Hartl, Dominik

2014-07-25

CXCL8 (IL-8) recruits and activates neutrophils through the G protein-coupled chemokine receptor CXCR1. We showed previously that elastase cleaves CXCR1 and thereby impairs antibacterial host defense. However, the molecular intracellular machinery involved in this process remained undefined. Here we demonstrate by using flow cytometry, confocal microscopy, subcellular fractionation, co-immunoprecipitation, and bioluminescence resonance energy transfer that combined α- and γ-secretase activities are functionally involved in elastase-mediated regulation of CXCR1 surface expression on human neutrophils, whereas matrix metalloproteases are dispensable. We further demonstrate that PAR-2 is stored in mobilizable compartments in neutrophils. Bioluminescence resonance energy transfer and co-immunoprecipitation studies showed that secretases, PAR-2, and CXCR1 colocalize and physically interact in a novel protease/secretase-chemokine receptor network. PAR-2 blocking experiments provided evidence that elastase increased intracellular presenilin-1 expression through PAR-2 signaling. When viewed in combination, these studies establish a novel functional network of elastase, secretases, and PAR-2 that regulate CXCR1 expression on neutrophils. Interfering with this network could lead to novel therapeutic approaches in neutrophilic diseases, such as cystic fibrosis or rheumatoid arthritis.

An Interactive Network of Elastase, Secretases, and PAR-2 Protein Regulates CXCR1 Receptor Surface Expression on Neutrophils*

PubMed Central

Bakele, Martina; Lotz-Havla, Amelie S.; Jakowetz, Anja; Carevic, Melanie; Marcos, Veronica; Muntau, Ania C.; Gersting, Soeren W.; Hartl, Dominik

2014-01-01

CXCL8 (IL-8) recruits and activates neutrophils through the G protein-coupled chemokine receptor CXCR1. We showed previously that elastase cleaves CXCR1 and thereby impairs antibacterial host defense. However, the molecular intracellular machinery involved in this process remained undefined. Here we demonstrate by using flow cytometry, confocal microscopy, subcellular fractionation, co-immunoprecipitation, and bioluminescence resonance energy transfer that combined α- and γ-secretase activities are functionally involved in elastase-mediated regulation of CXCR1 surface expression on human neutrophils, whereas matrix metalloproteases are dispensable. We further demonstrate that PAR-2 is stored in mobilizable compartments in neutrophils. Bioluminescence resonance energy transfer and co-immunoprecipitation studies showed that secretases, PAR-2, and CXCR1 colocalize and physically interact in a novel protease/secretase-chemokine receptor network. PAR-2 blocking experiments provided evidence that elastase increased intracellular presenilin-1 expression through PAR-2 signaling. When viewed in combination, these studies establish a novel functional network of elastase, secretases, and PAR-2 that regulate CXCR1 expression on neutrophils. Interfering with this network could lead to novel therapeutic approaches in neutrophilic diseases, such as cystic fibrosis or rheumatoid arthritis. PMID:24914212

Analysis of discontinuities across thin inhomogeneities, groundwater/surface water interactions in river networks, and circulation about slender bodies using slit elements in the Analytic Element Method

USDA-ARS?s Scientific Manuscript database

Groundwater and surface water contain interfaces across which hydrologic functions are discontinuous. Thin elements with high hydraulic conductivity in a porous media focus groundwater, which flows through such inhomogeneities and causes an abrupt change in stream function across their interfaces, a...

Black Holes as Brains: Neural Networks with Area Law Entropy

NASA Astrophysics Data System (ADS)

Dvali, Gia

2018-04-01

Motivated by the potential similarities between the underlying mechanisms of the enhanced memory storage capacity in black holes and in brain networks, we construct an artificial quantum neural network based on gravity-like synaptic connections and a symmetry structure that allows to describe the network in terms of geometry of a d-dimensional space. We show that the network possesses a critical state in which the gapless neurons emerge that appear to inhabit a (d-1)-dimensional surface, with their number given by the surface area. In the excitations of these neurons, the network can store and retrieve an exponentially large number of patterns within an arbitrarily narrow energy gap. The corresponding micro-state entropy of the brain network exhibits an area law. The neural network can be described in terms of a quantum field, via identifying the different neurons with the different momentum modes of the field, while identifying the synaptic connections among the neurons with the interactions among the corresponding momentum modes. Such a mapping allows to attribute a well-defined sense of geometry to an intrinsically non-local system, such as the neural network, and vice versa, it allows to represent the quantum field model as a neural network.

Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

PubMed Central

Engin, H. Billur; Guney, Emre; Keskin, Ozlem; Oliva, Baldo; Gursoy, Attila

2013-01-01

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the “guilt-by-association” principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis. PMID:24278371

Water: a responsive small molecule.

PubMed

Shultz, Mary Jane; Vu, Tuan Hoang; Meyer, Bryce; Bisson, Patrick

2012-01-17

Unique among small molecules, water forms a nearly tetrahedral yet flexible hydrogen-bond network. In addition to its flexibility, this network is dynamic: bonds are formed or broken on a picosecond time scale. These unique features make probing the local structure of water challenging. Despite the challenges, there is intense interest in developing a picture of the local water structure due to water's fundamental importance in many fields of chemistry. Understanding changes in the local network structure of water near solutes likely holds the key to unlock problems from analyzing parameters that determine the three dimensional structure of proteins to modeling the fate of volatile materials released into the atmosphere. Pictures of the local structure of water are heavily influenced by what is known about the structure of ice. In hexagonal I(h) ice, the most stable form of solid water under ordinary conditions, water has an equal number of donor and acceptor bonds; a kind of symmetry. This symmetric tetrahedral coordination is only approximately preserved in the liquid. The most obvious manifestation of this altered tetrahedral bonding is the greater density in the liquid compared with the solid. Formation of an interface or addition of solutes further modifies the local bonding in water. Because the O-H stretching frequency is sensitive to the environment, vibrational spectroscopy provides an excellent probe for the hydrogen-bond structure in water. In this Account, we examine both local interactions between water and small solutes and longer range interactions at the aqueous surface. Locally, the results suggest that water is not a symmetric donor or acceptor, but rather has a propensity to act as an acceptor. In interactions with hydrocarbons, action is centered at the water oxygen. For soluble inorganic salts, interaction is greater with the cation than the anion. The vibrational spectrum of the surface of salt solutions is altered compared with that of neat water. Studies of local salt-water interactions suggest that the picture of the local water structure and the ion distribution at the surface deduced from the surface vibrational spectrum should encompass both ions of the salt.

Interact - Access to the Arctic

NASA Astrophysics Data System (ADS)

Johansson, M.; Callaghan, T. V.

2013-12-01

INTERACT is currently a network of 50 terrestrial research stations from all Arctic countries, but is still growing. The network was inaugurated in January 2011 when it received an EU 7th Framework award. INTERACT's main objective is to build capacity for identifying, understanding, predicting and responding to diverse environmental changes throughout the wide environmental and land-use envelopes of the Arctic. Implicit in this objective is the task to build capacity for monitoring, research, education and outreach. INTERACT is increasing access to the Arctic: 20 INTERACT research stations in Europe and Russia are offering Transnational Access and so far, 5600 person-days of access have been granted from the total of 10,000 offered. An INTERACT Station Managers' Forum facilitates a dialogue among station managers on subjects such as best practice in station management and standardised monitoring. The Station Managers' Forum has produced a unique 'one-stop-shop' for information from 45 research stations in an informative and attractive Station Catalogue that is available in hard copy and on the INTERACT web site (www.eu-interact.org). INTERACT also includes three joint research activities that are improving monitoring in remote, harsh environments and are making data capture and dissemination more efficient. Already, new equipment for measuring feedbacks from the land surface to the climate system has been installed at several locations, while best practices for sensor networking have been established. INTERACT networks with most of the high-level Arctic organisations: it includes AMAP and WWF as partners, is endorsed by IASC and CBMP, has signed MoUs with ISAC and the University of the Arctic, is a task within SAON, and contributes to the Cold Region community within GEO/GEOSS. INTERACT welcomes other interactions.

Microwave plasma induced surface modification of diamond-like carbon films

NASA Astrophysics Data System (ADS)

Rao Polaki, Shyamala; Kumar, Niranjan; Gopala Krishna, Nanda; Madapu, Kishore; Kamruddin, Mohamed; Dash, Sitaram; Tyagi, Ashok Kumar

2017-12-01

Tailoring the surface of diamond-like carbon (DLC) film is technically relevant for altering the physical and chemical properties, desirable for useful applications. A physically smooth and sp3 dominated DLC film with tetrahedral coordination was prepared by plasma-enhanced chemical vapor deposition technique. The surface of the DLC film was exposed to hydrogen, oxygen and nitrogen plasma for physical and chemical modifications. The surface modification was based on the concept of adsorption-desorption of plasma species and surface entities of films. Energetic chemical species of microwave plasma are adsorbed, leading to desorbtion of the surface carbon atoms due to energy and momentum exchange. The interaction of such reactive species with DLC films enhanced the roughness, surface defects and dangling bonds of carbon atoms. Adsorbed hydrogen, oxygen and nitrogen formed a covalent network while saturating the dangling carbon bonds around the tetrahedral sp3 valency. The modified surface chemical affinity depends upon the charge carriers and electron covalency of the adsorbed atoms. The contact angle of chemically reconstructed surface increases when a water droplet interacts either through hydrogen or van dear Waals bonding. These weak interactions influenced the wetting property of the DLC surface to a great extent.

Biomimetic oral mucin from polymer micelle networks

NASA Astrophysics Data System (ADS)

Authimoolam, Sundar Prasanth

Mucin networks are formed by the complexation of bottlebrush-like mucin glycoprotein with other small molecule glycoproteins. These glycoproteins create nanoscale strands that then arrange into a nanoporous mesh. These networks play an important role in ensuring surface hydration, lubricity and barrier protection. In order to understand the functional behavior in mucin networks, it is important to decouple their chemical and physical effects responsible for generating the fundamental property-function relationship. To achieve this goal, we propose to develop a synthetic biomimetic mucin using a layer-by-layer (LBL) deposition approach. In this work, a hierarchical 3-dimensional structures resembling natural mucin networks was generated using affinity-based interactions on synthetic and biological surfaces. Unlike conventional polyelectrolyte-based LBL methods, pre-assembled biotin-functionalized filamentous (worm-like) micelles was utilized as the network building block, which from complementary additions of streptavidin generated synthetic networks of desired thickness. The biomimetic nature in those synthetic networks are studied by evaluating its structural and bio-functional properties. Structurally, synthetic networks formed a nanoporous mesh. The networks demonstrated excellent surface hydration property and were able capable of microbial capture. Those functional properties are akin to that of natural mucin networks. Further, the role of synthetic mucin as a drug delivery vehicle, capable of providing localized and tunable release was demonstrated. By incorporating antibacterial curcumin drug loading within synthetic networks, bacterial growth inhibition was also demonstrated. Thus, such bioactive interfaces can serve as a model for independently characterizing mucin network properties and through its role as a drug carrier vehicle it presents exciting future opportunities for localized drug delivery, in regenerative applications and as bio-functional implant coats. KEYWORDS: Biomimic, Bioapplication, Drug delivery, Filomicelle, Mucin, Polymer networks.

Molecular origins of fluorocarbon hydrophobicity

PubMed Central

Dalvi, Vishwanath H.; Rossky, Peter J.

2010-01-01

We have undertaken atomistic molecular simulations to systematically determine the structural contributions to the hydrophobicity of fluorinated solutes and surfaces compared to the corresponding hydrocarbon, yielding a unified explanation for these phenomena. We have transformed a short chain alkane, n-octane, to n-perfluorooctane in stages. The free-energy changes and the entropic components calculated for each transformation stage yield considerable insight into the relevant physics. To evaluate the effect of a surface, we have also conducted contact-angle simulations of water on self-assembled monolayers of hydrocarbon and fluorocarbon thiols. Our results, which are consistent with experimental observations, indicate that the hydrophobicity of the fluorocarbon, whether the interaction with water is as solute or as surface, is due to its “fatness.” In solution, the extra work of cavity formation to accommodate a fluorocarbon, compared to a hydrocarbon, is not offset by enhanced energetic interactions with water. The enhanced hydrophobicity of fluorinated surfaces arises because fluorocarbons pack less densely on surfaces leading to poorer van der Waals interactions with water. We find that interaction of water with a hydrophobic solute/surface is primarily a function of van der Waals interactions and is substantially independent of electrostatic interactions. This independence is primarily due to the strong tendency of water at room temperature to maintain its hydrogen bonding network structure at an interface lacking hydrophilic sites. PMID:20643968

Is it the shape of the cavity, or the shape of the water in the cavity?

NASA Astrophysics Data System (ADS)

Snyder, Phillip W.; Lockett, Matthew R.; Moustakas, Demetri T.; Whitesides, George M.

2014-04-01

Historical interpretations of the thermodynamics characterizing biomolecular recognition have marginalized the role of water. An important (even, perhaps, dominant) contribution to molecular recognition in water comes from the "hydrophobic effect," in which non-polar portions of a ligand interact preferentially with non-polar regions of a protein. Water surrounds the ligand, and water fills the binding pocket of the protein: when the protein-ligand complex forms, and hydrophobic surfaces of the binding pocket and the ligand approach one another, the molecules (and hydrogen-bonded networks of molecules) of water associated with both surfaces rearrange and, in part, entirely escape into the bulk solution. It is now clear that neither of the two most commonly cited rationalizations for the hydrophobic effect-an entropy-dominated hydrophobic effect, in which ordered waters at the surface of the ligand, and water at the surface of the protein, are released to the bulk upon binding, and a "lock-and-key" model, in which the surface of a ligand interacts directly with a surface of a protein having a complementary shape-can account for water-mediated interactions between the ligand and the protein, and neither is sufficient to account for the experimental observation of both entropy- andenthalpy-dominated hydrophobic effects. What is now clear is that there is no single hydrophobic effect, with a universally applicable, common, thermodynamic description: different processes (i.e., partitioning between phases of different hydrophobicity, aggregation in water, and binding) with different thermodynamics, depend on the molecular-level details of the structures of the molecules involved, and of the aggregates that form. A "water-centric" description of the hydrophobic effect in biomolecular recognition focuses on the structures of water surrounding the ligand, and of water filling the binding pocket of the protein, both before and after binding. This view attributes the hydrophobic effect to changes in the free energy of the networks of hydrogen bonds that are formed, broken, or re-arranged when two hydrophobic surfaces approach (but do not necessarily contact) one another. The details of the molecular topography (and the polar character) of the mole- cular surfaces play an important role in determining the structure of these networks of hydrogen-bonded waters, and in the thermodynamic description of the hydrophobic effect(s). Theorists have led the formulation of this "water-centric view", although experiments are now supplying support for it. It poses complex problems for would-be "designers" of protein-ligand interactions, and for so-called "rational drug design".

Inter-subunit interactions across the upper voltage sensing-pore domain interface contribute to the concerted pore opening transition of Kv channels.

PubMed

Shem-Ad, Tzilhav; Irit, Orr; Yifrach, Ofer

2013-01-01

The tight electro-mechanical coupling between the voltage-sensing and pore domains of Kv channels lies at the heart of their fundamental roles in electrical signaling. Structural data have identified two voltage sensor pore inter-domain interaction surfaces, thus providing a framework to explain the molecular basis for the tight coupling of these domains. While the contribution of the intra-subunit lower domain interface to the electro-mechanical coupling that underlies channel opening is relatively well understood, the contribution of the inter-subunit upper interface to channel gating is not yet clear. Relying on energy perturbation and thermodynamic coupling analyses of tandem-dimeric Shaker Kv channels, we show that mutation of upper interface residues from both sides of the voltage sensor-pore domain interface stabilizes the closed channel state. These mutations, however, do not affect slow inactivation gating. We, moreover, find that upper interface residues form a network of state-dependent interactions that stabilize the open channel state. Finally, we note that the observed residue interaction network does not change during slow inactivation gating. The upper voltage sensing-pore interaction surface thus only undergoes conformational rearrangements during channel activation gating. We suggest that inter-subunit interactions across the upper domain interface mediate allosteric communication between channel subunits that contributes to the concerted nature of the late pore opening transition of Kv channels.

The Pascal Mars Scout Mission

NASA Technical Reports Server (NTRS)

Haberle, R. M.; Fonda, Mark (Technical Monitor)

2002-01-01

Except for Earth, Mars is the planet most amenable to surface-based climate studies. Its surface is accessible, and the kind of observations that are needed, such as meteorological measurements from a long-lived global network, are readily achievable. Weather controls the movement of dust, the exchange of water between the surface and atmosphere, and the cycling of CO2 between the poles. We know there is a weather signal, we know how to measure it, and we know how to interpret it. Pascal seeks to understand the long-term global behavior of near-surface weather systems on Mars, how they interact with its surface, and, therefore, how they control its climate system. To achieve this, Pascal delivers 18 Science Stations to the surface of the planet that operate for three Mars years (5.6 Earth years). The network has stations operating in the tropics, midlatitudes, and polar regions of both hemispheres. During entry, descent, and landing, each Pascal probe acquires deceleration measurements to determine thermal structure, and descent images to characterize local terrain. On the surface, each Science Station takes daily measurements of pressure, opacity, temperature, wind speed, and water vapor concentration and monthly panoramic images of the landing environment. These data will characterize the planet's climate system and how atmosphere-surface interactions control it. The Pascal mission is named after 17th century French Scientist, Blaise Pascal, who pioneered measurements of atmospheric pressure. Pressure is the most critical measurement because it records the "heartbeat" of the planet's general circulation and climate system.

Modeling self-organization of novel organic materials

NASA Astrophysics Data System (ADS)

Sayar, Mehmet

In this thesis, the structural organization of oligomeric multi-block molecules is analyzed by computational analysis of coarse-grained models. These molecules form nanostructures with different dimensionalities, and the nanostructured nature of these materials leads to novel structural properties at different length scales. Previously, a number of oligomeric triblock rodcoil molecules have been shown to self-organize into mushroom shaped noncentrosymmetric nanostructures. Interestingly, thin films of these molecules contain polar domains and a finite macroscopic polarization. However, the fully polarized state is not the equilibrium state. In the first chapter, by solving a model with dipolar and Ising-like short range interactions, we show that polar domains are stable in films composed of aggregates as opposed to isolated molecules. Unlike classical molecular systems, these nanoaggregates have large intralayer spacings (a ≈ 6 nm), leading to a reduction in the repulsive dipolar interactions that oppose polar order within layers. This enables the formation of a striped pattern with polar domains of alternating directions. The energies of the possible structures at zero temperature are computed exactly and results of Monte Carlo simulations are provided at non-zero temperatures. In the second chapter, the macroscopic polarization of such nanostructured films is analyzed in the presence of a short range surface interaction. The surface interaction leads to a periodic domain structure where the balance between the up and down domains is broken, and therefore films of finite thickness have a net macroscopic polarization. The polarization per unit volume is a function of film thickness and strength of the surface interaction. Finally, in chapter three, self-organization of organic molecules into a network of one dimensional objects is analyzed. Multi-block organic dendron rodcoil molecules were found to self-organize into supramolecular nanoribbons (threads) and form gels at very low concentrations. Here, the formation and structural properties of these networks are studied with Monte Carlo simulations. The model gelators can form intra and inter-thread bonds, and the threads have a finite stiffness. The results suggest that the high persistence length is a result of the interplay of thread stiffness and inter-thread interactions. Furthermore, this high persistence length enables the formation of networks at low concentrations.

Supramolecular Interactions in Secondary Plant Cell Walls: Effect of Lignin Chemical Composition Revealed with the Molecular Theory of Solvation.

PubMed

Silveira, Rodrigo L; Stoyanov, Stanislav R; Gusarov, Sergey; Skaf, Munir S; Kovalenko, Andriy

2015-01-02

Plant biomass recalcitrance, a major obstacle to achieving sustainable production of second generation biofuels, arises mainly from the amorphous cell-wall matrix containing lignin and hemicellulose assembled into a complex supramolecular network that coats the cellulose fibrils. We employed the statistical-mechanical, 3D reference interaction site model with the Kovalenko-Hirata closure approximation (or 3D-RISM-KH molecular theory of solvation) to reveal the supramolecular interactions in this network and provide molecular-level insight into the effective lignin-lignin and lignin-hemicellulose thermodynamic interactions. We found that such interactions are hydrophobic and entropy-driven, and arise from the expelling of water from the mutual interaction surfaces. The molecular origin of these interactions is carbohydrate-π and π-π stacking forces, whose strengths are dependent on the lignin chemical composition. Methoxy substituents in the phenyl groups of lignin promote substantial entropic stabilization of the ligno-hemicellulosic matrix. Our results provide a detailed molecular view of the fundamental interactions within the secondary plant cell walls that lead to recalcitrance.

Surface-groundwater interactions in hard rocks in Sardon Catchment of western Spain: An integrated modeling approach

NASA Astrophysics Data System (ADS)

Hassan, S. M. Tanvir; Lubczynski, Maciek W.; Niswonger, Richard G.; Su, Zhongbo

2014-09-01

The structural and hydrological complexity of hard rock systems (HRSs) affects dynamics of surface-groundwater interactions. These complexities are not well described or understood by hydrogeologists because simplified analyses typically are used to study HRSs. A transient, integrated hydrologic model (IHM) GSFLOW (Groundwater and Surface water FLOW) was calibrated and post-audited using 18 years of daily groundwater head and stream discharge data to evaluate the surface-groundwater interactions in semi-arid, ∼80 km2 granitic Sardon hilly catchment in Spain characterized by shallow water table conditions, relatively low storage, dense drainage networks and frequent, high intensity rainfall. The following hydrological observations for the Sardon Catchment, and more generally for HRSs were made: (i) significant bi-directional vertical flows occur between surface water and groundwater throughout the HRSs; (ii) relatively large groundwater recharge represents 16% of precipitation (P, 562 mm.y-1) and large groundwater exfiltration (∼11% of P) results in short groundwater flow paths due to a dense network of streams, low permeability and hilly topographic relief; deep, long groundwater flow paths constitute a smaller component of the water budget (∼1% of P); quite high groundwater evapotranspiration (∼5% of P and ∼7% of total evapotranspiration); low permeability and shallow soils are the main reasons for relatively large components of Hortonian flow and interflow (15% and 11% of P, respectively); (iii) the majority of drainage from the catchment leaves as surface water; (iv) declining 18 years trend (4.44 mm.y-1) of groundwater storage; and (v) large spatio-temporal variability of water fluxes. This IHM study of HRSs provides greater understanding of these relatively unknown hydrologic systems that are widespread throughout the world and are important for water resources in many regions.

[Construction and optimization of ecological network for nature reserves in Fujian Province, China].

PubMed

Gu, Fan; Huang, Yi Xiong; Chen, Chuan Ming; Cheng, Dong Liang; Guo, Jia Lei

2017-03-18

The nature reserve is very important to biodiversity maintenance. However, due to the urbanization, the nature reserve has been fragmented with reduction in area, leading to the loss of species diversity. Establishing ecological network can effectively connect the fragmented habitats and plays an important role in species conversation. In this paper, based on deciding habitat patches and the landscape cost surface in ArcGIS, a minimum cumulative resistance model was used to simulate the potential ecological network of Fujian provincial nature reserves. The connectivity and importance of network were analyzed and evaluated based on comparison of connectivity indices (including the integral index of connectivity and probability of connectivity) and gravity model both before and after the potential ecological network construction. The optimum ecological network optimization measures were proposed. The result demonstrated that woodlands, grasslands and wetlands together made up the important part of the nature reserve ecological network. The habitats with large area had a higher degree of importance in the network. After constructing the network, the connectivity level was significantly improved. Although interaction strength between different patches va-ried greatly, the corridors between patches with large interaction were very important. The research could provide scientific reference and basis for nature protection and planning in Fujian Province.

Selective adsorption of a supramolecular structure on flat and stepped gold surfaces

NASA Astrophysics Data System (ADS)

Peköz, Rengin; Donadio, Davide

2018-04-01

Halogenated aromatic molecules assemble on surfaces forming both hydrogen and halogen bonds. Even though these systems have been intensively studied on flat metal surfaces, high-index vicinal surfaces remain challenging, as they may induce complex adsorbate structures. The adsorption of 2,6-dibromoanthraquinone (2,6-DBAQ) on flat and stepped gold surfaces is studied by means of van der Waals corrected density functional theory. Equilibrium geometries and corresponding adsorption energies are systematically investigated for various different adsorption configurations. It is shown that bridge sites and step edges are the preferred adsorption sites for single molecules on flat and stepped surfaces, respectively. The role of van der Waals interactions, halogen bonds and hydrogen bonds are explored for a monolayer coverage of 2,6-DBAQ molecules, revealing that molecular flexibility and intermolecular interactions stabilize two-dimensional networks on both flat and stepped surfaces. Our results provide a rationale for experimental observation of molecular carpeting on high-index vicinal surfaces of transition metals.

Ground-based Network and Supersite Measurements for Studying Aerosol Properties and Aerosol-Cloud Interactions

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Holben, Brent N.

2008-01-01

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations contain large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. The development and deployment of AERONET (AErosol RObotic NETwork) sunphotometer network and SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile supersite are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To characterize the regional natural and anthropogenic aerosols, AERONET is an internationally federated network of unique sunphotometry that contains more than 250 permanent sites worldwide. Since 1993, there are more than 480 million aerosol optical depth observations and about 15 sites have continuous records longer than 10 years for annual/seasonal trend analyses. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instrument into three categories: flux radiometer, radiance sensor and in-situ probe. Through participation in many satellite remote-sensing/retrieval and validation projects over eight years, SMART-COMMIT have gradually refine( and been proven vital for field deployment. In this paper, we will demonstrate the capability of AERONET SMART-COMMIT in current Asian Monsoon Year-2008 campaigns that are designed and being executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., airborne dust, smoke, mega-city pollutant). Feedback mechanisms between aerosol radiative effects and monsoon dynamics have been recently proposed, however there is a lack of consensus on whether aerosol forcing would be more likely to enhance or reduce the strength of the monsoon circulation. We envision robust approaches which well-collocated ground-based measurements and space-borne observations will greatly advance our understanding of absorbing aerosols (e.g., "Global Dimming" vs. "Elevated Heat-Pump" effects) on aerosol cloud water cycle interactions.

Chemical camouflage: a key process in shaping an ant-treehopper and fig-fig wasp mutualistic network.

PubMed

Wang, Bo; Lu, Min; Cook, James M; Yang, Da-Rong; Dunn, Derek W; Wang, Rui-Wu

2018-01-30

Different types of mutualisms may interact, co-evolve and form complex networks of interdependences, but how species interact in networks of a mutualistic community and maintain its stability remains unclear. In a mutualistic network between treehoppers-weaver ants and fig-pollinating wasps, we found that the cuticular hydrocarbons of the treehoppers are more similar to the surface chemical profiles of fig inflorescence branches (FIB) than the cuticular hydrocarbons of the fig wasps. Behavioral assays showed that the cuticular hydrocarbons from both treehoppers and FIBs reduce the propensity of weaver ants to attack treehoppers even in the absence of honeydew rewards, suggesting that chemical camouflage helps enforce the mutualism between weaver ants and treehoppers. High levels of weaver ant and treehopper abundances help maintain the dominance of pollinating fig wasps in the fig wasp community and also increase fig seed production, as a result of discriminative predation and disturbance by weaver ants of ovipositing non-pollinating fig wasps (NPFWs). Ants therefore help preserve this fig-pollinating wasp mutualism from over exploitation by NPFWs. Our results imply that in this mutualistic network chemical camouflage plays a decisive role in regulating the behavior of a key species and indirectly shaping the architecture of complex arthropod-plant interactions.

Networks within networks: floods, droughts, and the assembly of algal-based food webs in a Mediterranean river

NASA Astrophysics Data System (ADS)

Power, M. E.; Limm, M.; Finlay, J. C.; Welter, J.; Furey, P.; Lowe, R.; Hondzo, M.; Dietrich, W. E.; Bode, C. A.; National CenterEarth Surface Dynamics

2011-12-01

Riverine biota live within several networks. Organisms are embedded in food webs, whose structure and dynamics respond to environmental changes down river drainages. In sunlit rivers, food webs are fueled by attached algae. Primary producer biomass in the Eel River of Northwestern California, as in many sunlit, temperate rivers worldwide, is dominated by the macroalga Cladophora, which grows as a hierarchical, branched network. Cladophora proliferations vastly amplify the ecological surface area and the diversity microhabitats available to microbes. Environmental conditions (light, substrate age or stability, flow, redox gradients) change in partially predictable ways along both Cladophora fronds and river drainage networks, from the frond tips (or headwaters) to their base (or river mouth). We are interested in the ecological and biogeochemical consequences, at the catchment scale, of cross-scale interactions of microbial food webs on Cladophora with macro-organismal food webs, as these change down river drainages. We are beginning to explore how seasonal, hydrologic and macro-consumer control over the production and fate of Cladophora and its epiphytes could mediate ecosystem linkages of the river, its watershed, and nearshore marine ecosystems. Of the four interacting networks we consider, the web of microbial interactions is the most poorly known, and possibly the least hierarchical due to the prevalence of metabolic processing chains (waste products of some members become resources for others) and mutualisms.

The study of intermolecular interactions in NLO crystal melaminium chloride hemihydrate using DFT simulation and Hirshfeld surface analysis

NASA Astrophysics Data System (ADS)

Sangeetha, K.; Kumar, V. R. Suresh; Marchewka, M. K.; Binoy, J.

2018-05-01

Since, the intermolecular interactions play a crucial role in the formation of crystalline network, its analysis throws light on structure dependent crystalline properties. In the present study, DFT based vibrational spectral investigation has been performed in the stretching region (3500 cm-1 - 2800 cm-1) of IR and Raman spectra of melaminium chloride hemihydrates. The intermolecular interaction has been investigated by analyzing the half width of the OH and NH stretching profile of the deconvoluted spectra. Correlation of vibrational spectra with Hirshfeld surface analysis and finger print plot has been contemplated and molecular docking studies has been performed on melaminium chloride hemihydrate to assess its role in the drug transport mechanism and toxicity to human body.

Confinement properties of 2D porous molecular networks on metal surfaces

NASA Astrophysics Data System (ADS)

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-04-01

Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article.

Confinement properties of 2D porous molecular networks on metal surfaces.

PubMed

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-04-20

Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article.

Predicting wettability behavior of fluorosilica coated metal surface using optimum neural network

NASA Astrophysics Data System (ADS)

Taghipour-Gorjikolaie, Mehran; Valipour Motlagh, Naser

2018-02-01

The interaction between variables, which are effective on the surface wettability, is very complex to predict the contact angles and sliding angles of liquid drops. In this paper, in order to solve this complexity, artificial neural network was used to develop reliable models for predicting the angles of liquid drops. Experimental data are divided into training data and testing data. By using training data and feed forward structure for the neural network and using particle swarm optimization for training the neural network based models, the optimum models were developed. The obtained results showed that regression index for the proposed models for the contact angles and sliding angles are 0.9874 and 0.9920, respectively. As it can be seen, these values are close to unit and it means the reliable performance of the models. Also, it can be inferred from the results that the proposed model have more reliable performance than multi-layer perceptron and radial basis function based models.

Effects of spatial configuration of imperviousness and green infrastructure networks on hydrologic response in a residential sewershed

NASA Astrophysics Data System (ADS)

Lim, Theodore C.; Welty, Claire

2017-09-01

Green infrastructure (GI) is an approach to stormwater management that promotes natural processes of infiltration and evapotranspiration, reducing surface runoff to conventional stormwater drainage infrastructure. As more urban areas incorporate GI into their stormwater management plans, greater understanding is needed on the effects of spatial configuration of GI networks on hydrological performance, especially in the context of potential subsurface and lateral interactions between distributed facilities. In this research, we apply a three-dimensional, coupled surface-subsurface, land-atmosphere model, ParFlow.CLM, to a residential urban sewershed in Washington DC that was retrofitted with a network of GI installations between 2009 and 2015. The model was used to test nine additional GI and imperviousness spatial network configurations for the site and was compared with monitored pipe-flow data. Results from the simulations show that GI located in higher flow-accumulation areas of the site intercepted more surface runoff, even during wetter and multiday events. However, a comparison of the differences between scenarios and levels of variation and noise in monitored data suggests that the differences would only be detectable between the most and least optimal GI/imperviousness configurations.

Multi-scale Quantitative Precipitation Forecasting Using Nonlinear and Nonstationary Teleconnection Signals and Artificial Neural Network Models

EPA Science Inventory

Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals...

Chemistry of anthracene-acetylene oligomers XXV: on-surface chirality of a self-assembled molecular network of a fan-blade-shaped anthracene-acetylene macrocycle with a long alkyl chain.

PubMed

Tsuya, Takuya; Iritani, Kohei; Tahara, Kazukuni; Tobe, Yoshito; Iwanaga, Tetsuo; Toyota, Shinji

2015-03-27

An anthracene cyclic dimer with two different linkers and a dodecyl group was synthesized by means of coupling reactions. The calculated structure had a planar macrocyclic π core and a linear alkyl chain. Scanning tunneling microscopy observations at the 1-phenyloctane/graphite interface revealed that the molecules formed a self-assembled monolayer that consisted of linear striped bright and dark bands. In each domain, the molecular network consisted of either Re or Si molecules that differed in the two-dimensional chirality about the macrocyclic faces, which led to a unique conglomerate-type self-assembly. The molecular packing mode and the conformation of the alkyl chains are discussed in terms of the intermolecular interactions and the interactions between the molecules and the graphite surface with the aid of MM3 simulations of a model system. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Distinct Adsorption Configurations and Self-Assembly Characteristics of Fibrinogen on Chemically Uniform and Alternating Surfaces including Block Copolymer Nanodomains

PubMed Central

2015-01-01

Understanding protein–surface interactions is crucial to solid-state biomedical applications whose functionality is directly correlated with the precise control of the adsorption configuration, surface packing, loading density, and bioactivity of protein molecules. Because of the small dimensions and highly amphiphilic nature of proteins, investigation of protein adsorption performed on nanoscale topology can shed light on subprotein-level interaction preferences. In this study, we examine the adsorption and assembly behavior of a highly elongated protein, fibrinogen, on both chemically uniform (as-is and buffered HF-treated SiO2/Si, and homopolymers of polystyrene and poly(methyl methacrylate)) and varying (polystyrene-block-poly(methyl methacrylate)) surfaces. By focusing on high-resolution imaging of individual protein molecules whose configurations are influenced by protein–surface rather than protein–protein interactions, fibrinogen conformations characteristic to each surface are identified and statistically analyzed for structural similarities/differences in key protein domains. By exploiting block copolymer nanodomains whose repeat distance is commensurate with the length of the individual protein, we determine that fibrinogen exhibits a more neutral tendency for interaction with both polystyrene and poly(methyl methacrylate) blocks relative to the case of common globular proteins. Factors affecting fibrinogen–polymer interactions are discussed in terms of hydrophobic and electrostatic interactions. In addition, assembly and packing attributes of fibrinogen are determined at different loading conditions. Primary orientations of fibrinogen and its rearrangements with respect to the underlying diblock nanodomains associated with different surface coverage are explained by pertinent protein interaction mechanisms. On the basis of two-dimensional stacking behavior, a protein assembly model is proposed for the formation of an extended fibrinogen network on the diblock copolymer. PMID:24708538

Hydrophobic-Interaction-Induced Stiffening of α -Synuclein Fibril Networks

NASA Astrophysics Data System (ADS)

Semerdzhiev, Slav A.; Lindhoud, Saskia; Stefanovic, Anja; Subramaniam, Vinod; van der Schoot, Paul; Claessens, Mireille M. A. E.

2018-05-01

In water, networks of semiflexible fibrils of the protein α -synuclein stiffen significantly with increasing temperature. We make plausible that this reversible stiffening is a result of hydrophobic contacts between the fibrils that become more prominent with increasing temperature. The good agreement of our experimentally observed temperature dependence of the storage modulus of the network with a scaling theory linking network elasticity with reversible cross-linking enables us to quantify the endothermic binding enthalpy and estimate the effective size of hydrophobic patches on the fibril surface. Our findings may not only shed light on the role of amyloid deposits in disease conditions, but can also inspire new approaches for the design of thermoresponsive materials.

Hydrophobic-Interaction-Induced Stiffening of α-Synuclein Fibril Networks.

PubMed

Semerdzhiev, Slav A; Lindhoud, Saskia; Stefanovic, Anja; Subramaniam, Vinod; van der Schoot, Paul; Claessens, Mireille M A E

2018-05-18

In water, networks of semiflexible fibrils of the protein α-synuclein stiffen significantly with increasing temperature. We make plausible that this reversible stiffening is a result of hydrophobic contacts between the fibrils that become more prominent with increasing temperature. The good agreement of our experimentally observed temperature dependence of the storage modulus of the network with a scaling theory linking network elasticity with reversible cross-linking enables us to quantify the endothermic binding enthalpy and estimate the effective size of hydrophobic patches on the fibril surface. Our findings may not only shed light on the role of amyloid deposits in disease conditions, but can also inspire new approaches for the design of thermoresponsive materials.

Streamflow simulation for continental-scale river basins

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Lettenmaier, Dennis P.; Liang, Xu; Wetzel, Suzanne W.; Wood, Eric F.

1997-04-01

A grid network version of the two-layer variable infiltration capacity (VIC-2L) macroscale hydrologic model is described. VIC-2L is a hydrologically based soil- vegetation-atmosphere transfer scheme designed to represent the land surface in numerical weather prediction and climate models. The grid network scheme allows streamflow to be predicted for large continental rivers. Off-line (observed and estimated surface meteorological and radiative forcings) applications of the model to the Columbia River (1° latitude-longitude spatial resolution) and Delaware River (0.5° resolution) are described. The model performed quite well in both applications, reproducing the seasonal hydrograph and annual flow volumes to within a few percent. Difficulties in reproducing observed streamflow in the arid portion of the Snake River basin are attributed to groundwater-surface water interactions, which are not modeled by VIC-2L.

Digital map and situation surface: a team-oriented multidisplay workspace for network enabled situation analysis

NASA Astrophysics Data System (ADS)

Peinsipp-Byma, E.; Geisler, Jürgen; Bader, Thomas

2009-05-01

System concepts for network enabled image-based ISR (intelligence, surveillance, reconnaissance) is the major mission of Fraunhofer IITB's applied research in the area of defence and security solutions. For the TechDemo08 as part of the NATO CNAD POW Defence against terrorism Fraunhofer IITB advanced a new multi display concept to handle the shear amount and high complexity of ISR data acquired by networked, distributed surveillance systems with the objective to support the generation of a common situation picture. Amount and Complexity of ISR data demands an innovative man-machine interface concept for humans to deal with it. The IITB's concept is the Digital Map & Situation Surface. This concept offers to the user a coherent multi display environment combining a horizontal surface for the situation overview from the bird's eye view, an attached vertical display for collateral information and so-called foveatablets as personalized magic lenses in order to obtain high resolved and role-specific information about a focused areaof- interest and to interact with it. In the context of TechDemo08 the Digital Map & Situation Surface served as workspace for team-based situation visualization and analysis. Multiple sea- and landside surveillance components were connected to the system.

Spatially-Interactive Biomolecular Networks Organized by Nucleic Acid Nanostructures

PubMed Central

Fu, Jinglin; Liu, Minghui; Liu, Yan; Yan, Hao

2013-01-01

Conspectus Living systems have evolved a variety of nanostructures to control the molecular interactions that mediate many functions including the recognition of targets by receptors, the binding of enzymes to substrates, and the regulation of enzymatic activity. Mimicking these structures outside of the cell requires methods that offer nanoscale control over the organization of individual network components. Advances in DNA nanotechnology have enabled the design and fabrication of sophisticated one-, two- and three-dimensional (1D, 2D and 3D) nanostructures that utilize spontaneous and sequence specific DNA hybridization. Compared to other self-assembling biopolymers, DNA nanostructures offer predictable and programmable interactions, and surface features to which other nanoparticles and bio-molecules can be precisely positioned. The ability to control the spatial arrangement of the components while constructing highly-organized networks will lead to various applications of these systems. For example, DNA nanoarrays with surface displays of molecular probes can sense noncovalent hybridization interactions with DNA, RNA, and proteins and covalent chemical reactions. DNA nanostructures can also align external molecules into well-defined arrays, which may improve the resolution of many structural determination methods, such as X-ray diffraction, cryo-EM, NMR, and super-resolution fluorescence. Moreover, by constraining target entities to specific conformations, self-assembled DNA nanostructures can serve as molecular rulers to evaluate conformation-dependent activities. This Account describes the most recent advances in the DNA nanostructure directed assembly of biomolecular networks and explores the possibility of applying this technology to other fields of study. Recently, several reports have demonstrated the DNA nanostructure directed assembly of spatially-interactive biomolecular networks. For example, researchers have constructed synthetic multi-enzyme cascades by organizing the position of the components using DNA nanoscaffolds in vitro, or by utilizing RNA matrices in vivo. These structures display enhanced efficiency compared to the corresponding unstructured enzyme mixtures. Such systems are designed to mimic cellular function, where substrate diffusion between enzymes is facilitated and reactions are catalyzed with high efficiency and specificity. In addition, researchers have assembled multiple choromophores into arrays using a DNA nanoscaffold that optimizes the relative distance between the dyes and their spatial organization. The resulting artificial light harvesting system exhibits efficient cascading energy transfers. Finally, DNA nanostructures have been used as assembly templates to construct nanodevices that execute rationally-designed behaviors, including cargo loading, transportation and route control. PMID:22642503

Calving seismicity from iceberg-sea surface interactions

USGS Publications Warehouse

Bartholomaus, T.C.; Larsen, C.F.; O'Neel, S.; West, M.E.

2012-01-01

Iceberg calving is known to release substantial seismic energy, but little is known about the specific mechanisms that produce calving icequakes. At Yahtse Glacier, a tidewater glacier on the Gulf of Alaska, we draw upon a local network of seismometers and focus on 80 hours of concurrent, direct observation of the terminus to show that calving is the dominant source of seismicity. To elucidate seismogenic mechanisms, we synchronized video and seismograms to reveal that the majority of seismic energy is produced during iceberg interactions with the sea surface. Icequake peak amplitudes coincide with the emergence of high velocity jets of water and ice from the fjord after the complete submergence of falling icebergs below sea level. These icequakes have dominant frequencies between 1 and 3 Hz. Detachment of an iceberg from the terminus produces comparatively weak seismic waves at frequencies between 5 and 20 Hz. Our observations allow us to suggest that the most powerful sources of calving icequakes at Yahtse Glacier include iceberg-sea surface impact, deceleration under the influence of drag and buoyancy, and cavitation. Numerical simulations of seismogenesis during iceberg-sea surface interactions support our observational evidence. Our new understanding of iceberg-sea surface interactions allows us to reattribute the sources of calving seismicity identified in earlier studies and offer guidance for the future use of seismology in monitoring iceberg calving.

Inferring topological features of proteins from amino acid residue networks

NASA Astrophysics Data System (ADS)

Alves, Nelson Augusto; Martinez, Alexandre Souto

2007-02-01

Topological properties of native folds are obtained from statistical analysis of 160 low homology proteins covering the four structural classes. This is done analyzing one, two and three-vertex joint distribution of quantities related to the corresponding network of amino acid residues. Emphasis on the amino acid residue hydrophobicity leads to the definition of their center of mass as vertices in this contact network model with interactions represented by edges. The network analysis helps us to interpret experimental results such as hydrophobic scales and fraction of buried accessible surface area in terms of the network connectivity. Moreover, those networks show assortative mixing by degree. To explore the vertex-type dependent correlations, we build a network of hydrophobic and polar vertices. This procedure presents the wiring diagram of the topological structure of globular proteins leading to the following attachment probabilities between hydrophobic-hydrophobic 0.424(5), hydrophobic-polar 0.419(2) and polar-polar 0.157(3) residues.

Highly viscous antibody solutions are a consequence of network formation caused by domain-domain electrostatic complementarities: insights from coarse-grained simulations.

PubMed

Buck, Patrick M; Chaudhri, Anuj; Kumar, Sandeep; Singh, Satish K

2015-01-05

Therapeutic monoclonal antibody (mAb) candidates that form highly viscous solutions at concentrations above 100 mg/mL can lead to challenges in bioprocessing, formulation development, and subcutaneous drug delivery. Earlier studies of mAbs with concentration-dependent high viscosity have indicated that mAbs with negatively charged Fv regions have a dipole-like quality that increases the likelihood of reversible self-association. This suggests that weak electrostatic intermolecular interactions can form transient antibody networks that participate in resistance to solution deformation under shear stress. Here this hypothesis is explored by parametrizing a coarse-grained (CG) model of an antibody using the domain charges from four different mAbs that have had their concentration-dependent viscosity behaviors previously determined. Multicopy molecular dynamics simulations were performed for these four CG mAbs at several concentrations to understand the effect of surface charge on mass diffusivity, pairwise interactions, and electrostatic network formation. Diffusion coefficients computed from simulations were in qualitative agreement with experimentally determined viscosities for all four mAbs. Contact analysis revealed an overall greater number of pairwise interactions for the two mAbs in this study with high concentration viscosity issues. Further, using equilibrated solution trajectories, the two mAbs with high concentration viscosity issues quantitatively formed more features of an electrostatic network than the other mAbs. The change in the number of these network features as a function of concentration is related to the number of pairwise interactions formed by electrostatic complementarities between antibody domains. Thus, transient antibody network formation caused by domain-domain electrostatic complementarities is the most probable origin of high concentration viscosity for mAbs in this study.

The Interaction between Heterotrophic Bacteria and Coliform, Fecal Coliform, Fecal Streptococci Bacteria in the Water Supply Networks.

PubMed

Amanidaz, Nazak; Zafarzadeh, Ali; Mahvi, Amir Hossein

2015-12-01

This study investigated the interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in water supply networks. This study was conducted during 2013 on water supply distribution network in Aq Qala City, Golestan Province, Northern Iran and standard methods were applied for microbiological analysis. The surface method was applied to test the heterotrophic bacteria and MPN method was used for coliform, fecal coliform and fecal streptococci bacteria measurements. In 114 samples, heterotrophic bacteria count were over 500 CFU/ml, which the amount of fecal coliform, coliform, and fecal streptococci were 8, 32, and 20 CFU/100 ml, respectively. However, in the other 242 samples, with heterotrophic bacteria count being less than 500 CFU/ml, the amount of fecal coliform, coliform, and fecal streptococci was 7, 23, and 11 CFU/100ml, respectively. The relationship between heterotrophic bacteria, coliforms and fecal streptococci was highly significant (P<0.05). We observed the concentration of coliforms, fecal streptococci bacteria being high, whenever the concentration of heterotrophic bacteria in the water network systems was high. Interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in the Aq Qala City water supply networks was not notable. It can be due to high concentrations of organic carbon, bio-films and nutrients, which are necessary for growth, and survival of all microorganisms.

The Interaction between Heterotrophic Bacteria and Coliform, Fecal Coliform, Fecal Streptococci Bacteria in the Water Supply Networks

PubMed Central

AMANIDAZ, Nazak; ZAFARZADEH, Ali; MAHVI, Amir Hossein

2015-01-01

Background: This study investigated the interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in water supply networks. Methods: This study was conducted during 2013 on water supply distribution network in Aq Qala City, Golestan Province, Northern Iran and standard methods were applied for microbiological analysis. The surface method was applied to test the heterotrophic bacteria and MPN method was used for coliform, fecal coliform and fecal streptococci bacteria measurements. Results: In 114 samples, heterotrophic bacteria count were over 500 CFU/ml, which the amount of fecal coliform, coliform, and fecal streptococci were 8, 32, and 20 CFU/100 ml, respectively. However, in the other 242 samples, with heterotrophic bacteria count being less than 500 CFU/ml, the amount of fecal coliform, coliform, and fecal streptococci was 7, 23, and 11 CFU/100ml, respectively. The relationship between heterotrophic bacteria, coliforms and fecal streptococci was highly significant (P<0.05). We observed the concentration of coliforms, fecal streptococci bacteria being high, whenever the concentration of heterotrophic bacteria in the water network systems was high. Conclusion: Interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in the Aq Qala City water supply networks was not notable. It can be due to high concentrations of organic carbon, bio-films and nutrients, which are necessary for growth, and survival of all microorganisms. PMID:26811820

A novel approach to model dynamic flow interactions between storm sewer system and overland surface for different land covers in urban areas

NASA Astrophysics Data System (ADS)

Chang, Tsang-Jung; Wang, Chia-Ho; Chen, Albert S.

2015-05-01

In this study, we developed a novel approach to simulate dynamic flow interactions between storm sewers and overland surface for different land covers in urban areas. The proposed approach couples the one-dimensional (1D) sewer flow model (SFM) and the two-dimensional (2D) overland flow model (OFM) with different techniques depending on the land cover type of the study areas. For roads, pavements, plazas, and so forth where rainfall becomes surface runoff before entering the sewer system, the rainfall-runoff process is simulated directly in the 2D OFM, and the runoff is drained to the sewer network via inlets, which is regarded as the input to 1D SFM. For green areas on which rainfall falls into the permeable ground surface and the generated direct runoff traverses terrain, the deduction rate is applied to the rainfall for reflecting the soil infiltration in the 2D OFM. For flat building roofs with drainage facilities allowing rainfall to drain directly from the roof to sewer networks, the rainfall-runoff process is simulated using the hydrological module in the 1D SFM where no rainfall is applied to these areas in the 2D OFM. The 1D SFM is used for hydraulic simulations in the sewer network. Where the flow in the drainage network exceeds its capacity, a surcharge occurs and water may spill onto the ground surface if the pressure head in a manhole exceeds the ground elevation. The overflow discharge from the sewer system is calculated by the 1D SFM and considered a point source in the 2D OFM. The overland flow will return into the sewer network when it reaches an inlet that connects to an un-surcharged manhole. In this case, the inlet is considered as a point sink in the 2D OFM and an inflow to a manhole in the 1D SFM. The proposed approach was compared to other five urban flood modelling techniques with four rainfall events that had previously recorded inundation areas. The merits and drawbacks of each modelling technique were compared and discussed. Based on the simulated results, the proposed approach was found to simulate floodings closer to the survey records than other approaches because the physical rainfall-runoff phenomena in urban environment were better reflected.

Metal adatoms generated by the co-play of melamine assembly and subsequent CO adsorption.

PubMed

Wang, Li; Chen, Qiwei; Shi, Hong; Liu, Huihui; Ren, Xinguo; Wang, Bing; Wu, Kai; Shao, Xiang

2016-01-28

Molecular self-assembly films are expected to tailor the surface process by the periodic nanostructures and add-on functional groups. In this work, a molecular network of melamine with featured pores of subnanometer size is prepared on the Au(111) surface, and is found to be able to trap the gold adatoms and concomitant single vacancies generated under the impingement of CO molecules at room temperature. DFT calculations suggest that the strong CO-Au adatom interaction as well as the high adhesion of the Au adatom inside the melamine pore could well be the driving force behind such process. This study not only sheds light onto the interactions between gasses and the metal surface that is covered by molecular self-assembly films, but also provides a novel route to manipulate the monoatomic surface species which is of catalytic interest.

Hydration of excess electrons trapped in charge pockets on molecular surfaces

NASA Astrophysics Data System (ADS)

Jalbout, Abraham F.; Del Castillo, R.; Adamowicz, Ludwik

2007-01-01

In this work we strive to design a novel electron trap located on a molecular surface. The process of electron trapping involves hydration of the trapped electron. Previous calculations on surface electron trapping revealed that clusters of OH groups can form stable hydrogen-bonded networks on one side of a hydrocarbon surface (i.e. cyclohexane sheets), while the hydrogen atoms on the opposite side of the surface form pockets of positive charge that can attract extra negative charge. The excess electron density on such surfaces can be further stabilized by interactions with water molecules. Our calculations show that these anionic systems are stable with respect to vertical electron detachment (VDE).

Adsorption of guanidinium collectors on aluminosilicate minerals - a density functional study.

PubMed

Nulakani, Naga Venkateswara Rao; Baskar, Prathab; Patra, Abhay Shankar; Subramanian, Venkatesan

2015-10-07

In this density functional theory based investigation, we have modelled and studied the adsorption behaviour of guanidinium cations and substituted (phenyl, methoxy phenyl, nitro phenyl and di-nitro phenyl) guanidinium cationic collectors on the basal surfaces of kaolinite and goethite. The adsorption behaviour is assessed in three different media, such as gas, explicit water and pH medium, to understand the affinity of GC collectors to the SiO4 tetrahedral and AlO6 octahedral surfaces of kaolinite. The tetrahedral siloxane surface possesses a larger binding affinity to GC collectors than the octahedral sites due to the presence of surface exposed oxygen atoms that are active in the intermolecular interactions. Furthermore, the inductive electronic effects of substituted guanidinium cations also play a key role in the adsorption mechanism. Highly positive cations result in a stronger electrostatic interaction and preferential adsorption with the kaolinite surfaces than low positive cations. Computed interaction energies and electron densities at the bond critical points suggest that the adsorption of guanidinium cations on the surfaces of kaolinite and goethite is due to the formation of intra/inter hydrogen bonding networks. Also, the electrostatic interaction favours the high adsorption ability of GC collectors in the pH medium than gas phase and water medium. The structures and energies of GC collectors pave an intuitive view for future experimental studies on mineral flotation.

Evaluation of Deep Learning Models for Predicting CO2 Flux

NASA Astrophysics Data System (ADS)

Halem, M.; Nguyen, P.; Frankel, D.

2017-12-01

Artificial neural networks have been employed to calculate surface flux measurements from station data because they are able to fit highly nonlinear relations between input and output variables without knowing the detail relationships between the variables. However, the accuracy in performing neural net estimates of CO2 flux from observations of CO2 and other atmospheric variables is influenced by the architecture of the neural model, the availability, and complexity of interactions between physical variables such as wind, temperature, and indirect variables like latent heat, and sensible heat, etc. We evaluate two deep learning models, feed forward and recurrent neural network models to learn how they each respond to the physical measurements, time dependency of the measurements of CO2 concentration, humidity, pressure, temperature, wind speed etc. for predicting the CO2 flux. In this paper, we focus on a) building neural network models for estimating CO2 flux based on DOE data from tower Atmospheric Radiation Measurement data; b) evaluating the impact of choosing the surface variables and model hyper-parameters on the accuracy and predictions of surface flux; c) assessing the applicability of the neural network models on estimate CO2 flux by using OCO-2 satellite data; d) studying the efficiency of using GPU-acceleration for neural network performance using IBM Power AI deep learning software and packages on IBM Minsky system.

Molecular energy dissipation in nanoscale networks of dentin matrix protein 1 is strongly dependent on ion valence

NASA Astrophysics Data System (ADS)

Adams, J.; Fantner, G. E.; Fisher, L. W.; Hansma, P. K.

2008-09-01

The fracture resistance of biomineralized tissues such as bone, dentin, and abalone is greatly enhanced through the nanoscale interactions of stiff inorganic mineral components with soft organic adhesive components. A proper understanding of the interactions that occur within the organic component, and between the organic and inorganic components, is therefore critical for a complete understanding of the mechanics of these tissues. In this paper, we use atomic force microscope (AFM) force spectroscopy and dynamic force spectroscopy to explore the effect of ionic interactions within a nanoscale system consisting of networks of dentin matrix protein 1 (DMP1) (a component of both bone and dentin organic matrix), a mica surface and an AFM tip. We find that DMP1 is capable of dissipating large amounts of energy through an ion-mediated mechanism, and that the effectiveness increases with increasing ion valence.

Mesoporous gold sponges: electric charge-assisted seed mediated synthesis and application as surface-enhanced Raman scattering substrates

NASA Astrophysics Data System (ADS)

Yi, Zao; Luo, Jiangshan; Tan, Xiulan; Yi, Yong; Yao, Weitang; Kang, Xiaoli; Ye, Xin; Zhu, Wenkun; Duan, Tao; Yi, Yougen; Tang, Yongjian

2015-11-01

Mesoporous gold sponges were prepared using 4-dimethylaminopyridine (DMAP)-stabilized Au seeds. This is a general process, which involves a simple template-free method, room temperature reduction of HAuCl4·4H2O with hydroxylamine. The formation process of mesoporous gold sponges could be accounted for the electrostatic interaction (the small Au nanoparticles (~3 nm) and the positively charged DMAP-stabilized Au seeds) and Ostwald ripening process. The mesoporous gold sponges had appeared to undergo electrostatic adsorption initially, sequentially linear aggregation, welding and Ostwald ripening, then, they randomly cross link into self-supporting, three-dimensional networks with time. The mesoporous gold sponges exhibit higher surface area than the literature. In addition, application of the spongelike networks as an active material for surface-enhanced Raman scattering has been investigated by employing 4-aminothiophenol (4-ATP) molecules as a probe.

Mesoporous gold sponges: electric charge-assisted seed mediated synthesis and application as surface-enhanced Raman scattering substrates

PubMed Central

Yi, Zao; Luo, Jiangshan; Tan, Xiulan; Yi, Yong; Yao, Weitang; Kang, Xiaoli; Ye, Xin; Zhu, Wenkun; Duan, Tao; Yi, Yougen; Tang, Yongjian

2015-01-01

Mesoporous gold sponges were prepared using 4-dimethylaminopyridine (DMAP)-stabilized Au seeds. This is a general process, which involves a simple template-free method, room temperature reduction of HAuCl4·4H2O with hydroxylamine. The formation process of mesoporous gold sponges could be accounted for the electrostatic interaction (the small Au nanoparticles (~3 nm) and the positively charged DMAP-stabilized Au seeds) and Ostwald ripening process. The mesoporous gold sponges had appeared to undergo electrostatic adsorption initially, sequentially linear aggregation, welding and Ostwald ripening, then, they randomly cross link into self-supporting, three-dimensional networks with time. The mesoporous gold sponges exhibit higher surface area than the literature. In addition, application of the spongelike networks as an active material for surface-enhanced Raman scattering has been investigated by employing 4-aminothiophenol (4-ATP) molecules as a probe. PMID:26538365

Rapid molecular evolution across amniotes of the IIS/TOR network

PubMed Central

McGaugh, Suzanne E.; Bronikowski, Anne M.; Kuo, Chih-Horng; Reding, Dawn M.; Addis, Elizabeth A.; Flagel, Lex E.; Janzen, Fredric J.

2015-01-01

The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades. PMID:25991861

Rapid molecular evolution across amniotes of the IIS/TOR network.

PubMed

McGaugh, Suzanne E; Bronikowski, Anne M; Kuo, Chih-Horng; Reding, Dawn M; Addis, Elizabeth A; Flagel, Lex E; Janzen, Fredric J; Schwartz, Tonia S

2015-06-02

The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades.

Tensegrity II. How structural networks influence cellular information processing networks

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein

PubMed Central

Quinlan, Devin S.; Raman, Rahul; Tharakaraman, Kannan; Subramanian, Vidya; del Hierro, Gabriella; Sasisekharan, Ram

2017-01-01

Recently, progress has been made in the development of vaccines and monoclonal antibody cocktails that target the Ebola coat glycoprotein (GP). Based on the mutation rates for Ebola virus given its natural sequence evolution, these treatment strategies are likely to impose additional selection pressure to drive acquisition of mutations in GP that escape neutralization. Given the high degree of sequence conservation among GP of Ebola viruses, it would be challenging to determine the propensity of acquiring mutations in response to vaccine or treatment with one or a cocktail of monoclonal antibodies. In this study, we analyzed the mutability of each residue using an approach that captures the structural constraints on mutability based on the extent of its inter-residue interaction network within the three-dimensional structure of the trimeric GP. This analysis showed two distinct clusters of highly networked residues along the GP1-GP2 interface, part of which overlapped with epitope surfaces of known neutralizing antibodies. This network approach also permitted us to identify additional residues in the network of the known hotspot residues of different anti-Ebola antibodies that would impact antibody-epitope interactions. PMID:28397835

Conformational Heterogeneity of the HIV Envelope Glycan Shield.

PubMed

Yang, Mingjun; Huang, Jing; Simon, Raphael; Wang, Lai-Xi; MacKerell, Alexander D

2017-06-30

To better understand the conformational properties of the glycan shield covering the surface of the HIV gp120/gp41 envelope (Env) trimer, and how the glycan shield impacts the accessibility of the underlying protein surface, we performed enhanced sampling molecular dynamics (MD) simulations of a model glycosylated HIV Env protein and related systems. Our simulation studies revealed a conformationally heterogeneous glycan shield with a network of glycan-glycan interactions more extensive than those observed to date. We found that partial preorganization of the glycans potentially favors binding by established broadly neutralizing antibodies; omission of several specific glycans could increase the accessibility of other glycans or regions of the protein surface to antibody or CD4 receptor binding; the number of glycans that can potentially interact with known antibodies is larger than that observed in experimental studies; and specific glycan conformations can maximize or minimize interactions with individual antibodies. More broadly, the enhanced sampling MD simulations described here provide a valuable tool to guide the engineering of specific Env glycoforms for HIV vaccine design.

Microenvironment Influences Interaction of Signaling Molecules | Center for Cancer Research

Cancer.gov

Tumor progression depends not only on events that occur within cancer cells but also on the interaction of cancer cells with their environment, which can regulate tumor growth and metastasis and modulate the formation of new blood vessels to nourish the tumor. All cells communicate with other cells around them, including endothelial cells (the cells that make up blood vessels). They also interact with the extracellular matrix (ECM), a network of sugars and proteins that supports cells. Communication between neighboring cells and molecules often occurs through interaction among and between molecules on the cell surface and molecules of the ECM. Defining these interactions should facilitate the development of novel approaches to limit tumor progression.

Supramolecular assembly of (Z)-ethyl 2-cyano-3-((4-fluorophenyl)amino) acrylate, crystal structure, Hirshfeld surface analysis and DFT studies

NASA Astrophysics Data System (ADS)

Matos, Catiúcia R. M. O.; Vitorino, Letícia S.; de Oliveira, Pedro H. R.; de Souza, Maria Cecília B. V.; Cunha, Anna C.; Boechat, Fernanda da C. S.; Resende, Jackson A. L. C.; Carneiro, José Walkimar de M.; Ronconi, Célia M.

2016-09-01

A mixture of the E and Z isomers of ethyl 2-cyano-3-((4-fluorophenyl)amino) acrylate was synthesized and characterized by elemental analysis, attenuated total reflectance-Fourier transform infrared spectroscopy, 1H and 13C nuclear magnetic resonance spectroscopy. The structure of the Z isomer was determined by single crystal X-ray diffraction, which revealed a three-dimensional supramolecular network governed by Csbnd H⋯N, Csbnd H⋯O, and Csbnd H⋯F hydrogen bonds and π⋯π stacking interactions. The combination of these interactions plays an important role in stabilizing the self-assembly process and the molecular conformation. Hirshfeld surface analysis indicated the roles of the noncovalent interactions in the crystal packing, which were quantified by fingerprint plots and DFT calculations.

A coupled geomorphic and ecological model of tidal marsh evolution.

PubMed

Kirwan, Matthew L; Murray, A Brad

2007-04-10

The evolution of tidal marsh platforms and interwoven channel networks cannot be addressed without treating the two-way interactions that link biological and physical processes. We have developed a 3D model of tidal marsh accretion and channel network development that couples physical sediment transport processes with vegetation biomass productivity. Tidal flow tends to cause erosion, whereas vegetation biomass, a function of bed surface depth below high tide, influences the rate of sediment deposition and slope-driven transport processes such as creek bank slumping. With a steady, moderate rise in sea level, the model builds a marsh platform and channel network with accretion rates everywhere equal to the rate of sea-level rise, meaning water depths and biological productivity remain temporally constant. An increase in the rate of sea-level rise, or a reduction in sediment supply, causes marsh-surface depths, biomass productivity, and deposition rates to increase while simultaneously causing the channel network to expand. Vegetation on the marsh platform can promote a metastable equilibrium where the platform maintains elevation relative to a rapidly rising sea level, although disturbance to vegetation could cause irreversible loss of marsh habitat.

Polymorphism and metal-induced structural transformation in 5,5'-bis(4-pyridyl)(2,2'-bispyrimidine) adlayers on Au(111).

PubMed

Hötger, Diana; Carro, Pilar; Gutzler, Rico; Wurster, Benjamin; Chandrasekar, Rajadurai; Klyatskaya, Svetlana; Ruben, Mario; Salvarezza, Roberto C; Kern, Klaus; Grumelli, Doris

2018-05-31

Metal-organic coordination networks self-assembled on surfaces have emerged as functional low-dimensional architectures with potential applications ranging from the fabrication of functional nanodevices to electrocatalysis. Among them, bis-pyridyl-bispyrimidine (PBP) and Fe-PBP on noble metal surfaces appear as interesting systems in revealing the details of the molecular self-assembly and the effect of metal incorporation on the organic network arrangement. Herein, we report a combined STM, XPS, and DFT study revealing polymorphism in bis-pyridyl-bispyrimidine adsorbed adlayers on the reconstructed Au(111) surface. The polymorphic structures are converted by the addition of Fe adatoms into one unique Fe-PBP surface structure. DFT calculations show that while all PBP phases exhibit a similar thermodynamic stability, metal incorporation selects the PBP structure that maximizes the number of metal-N close contacts. Charge transfer from the Fe adatoms to the Au substrate and N-Fe interactions stabilize the Fe-PBP adlayer. The increased thermodynamic stability of the metal-stabilized structure leads to its sole expression on the surface.

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions

NASA Astrophysics Data System (ADS)

Nguyen, Thuong T.; Székely, Eszter; Imbalzano, Giulio; Behler, Jörg; Csányi, Gábor; Ceriotti, Michele; Götz, Andreas W.; Paesani, Francesco

2018-06-01

The accurate representation of multidimensional potential energy surfaces is a necessary requirement for realistic computer simulations of molecular systems. The continued increase in computer power accompanied by advances in correlated electronic structure methods nowadays enables routine calculations of accurate interaction energies for small systems, which can then be used as references for the development of analytical potential energy functions (PEFs) rigorously derived from many-body (MB) expansions. Building on the accuracy of the MB-pol many-body PEF, we investigate here the performance of permutationally invariant polynomials (PIPs), neural networks, and Gaussian approximation potentials (GAPs) in representing water two-body and three-body interaction energies, denoting the resulting potentials PIP-MB-pol, Behler-Parrinello neural network-MB-pol, and GAP-MB-pol, respectively. Our analysis shows that all three analytical representations exhibit similar levels of accuracy in reproducing both two-body and three-body reference data as well as interaction energies of small water clusters obtained from calculations carried out at the coupled cluster level of theory, the current gold standard for chemical accuracy. These results demonstrate the synergy between interatomic potentials formulated in terms of a many-body expansion, such as MB-pol, that are physically sound and transferable, and machine-learning techniques that provide a flexible framework to approximate the short-range interaction energy terms.

Man-made New Orleans: some interactions between the physical and esthetic environments

Treesearch

Ronald F. Lockmann

1977-01-01

The relations between the physical environment and esthetic dimensions of the New Orleans cultural landscape are examined. The esthetic characteristics associated with New Orleans urban morphology are examined with respect to possible constraints by the physical environment. Salient townscape features such as street grid system, surface-drainage network, and spatial...

Cell-micropatterning by micromolding in capillary technique based on UV polymerization

NASA Astrophysics Data System (ADS)

Park, Min J.; Choi, Won M.; Park, O. O.

2006-01-01

Although optical lithography or photolithography is one of the most well-established techniques for micro, nano-fabrication, its usage with proteins and cells is restricted by steps that must be carried out in harsh organic solvents. Here, we present simple methods for cell-micropatterning using poly(dimethylsiloxane) (PDMS) as a mold. Cell non-adhesive surface or nonfouling surface providing a physico-chemical barrier to cell attachment was introduced for biomaterial pattering, where cells fail to interact with the surface over desired periods of time determined by each application. Poly(ethylene glycol) (PEG) was selected as nonfouling material to inhibit protein adsorption from biological media. The fouling resistance of PEG polymer is often explained by a steric repulsion interaction, resulting from the compression of PEG chains as proteins approach the surface. We also chose fibronectin to direct cell attachment because it is an extracellular matrix protein that is involved in the adhesion and spreading of anchorage-dependent cells. In our experiment, we propose two methods by application of micromolding in capillary (MIMIC) method based on UV polymerization to obtain a surface of alternating PEG and fibronectin. First to fabricate PEG microstructure via MIMIC method, a pre-patterned PDMS mold is placed on a desired substrate, and then the relief structure in the mold forms a network of empty channels. A drop of ethylene glycol monomer solution containing initiator for UV polymerization is placed at the open ends of the network of channels, which is then polymerized by exposure to UV light at room temperature. Once PEG microstructure is fabricated, incubation of the patterned surface in a fibronectin-containing solution allows back-filling of only the bare regions with fibronectin via adsorption. In the alternative method, a substrate is first incubated in a fibronectin-containing solution, leading to the adsorption of fibronectin over the entire surface, and the fibronectin-adsorbed substrate is then micropatterned with the PEG by MIMIC based on UV polymerization. Both methods create reproducible alternating PEG and fibronectin patterns applicable to cell-surface interactions on the microscale.

Surface-groundwater interactions in hard rocks in Sardon Catchment of western Spain: an integrated modeling approach

USGS Publications Warehouse

Hassan, S.M. Tanvir; Lubczynski, Maciek W.; Niswonger, Richard G.; Zhongbo, Su

2014-01-01

The structural and hydrological complexity of hard rock systems (HRSs) affects dynamics of surface–groundwater interactions. These complexities are not well described or understood by hydrogeologists because simplified analyses typically are used to study HRSs. A transient, integrated hydrologic model (IHM) GSFLOW (Groundwater and Surface water FLOW) was calibrated and post-audited using 18 years of daily groundwater head and stream discharge data to evaluate the surface–groundwater interactions in semi-arid, ∼80 km2 granitic Sardon hilly catchment in Spain characterized by shallow water table conditions, relatively low storage, dense drainage networks and frequent, high intensity rainfall. The following hydrological observations for the Sardon Catchment, and more generally for HRSs were made: (i) significant bi-directional vertical flows occur between surface water and groundwater throughout the HRSs; (ii) relatively large groundwater recharge represents 16% of precipitation (P, 562 mm.y−1) and large groundwater exfiltration (∼11% of P) results in short groundwater flow paths due to a dense network of streams, low permeability and hilly topographic relief; deep, long groundwater flow paths constitute a smaller component of the water budget (∼1% of P); quite high groundwater evapotranspiration (∼5% of P and ∼7% of total evapotranspiration); low permeability and shallow soils are the main reasons for relatively large components of Hortonian flow and interflow (15% and 11% of P, respectively); (iii) the majority of drainage from the catchment leaves as surface water; (iv) declining 18 years trend (4.44 mm.y−1) of groundwater storage; and (v) large spatio-temporal variability of water fluxes. This IHM study of HRSs provides greater understanding of these relatively unknown hydrologic systems that are widespread throughout the world and are important for water resources in many regions.

Microstructure and rheology of particle stabilized emulsions: Effects of particle shape and inter-particle interactions.

PubMed

Katepalli, Hari; John, Vijay T; Tripathi, Anubhav; Bose, Arijit

2017-01-01

Using fumed and spherical silica particles of similar hydrodynamic size, we investigated the effects of particle shape and inter-particle interactions on the formation, stability and rheology of bromohexadecane-in-water Pickering emulsions. The interparticle interactions were varied from repulsive to attractive by modifying the salt concentration in the aqueous phase. Optical microscope images revealed smaller droplet sizes for the fumed silica stabilized emulsions. All the emulsions remained stable for several weeks. Cryo-SEM images of the emulsion droplets showed a hexagonally packed single layer of particles at oil-water interfaces in emulsions stabilized with silica spheres, irrespective of the nature of the inter-particle interactions. Thus, entropic, excluded volume interactions dominate the fate of spherical particles at oil-water interfaces. On the other hand, closely packed layers of particles were observed at oil-water interfaces for the fumed silica stabilized emulsions for both attractive and repulsive interparticle interactions. At the high salt concentrations, attractive inter-particles interactions led to aggregation of fumed silica particles, and multiple layers of these particles were then observed on the droplet surfaces. A network of fumed silica particles was also observed between the emulsion droplets, suggesting that enthalpic interactions are responsible for the determining particle configurations at oil-water interfaces as well as in the aqueous phase. Steady shear viscosity measurements over a range of shear stresses, as well as oscillatory shear measurements at 1Hz confirm the presence of a network in fumed silica suspensions and emulsions, and the lack of such a network when spherical particles are used. The fractal structure of fumed silica leads to several contact points and particle interlocking in the water as well as on the bromohexadecane-water interfaces, with corresponding effects on the structure and rheology of the emulsions. The attenuation of droplet motion due to the formation of a particle network can be exploited for stabilizing emulsions and for modulating their rheology. Copyright © 2016 Elsevier Inc. All rights reserved.

NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions

NASA Astrophysics Data System (ADS)

Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.

2016-12-01

Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.

Humans reclaimed lands in NorthEastern Italy and artificial drainage networks: effects of 30 years of Agricultural Surface Water Management

NASA Astrophysics Data System (ADS)

Sofia, Giulia; Pizzulli, Federica; Tarolli, Paolo

2017-04-01

Agriculture and land-use management has changed drastically in Italy since the end of the Second World War, driven by local but also European agricultural policies. As a result of these changes in farming practices and land use, many drainage networks have changed producing a greater exposure to flooding with a broad range of impacts on society, also because of climate inputs coupling with the human drivers. This study focuses on two main points: which kind of land use and farming changes have been observed in the most recent years ( 30 years)? How do these changes interact with climate and soil conditions? An open challenge to understand how these changes influence the watershed response, is, in fact, to understand if rainfall characteristics and climate have a synergistic effect, if their interaction matters, or to understand what element has the greatest influence on the watershed response connected to agricultural changes. The work is based on a simple model of water infiltration due to soil properties, and a connected evaluation of the distributed surface water storage offered by artificial drainage networks in a study area in Veneto (north-eastern Italy). The analysis shows that economic changes control the development of agro-industrial landscapes, with effects on the hydrological response. However, these changes deeply interact with antecedent soil conditions and climate characteristics. Intense and irregular rainfall events and events with a high recurrence should be expected to be the most critical. The presented outcomes highlight the importance of understanding how agricultural practices can be the driver of or can be used to avoid, or at least mitigate, flooding. The proposed methods can be valuable tools in evaluating the costs and benefits of the management of water in agriculture to inform better policy decision-making. References Sofia G, Tarolli P. 2017. Hydrological Response to 30 years of Agricultural Surface Water Management. Land 6 (1): 3 DOI: 10.3390/land6010003 Sofia G, Roder G, Dalla Fontana G, Tarolli P. 2017. Flood dynamics in urbanised landscapes: 100 years of climate and humans' interaction. Scientific Reports 7, 40527 DOI: 10.1038/srep40527

Interpreting stream sediment fingerprints against primary and secondary source signatures in agricultural catchments

NASA Astrophysics Data System (ADS)

Blake, Will H.; Haley, Steve; Smith, Hugh G.; Taylor, Alex; Goddard, Rupert; Lewin, Sean; Fraser, David

2013-04-01

Many sediment fingerprinting studies adopt a black box approach to source apportionment whereby the properties of downstream sediment are compared quantitatively to the geochemical fingerprints of potential catchment sources without consideration of potential signature development or modification during transit. Working within a source-pathway-receptor framework, this study aimed to undertake sediment source apportionment within 6 subcatchments of an agricultural river basin with specific attention to the potential role of contaminants (vehicle emissions and mine waste) in development of stream sediment signatures. Fallout radionuclide (FRN) and geochemical fingerprinting methods were adopted independently to establish source signatures for primary sediment sources of surface and subsurface soil materials under various land uses plus reworked mine and 'secondary' soil material deposited, in transit, along road networks. FRN data demonstrated expected variability between surface soil (137Cs = 14 ± 3 Bq kg-1; 210Pbxs = 40 ± 7 Bq kg-1) and channel bank materials (137Cs = 3 ± 1 Bq kg-1; 210Pbxs = 24 ± 5 Bq kg-1) but road transported soil material was considerably elevated in 210Pbxs (up to 673 ± 51 Bq kg-1) due to sediment interaction with pluvial surface water within the road network. Geochemical discrimination between surface and subsurface soil materials was dominated by alkaline earth and alkali metals e.g. Ba, Rb, Ca, K, Mg which are sensitive to weathering processes in soil. Magnetic susceptibility and heavy metals were important discriminators of road transported material which demonstrated transformation of the signatures of material transported via the road network. Numerical unmixing of stream sediment indicated that alongside channel bank erosion, road transported material was an important component in some systems in accord with FRN evidence. While mining spoil also ranked as a significant source in an affected catchment, perhaps related to legacy sediment, the potential role of dissolved metal leaching and subsequent sediment-water interaction within the channel on signature modification remained unclear. Consideration of sediment signature modification en route from primary source to stream elucidated important information regarding sediment transfer pathways and dynamics relevant to sediment management decisions. Further work on sediment-water interactions and potential for signature transformation in the channel environment is required.

Network biology discovers pathogen contact points in host protein-protein interactomes.

PubMed

Ahmed, Hadia; Howton, T C; Sun, Yali; Weinberger, Natascha; Belkhadir, Youssef; Mukhtar, M Shahid

2018-06-13

In all organisms, major biological processes are controlled by complex protein-protein interactions networks (interactomes), yet their structural complexity presents major analytical challenges. Here, we integrate a compendium of over 4300 phenotypes with Arabidopsis interactome (AI-1 MAIN ). We show that nodes with high connectivity and betweenness are enriched and depleted in conditional and essential phenotypes, respectively. Such nodes are located in the innermost layers of AI-1 MAIN and are preferential targets of pathogen effectors. We extend these network-centric analyses to Cell Surface Interactome (CSI LRR ) and predict its 35 most influential nodes. To determine their biological relevance, we show that these proteins physically interact with pathogen effectors and modulate plant immunity. Overall, our findings contrast with centrality-lethality rule, discover fast information spreading nodes, and highlight the structural properties of pathogen targets in two different interactomes. Finally, this theoretical framework could possibly be applicable to other inter-species interactomes to reveal pathogen contact points.

DNA-carbon nano onion aggregate: triangle, hexagon, six-petal flower to dead-end network

NASA Astrophysics Data System (ADS)

Babar, Dipak Gorakh; Pakhira, Bholanath; Sarkar, Sabyasachi

2017-08-01

The interaction between calf-thymus (CT) dsDNA and water soluble carbon nano onion (wsCNO) in water follows denaturation of dsDNA (double stranded) to ssDNA (single stranded) as monitored by optical spectroscopy. The ssDNA concomitantly wraps the spiky surface of wsCNO to create triangular aggregate as the building block as observed by time-dependent SEM images. These triangles further aggregate leading to six-petal flower arrangement via hexagon and finally reach a dead end network as imaged by SEM and optical fluorescence microscopy. The dead-end network aggregate lost the intrinsic optical property of DNA suggesting complete loss of its activity.

Networks Depicting the Fine-Scale Co-Occurrences of Fungi in Soil Horizons.

PubMed

Toju, Hirokazu; Kishida, Osamu; Katayama, Noboru; Takagi, Kentaro

2016-01-01

Fungi in soil play pivotal roles in nutrient cycling, pest controls, and plant community succession in terrestrial ecosystems. Despite the ecosystem functions provided by soil fungi, our knowledge of the assembly processes of belowground fungi has been limited. In particular, we still have limited knowledge of how diverse functional groups of fungi interact with each other in facilitative and competitive ways in soil. Based on the high-throughput sequencing data of fungi in a cool-temperate forest in northern Japan, we analyzed how taxonomically and functionally diverse fungi showed correlated fine-scale distributions in soil. By uncovering pairs of fungi that frequently co-occurred in the same soil samples, networks depicting fine-scale co-occurrences of fungi were inferred at the O (organic matter) and A (surface soil) horizons. The results then led to the working hypothesis that mycorrhizal, endophytic, saprotrophic, and pathogenic fungi could form compartmentalized (modular) networks of facilitative, antagonistic, and/or competitive interactions in belowground ecosystems. Overall, this study provides a research basis for further understanding how interspecific interactions, along with sharing of niches among fungi, drive the dynamics of poorly explored biospheres in soil.

Effect of Amphiphiles on the Rheology of Triglyceride Networks

NASA Astrophysics Data System (ADS)

Seth, Jyoti

2014-11-01

Networks of aggregated crystallites form the structural backbone of many products from the food, cosmetic and pharmaceutical industries. Such materials are generally formulated by cooling a saturated solution to yield the desired solid fraction. Crystal nucleation and growth followed by aggregation leads to formation of a space percolating fractal-network. It is understood that microstructural hierarchy and particle-particle interactions determine material behavior during processing, storage and use. In this talk, rheology of suspensions of triglycerides (TAG, like tristearin) will be explored. TAGs exhibit a rich assortment of polymorphs and form suspensions that are evidently sensitive to surface modifying additives like surfactants and polymers. Here, a theoretical framework will be presented for suspensions containing TAG crystals interacting via pairwise potentials. The work builds on existing models of fractal aggregates to understand microstructure and its correlation with material rheology. Effect of amphiphilic additives is derived through variation of particle-particle interactions. Theoretical predictions for storage modulus will be compared against experimental observations and data from the literature and micro structural predictions against microscopy. Such a theory may serve as a step towards predicting short and long-term behavior of aggregated suspensions formulated via crystallization.

Statistical Mechanics of Temporal and Interacting Networks

NASA Astrophysics Data System (ADS)

Zhao, Kun

In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide a new framework to quantify the information encoded in these networks and to answer a fundamental problem in network science: how complex are temporal and growing networks. Finally, we consider two examples of critical phenomena in interacting networks. In particular, on one side we investigate the percolation of interacting networks by introducing antagonistic interactions. On the other side, we investigate a model of political election based on the percolation of antagonistic networks. The aim of this research is to show how antagonistic interactions change the physics of critical phenomena on interacting networks. We believe that the work presented in these thesis offers the possibility to appreciate the large variability of problems that can be addressed in the new framework of temporal and interacting networks.

Convective dynamics - Panel report

NASA Technical Reports Server (NTRS)

Carbone, Richard; Foote, G. Brant; Moncrieff, Mitch; Gal-Chen, Tzvi; Cotton, William; Heymsfield, Gerald

1990-01-01

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

The Unfolding MD Simulations of Cyclophilin: Analyzed by Surface Contact Networks and Their Associated Metrics

PubMed Central

Roy, Sourav; Basu, Sankar; Dasgupta, Dipak; Bhattacharyya, Dhananjay; Banerjee, Rahul

2015-01-01

Currently, considerable interest exists with regard to the dissociation of close packed aminoacids within proteins, in the course of unfolding, which could result in either wet or dry moltenglobules. The progressive disjuncture of residues constituting the hydrophobic core ofcyclophilin from L. donovani (LdCyp) has been studied during the thermal unfolding of the molecule, by molecular dynamics simulations. LdCyp has been represented as a surface contactnetwork (SCN) based on the surface complementarity (Sm) of interacting residues within themolecular interior. The application of Sm to side chain packing within proteins make it a very sensitive indicator of subtle perturbations in packing, in the thermal unfolding of the protein. Network based metrics have been defined to track the sequential changes in the disintegration ofthe SCN spanning the hydrophobic core of LdCyp and these metrics prove to be highly sensitive compared to traditional metrics in indicating the increased conformational (and dynamical) flexibility in the network. These metrics have been applied to suggest criteria distinguishing DMG, WMG and transition state ensembles and to identify key residues involved in crucial conformational/topological events during the unfolding process. PMID:26545107

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

Gošić, M.; Rubio, L. R. Bellot; Iniesta, J. C. del Toro

Small-scale internetwork magnetic fields are important ingredients of the quiet Sun. In this paper we analyze how they appear and disappear on the solar surface. Using high resolution Hinode magnetograms, we follow the evolution of individual magnetic elements in the interior of two supergranular cells at the disk center. From up to 38 hr of continuous measurements, we show that magnetic flux appears in internetwork regions at a rate of 120 ± 3 Mx cm{sup −2} day{sup −1} (3.7 ± 0.4 × 10{sup 24} Mx day{sup −1} over the entire solar surface). Flux disappears from the internetwork at a rate of 125 ± 6 Mx cm{sup −2} day{supmore » −1} (3.9 ± 0.5 × 10{sup 24} Mx day{sup −1}) through fading of magnetic elements, cancelation between opposite-polarity features, and interactions with network patches, which converts internetwork elements into network features. Most of the flux is lost through fading and interactions with the network, at nearly the same rate of about 50 Mx cm{sup −2} day{sup −1}. Our results demonstrate that the sources and sinks of internetwork magnetic flux are well balanced. Using the instantaneous flux appearance and disappearance rates, we successfully reproduce the time evolution of the total unsigned flux in the two supergranular cells.« less

Inference of Stream Network Fragmentation Patterns from Ground Water - Surface Water Interactions on the High Plains Aquifer

NASA Astrophysics Data System (ADS)

Chandler, D. G.; Yang, X.; Steward, D. R.; Gido, K.

2007-12-01

Stream networks in the Great Plains integrate fluxes from precipitation as surface runoff in discrete events and groundwater as base flow. Changes in land cover and agronomic practices and development of ground water resources to support irrigated agriculture have resulted in profound changes in the occurrence and magnitude of stream flows, especially near the Ogallala aquifer, where precipitation is low. These changes have demonstrably altered the aquatic habitat of western Kansas, with documented changes in fish populations, riparian communities and groundwater quality due to stream transmission losses. Forecasting future changes in aquatic and riparian ecology and groundwater quality requires a large scale spatially explicit model of groundwater- surface water interaction. In this study, we combine historical data on land use, stream flow, production well development and groundwater level observations with groundwater elevation modeling to support a geospatial framework for assessing changes in refugia for aquatic species in four rivers in western Kansas between 1965 and 2005. Decreased frequency and duration of streamflow occurred in all rivers, but the extent of change depended on the geomorphology of the river basin and the extent of groundwater development. In the absence of streamflow, refugia for aquatic species were defined as the stream reaches below the phreatic surface of the regional aquifer. Changes in extent, location and degree of fragmentation of gaining reaches was found to be a strong predictor of surface water occurrence during drought and a robust hydrological template for the analysis of changes in recharge to alluvial and regional aquifers and riparian and aquatic habitat.

Emergence of chirality in hexagonally packed monolayers of hexapentyloxytriphenylene on Au(111): a joint experimental and theoretical study.

PubMed

Sleczkowski, Piotr; Katsonis, Nathalie; Kapitanchuk, Oleksiy; Marchenko, Alexandr; Mathevet, Fabrice; Croset, Bernard; Lacaze, Emmanuelle

2014-11-11

We investigate the expression of chirality in a monolayer formed spontaneously by 2,3,6,7,10,11-pentyloxytriphenylene (H5T) on Au(111). We resolve its interface morphology by combining scanning tunneling microscopy (STM) with theoretical calculations of intermolecular and interfacial interaction potentials. We observe two commensurate structures. While both of them belong to a hexagonal space group, analogical to the triangular symmetry of the molecule and the hexagonal symmetry of the substrate surface, they surprisingly reveal a 2D chiral character. The corresponding breaking of symmetry arises for two reasons. First it is due to the establishment of a large molecular density on the substrate, which leads to a rotation of the molecules with respect to the molecular network crystallographic axes to avoid steric repulsion between neighboring alkoxy chains. Second it is due to the molecule-substrate interactions, leading to commensurable large crystallographic cells associated with the large size of the molecule. As a consequence, molecular networks disoriented with respect to the high symmetry directions of the substrate are induced. The high simplicity of the intermolecular and molecule-substrate van der Waals interactions leading to these observations suggests a generic character for this kind of symmetry breaking. We demonstrate that, for similar molecular densities, only two kinds of molecular networks are stabilized by the molecule-substrate interactions. The most stable network favors the interfacial interactions between terminal alkoxy tails and Au(111). The metastable one favors a specific orientation of the triphenylene core with its symmetry axes collinear to the Au⟨110⟩. This specific orientation of the triphenylene cores with respect to Au(111) appears associated with an energy advantage larger by at least 0.26 eV with respect to the disoriented core.

Acquisition and Neural Network Prediction of 3D Deformable Object Shape Using a Kinect and a Force-Torque Sensor.

PubMed

Tawbe, Bilal; Cretu, Ana-Maria

2017-05-11

The realistic representation of deformations is still an active area of research, especially for deformable objects whose behavior cannot be simply described in terms of elasticity parameters. This paper proposes a data-driven neural-network-based approach for capturing implicitly and predicting the deformations of an object subject to external forces. Visual data, in the form of 3D point clouds gathered by a Kinect sensor, is collected over an object while forces are exerted by means of the probing tip of a force-torque sensor. A novel approach based on neural gas fitting is proposed to describe the particularities of a deformation over the selectively simplified 3D surface of the object, without requiring knowledge of the object material. An alignment procedure, a distance-based clustering, and inspiration from stratified sampling support this process. The resulting representation is denser in the region of the deformation (an average of 96.6% perceptual similarity with the collected data in the deformed area), while still preserving the object's overall shape (86% similarity over the entire surface) and only using on average of 40% of the number of vertices in the mesh. A series of feedforward neural networks is then trained to predict the mapping between the force parameters characterizing the interaction with the object and the change in the object shape, as captured by the fitted neural gas nodes. This series of networks allows for the prediction of the deformation of an object when subject to unknown interactions.

Imaging and manipulation of adatoms on an alumina surface by noncontact atomic force microscopy

NASA Astrophysics Data System (ADS)

Simon, G. H.; Heyde, M.; Freund, H.-J.

2012-02-01

Noncontact atomic force microscopy (NC-AFM) has been performed on an aluminum oxide film grown on NiAl(110) in ultrahigh vacuum (UHV) at low temperature (5 K). Results reproduce the topography of the structural model, unlike scanning tunnelling microscopy (STM) images. Equipped with this extraordinary contrast the network of extended defects, which stems from domain boundaries intersecting the film surface, can be analysed in atomic detail. The knowledge of occurring surface structures opens up the opportunity to determine adsorption sites of individual adsorbates on the alumina film. The level of difficulty for such imaging depends on the imaging characteristics of the substrate and the interaction which can be maintained above the adsorbate. Positions of single adsorbed gold atoms within the unit cell have been determined despite their easy removal at slightly higher interaction strength. Preliminary manipulation experiments indicate a pick-up process for the vanishing of the gold adatoms from the film surface.

Surface-Directed Assembly of Sequence-Defined Synthetic Polymers into Networks of Hexagonally Patterned Nanoribbons with Controlled Functionalities

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

Chen, Chun-Long; Zuckermann, Ronald N.; DeYoreo, James J.

The exquisite self-assembly of proteins and peptides in nature into highly ordered functional materials has inspired innovative approaches to biomimetic materials design and synthesis. Here we report the assembly of peptoids—a class of highly stable sequence-defined synthetic polymers—into biomimetic materials on mica surfaces. The assembling 12-mer peptoid contains alternating acidic and aromatic residues, and the presence of Ca2+ cations creates peptoid-peptoid and peptoid-mica interactions that drive assembly. In situ atomic force microscopy (AFM) shows that peptoids first assemble into discrete nanoparticles, these particles then transform into hexagonally-patterned nanoribbons on mica surfaces. AFM-based dynamic force spectroscopy (DFS) studies show that peptoid-micamore » interactions are much stronger than peptoidpeptoid interactions in the presence of Ca2+, illuminating the physical parameters that drive peptoid assembly. We further demonstrate the display of functional groups at the N-terminus of assembling peptoid sequence to produce biomimetic materials with similar hierarchical structures. This research demonstrates that surface-directed peptoid assembly can be used as a robust platform to develop biomimetic coating materials for applications.« less

Detailed analysis of RNA-protein interactions within the bacterial ribosomal protein L5/5S rRNA complex.

PubMed

Perederina, Anna; Nevskaya, Natalia; Nikonov, Oleg; Nikulin, Alexei; Dumas, Philippe; Yao, Min; Tanaka, Isao; Garber, Maria; Gongadze, George; Nikonov, Stanislav

2002-12-01

The crystal structure of ribosomal protein L5 from Thermus thermophilus complexed with a 34-nt fragment comprising helix III and loop C of Escherichia coli 5S rRNA has been determined at 2.5 A resolution. The protein specifically interacts with the bulged nucleotides at the top of loop C of 5S rRNA. The rRNA and protein contact surfaces are strongly stabilized by intramolecular interactions. Charged and polar atoms forming the network of conserved intermolecular hydrogen bonds are located in two narrow planar parallel layers belonging to the protein and rRNA, respectively. The regions, including these atoms conserved in Bacteria and Archaea, can be considered an RNA-protein recognition module. Comparison of the T. thermophilus L5 structure in the RNA-bound form with the isolated Bacillus stearothermophilus L5 structure shows that the RNA-recognition module on the protein surface does not undergo significant changes upon RNA binding. In the crystal of the complex, the protein interacts with another RNA molecule in the asymmetric unit through the beta-sheet concave surface. This protein/RNA interface simulates the interaction of L5 with 23S rRNA observed in the Haloarcula marismortui 50S ribosomal subunit.

Detailed analysis of RNA-protein interactions within the bacterial ribosomal protein L5/5S rRNA complex.

PubMed Central

Perederina, Anna; Nevskaya, Natalia; Nikonov, Oleg; Nikulin, Alexei; Dumas, Philippe; Yao, Min; Tanaka, Isao; Garber, Maria; Gongadze, George; Nikonov, Stanislav

2002-01-01

The crystal structure of ribosomal protein L5 from Thermus thermophilus complexed with a 34-nt fragment comprising helix III and loop C of Escherichia coli 5S rRNA has been determined at 2.5 A resolution. The protein specifically interacts with the bulged nucleotides at the top of loop C of 5S rRNA. The rRNA and protein contact surfaces are strongly stabilized by intramolecular interactions. Charged and polar atoms forming the network of conserved intermolecular hydrogen bonds are located in two narrow planar parallel layers belonging to the protein and rRNA, respectively. The regions, including these atoms conserved in Bacteria and Archaea, can be considered an RNA-protein recognition module. Comparison of the T. thermophilus L5 structure in the RNA-bound form with the isolated Bacillus stearothermophilus L5 structure shows that the RNA-recognition module on the protein surface does not undergo significant changes upon RNA binding. In the crystal of the complex, the protein interacts with another RNA molecule in the asymmetric unit through the beta-sheet concave surface. This protein/RNA interface simulates the interaction of L5 with 23S rRNA observed in the Haloarcula marismortui 50S ribosomal subunit. PMID:12515387

Charge-specific size-dependent separation of water-soluble organic molecules by fluorinated nanoporous networks

NASA Astrophysics Data System (ADS)

Byun, Jeehye; Patel, Hasmukh A.; Thirion, Damien; Yavuz, Cafer T.

2016-11-01

Molecular architecture in nanoscale spaces can lead to selective chemical interactions and separation of species with similar sizes and functionality. Substrate specific sorbent chemistry is well known through highly crystalline ordered structures such as zeolites, metal organic frameworks and widely available nanoporous carbons. Size and charge-dependent separation of aqueous molecular contaminants, on the contrary, have not been adequately developed. Here we report a charge-specific size-dependent separation of water-soluble molecules through an ultra-microporous polymeric network that features fluorines as the predominant surface functional groups. Treatment of similarly sized organic molecules with and without charges shows that fluorine interacts with charges favourably. Control experiments using similarly constructed frameworks with or without fluorines verify the fluorine-cation interactions. Lack of a σ-hole for fluorine atoms is suggested to be responsible for this distinct property, and future applications of this discovery, such as desalination and mixed matrix membranes, may be expected to follow.

Charge-specific size-dependent separation of water-soluble organic molecules by fluorinated nanoporous networks

PubMed Central

Byun, Jeehye; Patel, Hasmukh A.; Thirion, Damien; Yavuz, Cafer T.

2016-01-01

Molecular architecture in nanoscale spaces can lead to selective chemical interactions and separation of species with similar sizes and functionality. Substrate specific sorbent chemistry is well known through highly crystalline ordered structures such as zeolites, metal organic frameworks and widely available nanoporous carbons. Size and charge-dependent separation of aqueous molecular contaminants, on the contrary, have not been adequately developed. Here we report a charge-specific size-dependent separation of water-soluble molecules through an ultra-microporous polymeric network that features fluorines as the predominant surface functional groups. Treatment of similarly sized organic molecules with and without charges shows that fluorine interacts with charges favourably. Control experiments using similarly constructed frameworks with or without fluorines verify the fluorine-cation interactions. Lack of a σ-hole for fluorine atoms is suggested to be responsible for this distinct property, and future applications of this discovery, such as desalination and mixed matrix membranes, may be expected to follow. PMID:27830697

Network of Surface-Displayed Glycolytic Enzymes in Mycoplasma pneumoniae and Their Interactions with Human Plasminogen

PubMed Central

Gründel, Anne; Pfeiffer, Melanie; Jacobs, Enno

2015-01-01

In different bacteria, primarily cytosolic and metabolic proteins are characterized as surface localized and interacting with different host factors. These moonlighting proteins include glycolytic enzymes, and it has been hypothesized that they influence the virulence of pathogenic species. The presence of surface-displayed glycolytic enzymes and their interaction with human plasminogen as an important host factor were investigated in the genome-reduced and cell wall-less microorganism Mycoplasma pneumoniae, a common agent of respiratory tract infections of humans. After successful expression of 19 glycolytic enzymes and production of polyclonal antisera, the localization of proteins in the mycoplasma cell was characterized using fractionation of total proteins, colony blot, mild proteolysis and immunofluorescence of M. pneumoniae cells. Eight glycolytic enzymes, pyruvate dehydrogenases A to C (PdhA-C), glyceraldehyde-3-phosphate dehydrogenase (GapA), lactate dehydrogenase (Ldh), phosphoglycerate mutase (Pgm), pyruvate kinase (Pyk), and transketolase (Tkt), were confirmed as surface expressed and all are able to interact with plasminogen. Plasminogen bound to recombinant proteins PdhB, GapA, and Pyk was converted to plasmin in the presence of urokinase plasminogen activator and plasmin-specific substrate d-valyl-leucyl-lysine-p-nitroanilide dihydrochloride. Furthermore, human fibrinogen was degraded by the complex of plasminogen and recombinant protein PdhB or Pgm. In addition, surface-displayed proteins (except PdhC) bind to human lung epithelial cells, and the interaction was reduced significantly by preincubation of cells with antiplasminogen. Our results suggest that plasminogen binding and activation by different surface-localized glycolytic enzymes of M. pneumoniae may play a role in successful and long-term colonization of the human respiratory tract. PMID:26667841

Specifying the core network supporting episodic simulation and episodic memory by activation likelihood estimation

PubMed Central

Benoit, Roland G.; Schacter, Daniel L.

2015-01-01

It has been suggested that the simulation of hypothetical episodes and the recollection of past episodes are supported by fundamentally the same set of brain regions. The present article specifies this core network via Activation Likelihood Estimation (ALE). Specifically, a first meta-analysis revealed joint engagement of core network regions during episodic memory and episodic simulation. These include parts of the medial surface, the hippocampus and parahippocampal cortex within the medial temporal lobes, and the lateral temporal and inferior posterior parietal cortices on the lateral surface. Both capacities also jointly recruited additional regions such as parts of the bilateral dorsolateral prefrontal cortex. All of these core regions overlapped with the default network. Moreover, it has further been suggested that episodic simulation may require a stronger engagement of some of the core network’s nodes as wells as the recruitment of additional brain regions supporting control functions. A second ALE meta-analysis indeed identified such regions that were consistently more strongly engaged during episodic simulation than episodic memory. These comprised the core-network clusters located in the left dorsolateral prefrontal cortex and posterior inferior parietal lobe and other structures distributed broadly across the default and fronto-parietal control networks. Together, the analyses determine the set of brain regions that allow us to experience past and hypothetical episodes, thus providing an important foundation for studying the regions’ specialized contributions and interactions. PMID:26142352

The DYNAFLUX / DYNACOLD (Dynamics, Fluxes, Stability, Succession and Landscape Formation in Cold Environments) Network (2004-2017)

NASA Astrophysics Data System (ADS)

Beylich, Achim A.

2017-04-01

There is a wide range of high-latitude and high-altitude cold climate landscapes within Europe, covering a significant proportion of the total land surface area. This spectrum of defined cold-climate landscapes represents a variety of stages of deglaciation history and landscape formation. We can find landscapes at different levels of postglacial stabilization which is providing the unique opportunity to study the interactions between geo-, bio-, social and socio-economic systems at the land surface. The DYNAFLUX / DYNACOLD Network (2004-2017) bridges across the geo-, bio-, social and socio-economic sciences in order to analyze the complex dynamics of adjustment, stabilization, succession and landscape formation during and after ice retreat and under ongoing anthropogenic influences. The network provides a multidisciplinary forum where researchers come together and discuss. In addition, this network is linking a number of other scientific networks, working groups and programs and creates an umbrella network and a forum for sharing knowledge and experience. The scientific focus of DYNAFLUX / DYNACOLD is also relevant for a number of end users, including risk and vulnerability assessment, sustainable land use, land management and conservation. In addition, present key questions related to environmental change like, e.g., hazards, permafrost degradation and loss of biodiversity are addressed and discussed. Further information is found under http://www.ngu.no/sediflux.

Surface energetics and protein-protein interactions: analysis and mechanistic implications

PubMed Central

Peri, Claudio; Morra, Giulia; Colombo, Giorgio

2016-01-01

Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions. PMID:27050828

Water Hydrogen-Bonding Network Structure and Dynamics at Phospholipid Multibilayer Surface: Femtosecond Mid-IR Pump-Probe Spectroscopy.

PubMed

Kundu, Achintya; Błasiak, Bartosz; Lim, Joon-Hyung; Kwak, Kyungwon; Cho, Minhaeng

2016-03-03

The water hydrogen-bonding network at a lipid bilayer surface is crucial to understanding membrane structures and its functional activities. With a phospholipid multibilayer mimicking a biological membrane, we study the temperature dependence of water hydrogen-bonding structure, distribution, and dynamics at a lipid multibilayer surface using femtosecond mid-IR pump-probe spectroscopy. We observe two distinguished vibrational lifetime components. The fast component (0.6 ps) is associated with water interacting with a phosphate part, whereas the slow component (1.9 ps) is with bulk-like choline-associated water. With increasing temperature, the vibrational lifetime of phosphate-associated water remains constant though its relative fraction dramatically increases. The OD stretch vibrational lifetime of choline-bound water slows down in a sigmoidal fashion with respect to temperature, indicating a noticeable change of the water environment upon the phase transition. The water structure and dynamics are thus shown to be in quantitative correlation with the structural change of liquid multibilayer upon the gel-to-liquid crystal phase transition.

Anomalous water dynamics at surfaces and interfaces: synergistic effects of confinement and surface interactions

NASA Astrophysics Data System (ADS)

Biswas, Rajib; Bagchi, Biman

2018-01-01

In nature, water is often found in contact with surfaces that are extended on the scale of molecule size but small on a macroscopic scale. Examples include lipid bilayers and reverse micelles as well as biomolecules like proteins, DNA and zeolites, to name a few. While the presence of surfaces and interfaces interrupts the continuous hydrogen bond network of liquid water, confinement on a mesoscopic scale introduces new features. Even when extended on a molecular scale, natural and biological surfaces often have features (like charge, hydrophobicity) that vary on the scale of the molecular diameter of water. As a result, many new and exotic features, which are not seen in the bulk, appear in the dynamics of water close to the surface. These different behaviors bear the signature of both water-surface interactions and of confinement. In other words, the altered properties are the result of the synergistic effects of surface-water interactions and confinement. Ultrafast spectroscopy, theoretical modeling and computer simulations together form powerful synergistic approaches towards an understanding of the properties of confined water in such systems as nanocavities, reverse micelles (RMs), water inside and outside biomolecules like proteins and DNA, and also between two hydrophobic walls. We shall review the experimental results and place them in the context of theory and simulations. For water confined within RMs, we discuss the possible interference effects propagating from opposite surfaces. Similar interference is found to give rise to an effective attractive force between two hydrophobic surfaces immersed and kept fixed at a separation of d, with the force showing an exponential dependence on this distance. For protein and DNA hydration, we shall examine a multitude of timescales that arise from frustration effects due to the inherent heterogeneity of these surfaces. We pay particular attention to the role of orientational correlations and modification of the same due to interaction with the surfaces.

Occurrence and photodegradation of methylmercury in surface water of Wen-Rui-Tang River network, Wenzhou, China.

PubMed

Pan, Shuihong; Feng, Chuchu; Lin, Jialu; Cheng, Lidong; Wang, Chengjun; Zuo, Yuegang

2017-04-01

The spatial distribution and seasonal variations of methylmercury (MeHg) in Wen-Rui-Tang (WRT) River network were investigated by monitoring the MeHg concentrations in surface water samples collected from 30 sites across the river network over four seasons. Detection frequencies and concentrations of MeHg were generally higher in January, indicating that low sunlight irradiation, wind speed, and temperature conditions might enhance the persistence of MeHg in surface water. The MeHg levels varied with sampling locations, with the highest concentrations being observed in the industrial area especially around wastewater outfall, revealing that the mercury contamination in WRT River mainly comes from the industrial wastewater. Photodegradation of MeHg in WRT River surface water and the effects of natural constituents such as fulvic acid (FA), ferric ions (Fe 3+ ), nitrate (NO 3 - ), and dissolved oxygen on the MeHg photodegradation in aqueous solutions were studied under the simulated sunlight. The experimental data indicated that the indirect photodecomposition of MeHg occurred in WRT River surface water. Photodegradation of MeHg in FA solution was initiated by triplet 3 FA* or MeHg-FA* via electron transfer interaction under light irradiations. The Fe 3+ and NO 3 - can absorb light energy to produce ·OH and enhance the photochemical degradation of MeHg. The MeHg photodecompositions in FA, nitrate, and Fe 3+ solutions were markedly accelerated after removing the dissolved oxygen.

Specifying the core network supporting episodic simulation and episodic memory by activation likelihood estimation.

PubMed

Benoit, Roland G; Schacter, Daniel L

2015-08-01

It has been suggested that the simulation of hypothetical episodes and the recollection of past episodes are supported by fundamentally the same set of brain regions. The present article specifies this core network via Activation Likelihood Estimation (ALE). Specifically, a first meta-analysis revealed joint engagement of expected core-network regions during episodic memory and episodic simulation. These include parts of the medial surface, the hippocampus and parahippocampal cortex within the medial temporal lobes, and the temporal and inferior posterior parietal cortices on the lateral surface. Both capacities also jointly recruited additional regions such as parts of the bilateral dorsolateral prefrontal cortex. All of these core regions overlapped with the default network. Moreover, it has further been suggested that episodic simulation may require a stronger engagement of some of the core network's nodes as well as the recruitment of additional brain regions supporting control functions. A second ALE meta-analysis indeed identified such regions that were consistently more strongly engaged during episodic simulation than episodic memory. These comprised the core-network clusters located in the left dorsolateral prefrontal cortex and posterior inferior parietal lobe and other structures distributed broadly across the default and fronto-parietal control networks. Together, the analyses determine the set of brain regions that allow us to experience past and hypothetical episodes, thus providing an important foundation for studying the regions' specialized contributions and interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effect of physiological conditions on the surface structure of proteins: Setting the scene for human digestion of emulsions

NASA Astrophysics Data System (ADS)

Maldonado-Valderrama, J.; Gunning, A. P.; Ridout, M. J.; Wilde, P. J.; Morris, V. J.

2009-10-01

Understanding and manipulating the interfacial mechanisms that control human digestion of food emulsions is a crucial step towards improved control of dietary intake. This article reports initial studies on the effects of the physiological conditions within the stomach on the properties of the film formed by the milk protein ( β -lactoglobulin) at the air-water interface. Atomic force microscopy (AFM), surface tension and surface rheology techniques were used to visualize and examine the effect of gastric conditions on the network structure. The effects of changes in temperature, pH and ionic strength on a pre-formed interfacial structure were characterized in order to simulate the actual digestion process. Changes in ionic strength had little effect on the surface properties. In isolation, acidification reduced both the dilatational and the surface shear modulus, mainly due to strong repulsive electrostatic interactions within the surface layer and raising the temperature to body temperature accelerated the rearrangements within the surface layer, resulting in a decrease of the dilatational response and an increase of surface pressure. Together pH and temperature display an unexpected synergism, independent of the ionic strength. Thus, exposure of a pre-formed interfacial β -lactoglobulin film to simulated gastric conditions reduced the surface dilatational modulus and surface shear moduli. This is attributed to a weakening of the surface network in which the surface rearrangements of the protein prior to exposure to gastric conditions might play a crucial role.

Protein interaction networks from literature mining

NASA Astrophysics Data System (ADS)

Ihara, Sigeo

2005-03-01

The ability to accurately predict and understand physiological changes in the biological network system in response to disease or drug therapeutics is of crucial importance in life science. The extensive amount of gene expression data generated from even a single microarray experiment often proves difficult to fully interpret and comprehend the biological significance. An increasing knowledge of protein interactions stored in the PubMed database, as well as the advancement of natural language processing, however, makes it possible to construct protein interaction networks from the gene expression information that are essential for understanding the biological meaning. From the in house literature mining system we have developed, the protein interaction network for humans was constructed. By analysis based on the graph-theoretical characterization of the total interaction network in literature, we found that the network is scale-free and semantic long-ranged interactions (i.e. inhibit, induce) between proteins dominate in the total interaction network, reducing the degree exponent. Interaction networks generated based on scientific text in which the interaction event is ambiguously described result in disconnected networks. In contrast interaction networks based on text in which the interaction events are clearly stated result in strongly connected networks. The results of protein-protein interaction networks obtained in real applications from microarray experiments are discussed: For example, comparisons of the gene expression data indicative of either a good or a poor prognosis for acute lymphoblastic leukemia with MLL rearrangements, using our system, showed newly discovered signaling cross-talk.

Ground-Based Network and Supersite Observations to Complement and Enrich EOS Research

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Holben, Brent N.; Welton, Ellsworth J.

2011-01-01

Since 1997 NASA has been successfully launching a series of satellites - the Earth Observing System (EOS) - to intensively study, and gain a better understanding of, the Earth as an integrated system. Space-borne remote sensing observations, however, are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. Through numerous participations, particularly but not limited to the EOS remote-sensing/retrieval and validation projects over the years, NASA/GSFC has developed and continuously refined ground-based networks and mobile observatories that proved to be vital in providing high temporal measurements, which complement and enrich the satellite observations. These are: the AERO NET (AErosol RObotic NETwork) a federation of ground-based globally distributed network of spectral sun-sky photometers; the MPLNET (Micro-Pulse Lidar NETwork, a similarly organized network of micro-pulse lidar systems measuring aerosol and cloud vertical structure continuously; and the SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere, mobile observatories, a suite of spectral radiometers and in-situ probes acquiring supersite measurements. Most MPLNET sites are collocated with those of AERONET, and both networks always support the deployment of SMART-COMMIT worldwide. These data products follow the data structure of EOS conventions: Level-0, instrument archived raw data; Level-1 (or 1.5), real-time data with no (or limited) quality assurance; Level-2, not real high temporal and spectral resolutions. In this talk, we will present NASA/GSFC groundbased facilities, serving as network or supersite observations, which have been playing key roles in major international research projects over diverse aerosol regimes to complement and enrich the EOS scientific research.

The xyloglucan-cellulose assembly at the atomic scale.

PubMed

Hanus, Jaroslav; Mazeau, Karim

2006-05-01

The assembly of cell wall components, cellulose and xyloglucan (XG), was investigated at the atomistic scale using molecular dynamics simulations. A molecular model of a cellulose crystal corresponding to the allomorph Ibeta and exhibiting a flexible complex external morphology was employed to mimic the cellulose microfibril. The xyloglucan molecules considered were the three typical basic repeat units, differing only in the size of one of the lateral chain. All the investigated XG fragments adsorb nonspecifically onto cellulose fiber; multiple arrangements are equally probable, and every cellulose surface was capable of binding the short XG molecules. The following structural effects emerged: XG molecules that do not have any long side chains tended to adapt themselves nicely to the topology of the microfibril, forming a flat, outstretched conformation with all the sugar residues interacting with the surface. In contrast, the XG molecules, which have long side chains, were not able to adopt a flat conformation that would enable the interaction of all the XG residues with the surface. In addition to revealing the fundamental atomistic details of the XG adsorption on cellulose, the present calculations give a comprehensive understanding of the way the XG molecules can unsorb from cellulose to create a network that forms the cell wall. Our revisited view of the adsorption features of XG on cellulose microfibrils is consistent with experimental data, and a model of the network is proposed. Copyright (c) 2006 Wiley Periodicals, Inc.

The TOPOMOD-ITN project: unravel the origin of Earth's topography from modelling deep-surface processes

NASA Astrophysics Data System (ADS)

Faccenna, C.; Funiciello, F.

2012-04-01

EC-Marie Curie Initial Training Networks (ITN) projects aim to improve the career perspectives of young generations of researchers. Institutions from both academic and industry sectors form a collaborative network to recruit research fellows and provide them with opportunities to undertake research in the context of a joint research training program. In this frame, TOPOMOD - one of the training activities of EPOS, the new-born European Research Infrastructure for Geosciences - is a funded ITN project designed to investigate and model how surface processes interact with crustal tectonics and mantle convection to originate and develop topography of the continents over a wide range of spatial and temporal scales. The multi-disciplinary approach combines geophysics, geochemistry, tectonics and structural geology with advanced geodynamic numerical/analog modelling. TOPOMOD involves 8 European research teams internationally recognized for their excellence in complementary fields of Earth Sciences (Roma TRE, Utrecht, GFZ, ETH, Cambridge, Durham, Rennes, Barcelona), to which are associated 5 research institutions (CNR-Italy, Univ. Parma, Univ. Lausanne, Univ. Montpellier, Univ. Mainz) , 3 high-technology enterprises (Malvern Instruments, TNO, G.O. Logical Consulting) and 1 large multinational oil and gas company (ENI). This unique network places emphasis in experience-based training increasing the impact and international visibility of European research in modeling. Long-term collaboration and synergy are established among the overmentioned research teams through 15 cross-disciplinary research projects that combine case studies in well-chosen target areas from the Mediterranean, the Middle and Far East, west Africa, and South America, with new developments in structural geology, geomorphology, seismology, geochemistry, InSAR, laboratory and numerical modelling of geological processes from the deep mantle to the surface. These multidisciplinary projects altogether aim to answer a key question in earth Sciences: how do deep and surface processes interact to shape and control the topographic evolution of our planet.

Sialic acid-triggered macroscopic properties switching on a smart polymer surface

NASA Astrophysics Data System (ADS)

Xiong, Yuting; Li, Minmin; Wang, Hongxi; Qing, Guangyan; Sun, Taolei

2018-01-01

Constructing smart surfaces with responsive polymers capable of dynamically and reversibly changing their chemical and physical properties by responding to the recognition of biomolecules remains a challenging task. And, the key to achieving this purpose relies on the design of polymers to precisely interact with the target molecule and successfully transform the interaction signal into tunable macroscopic properties, further achieve special bio-functions. Herein, inspired by carbohydrate-carbohydrate interaction (CCI) in life system, we developed a three-component copolymer poly(NIPAAm-co-PT-co-Glc) bearing a binding unit glucose (Glc) capable of recognizing sialic acid, a type of important molecular targets for cancer diagnosis and therapy, and reported the sialic acid triggered macroscopic properties switching on this smart polymer surface. Detailed mechanism studies indicated that multiple hydrogen bonding interactions between Glc unit and Neu5Ac destroyed the initial hydrogen bond network of the copolymer, leading to a reversible "contraction-to-swelling" conformational transition of the copolymer chains, accompanied with distinct macroscopic property switching (i.e., surface wettability, morphology, stiffness) of the copolymer film. And these features enabled this copolymer to selectively capture sialic acid-containing glycopeptides from complex protein samples. This work provides an inspiration for the design of novel smart polymeric materials with sensitive responsiveness to sialic acid, which would promote the development of sialic acid-specific bio-devices and drug delivery systems.

It's a Sooty Problem: Black Carbon and Aerosols from Space

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2005-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with solar radiation, clouds and precipitation is lacking despite decades of research. Just recently we recognized that understanding the global aerosol system is fundamental for progress in climate change and hydrological cycle research. While a single instrument was used to demonstrate 50 yrs ago that the global CO2 levels are rising, posing thread to our climate, we need an may of satellites, surface networks of radiometers, elaborated laboratory and field experiments coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week), variability of the chemical composition and complex chemical and physical processes in the atmosphere. The result is a heterogeneous distribution of aerosol and their properties. The new generation of satellites and surface networks of radiometers provides exciting opportunities to measure the aerosol properties and their interaction with clouds and climate. However farther development in the satellite capability, aerosol chemical models and climate models is needed to fully decipher the aerosol secrets with accuracy required to predict future climates.

Coevolution of dynamical states and interactions in dynamic networks

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi

2004-06-01

We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.

A versatile system for processing geostationary satellite data with run-time visualization capability

NASA Technical Reports Server (NTRS)

Landsfeld, M.; Gautier, C.; Figel, T.

1995-01-01

To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. We are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government agencies. Our contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface and satellite observations and complex modeling of the interaction of radiation with clouds. One of our first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, we have produced an environment whereby we can easily modify and monitor the data processing as required. Through the principles of modular programming, we have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants. In this way, the data flow can be interactively assessed and altered as needed. In this environment, the intermediate data processing 'images' can be viewed, enabling the investigator to easily monitor the various data processing steps as they progress. Additionally, this environment allows the rapid testing of new processing modules and allows their effects to be visually compared with previous results.

How to most effectively expand the global surface ozone observing network

NASA Astrophysics Data System (ADS)

Sofen, E. D.; Bowdalo, D.; Evans, M. J.

2016-02-01

Surface ozone observations with modern instrumentation have been made around the world for more than 40 years. Some of these observations have been made as one-off activities with short-term, specific science objectives and some have been made as part of wider networks which have provided a foundational infrastructure of data collection, calibration, quality control, and dissemination. These observations provide a fundamental underpinning to our understanding of tropospheric chemistry, air quality policy, atmosphere-biosphere interactions, etc. brought together eight of these networks to provide a single data set of surface ozone observations. We investigate how representative this combined data set is of global surface ozone using the output from a global atmospheric chemistry model. We estimate that on an area basis, 25 % of the globe is observed (34 % land, 21 % ocean). Whereas Europe and North America have almost complete coverage, other continents, Africa, South America, Australia, and Asia (12-17 %) show significant gaps. Antarctica is surprisingly well observed (78 %). Little monitoring occurs over the oceans, with the tropical and southern oceans particularly poorly represented. The surface ozone over key biomes such as tropical forests and savanna is almost completely unmonitored. A chemical cluster analysis suggests that a significant number of observations are made of polluted air masses, but cleaner air masses whether over the land or ocean (especially again in the tropics) are significantly under-observed. The current network is unlikely to see the impact of the El Niño-Southern Oscillation (ENSO) but may be capable of detecting other planetary-scale signals. Model assessment and validation activities are hampered by a lack of observations in regions where the models differ substantially, as is the ability to monitor likely changes in surface ozone over the next century. Using our methodology we are able to suggest new sites which would help to close the gap in our ability to measure global surface ozone. An additional 20 surface ozone monitoring sites (a 20 % increase in the World Meteorological Organization Global Atmosphere Watch (WMO GAW) ozone sites or a 1 % increase in the total background network) located on 10 islands and in 10 continental regions would almost double the area observed. The cost of this addition to the network is small compared to other expenditure on atmospheric composition research infrastructure and would provide a significant long-term benefit to our understanding of the composition of the atmosphere, information which will also be available for consideration by air quality control managers and policy makers.

Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles

2004-02-01

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

Interaction Control to Synchronize Non-synchronizable Networks.

PubMed

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-11-17

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks' exact interaction topology and consequently have implications for biological and self-organizing technical systems.

Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining

PubMed Central

2012-01-01

Background Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genome-wide, Centrality and Ontology-based Network Discovery using Literature data (CONDL) approach to analyse the genes and gene interaction networks associated with fever or vaccine-related fever responses. Results Over 170,000 fever-related articles from PubMed abstracts and titles were retrieved and analysed at the sentence level using natural language processing techniques to identify genes and vaccines (including 186 Vaccine Ontology terms) as well as their interactions. This resulted in a generic fever network consisting of 403 genes and 577 gene interactions. A vaccine-specific fever sub-network consisting of 29 genes and 28 gene interactions was extracted from articles that are related to both fever and vaccines. In addition, gene-vaccine interactions were identified. Vaccines (including 4 specific vaccine names) were found to directly interact with 26 genes. Gene set enrichment analysis was performed using the genes in the generated interaction networks. Moreover, the genes in these networks were prioritized using network centrality metrics. Making scientific discoveries and generating new hypotheses were possible by using network centrality and gene set enrichment analyses. For example, our study found that the genes in the generic fever network were more enriched in cell death and responses to wounding, and the vaccine sub-network had more gene enrichment in leukocyte activation and phosphorylation regulation. The most central genes in the vaccine-specific fever network are predicted to be highly relevant to vaccine-induced fever, whereas genes that are central only in the generic fever network are likely to be highly relevant to generic fever responses. Interestingly, no Toll-like receptors (TLRs) were found in the gene-vaccine interaction network. Since multiple TLRs were found in the generic fever network, it is reasonable to hypothesize that vaccine-TLR interactions may play an important role in inducing fever response, which deserves a further investigation. Conclusions This study demonstrated that ontology-based literature mining is a powerful method for analyzing gene interaction networks and generating new scientific hypotheses. PMID:23256563

Origin of the Giant Honeycomb Network of Quinones on Cu(111)

NASA Astrophysics Data System (ADS)

Einstein, T. L.; Kim, Kwangmoo; Wyrick, Jon; Cheng, Zhihai; Bartels, Ludwig; Berland, Kristian; Hyldgaard, Per

2011-03-01

We discuss the factors that lead to the amazing regular giant honeycomb network formed by quinones on Cu(111). Using a related lattice gas model with many characteristic energies, we can reproduce many experimental features. These models require a long-range attraction, which can be attributed to indirect interactions mediated by the Shockley surface state of Cu(111). However, Wyrick's preceding talk gave evidence that the network self-selects for the size of the pore rather than for the periodicity of the superstructure, suggesting that confined states are the key ingredient. We discuss this phenomenon in terms of the magic numbers of 2D quantum dots. We also report calculations of the effects of anthraquinones (AQ) in modifying the surface states by considering a superlattice of AQ chains with various separations. We discuss implications of these results for tuning the electronic states and, thence, superstructures. Supported by (TLE) NSF CHE 07-50334 & UMD MRSEC DMR 05-20471, (JW & LB) NSF CHE NSF CHE 07-49949, (KB & PH) Swedish Vetenskapsrådet VR 621-2008-4346.

Cell surface retention sequence binding protein-1 interacts with the v-sis gene product and platelet-derived growth factor beta-type receptor in simian sarcoma virus-transformed cells.

PubMed

Boensch, C; Huang, S S; Connolly, D T; Huang, J S

1999-04-09

The cell surface retention sequence (CRS) binding protein-1 (CRSBP-1) is a newly identified membrane glycoprotein which is hypothesized to be responsible for cell surface retention of the oncogene v-sis and c-sis gene products and other secretory proteins containing CRSs. In simian sarcoma virus-transformed NIH 3T3 cells (SSV-NIH 3T3 cells), a fraction of CRSBP-1 was demonstrated at the cell surface and underwent internalization/recycling as revealed by cell surface 125I labeling and its resistance/sensitivity to trypsin digestion. However, the majority of CRSBP-1 was localized in intracellular compartments as evidenced by the resistance of most of the 35S-metabolically labeled CRSBP-1 to trypsin digestion, and by indirect immunofluorescent staining. CRSBP-1 appeared to form complexes with proteolytically processed forms (generated at and/or after the trans-Golgi network) of the v-sis gene product and with a approximately 140-kDa proteolytically cleaved form of the platelet-derived growth factor (PDGF) beta-type receptor, as demonstrated by metabolic labeling and co-immunoprecipitation. CRSBP-1, like the v-sis gene product and PDGF beta-type receptor, underwent rapid turnover which was blocked in the presence of 100 microM suramin. In normal and other transformed NIH 3T3 cells, CRSBP-1 was relatively stable and did not undergo rapid turnover and internalization/recycling at the cell surface. These results suggest that in SSV-NIH 3T3 cells, CRSBP-1 interacts with and forms ternary and binary complexes with the newly synthesized v-sis gene product and PDGF beta-type receptor at the trans-Golgi network and that the stable binary (CRSBP-1.v-sis gene product) complex is transported to the cell surface where it presents the v-sis gene product to unoccupied PDGF beta-type receptors during internalization/recycling.

Spatio-temporal patterns in land use and management affecting surface runoff response of agricultural catchments - a review

NASA Astrophysics Data System (ADS)

Fiener, P.; Auerswald, K.; van Oost, K.

2009-04-01

In many landscapes, land use creates a complex pattern in addition to the patterns resulting from soil, topography and rain. Despite the static layout of fields, a spatio-temporally highly variable situation regarding the surface runoff and erosion processes results from the asynchronous seasonal variation associated with different land uses. While the behaviour of individual land-uses and their seasonal variation is analyzed in many studies, the spatio-temporal interaction related to this pattern is rarely studied despite its crucial influence on hydrological and geomorphic response of catchments. The difficulty in studying such interactions mainly results from the fact that it is impossible to set up a replicated experiment on the landscape scale. The purpose of this review is to present the advances made thus far in quantifying the effects of patchiness of land use and management on surface runoff response in agricultural catchments. We will focus on the effects of spatio-temporal patterns in land use patches on hydraulic connectivity between patches and within catchments. This will include the temporal patterns in land management affecting infiltration, surface roughness and hence runoff concentration within single fields or land use patches insofar as these effects must be known to evaluate the combined effect of patch behaviour in space and time on catchment connectivity and surface runoff. Surface runoff effects of patchiness and connectivity between patches or within a catchment, can either be addressed by modelling studies or by comprehensive catchment field measurements, e.g. paired-watershed experiments or landscape scale studies on different scales. This limits our review to studies at the scale of small catchments < 10 km², where the time constant of the network (i.e. travel time through it) is smaller than the infiltration phase. Despite this limitation, these small catchments are important as they constitute 2/3 of the total surface of large water drainage networks.

PAHs behavior in surface water and groundwater of the Yellow River estuary: Evidence from isotopes and hydrochemistry.

PubMed

Li, Jing; Li, Fadong; Liu, Qiang

2017-07-01

Large-scale irrigation projects have impacted the regional surface-groundwater interactions in the North China Plain (NCP). Given this concern, the aim of this study is to evaluate levels of PAH pollution, identify the sources of the PAHs, analyze the influence of surface-groundwater interactions on PAH distribution, and propose urgent management strategies for PAHs in China's agricultural areas. PAH concentrations, hydrochemical indicators and stable isotopic compositions (δ 18 O and δ 2 H) were determined for surface water (SW) and groundwater (GW) samples. PAHs concentrations in surface water and groundwater varied from 11.84 to 393.12 ng/L and 8.51-402.84 ng/L, respectively, indicating mild pollution. The seasonal variations showed the following trend: PAHs in surface water at the low-water phase > PAHs in groundwater at the low-water phase > PAHs in surface water at the high-water phase > PAHs in groundwater at the high-water phase. Hydrochemical and δ 18 O value of most groundwater samples distributed between the Yellow River and seawater. The mean value of mixture ratio of the Yellow River water recharge to the groundwater was 65%, few anomalous sites can reach to 90%. Surface-groundwater interactions influence the spatial distribution of PAHs in the study area. In light of the ongoing serious pollution, management practices for source control, improved control technologies, and the construction of a monitoring network to warn of increased risk are urgently needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Interaction of D2 with H2O amorphous ice studied by temperature-programmed desorption experiments.

PubMed

Amiaud, L; Fillion, J H; Baouche, S; Dulieu, F; Momeni, A; Lemaire, J L

2006-03-07

The gas-surface interaction of molecular hydrogen D2 with a thin film of porous amorphous solid water (ASW) grown at 10 K by slow vapor deposition has been studied by temperature-programmed-desorption (TPD) experiments. Molecular hydrogen diffuses rapidly into the porous network of the ice. The D2 desorption occurring between 10 and 30 K is considered here as a good probe of the effective surface of ASW interacting with the gas. The desorption kinetics have been systematically measured at various coverages. A careful analysis based on the Arrhenius plot method has provided the D2 binding energies as a function of the coverage. Asymmetric and broad distributions of binding energies were found, with a maximum population peaking at low energy. We propose a model for the desorption kinetics that assumes a complete thermal equilibrium of the molecules with the ice film. The sample is characterized by a distribution of adsorption sites that are filled according to a Fermi-Dirac statistic law. The TPD curves can be simulated and fitted to provide the parameters describing the distribution of the molecules as a function of their binding energy. This approach contributes to a correct description of the interaction of molecular hydrogen with the surface of possibly porous grain mantles in the interstellar medium.

Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2016-12-01

In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

Characterization of the periplasmic redox network that sustains the versatile anaerobic metabolism of Shewanella oneidensis MR-1

PubMed Central

Alves, Mónica N.; Neto, Sónia E.; Alves, Alexandra S.; Fonseca, Bruno M.; Carrêlo, Afonso; Pacheco, Isabel; Paquete, Catarina M.; Soares, Cláudio M.; Louro, Ricardo O.

2015-01-01

The versatile anaerobic metabolism of the Gram-negative bacterium Shewanella oneidensis MR-1 (SOMR-1) relies on a multitude of redox proteins found in its periplasm. Most are multiheme cytochromes that carry electrons to terminal reductases of insoluble electron acceptors located at the cell surface, or bona fide terminal reductases of soluble electron acceptors. In this study, the interaction network of several multiheme cytochromes was explored by a combination of NMR spectroscopy, activity assays followed by UV-visible spectroscopy and comparison of surface electrostatic potentials. From these data the small tetraheme cytochrome (STC) emerges as the main periplasmic redox shuttle in SOMR-1. It accepts electrons from CymA and distributes them to a number of terminal oxidoreductases involved in the respiration of various compounds. STC is also involved in the electron transfer pathway to reduce nitrite by interaction with the octaheme tetrathionate reductase (OTR), but not with cytochrome c nitrite reductase (ccNiR). In the main pathway leading the metal respiration STC pairs with flavocytochrome c (FccA), the other major periplasmic cytochrome, which provides redundancy in this important pathway. The data reveals that the two proteins compete for the binding site at the surface of MtrA, the decaheme cytochrome inserted on the periplasmic side of the MtrCAB–OmcA outer-membrane complex. However, this is not observed for the MtrA homologues. Indeed, neither STC nor FccA interact with MtrD, the best replacement for MtrA, and only STC is able to interact with the decaheme cytochrome DmsE of the outer-membrane complex DmsEFABGH. Overall, these results shown that STC plays a central role in the anaerobic respiratory metabolism of SOMR-1. Nonetheless, the trans-periplasmic electron transfer chain is functionally resilient as a consequence of redundancies that arise from the presence of alternative pathways that bypass/compete with STC. PMID:26175726

A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.

PubMed

Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo

2015-07-01

In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.

Modeling and optimization of fermentation variables for enhanced production of lactase by isolated Bacillus subtilis strain VUVD001 using artificial neural networking and response surface methodology.

PubMed

Venkateswarulu, T C; Prabhakar, K Vidya; Kumar, R Bharath; Krupanidhi, S

2017-07-01

Modeling and optimization were performed to enhance production of lactase through submerged fermentation by Bacillus subtilis VUVD001 using artificial neural networks (ANN) and response surface methodology (RSM). The effect of process parameters namely temperature (°C), pH, and incubation time (h) and their combinational interactions on production was studied in shake flask culture by Box-Behnken design. The model was validated by conducting an experiment at optimized process variables which gave the maximum lactase activity of 91.32 U/ml. Compared to traditional activity, 3.48-folds improved production was obtained after RSM optimization. This study clearly shows that both RSM and ANN models provided desired predictions. However, compared with RSM (R 2  = 0.9496), the ANN model (R 2  = 0.99456) gave a better prediction for the production of lactase.

Analysing Health Professionals' Learning Interactions in an Online Social Network: A Longitudinal Study.

PubMed

Li, Xin; Verspoor, Karin; Gray, Kathleen; Barnett, Stephen

2016-01-01

This paper summarises a longitudinal analysis of learning interactions occurring over three years among health professionals in an online social network. The study employs the techniques of Social Network Analysis (SNA) and statistical modeling to identify the changes in patterns of interaction over time and test associated structural network effects. SNA results indicate overall low participation in the network, although some participants became active over time and even led discussions. In particular, the analysis has shown that a change of lead contributor results in a change in learning interaction and network structure. The analysis of structural network effects demonstrates that the interaction dynamics slow down over time, indicating that interactions in the network are more stable. The health professionals may be reluctant to share knowledge and collaborate in groups but were interested in building personal learning networks or simply seeking information.

Revealing hidden insect-fungus interactions; moderately specialized, modular and anti-nested detritivore networks.

PubMed

Jacobsen, Rannveig M; Sverdrup-Thygeson, Anne; Kauserud, Håvard; Birkemoe, Tone

2018-04-11

Ecological networks are composed of interacting communities that influence ecosystem structure and function. Fungi are the driving force for ecosystem processes such as decomposition and carbon sequestration in terrestrial habitats, and are strongly influenced by interactions with invertebrates. Yet, interactions in detritivore communities have rarely been considered from a network perspective. In the present study, we analyse the interaction networks between three functional guilds of fungi and insects sampled from dead wood. Using DNA metabarcoding to identify fungi, we reveal a diversity of interactions differing in specificity in the detritivore networks, involving three guilds of fungi. Plant pathogenic fungi were relatively unspecialized in their interactions with insects inhabiting dead wood, while interactions between the insects and wood-decay fungi exhibited the highest degree of specialization, which was similar to estimates for animal-mediated seed dispersal networks in previous studies. The low degree of specialization for insect symbiont fungi was unexpected. In general, the pooled insect-fungus networks were significantly more specialized, more modular and less nested than randomized networks. Thus, the detritivore networks had an unusual anti-nested structure. Future studies might corroborate whether this is a common aspect of networks based on interactions with fungi, possibly owing to their often intense competition for substrate. © 2018 The Author(s).

Network Physiology: How Organ Systems Dynamically Interact

PubMed Central

Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

2015-01-01

We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073

Experimenter's laboratory for visualized interactive science

NASA Technical Reports Server (NTRS)

Hansen, Elaine R.; Klemp, Marjorie K.; Lasater, Sally W.; Szczur, Marti R.; Klemp, Joseph B.

1992-01-01

The science activities of the 1990's will require the analysis of complex phenomena and large diverse sets of data. In order to meet these needs, we must take advantage of advanced user interaction techniques: modern user interface tools; visualization capabilities; affordable, high performance graphics workstations; and interoperable data standards and translator. To meet these needs, we propose to adopt and upgrade several existing tools and systems to create an experimenter's laboratory for visualized interactive science. Intuitive human-computer interaction techniques have already been developed and demonstrated at the University of Colorado. A Transportable Applications Executive (TAE+), developed at GSFC, is a powerful user interface tool for general purpose applications. A 3D visualization package developed by NCAR provides both color shaded surface displays and volumetric rendering in either index or true color. The Network Common Data Form (NetCDF) data access library developed by Unidata supports creation, access and sharing of scientific data in a form that is self-describing and network transparent. The combination and enhancement of these packages constitutes a powerful experimenter's laboratory capable of meeting key science needs of the 1990's. This proposal encompasses the work required to build and demonstrate this capability.

Experimenter's laboratory for visualized interactive science

NASA Technical Reports Server (NTRS)

Hansen, Elaine R.; Klemp, Marjorie K.; Lasater, Sally W.; Szczur, Marti R.; Klemp, Joseph B.

1993-01-01

The science activities of the 1990's will require the analysis of complex phenomena and large diverse sets of data. In order to meet these needs, we must take advantage of advanced user interaction techniques: modern user interface tools; visualization capabilities; affordable, high performance graphics workstations; and interoperatable data standards and translator. To meet these needs, we propose to adopt and upgrade several existing tools and systems to create an experimenter's laboratory for visualized interactive science. Intuitive human-computer interaction techniques have already been developed and demonstrated at the University of Colorado. A Transportable Applications Executive (TAE+), developed at GSFC, is a powerful user interface tool for general purpose applications. A 3D visualization package developed by NCAR provides both color-shaded surface displays and volumetric rendering in either index or true color. The Network Common Data Form (NetCDF) data access library developed by Unidata supports creation, access and sharing of scientific data in a form that is self-describing and network transparent. The combination and enhancement of these packages constitutes a powerful experimenter's laboratory capable of meeting key science needs of the 1990's. This proposal encompasses the work required to build and demonstrate this capability.

Critical factors in recruiting health maintenance organization physicians.

PubMed

Fisher, N B; Smith, H L; Pasternak, D P

1993-01-01

What factors facilitate successful physician recruiting by health care organizations? Answers surfaced in a study of physician recruiting by a large HMO in the Southwest. Professional networking and word-of-mouth advertising appear to be the prominent means by which physicians learn of attractive staff positions. Successful recruiting also depends on a practice setting that fosters quality care, emphasis on patient care delivery, and collegial interaction.

Water vapor adsorption on goethite.

PubMed

Song, Xiaowei; Boily, Jean-François

2013-07-02

Goethite (α-FeOOH) is an important mineral contributing to processes of atmospheric and terrestrial importance. Their interactions with water vapor are particularly relevant in these contexts. In this work, molecular details of water vapor (0.0-19.0 Torr; 0-96% relative humidity at 25 °C) adsorption at surfaces of synthetic goethite nanoparticles reacted with and without HCl and NaCl were resolved using vibrational spectroscopy. This technique probed interactions between surface (hydr)oxo groups and liquid water-like films. Molecular dynamics showed that structures and orientations adopted by these waters are comparable to those adopted at the interface with liquid water. Particle surfaces reacted with HCl accumulated less water than acid-free surfaces due to disruptions in hydrogen bond networks by chemisorbed waters and chloride. Particles reacted with NaCl had lower loadings below ∼10 Torr water vapor but greater loadings above this value than salt-free surfaces. Water adsorption reactions were here affected by competitive hydration of coexisting salt-free surface regions, adsorbed chloride and sodium, as well as precipitated NaCl. Collectively, the findings presented in this study add further insight into the initial mechanisms of thin water film formation at goethite surfaces subjected to variations in water vapor pressure that are relevant to natural systems.

Growth Anomalies in Supramolecular Networks: 4,4'-Biphenyldicarboxylic Acid on Cu(001)

NASA Astrophysics Data System (ADS)

Schwarz, Daniel; van Gastel, Raoul; Zandvliet, Harold J. W.; Poelsema, Bene

2013-02-01

We have used low energy electron microscopy to demonstrate how the interaction of 4,4'-biphenyldicarboxylic acid (BDA) molecules with (steps on) the Cu(001) surface determines the structure of supramolecular BDA networks on a mesoscopic length scale. Our in situ real time observations reveal that steps are permeable to individual molecules but that the change in crystal registry between different layers of the Cu substrate causes them to be completely impermeable to condensed BDA domains. The resulting growth instabilities determine the evolution of the domain shape and include a novel Mullins-Sekerka-type growth instability that is characterized by high growth rates along, instead of perpendicular to, the Cu steps. This growth instability is responsible for the majority of residual defects in the BDA networks.

CentNet—A deployable 100-station network for surface exchange research

NASA Astrophysics Data System (ADS)

Oncley, S.; Horst, T. W.; Semmer, S.; Militzer, J.; Maclean, G.; Knudson, K.

2014-12-01

Climate, air quality, atmospheric composition, surface hydrology, and ecological processes are directly affected by the Earth's surface. Complexity of this surface exists at multiple spatial scales, which complicates the understanding of these processes. NCAR/EOL currently provides a facility to the research community to make direct eddy-covariance flux observations to quantify surface-atmosphere interactions. However, just as model resolution has continued to increase, there is a need to increase the spatial density of flux measurements to capture the wide variety of scales that contribute to exchange processes close to the surface. NCAR/EOL now has developed the CentNet facility, that is envisioned to have on the order of 100 surface flux stations deployable for periods of months to years. Each station would measure standard meteorological variables, all components of the surface energy balance (including turbulence fluxes and radiation), atmospheric composition, and other quantities to characterize the surface. Thus, CentNet can support observational research in the biogeosciences, hydrology, urban meteorology, basic meteorology, and turbulence. CentNet has been designed to be adaptable to a wide variety of research problems while keeping operations manageable. Tower infrastructure has been designed to be lightweight, easily deployed, and with a minimal set-up footprint. CentNet uses sensor networks to increase spatial sampling at each station. The data system saves every sample on site to retain flexibility in data analysis. We welcome guidance on development and funding priorities as we build CentNet.

pH-Responsive Shape Memory Poly(ethylene glycol)-Poly(ε-caprolactone)-based Polyurethane/Cellulose Nanocrystals Nanocomposite.

PubMed

Li, Ying; Chen, Hongmei; Liu, Dian; Wang, Wenxi; Liu, Ye; Zhou, Shaobing

2015-06-17

In this study, we developed a pH-responsive shape-memory polymer nanocomposite by blending poly(ethylene glycol)-poly(ε-caprolactone)-based polyurethane (PECU) with functionalized cellulose nanocrystals (CNCs). CNCs were functionalized with pyridine moieties (CNC-C6H4NO2) through hydroxyl substitution of CNCs with pyridine-4-carbonyl chloride and with carboxyl groups (CNC-CO2H) via 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO) mediated surface oxidation, respectively. At a high pH value, the CNC-C6H4NO2 had attractive interactions from the hydrogen bonding between pyridine groups and hydroxyl moieties; at a low pH value, the interactions reduced or disappeared due to the protonation of pyridine groups, which are a Lewis base. The CNC-CO2H responded to pH variation in an opposite manner. The hydrogen bonding interactions of both CNC-C6H4NO2 and CNC-CO2H can be readily disassociated by altering pH values, endowing the pH-responsiveness of CNCs. When these functionalized CNCs were added in PECU polymer matrix to form nanocomposite network which was confirmed with rheological measurements, the mechanical properties of PECU were not only obviously improved but also the pH-responsiveness of CNCs could be transferred to the nanocomposite network. The pH-sensitive CNC percolation network in polymer matrix served as the switch units of shape-memory polymers (SMPs). Furthermore, the modified CNC percolation network and polymer molecular chains also had strong hydrogen bonding interactions among hydroxyl, carboxyl, pyridine moieties, and isocyanate groups, which could be formed or destroyed through changing pH value. The shape memory function of the nanocomposite network was only dependent on the pH variation of the environment. Therefore, this pH-responsive shape-memory nancomposite could be potentially developed into a new smart polymer material.

Specific non-monotonous interactions increase persistence of ecological networks.

PubMed

Yan, Chuan; Zhang, Zhibin

2014-03-22

The relationship between stability and biodiversity has long been debated in ecology due to opposing empirical observations and theoretical predictions. Species interaction strength is often assumed to be monotonically related to population density, but the effects on stability of ecological networks of non-monotonous interactions that change signs have not been investigated previously. We demonstrate that for four kinds of non-monotonous interactions, shifting signs to negative or neutral interactions at high population density increases persistence (a measure of stability) of ecological networks, while for the other two kinds of non-monotonous interactions shifting signs to positive interactions at high population density decreases persistence of networks. Our results reveal a novel mechanism of network stabilization caused by specific non-monotonous interaction types through either increasing stable equilibrium points or reducing unstable equilibrium points (or both). These specific non-monotonous interactions may be important in maintaining stable and complex ecological networks, as well as other networks such as genes, neurons, the internet and human societies.

Interaction Control to Synchronize Non-synchronizable Networks

PubMed Central

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-01-01

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks’ exact interaction topology and consequently have implications for biological and self-organizing technical systems. PMID:27853266

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

PubMed

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

2016-09-15

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

Deciphering microbial interactions and detecting keystone species with co-occurrence networks.

PubMed

Berry, David; Widder, Stefanie

2014-01-01

Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

Spectrin-ankyrin interaction mechanics: A key force balance factor in the red blood cell membrane skeleton.

PubMed

Saito, Masakazu; Watanabe-Nakayama, Takahiro; Machida, Shinichi; Osada, Toshiya; Afrin, Rehana; Ikai, Atsushi

2015-01-01

As major components of red blood cell (RBC) cytoskeleton, spectrin and F-actin form a network that covers the entire cytoplasmic surface of the plasma membrane. The cross-linked two layered structure, called the membrane skeleton, keeps the structural integrity of RBC under drastically changing mechanical environment during circulation. We performed force spectroscopy experiments on the atomic force microscope (AFM) as a means to clarify the mechanical characteristics of spectrin-ankyrin interaction, a key factor in the force balance of the RBC cytoskeletal structure. An AFM tip was functionalized with ANK1-62k and used to probe spectrin crosslinked to mica surface. A force spectroscopy study gave a mean unbinding force of ~30 pN under our experimental conditions. Two energy barriers were identified in the unbinding process. The result was related to the well-known flexibility of spectrin tetramer and participation of ankyrin 1-spectrin interaction in the overall balance of membrane skeleton dynamics. Copyright © 2015 Elsevier B.V. All rights reserved.

Structured teleconnections reveal the South American monsoon onset: A network approach

NASA Astrophysics Data System (ADS)

Ciemer, Catrin; Ekhtiari, Nikoo; Barbosa, Henrique; Boers, Niklas; Donner, Reik; Kurths, Jürgen; Rammig, Anja; Winkelmann, Ricarda

2017-04-01

The regional onset dates of the global monsoon systems are, to first order, determined by the seasonal shift of the intertropical convergence zone. However, precise onset dates vary substantially from year to year due to the complexity of the involved mechanisms. In this study, we investigate processes determining the onset of the South American monsoon system (SAMS). In recent years, a trend towards later onset dates of the SAMS has been observed. A later onset of the monsoon can have severe impacts on agriculture and infrastructure such as farming, water transport routes, and the stability of the Amazon rainforest in the long term. Possible reasons for this shift involve a multitude of climatic phenomena and variables relevant for the SAMS. To account for the highly interactive nature of the SAMS, we here investigate it with the help of complex networks. By studying the temporal changes of the correlation structure in spatial rainfall networks, we are able to determine coherent areas of similar precipitation patterns, spot teleconnections in terms of strongly correlated areas, detect key regions for precipitation correlations, and finally reveal the monsoon onset by an abrupt shift from an unordered to an ordered correlation structure of the network. To further evaluate the shift in the monsoon onset, we couple our rainfall network to a network of climate networks using sea surface temperature as a second variable. We are thereby able to emphasize oceanic regions that are particularly important for the SAMS and anticipate the influence of future changes of sea-surface temperature on the SAMS.

BrainNet Viewer: a network visualization tool for human brain connectomics.

PubMed

Xia, Mingrui; Wang, Jinhui; He, Yong

2013-01-01

The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

Effect of interaction strength on robustness of controlling edge dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pang, Shao-Peng; Hao, Fei

2018-05-01

Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

Nonlinear dynamics in the perceptual grouping of connected surfaces.

PubMed

Hock, Howard S; Schöner, Gregor

2016-09-01

Evidence obtained using the dynamic grouping method has shown that the grouping of an object's connected surfaces has properties characteristic of a nonlinear dynamical system. When a surface's luminance changes, one of its boundaries is perceived moving across the surface. The direction of this dynamic grouping (DG) motion indicates which of two flanking surfaces has been grouped with the changing surface. A quantitative measure of overall grouping strength (affinity) for adjacent surfaces is provided by the frequency of DG motion perception in directions promoted by the grouping variables. It was found that: (1) variables affecting surface grouping for three-surface objects evolve over time, settling at stable levels within a single fixation, (2) how often DG motion is perceived when a surface's luminance is perturbed (changed) depends on the pre-perturbation affinity state of the surface grouping, (3) grouping variables promoting the same surface grouping combine cooperatively and nonlinearly (super-additively) in determining the surface grouping's affinity, (4) different DG motion directions during different trials indicate that surface grouping can be bistable, which implies that inhibitory interactions have stabilized one of two alternative surface groupings, and (5) when alternative surface groupings have identical affinity, stochastic fluctuations can break the symmetry and inhibitory interactions can then stabilize one of the surface groupings, providing affinity levels are not too high (which results in bidirectional DG motion). A surface-grouping network is proposed within which boundaries vary in salience. Low salience or suppressed boundaries instantiate surface grouping, and DG motion results from changes in boundary salience. Copyright © 2015 Elsevier Ltd. All rights reserved.

An experimental point of view on hydration/solvation in halophilic proteins

PubMed Central

Talon, Romain; Coquelle, Nicolas; Madern, Dominique; Girard, Eric

2014-01-01

Protein-solvent interactions govern the behaviors of proteins isolated from extreme halophiles. In this work, we compared the solvent envelopes of two orthologous tetrameric malate dehydrogenases (MalDHs) from halophilic and non-halophilic bacteria. The crystal structure of the MalDH from the non-halophilic bacterium Chloroflexus aurantiacus (Ca MalDH) solved, de novo, at 1.7 Å resolution exhibits numerous water molecules in its solvation shell. We observed that a large number of these water molecules are arranged in pentagonal polygons in the first hydration shell of Ca MalDH. Some of them are clustered in large networks, which cover non-polar amino acid surface. The crystal structure of MalDH from the extreme halophilic bacterium Salinibacter ruber (Sr) solved at 1.55 Å resolution shows that its surface is strongly enriched in acidic amino acids. The structural comparison of these two models is the first direct observation of the relative impact of acidic surface enrichment on the water structure organization between a halophilic protein and its non-adapted counterpart. The data show that surface acidic amino acids disrupt pentagonal water networks in the hydration shell. These crystallographic observations are discussed with respect to halophilic protein behaviors in solution PMID:24600446

An experimental point of view on hydration/solvation in halophilic proteins.

PubMed

Talon, Romain; Coquelle, Nicolas; Madern, Dominique; Girard, Eric

2014-01-01

Protein-solvent interactions govern the behaviors of proteins isolated from extreme halophiles. In this work, we compared the solvent envelopes of two orthologous tetrameric malate dehydrogenases (MalDHs) from halophilic and non-halophilic bacteria. The crystal structure of the MalDH from the non-halophilic bacterium Chloroflexus aurantiacus (Ca MalDH) solved, de novo, at 1.7 Å resolution exhibits numerous water molecules in its solvation shell. We observed that a large number of these water molecules are arranged in pentagonal polygons in the first hydration shell of Ca MalDH. Some of them are clustered in large networks, which cover non-polar amino acid surface. The crystal structure of MalDH from the extreme halophilic bacterium Salinibacter ruber (Sr) solved at 1.55 Å resolution shows that its surface is strongly enriched in acidic amino acids. The structural comparison of these two models is the first direct observation of the relative impact of acidic surface enrichment on the water structure organization between a halophilic protein and its non-adapted counterpart. The data show that surface acidic amino acids disrupt pentagonal water networks in the hydration shell. These crystallographic observations are discussed with respect to halophilic protein behaviors in solution.

Identification of novel direct protein-protein interactions by irradiating living cells with femtosecond UV laser pulses.

PubMed

Itri, Francesco; Monti, Daria Maria; Chino, Marco; Vinciguerra, Roberto; Altucci, Carlo; Lombardi, Angela; Piccoli, Renata; Birolo, Leila; Arciello, Angela

2017-10-07

The identification of protein-protein interaction networks in living cells is becoming increasingly fundamental to elucidate main biological processes and to understand disease molecular bases on a system-wide level. We recently described a method (LUCK, Laser UV Cross-linKing) to cross-link interacting protein surfaces in living cells by UV laser irradiation. By using this innovative methodology, that does not require any protein modification or cell engineering, here we demonstrate that, upon UV laser irradiation of HeLa cells, a direct interaction between GAPDH and alpha-enolase was "frozen" by a cross-linking event. We validated the occurrence of this direct interaction by co-immunoprecipitation and Immuno-FRET analyses. This represents a proof of principle of the LUCK capability to reveal direct protein interactions in their physiological environment. Copyright © 2017 Elsevier Inc. All rights reserved.

Characterization of the Porphyromonas gingivalis Type IX Secretion Trans-envelope PorKLMNP Core Complex*

PubMed Central

Vincent, Maxence S.; Canestrari, Mickaël J.; Leone, Philippe; Stathopulos, Julien; Ize, Bérengère; Zoued, Abdelrahim; Cambillau, Christian; Kellenberger, Christine; Roussel, Alain

2017-01-01

The transport of proteins at the cell surface of Bacteroidetes depends on a secretory apparatus known as type IX secretion system (T9SS). This machine is responsible for the cell surface exposition of various proteins, such as adhesins, required for gliding motility in Flavobacterium, S-layer components in Tannerella forsythia, and tooth tissue-degrading enzymes in the oral pathogen Porphyromonas gingivalis. Although a number of subunits of the T9SS have been identified, we lack details on the architecture of this secretion apparatus. Here we provide evidence that five of the genes encoding the core complex of the T9SS are co-transcribed and that the gene products are distributed in the cell envelope. Protein-protein interaction studies then revealed that these proteins oligomerize and interact through a dense network of contacts. PMID:28057754

Weighted projected networks: mapping hypergraphs to networks.

PubMed

López, Eduardo

2013-05-01

Many natural, technological, and social systems incorporate multiway interactions, yet are characterized and measured on the basis of weighted pairwise interactions. In this article, I propose a family of models in which pairwise interactions originate from multiway interactions, by starting from ensembles of hypergraphs and applying projections that generate ensembles of weighted projected networks. I calculate analytically the statistical properties of weighted projected networks, and suggest ways these could be used beyond theoretical studies. Weighted projected networks typically exhibit weight disorder along links even for very simple generating hypergraph ensembles. Also, as the size of a hypergraph changes, a signature of multiway interaction emerges on the link weights of weighted projected networks that distinguishes them from fundamentally weighted pairwise networks. This signature could be used to search for hidden multiway interactions in weighted network data. I find the percolation threshold and size of the largest component for hypergraphs of arbitrary uniform rank, translate the results into projected networks, and show that the transition is second order. This general approach to network formation has the potential to shed new light on our understanding of weighted networks.

Inversion of surface parameters using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Olvera, J.; Fung, A. K.; Manry, M. T.

1992-01-01

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.

Electrical and galvanomagnetic properties of nanoporous carbon samples impregnated with bromine

NASA Astrophysics Data System (ADS)

Danishevskii, A. M.; Popov, V. V.; Kyutt, R. N.; Gordeev, S. K.

2013-07-01

Nanoporous carbon samples with a large specific surface area can be filled with heavier elements or their compounds, which makes it possible to investigate the interaction of their electronic subsystems with carbon. One of the elements convenient for filling pores of carbon materials is bromine. Impregnation of nanoporous carbon samples with bromine causes the occurrence of the processes of micropore filling, monolayer adsorption, and intercalation. It has been found that samples impregnated with bromine substantially change their electrical and galvanomagnetic properties, and these changes depend on the structure of the samples. It has been shown that, if in the skeleton of a porous carbon sample there is a fraction of graphite clusters, the impregnation of the sample with bromine increases the concentration of charged carriers (holes). But when the sample has a quasi-amorphous structure, the injection of bromine into the sample leads to the appearance of a certain concentration of electrons in addition to charged mobile holes of the initial sample; i.e., the electrical conductivity becomes bipolar. In the former case, bromine molecules intercalate graphite clusters and, since bromine is an acceptor during intercalation of graphite, the hole concentration in the carbon skeleton network increases. In the latter case, bromine molecules can only be adsorbed on pore walls. As a result, the adsorption interaction between the electron shells of bromine molecules and the carbon surface leads to the formation of a donor layer near the surface and to the generation of electrons in the carbon skeleton network.

Lavoisier: A Low Altitude Balloon Network for Probing the Deep Atmosphere and Surface of Venus

NASA Technical Reports Server (NTRS)

Chaasefiere, E.; Berthelier, J. J.; Bertaux, J.-L.; Quemerais, E.; Pommereau, J.-P.; Rannou, P.; Raulin, F.; Coll, P.; Coscia, D.; Jambon, A.;

The Monterey Ocean Observing System Development Program

NASA Astrophysics Data System (ADS)

Chaffey, M.; Graybeal, J. B.; O'Reilly, T.; Ryan, J.

2004-12-01

The Monterey Bay Aquarium Research Institute (MBARI) has a major development program underway to design, build, test and apply technology suitable to deep ocean observatories. The Monterey Ocean Observing System (MOOS) program is designed to form a large-scale instrument network that provides generic interfaces, intelligent instrument support, data archiving and near-real-time interaction for observatory experiments. The MOOS mooring system is designed as a portable surface mooring based seafloor observatory that provides data and power connections to both seafloor and ocean surface instruments through a specialty anchor cable. The surface mooring collects solar and wind energy for powering instruments and transmits data to shore-side researchers using a satellite communications modem. The use of a high modulus anchor cable to reach seafloor instrument networks is a high-risk development effort that is critical for the overall success of the portable observatory concept. An aggressive field test program off the California coast is underway to improve anchor cable constructions as well as end-to-end test overall system design. The overall MOOS observatory systems view is presented and the results of our field tests completed to date are summarized.

Molecular dynamics simulation of water at mineral surfaces: Structure, dynamics, energetics and hydrogen bonding

NASA Astrophysics Data System (ADS)

Kalinichev, A. G.; Wang, J.; Kirkpatrick, R.

2006-05-01

Fundamental molecular-level understanding of the properties of aqueous mineral interfaces is of great importance for many geochemical and environmental systems. Interaction between water and mineral surfaces substantially affects the properties of both phases, including the reactivity and functionality of the substrate surface, and the structure, dynamics, and energetics of the near surface aqueous phase. Experimental studies of interfacial water structure and dynamics using surface-sensitive techniques such as sum-frequency vibrational spectroscopy or X-ray and neutron reflectivity are not always possible for many practically important substrates, and their results often require interpretation concerning the atomistic mechanisms responsible for the observed behavior. Molecular computer simulations can provide new insight into the underlying molecular- level relationships between the inorganic substrate structure and composition and the structure, ordering, and dynamics of interfacial water. We have performed a series of molecular dynamics (MD) computer simulations of aqueous interfaces with several silicates (quartz, muscovite, and talc) and hydroxides (brucite, portlandite, gibbsite, Ca/Al and Mg/Al double hydroxides) to quantify the effects of the substrate mineral structure and composition on the structural, transport, and thermodynamic properties of water on these mineral surfaces. Due to the prevalent effects of the development of well-interconnected H-bonding networks across the mineral- water interfaces, all the hydroxide surfaces (including a fully hydroxylated quartz surface) show very similar H2O density profiles perpendicular to the interface. However, the predominant orientations of the interfacial H2O molecules and their detailed 2-dimensional near-surface structure and dynamics parallel to the interface are quite different reflecting the differences in the substrate structural charge distribution and the density and orientations of the surface OH groups. The H2O density profiles and other structural and dynamic characteristics of water at the two siloxane surfaces are very different from each other and from the hydroxide surfaces, since the muscovite surface is negatively charged and hydrophilic, while the talc surface is electrostatically neutral and hydrophobic. In general, at hydrophilic neutral surfaces both donating and accepting H-bonds from the H2O molecules are contributing to the development of the interfacial H-bond network, whereas at hydrophilic but charged surfaces only accepting or donating H-bonds with H2O molecules are possible. At the hydrophobic talc surface H-bonds among H2O molecules dominate the interfacial H-bond network and the water-surface interactions are very weak. The first water layer at all substrates is well ordered parallel to the surface, reflecting substrate crystal structures and indicating the reduced translational and orientational mobility of interfacial H2O molecules. At longer time scale (~100ps) their dynamics can be decomposed into a slow, virtually frozen, regime due to the substrate- bound H2O and a faster regime of almost free water reflecting the dynamics far from the surface. At shorter times (>10ps) the two dynamical regimes are superimposed. The much higher ordering of interfacial water (compared to bulk liquid) can not be adequately described as simply "ice-like". To some extent, it rather resembles the behavior of supercooled water.

ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation.

PubMed

Adeshina, A M; Hashim, R

2016-03-01

Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.

ConnectViz: Accelerated approach for brain structural connectivity using Delaunay triangulation.

PubMed

Adeshina, A M; Hashim, R

2015-02-06

Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using Compute Unified Device Architecture (CUDA), extending the previously proposed SurLens Visualization and Computer Aided Hepatocellular Carcinoma (CAHECA) frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, United States. Significantly, our proposed framework is able to generates and extracts points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.

Modeling and simulating networks of interdependent protein interactions.

PubMed

Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

2018-05-21

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package (https://bioconda.github.io).

A versatile system for processing geostationary satellite data with run-time visualization capability

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

Landsfeld, M.; Gautier, C.; Figel, T.

1995-01-01

To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. The authors are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government. The author`s contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface andmore » satellite observations and complex modeling of the interaction of radiation with clouds. One of the first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived. These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, the authors have produced an environment whereby they can easily modify and monitor the data processing as required. Through the principles of modular programming, they have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants.« less

Guiding neuron development with planar surface gradients of substrate cues deposited using microfluidic devices.

PubMed

Millet, Larry J; Stewart, Matthew E; Nuzzo, Ralph G; Gillette, Martha U

2010-06-21

Wiring the nervous system relies on the interplay of intrinsic and extrinsic signaling molecules that control neurite extension, neuronal polarity, process maturation and experience-dependent refinement. Extrinsic signals establish and enrich neuron-neuron interactions during development. Understanding how such extrinsic cues direct neurons to establish neural connections in vitro will facilitate the development of organized neural networks for investigating the development and function of nervous system networks. Producing ordered networks of neurons with defined connectivity in vitro presents special technical challenges because the results must be compliant with the biological requirements of rewiring neural networks. Here we demonstrate the ability to form stable, instructive surface-bound gradients of laminin that guide postnatal hippocampal neuron development in vitro. Our work uses a three-channel, interconnected microfluidic device that permits the production of adlayers of planar substrates through the combination of laminar flow, diffusion and physisorption. Through simple flow modifications, a variety of patterns and gradients of laminin (LN) and fluorescein isothiocyanate-conjugated poly-l-lysine (FITC-PLL) were deposited to present neurons with an instructive substratum to guide neuronal development. We present three variations in substrate design that produce distinct growth regimens for postnatal neurons in dispersed cell cultures. In the first approach, diffusion-mediated gradients of LN were formed on cover slips to guide neurons toward increasing LN concentrations. In the second approach, a combined gradient of LN and FITC-PLL was produced using aspiration-driven laminar flow to restrict neuronal growth to a 15 microm wide growth zone at the center of the two superimposed gradients. The last approach demonstrates the capacity to combine binary lines of FITC-PLL in conjunction with surface gradients of LN and bovine serum albumin (BSA) to produce substrate adlayers that provide additional levels of control over growth. This work demonstrates the advantages of spatio-temporal fluid control for patterning surface-bound gradients using a simple microfluidics-based substrate deposition procedure. We anticipate that this microfluidics-based patterning approach will provide instructive patterns and surface-bound gradients to enable a new level of control in guiding neuron development and network formation.

Deciphering microbial interactions and detecting keystone species with co-occurrence networks

PubMed Central

Berry, David; Widder, Stefanie

2014-01-01

Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets. PMID:24904535

Opto-Electronically Efficient Conjugated Polymers by Stress-Induced Molecular Constraints

DTIC Science & Technology

2012-07-15

TEM, JEOL JEM-2010) and checked by weight losses obtained from the thermogravimetric scans (TGA, Perkin-Elmer).[49-55] Scheme 1. Grafting P3HT...further analysis of the conduction pathways, e.g., the linear resistance networks,[40] but even without it, the jump frequency is predicted to...Nanocomposites: CNT Surface grafting, p-p interactions, and Gold Nanoparticles adsorption effect, Mater Thesis, Department of Materials Science and Engineering

Electrostatic-Interaction-Assisted Construction of 3D Networks of Manganese Dioxide Nanosheets for Flexible High-Performance Solid-State Asymmetric Supercapacitors.

PubMed

Liu, Na; Su, Yanli; Wang, Zhiqiang; Wang, Zhen; Xia, Jinsong; Chen, Yong; Zhao, Zhigang; Li, Qingwen; Geng, Fengxia

2017-08-22

A three-dimensional (3D) macroscopic network of manganese oxide (MnO 2 ) sheets was synthesized by an easily scalable solution approach, grafting the negatively charged surfaces of the MnO 2 sheets with an aniline monomer by electrostatic interactions followed by a quick chemical oxidizing polymerization reaction. The obtained structure possessed MnO 2 sheets interconnected with polyaniline chains, producing a 3D monolith rich in mesopores. The MnO 2 sheets had almost all their reactive centers exposed on the electrode surface, and combined with the electron transport highways provided by polyaniline and the shortened diffusion paths provided by the porous structure, the deliberately designed electrode achieved an excellent capacitance of 762 F g -1 at a current of 1 A g -1 and cycling performance with a capacity retention of 90% over 8000 cycles. Furthermore, a flexible asymmetric supercapacitor based on the constructed electrode and activated carbon serving as the positive and negative electrodes, respectively, was successfully fabricated, delivering a maximum energy density of 40.2 Wh kg -1 (0.113 Wh cm -2 ) and power density of 6227.0 W kg -1 (17.44 W cm -2 ) in a potential window of 0-1.7 V in a PVA/Na 2 SO 4 gel electrolyte.

Nonlinear Dynamics on Interconnected Networks

NASA Astrophysics Data System (ADS)

Arenas, Alex; De Domenico, Manlio

2016-06-01

Networks of dynamical interacting units can represent many complex systems, from the human brain to transportation systems and societies. The study of these complex networks, when accounting for different types of interactions has become a subject of interest in the last few years, especially because its representational power in the description of users' interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.) [1], or in representing different transportation modes in urban networks [2,3]. The general name coined for these networks is multilayer networks, where each layer accounts for a type of interaction (see Fig. 1).

Photonic crystal biosensor microplates with integrated fluid networks for high throughput applications in drug discovery

NASA Astrophysics Data System (ADS)

Choi, Charles J.; Chan, Leo L.; Pineda, Maria F.; Cunningham, Brian T.

2007-09-01

Assays used in pharmaceutical research require a system that can not only detect biochemical interactions with high sensitivity, but that can also perform many measurements in parallel while consuming low volumes of reagents. While nearly all label-free biosensor transducers to date have been interfaced with a flow channel, the liquid handling system is typically aligned and bonded to the transducer for supplying analytes to only a few sensors in parallel. In this presentation, we describe a fabrication approach for photonic crystal biosensors that utilizes nanoreplica molding to produce a network of sensors that are automatically self-aligned with a microfluidic network in a single process step. The sensor/fluid network is inexpensively produced on large surface areas upon flexible plastic substrates, allowing the device to be incorporated into standard format 96-well microplates. A simple flow scheme using hydrostatic pressure applied through a single control point enables immobilization of capture ligands upon a large number of sensors with 220 nL of reagent, and subsequent exposure of the sensors to test samples. A high resolution imaging detection instrument is capable of monitoring the binding within parallel channels at rates compatible with determining kinetic binding constants between the immobilized ligands and the analytes. The first implementation of this system is capable of monitoring the kinetic interactions of 11 flow channels at once, and a total of 88 channels within an integrated biosensor microplate in rapid succession. The system was initially tested to characterize the interaction between sets of proteins with known binding behavior.

Applications of Social Network Analysis

NASA Astrophysics Data System (ADS)

Thilagam, P. Santhi

A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

Characterizing the topology of probabilistic biological networks.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software implemented and the alignments found in this paper are available at http://bioinformatics.cise.ufl.edu/projects/probNet/.

Human Dopamine Receptors Interaction Network (DRIN): a systems biology perspective on topology, stability and functionality of the network.

PubMed

Podder, Avijit; Jatana, Nidhi; Latha, N

2014-09-21

Dopamine receptors (DR) are one of the major neurotransmitter receptors present in human brain. Malfunctioning of these receptors is well established to trigger many neurological and psychiatric disorders. Taking into consideration that proteins function collectively in a network for most of the biological processes, the present study is aimed to depict the interactions between all dopamine receptors following a systems biology approach. To capture comprehensive interactions of candidate proteins associated with human dopamine receptors, we performed a protein-protein interaction network (PPIN) analysis of all five receptors and their protein partners by mapping them into human interactome and constructed a human Dopamine Receptors Interaction Network (DRIN). We explored the topology of dopamine receptors as molecular network, revealing their characteristics and the role of central network elements. More to the point, a sub-network analysis was done to determine major functional clusters in human DRIN that govern key neurological pathways. Besides, interacting proteins in a pathway were characterized and prioritized based on their affinity for utmost drug molecules. The vulnerability of different networks to the dysfunction of diverse combination of components was estimated under random and direct attack scenarios. To the best of our knowledge, the current study is unique to put all five dopamine receptors together in a common interaction network and to understand the functionality of interacting proteins collectively. Our study pinpointed distinctive topological and functional properties of human dopamine receptors that have helped in identifying potential therapeutic drug targets in the dopamine interaction network. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ant-Plant Interaction in a Tropical Savanna: May the Network Structure Vary over Time and Influence on the Outcomes of Associations?

PubMed Central

Lange, Denise; Del-Claro, Kleber

2014-01-01

Plant-animal interactions occur in a community context of dynamic and complex ecological interactive networks. The understanding of who interacts with whom is a basic information, but the outcomes of interactions among associates are fundamental to draw valid conclusions about the functional structure of the network. Ecological networks studies in general gave little importance to know the true outcomes of interactions and how they may change over time. We evaluate the dynamic of an interaction network between ants and plants with extrafloral nectaries, by verifying the temporal variation in structure and outcomes of mutualism for the plant community (leaf herbivory). To reach this goal, we used two tools: bipartite network analysis and experimental manipulation. The networks exhibited the same general pattern as other mutualistic networks: nestedness, asymmetry and low specialization and this pattern was maintained over time, but with internal changes (species degree, connectance and ant abundance). These changes influenced the protection effectiveness of plants by ants, which varied over time. Our study shows that interaction networks between ants and plants are dynamic over time, and that these alterations affect the outcomes of mutualisms. In addition, our study proposes that the set of single systems that shape ecological networks can be manipulated for a greater understanding of the entire system. PMID:25141007

Modularity, pollination systems, and interaction turnover in plant-pollinator networks across space.

PubMed

Carstensen, Daniel W; Sabatino, Malena; Morellato, Leonor Patricia C

2016-05-01

Mutualistic interaction networks have been shown to be structurally conserved over space and time while pairwise interactions show high variability. In such networks, modularity is the division of species into compartments, or modules, where species within modules share more interactions with each other than they do with species from other modules. Such a modular structure is common in mutualistic networks and several evolutionary and ecological mechanisms have been proposed as underlying drivers. One prominent explanation is the existence of pollination syndromes where flowers tend to attract certain pollinators as determined by a set of traits. We investigate the modularity of seven community level plant-pollinator networks sampled in rupestrian grasslands, or campos rupestres, in SE Brazil. Defining pollination systems as corresponding groups of flower syndromes and pollinator functional groups, we test the two hypotheses that (1) interacting species from the same pollination system are more often assigned to the same module than interacting species from different pollination systems and; that (2) interactions between species from the same pollination system are more consistent across space than interactions between species from different pollination systems. Specifically we ask (1) whether networks are consistently modular across space; (2) whether interactions among species of the same pollination system occur more often inside modules, compared to interactions among species of different pollination systems, and finally; (3) whether the spatial variation in interaction identity, i.e., spatial interaction rewiring, is affected by trait complementarity among species as indicated by pollination systems. We confirm that networks are consistently modular across space and that interactions within pollination systems principally occur inside modules. Despite a strong tendency, we did not find a significant effect of pollination systems on the spatial consistency of pairwise interactions. These results indicate that the spatial rewiring of interactions could be constrained by pollination systems, resulting in conserved network structures in spite of high variation in pairwise interactions. Our findings suggest a relevant role of pollination systems in structuring plant-pollinator networks and we argue that structural patterns at the sub-network level can help us to fully understand how and why interactions vary across space and time.

Limitation of degree information for analyzing the interaction evolution in online social networks

NASA Astrophysics Data System (ADS)

Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

2014-04-01

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach.

PubMed

Zafar, Mohd; Van Vinh, N; Behera, Shishir Kumar; Park, Hung-Suck

2017-04-01

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box-Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand-metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model-genetic algorithm (RSM-GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47μg/g) is facilitated at 30.22mg C/L of EtOH with initial As(III) concentration of 196.77μg/L at pH5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM. Copyright © 2016. Published by Elsevier B.V.

Determination of the Interaction Position of Gamma Photons in Monolithic Scintillators Using Neural Network Fitting

NASA Astrophysics Data System (ADS)

Conde, P.; Iborra, A.; González, A. J.; Hernández, L.; Bellido, P.; Moliner, L.; Rigla, J. P.; Rodríguez-Álvarez, M. J.; Sánchez, F.; Seimetz, M.; Soriano, A.; Vidal, L. F.; Benlloch, J. M.

2016-02-01

In Positron Emission Tomography (PET) detectors based on monolithic scintillators, the photon interaction position needs to be estimated from the light distribution (LD) on the photodetector pixels. Due to the finite size of the scintillator volume, the symmetry of the LD is truncated everywhere except for the crystal center. This effect produces a poor estimation of the interaction positions towards the edges, an especially critical situation when linear algorithms, such as Center of Gravity (CoG), are used. When all the crystal faces are painted black, except the one in contact with the photodetector, the LD can be assumed to behave as the inverse square law, providing a simple theoretical model. Using this LD model, the interaction coordinates can be determined by means of fitting each event to a theoretical distribution. In that sense, the use of neural networks (NNs) has been shown to be an effective alternative to more traditional fitting techniques as nonlinear least squares (LS). The multilayer perceptron is one type of NN which can model non-linear functions well and can be trained to accurately generalize when presented with new data. In this work we have shown the capability of NNs to approximate the LD and provide the interaction coordinates of γ-photons with two different photodetector setups. One experimental setup was based on analog Silicon Photomultipliers (SiPMs) and a charge division diode network, whereas the second setup was based on digital SiPMs (dSiPMs). In both experiments NNs minimized border effects. Average spatial resolutions of 1.9 ±0.2 mm and 1.7 ±0.2 mm for the entire crystal surface were obtained for the analog and dSiPMs approaches, respectively.

Salt-bridge networks within globular and disordered proteins: characterizing trends for designable interactions.

PubMed

Basu, Sankar; Mukharjee, Debasish

2017-07-01

There has been considerable debate about the contribution of salt bridges to the stabilization of protein folds, in spite of their participation in crucial protein functions. Salt bridges appear to contribute to the activity-stability trade-off within proteins by bringing high-entropy charged amino acids into close contacts during the course of their functions. The current study analyzes the modes of association of salt bridges (in terms of networks) within globular proteins and at protein-protein interfaces. While the most common and trivial type of salt bridge is the isolated salt bridge, bifurcated salt bridge appears to be a distinct salt-bridge motif having a special topology and geometry. Bifurcated salt bridges are found ubiquitously in proteins and interprotein complexes. Interesting and attractive examples presenting different modes of interaction are highlighted. Bifurcated salt bridges appear to function as molecular clips that are used to stitch together large surface contours at interacting protein interfaces. The present work also emphasizes the key role of salt-bridge-mediated interactions in the partial folding of proteins containing long stretches of disordered regions. Salt-bridge-mediated interactions seem to be pivotal to the promotion of "disorder-to-order" transitions in small disordered protein fragments and their stabilization upon binding. The results obtained in this work should help to guide efforts to elucidate the modus operandi of these partially disordered proteins, and to conceptualize how these proteins manage to maintain the required amount of disorder even in their bound forms. This work could also potentially facilitate explorations of geometrically specific designable salt bridges through the characterization of composite salt-bridge networks. Graphical abstract ᅟ.

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.

Assessing the Increase in Specific Surface Area for Electrospun Fibrous Network due to Pore Induction.

PubMed

Katsogiannis, Konstantinos Alexandros G; Vladisavljević, Goran T; Georgiadou, Stella; Rahmani, Ramin

2016-10-26

The effect of pore induction on increasing electrospun fibrous network specific surface area was investigated in this study. Theoretical models based on the available surface area of the fibrous network and exclusion of the surface area lost due to fiber-to-fiber contacts were developed. The models for calculation of the excluded area are based on Hertzian, Derjaguin-Muller-Toporov (DMT), and Johnson-Kendall-Roberts (JKR) contact models. Overall, the theoretical models correlated the network specific surface area to the material properties including density, surface tension, Young's modulus, Poisson's ratio, as well as network physical properties, such as density and geometrical characteristics including fiber radius, fiber aspect ratio and network thickness. Pore induction proved to increase the network specific surface area up to 52%, compared to the maximum surface area that could be achieved by nonporous fiber network with the same physical properties and geometrical characteristics. The model based on Johnson-Kendall-Roberts contact model describes accurately the fiber-to-fiber contact area under the experimental conditions used for pore generation. The experimental results and the theoretical model based on Johnson-Kendall-Roberts contact model show that the increase in network surface area due to pore induction can reach to up to 58%.

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

PubMed Central

Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby-Joe; Hon, Gary C; Myers, Chad L; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G; Ideker, Trey; Dolinski, Kara; Batada, Nizar N; Tyers, Mike

2006-01-01

Background The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID () and SGD () databases. Conclusion Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks. PMID:16762047

Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast

PubMed Central

Ye, Ping; Peyser, Brian D; Spencer, Forrest A; Bader, Joel S

2005-01-01

Background In a genetic interaction, the phenotype of a double mutant differs from the combined phenotypes of the underlying single mutants. When the single mutants have no growth defect, but the double mutant is lethal or exhibits slow growth, the interaction is termed synthetic lethality or synthetic fitness. These genetic interactions reveal gene redundancy and compensating pathways. Recently available large-scale data sets of genetic interactions and protein interactions in Saccharomyces cerevisiae provide a unique opportunity to elucidate the topological structure of biological pathways and how genes function in these pathways. Results We have defined congruent genes as pairs of genes with similar sets of genetic interaction partners and constructed a genetic congruence network by linking congruent genes. By comparing path lengths in three types of networks (genetic interaction, genetic congruence, and protein interaction), we discovered that high genetic congruence not only exhibits correlation with direct protein interaction linkage but also exhibits commensurate distance with the protein interaction network. However, consistent distances were not observed between genetic and protein interaction networks. We also demonstrated that congruence and protein networks are enriched with motifs that indicate network transitivity, while the genetic network has both transitive (triangle) and intransitive (square) types of motifs. These results suggest that robustness of yeast cells to gene deletions is due in part to two complementary pathways (square motif) or three complementary pathways, any two of which are required for viability (triangle motif). Conclusion Genetic congruence is superior to genetic interaction in prediction of protein interactions and function associations. Genetically interacting pairs usually belong to parallel compensatory pathways, which can generate transitive motifs (any two of three pathways needed) or intransitive motifs (either of two pathways needed). PMID:16283923

Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird-plant network.

PubMed

Vizentin-Bugoni, Jeferson; Maruyama, Pietro Kiyoshi; Sazima, Marlies

2014-04-07

Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird-plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought.

Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird–plant network

PubMed Central

Vizentin-Bugoni, Jeferson; Maruyama, Pietro Kiyoshi; Sazima, Marlies

2014-01-01

Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird–plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought. PMID:24552835

Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasites.

PubMed

Liu, Xuewu; Huang, Yuxiao; Liang, Jiao; Zhang, Shuai; Li, Yinghui; Wang, Jun; Shen, Yan; Xu, Zhikai; Zhao, Ya

2014-11-30

The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Although several interactions between human and parasite proteins have been discovered, the mechanism related to invasion remains poorly understood because numerous human-parasite protein interactions have not yet been identified. High-throughput screening experiments are not feasible for malarial parasites due to difficulty in expressing the parasite proteins. Here, we performed computational prediction of the PPIs involved in malaria parasite invasion to elucidate the mechanism by which invasion occurs. In this study, an expectation maximization algorithm was used to estimate the probabilities of domain-domain interactions (DDIs). Estimates of DDI probabilities were then used to infer PPI probabilities. We found that our prediction performance was better than that based on the information of D. melanogaster alone when information related to the six species was used. Prediction performance was assessed using protein interaction data from S. cerevisiae, indicating that the predicted results were reliable. We then used the estimates of DDI probabilities to infer interactions between 490 parasite and 3,787 human membrane proteins. A small-scale dataset was used to illustrate the usability of our method in predicting interactions between human and parasite proteins. The positive predictive value (PPV) was lower than that observed in S. cerevisiae. We integrated gene expression data to improve prediction accuracy and to reduce false positives. We identified 80 membrane proteins highly expressed in the schizont stage by fast Fourier transform method. Approximately 221 erythrocyte membrane proteins were identified using published mass spectral datasets. A network consisting of 205 interactions was predicted. Results of network analysis suggest that SNARE proteins of parasites and APP of humans may function in the invasion of RBCs by parasites. We predicted a small-scale PPI network that may be involved in parasite invasion of RBCs by integrating DDI information and expression profiles. Experimental studies should be conducted to validate the predicted interactions. The predicted PPIs help elucidate the mechanism of parasite invasion and provide directions for future experimental investigations.

Geomorphic Mapping and Paleoterrain Generation for use in Modeling Holocene (8,000 1,500 yr) Agropastoral Landuse and Landscape Interactions in Southeast Spain

NASA Astrophysics Data System (ADS)

Arrowsmith, J. R.; Dimaggio, E. N.; Barton, C. M.; Sarjoughian, H. S.; Fall, P.; Falconer, S. E.; Ullah, I. I.

2006-12-01

Dramatic changes in land use were associated with the rise of agriculture in the mid Holocene. Both the surface properties and the drainage networks were changed. Along with the direct modifications to surface properties (vegetation change, sediment liberation, and compaction) and drainage network alteration (terracing, canals), up and downstream responses in the watersheds communicated these changes throughout the landscape. The magnitude, rate, and feedbacks with the growing human populations are critical questions in our effort to assess human-landscape interactions. Our interdisciplinary team has focused on two field sites around the Mediterranean for model development and testing. We are combining high resolution process- based models of landscape change implemented within the GRASS GIS with agent based models of agropastoral behavior and driven by high resolution climate and vegetation models. In the Spanish field area (Penaguila Valley, 38.41 N 0.23 W), we have produced detailed (1:10,000) geomorphic maps which we combine with high resolution Digital Elevation Models (DEMs) on which we can run the surface process models to assess the portions of the landscape that are most sensitive to the postulated agropastoral landuse changes. To support this modeling we have produced the 1 m DEMs from softcopy photogrammetry. This DEM has greatly improved our overall spatial resolution to permit more accurate terrace correlations and improved quantitative assessment of morphologic processes (e.g. channel erosion, slope stability). In stereo, we have mapped overall landscape morphology that emphasizes areas of active erosion and alluvial terrace surfaces. Alluvial terraces are crucial to this research because they record periods of past stable topography and those of mid Holocene age were settled and farmed. We have correlated mapped terraces across the landscape using elevation and morphological distinctions. Using ArcGIS, we interpolated surfaces across equivalent terraces using triangulated irregular networks (TINs) allowing reconstruction of multiple regional landscapes to establish a chronosequence of absolute landscape change. This mapping and reconstruction will be field checked and numerical age constraints applied. Interestingly, our tentative age assessment of the lowest broad surface indicates that it was occupied about 5 ka, and now has been incised by 20 m. Archeological sites have been cut by the incision. This change from a broad low relief alluvial surface to one cut by narrow channels may have been an important change for the local populations and caused them to change their behaviors, even though it may have been initially triggered by distributed landscape change in the watershed, due to agropastoral activities.

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Patterns and drivers for wetland connections in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Christensen, Jay R.; Alexander, Laurie C.

2017-01-01

Ecosystem function in rivers, lakes and coastal waters depends on the functioning of upstream aquatic ecosystems, necessitating an improved understanding of watershed-scale interactions including variable surface-water flows between wetlands and streams. As surface water in the Prairie Pothole Region expands in wet years, surface-water connections occur between many depressional wetlands and streams. Minimal research has explored the spatial patterns and drivers for the abundance of these connections, despite their potential to inform resource management and regulatory programs including the U.S. Clean Water Act. In this study, wetlands were identified that did not intersect the stream network, but were shown with Landsat images (1990–2011) to become merged with the stream network as surface water expanded. Wetlands were found to spill into or consolidate with other wetlands within both small (2–10 wetlands) and large (>100 wetlands) wetland clusters, eventually intersecting a stream channel, most often via a riparian wetland. These surface-water connections occurred over a wide range of wetland distances from streams (averaging 90–1400 m in different ecoregions). Differences in the spatial abundance of wetlands that show a variable surface-water connection to a stream were best explained by smaller wetland-to-wetland distances, greater wetland abundance, and maximum surface-water extent. This analysis demonstrated that wetland arrangement and surface water expansion are important mechanisms for depressional wetlands to connect to streams and provides a first step to understanding the frequency and abundance of these surface-water connections across the Prairie Pothole Region.

Host-Guest Chemistry in Integrated Porous Space Formed by Molecular Self-Assembly at Liquid-Solid Interfaces.

PubMed

Iritani, Kohei; Tahara, Kazukuni; De Feyter, Steven; Tobe, Yoshito

2017-05-16

Host-guest chemistry in two-dimensional (2D) space, that is, physisorbed monolayers of a single atom or a single molecular thickness on surfaces, has become a subject of intense current interest because of perspectives for various applications in molecular-scale electronics, selective sensors, and tailored catalysis. Scanning tunneling microscopy has been used as a powerful tool for the visualization of molecules in real space on a conducting substrate surface. For more than a decade, we have been investigating the self-assembly of a series of triangle-shaped phenylene-ethynylene macrocycles called dehydrobenzo[12]annulenes (DBAs). These molecules are substituted with six alkyl chains and are capable of forming hexagonal porous 2D molecular networks via van der Waals interactions between interdigitated alkyl chains at the interface of organic solvents and graphite. The dimension of the nanoporous space or nanowell formed by the self-assembly of DBAs can be controlled from 1.6 to 4.7 nm by simply changing the alkyl chain length from C 6 to C 20 . Single molecules as well as homoclusters and heteroclusters are capable of coadsorbing within the host matrix using shape- and size-complementarity principles. Moreover, on the basis of the versatility of the DBA molecules that allows chemical modification of the alkyl chain terminals, we were able to decorate the interior space of the nanoporous networks with functional groups such as azobenzenedicarboxylic acid for photoresponsive guest adsorption/desorption or fluoroalkanes and tetraethylene glycol groups for selective guest binding by electrostatic interactions and zinc-porphyrin units for complexation with a guest by charge-transfer interactions. In this Feature Article, we describe the general aspects of molecular self-assembly at liquid/solid interfaces, followed by the formation of programmed porous molecular networks using rationally designed molecular building blocks. We focus on our own work involving host-guest chemistry in integrated nanoporous space that is modified for specific purposes.

Numerical study of groundwater flow cycling controlled by seawater/freshwater interaction in a coastal karst aquifer through conduit network using CFPv2.

PubMed

Xu, Zexuan; Hu, Bill X; Davis, Hal; Kish, Stephen

2015-11-01

In this study, a groundwater flow cycling in a karst springshed and an interaction between two springs, Spring Creek Springs and Wakulla Springs, through a subground conduit network are numerically simulated using CFPv2, the latest research version of MODFLOW-CFP (Conduit Flow Process). The Spring Creek Springs and Wakulla Springs, located in a marine estuary and 11 miles inland, respectively, are two major groundwater discharge spots in the Woodville Karst Plain (WKP), North Florida, USA. A three-phase conceptual model of groundwater flow cycling between the two springs and surface water recharge from a major surface creek (Lost Creek) was proposed in various rainfall conditions. A high permeable subground karst conduit network connecting the two springs was found by tracer tests and cave diving. Flow rate of discharge, salinity, sea level and tide height at Spring Creek Springs could significantly affect groundwater discharge and water stage at Wakulla Springs simultaneously. Based on the conceptual model, a numerical hybrid discrete-continuum groundwater flow model is developed using CFPv2 and calibrated by field measurements. Non-laminar flows in conduits and flow exchange between conduits and porous medium are implemented in the hybrid coupling numerical model. Time-variable salinity and equivalent freshwater head boundary conditions at the submarine spring as well as changing recharges have significant impacts on seawater/freshwater interaction and springs' discharges. The developed numerical model is used to simulate the dynamic hydrological process and quantitatively represent the three-phase conceptual model from June 2007 to June 2010. Simulated results of two springs' discharges match reasonably well to measurements with correlation coefficients 0.891 and 0.866 at Spring Creeks Springs and Wakulla Springs, respectively. The impacts of sea level rise on regional groundwater flow field and relationship between the inland springs and submarine springs are evaluated as well in this study. Copyright © 2015 Elsevier B.V. All rights reserved.

Numerical study of groundwater flow cycling controlled by seawater/freshwater interaction in a coastal karst aquifer through conduit network using CFPv2

NASA Astrophysics Data System (ADS)

Xu, Zexuan; Hu, Bill X.; Davis, Hal; Kish, Stephen

2015-11-01

In this study, a groundwater flow cycling in a karst springshed and an interaction between two springs, Spring Creek Springs and Wakulla Springs, through a subground conduit network are numerically simulated using CFPv2, the latest research version of MODFLOW-CFP (Conduit Flow Process). The Spring Creek Springs and Wakulla Springs, located in a marine estuary and 11 miles inland, respectively, are two major groundwater discharge spots in the Woodville Karst Plain (WKP), North Florida, USA. A three-phase conceptual model of groundwater flow cycling between the two springs and surface water recharge from a major surface creek (Lost Creek) was proposed in various rainfall conditions. A high permeable subground karst conduit network connecting the two springs was found by tracer tests and cave diving. Flow rate of discharge, salinity, sea level and tide height at Spring Creek Springs could significantly affect groundwater discharge and water stage at Wakulla Springs simultaneously. Based on the conceptual model, a numerical hybrid discrete-continuum groundwater flow model is developed using CFPv2 and calibrated by field measurements. Non-laminar flows in conduits and flow exchange between conduits and porous medium are implemented in the hybrid coupling numerical model. Time-variable salinity and equivalent freshwater head boundary conditions at the submarine spring as well as changing recharges have significant impacts on seawater/freshwater interaction and springs' discharges. The developed numerical model is used to simulate the dynamic hydrological process and quantitatively represent the three-phase conceptual model from June 2007 to June 2010. Simulated results of two springs' discharges match reasonably well to measurements with correlation coefficients 0.891 and 0.866 at Spring Creeks Springs and Wakulla Springs, respectively. The impacts of sea level rise on regional groundwater flow field and relationship between the inland springs and submarine springs are evaluated as well in this study.

User interaction in smart ambient environment targeted for senior citizen.

PubMed

Pulli, Petri; Hyry, Jaakko; Pouke, Matti; Yamamoto, Goshiro

2012-11-01

Many countries are facing a problem when the age-structure of the society is changing. The numbers of senior citizen are rising rapidly, and caretaking personnel numbers cannot match the problems and needs of these citizens. Using smart, ubiquitous technologies can offer ways in coping with the need of more nursing staff and the rising costs of taking care of senior citizens for the society. Helping senior citizens with a novel, easy to use interface that guides and helps, could improve their quality of living and make them participate more in daily activities. This paper presents a projection-based display system for elderly people with memory impairments and the proposed user interface for the system. The user's process recognition based on a sensor network is also described. Elderly people wearing the system can interact the projected user interface by tapping physical surfaces (such as walls, tables, or doors) using them as a natural, haptic feedback input surface.

Building Complex Kondo Impurities by Manipulating Entangled Spin Chains.

PubMed

Choi, Deung-Jang; Robles, Roberto; Yan, Shichao; Burgess, Jacob A J; Rolf-Pissarczyk, Steffen; Gauyacq, Jean-Pierre; Lorente, Nicolás; Ternes, Markus; Loth, Sebastian

2017-10-11

The creation of molecule-like structures in which magnetic atoms interact controllably is full of potential for the study of complex or strongly correlated systems. Here, we create spin chains in which a strongly correlated Kondo state emerges from magnetic coupling of transition-metal atoms. We build chains up to ten atoms in length by placing Fe and Mn atoms on a Cu 2 N surface with a scanning tunneling microscope. The atoms couple antiferromagnetically via superexchange interaction through the nitrogen atom network of the surface. The emergent Kondo resonance is spatially distributed along the chain. Its strength can be controlled by mixing atoms of different transition metal elements and manipulating their spatial distribution. We show that the Kondo screening of the full chain by the electrons of the nonmagnetic substrate depends on the interatomic entanglement of the spins in the chain, demonstrating the prerequisites to build and probe spatially extended strongly correlated nanostructures.

Surface folding-induced attraction and motion of particles in a soft elastic gel: cooperative effects of surface tension, elasticity, and gravity.

PubMed

Chakrabarti, Aditi; Chaudhury, Manoj K

2013-12-17

We report some experimental observations regarding a new type of long-range interaction between rigid particles that prevails when they are suspended in an ultrasoft elastic gel. A denser particle submerges itself to a considerable depth inside the gel and becomes elasto-buoyant by balancing its weight against the elastic force exerted by the surrounding medium. By virtue of a large elasto-capillary length, the surface of the gel wraps around the particle and closes to create a line singularity connecting the particle to the free surface of the gel. A substantial amount of tensile strain is thus developed in the gel network parallel to the free surface that penetrates to a significant depth inside the gel. The field of this tensile strain is rather long-range because of a large gravito-elastic correlation length and sufficiently strong to pull two submerged particles into contact. The particles move toward each other with an effective force following an inverse linear distance law. When more monomers or dimers of the particles are released inside the gel, they orient rather freely inside the capsules where they are located and attract each other to form closely packed clusters. Eventually, these clusters themselves interact and coalesce. This is an emergent phenomenon in which gravity, capillarity, and elasticity work in tandem to create a long-range interaction. We also present the results of a related experiment, in which a particle suspended inside a thickness-graded gel moves accompanied by the continuous folding and the relaxation of the gel's surface.

Computational design of protein interactions: designing proteins that neutralize influenza by inhibiting its hemagglutinin surface protein

NASA Astrophysics Data System (ADS)

Fleishman, Sarel

2012-02-01

Molecular recognition underlies all life processes. Design of interactions not seen in nature is a test of our understanding of molecular recognition and could unlock the vast potential of subtle control over molecular interaction networks, allowing the design of novel diagnostics and therapeutics for basic and applied research. We developed the first general method for designing protein interactions. The method starts by computing a region of high affinity interactions between dismembered amino acid residues and the target surface and then identifying proteins that can harbor these residues. Designs are tested experimentally for binding the target surface and successful ones are affinity matured using yeast cell surface display. Applied to the conserved stem region of influenza hemagglutinin we designed two unrelated proteins that, following affinity maturation, bound hemagglutinin at subnanomolar dissociation constants. Co-crystal structures of hemagglutinin bound to the two designed binders were within 1Angstrom RMSd of their models, validating the accuracy of the design strategy. One of the designed proteins inhibits the conformational changes that underlie hemagglutinin's cell-invasion functions and blocks virus infectivity in cell culture, suggesting that such proteins may in future serve as diagnostics and antivirals against a wide range of pathogenic influenza strains. We have used this method to obtain experimentally validated binders of several other target proteins, demonstrating the generality of the approach. We discuss the combination of modeling and high-throughput characterization of design variants which has been key to the success of this approach, as well as how we have used the data obtained in this project to enhance our understanding of molecular recognition. References: Science 332:816 JMB, in press Protein Sci 20:753

Convergent transmission of RNAi guide-target mismatch information across Argonaute internal allosteric network.

PubMed

Joseph, Thomas T; Osman, Roman

2012-01-01

In RNA interference, a guide strand derived from a short dsRNA such as a microRNA (miRNA) is loaded into Argonaute, the central protein in the RNA Induced Silencing Complex (RISC) that silences messenger RNAs on a sequence-specific basis. The positions of any mismatched base pairs in an miRNA determine which Argonaute subtype is used. Subsequently, the Argonaute-guide complex binds and silences complementary target mRNAs; certain Argonautes cleave the target. Mismatches between guide strand and the target mRNA decrease cleavage efficiency. Thus, loading and silencing both require that signals about the presence of a mismatched base pair are communicated from the mismatch site to effector sites. These effector sites include the active site, to prevent target cleavage; the binding groove, to modify nucleic acid binding affinity; and surface allosteric sites, to control recruitment of additional proteins to form the RISC. To examine how such signals may be propagated, we analyzed the network of internal allosteric pathways in Argonaute exhibited through correlations of residue-residue interactions. The emerging network can be described as a set of pathways emanating from the core of the protein near the active site, distributed into the bulk of the protein, and converging upon a distributed cluster of surface residues. Nucleotides in the guide strand "seed region" have a stronger relationship with the protein than other nucleotides, concordant with their importance in sequence selectivity. Finally, any of several seed region guide-target mismatches cause certain Argonaute residues to have modified correlations with the rest of the protein. This arises from the aggregation of relatively small interaction correlation changes distributed across a large subset of residues. These residues are in effector sites: the active site, binding groove, and surface, implying that direct functional consequences of guide-target mismatches are mediated through the cumulative effects of a large number of internal allosteric pathways.

Convergent Transmission of RNAi Guide-Target Mismatch Information across Argonaute Internal Allosteric Network

PubMed Central

Joseph, Thomas T.; Osman, Roman

2012-01-01

In RNA interference, a guide strand derived from a short dsRNA such as a microRNA (miRNA) is loaded into Argonaute, the central protein in the RNA Induced Silencing Complex (RISC) that silences messenger RNAs on a sequence-specific basis. The positions of any mismatched base pairs in an miRNA determine which Argonaute subtype is used. Subsequently, the Argonaute-guide complex binds and silences complementary target mRNAs; certain Argonautes cleave the target. Mismatches between guide strand and the target mRNA decrease cleavage efficiency. Thus, loading and silencing both require that signals about the presence of a mismatched base pair are communicated from the mismatch site to effector sites. These effector sites include the active site, to prevent target cleavage; the binding groove, to modify nucleic acid binding affinity; and surface allosteric sites, to control recruitment of additional proteins to form the RISC. To examine how such signals may be propagated, we analyzed the network of internal allosteric pathways in Argonaute exhibited through correlations of residue-residue interactions. The emerging network can be described as a set of pathways emanating from the core of the protein near the active site, distributed into the bulk of the protein, and converging upon a distributed cluster of surface residues. Nucleotides in the guide strand “seed region” have a stronger relationship with the protein than other nucleotides, concordant with their importance in sequence selectivity. Finally, any of several seed region guide-target mismatches cause certain Argonaute residues to have modified correlations with the rest of the protein. This arises from the aggregation of relatively small interaction correlation changes distributed across a large subset of residues. These residues are in effector sites: the active site, binding groove, and surface, implying that direct functional consequences of guide-target mismatches are mediated through the cumulative effects of a large number of internal allosteric pathways. PMID:23028290

Co-crystal formation between two organic solids on the surface of Titan

NASA Astrophysics Data System (ADS)

Cable, M. L.; Vu, T. H.; Maynard-Casely, H. E.; Hodyss, R. P.

2017-12-01

Laboratory experiments of Titan molecular materials, informed by modeling, can help us to understand the complex and dynamic surface processes occurring on this moon at cryogenic temperatures. We previously demonstrated that two common organic materials on Titan, ethane and benzene, form a unique and stable co-crystalline structure at Titan surface temperatures. We have now characterized a second co-crystal that is stable on Titan, this time between two solids: acetylene and ammonia. The co-crystal forms within minutes at Titan surface temperature, as evidenced by new Raman spectral features in the lattice vibration and C-H bending regions. In addition, a red shift of the C-H stretching mode suggests that the acetylene-ammonia co-crystal is stabilized by a network of C-H···N interactions. Thermal stability studies indicate that this co-crystal remains intact to >110 K, and experiments with liquid methane and ethane reveal the co-crystal to be resistant to fluvial or pluvial exposure. Non-covalently bound structures such as these co-crystals point to far more complex surface interactions than previously believed on Titan. New physical and mechanical properties (deformation, plasticity, density, etc.), differences in storage of key species (i.e., ethane versus methane), variations in surface transport and new chemical gradients can all result in diverse surface features and chemistries of astrobiological interest.

Seamless growth of a supramolecular carpet

PubMed Central

Kim, Ju-Hyung; Ribierre, Jean-Charles; Yang, Yu Seok; Adachi, Chihaya; Kawai, Maki; Jung, Jaehoon; Fukushima, Takanori; Kim, Yousoo

2016-01-01

Organic/metal interfaces play crucial roles in the formation of intermolecular networks on metal surfaces and the performance of organic devices. Although their purity and uniformity have profound effects on the operation of organic devices, the formation of organic thin films with high interfacial uniformity on metal surfaces has suffered from the intrinsic limitation of molecular ordering imposed by irregular surface structures. Here we demonstrate a supramolecular carpet with widely uniform interfacial structure and high adaptability on a metal surface via a one-step process. The high uniformity is achieved with well-balanced interfacial interactions and site-specific molecular rearrangements, even on a pre-annealed amorphous gold surface. Co-existing electronic structures show selective availability corresponding to the energy region and the local position of the system. These findings provide not only a deeper insight into organic thin films with high structural integrity, but also a new way to tailor interfacial geometric and electronic structures. PMID:26839053

Differential C3NET reveals disease networks of direct physical interactions

PubMed Central

2011-01-01

Background Genes might have different gene interactions in different cell conditions, which might be mapped into different networks. Differential analysis of gene networks allows spotting condition-specific interactions that, for instance, form disease networks if the conditions are a disease, such as cancer, and normal. This could potentially allow developing better and subtly targeted drugs to cure cancer. Differential network analysis with direct physical gene interactions needs to be explored in this endeavour. Results C3NET is a recently introduced information theory based gene network inference algorithm that infers direct physical gene interactions from expression data, which was shown to give consistently higher inference performances over various networks than its competitors. In this paper, we present, DC3net, an approach to employ C3NET in inferring disease networks. We apply DC3net on a synthetic and real prostate cancer datasets, which show promising results. With loose cutoffs, we predicted 18583 interactions from tumor and normal samples in total. Although there are no reference interactions databases for the specific conditions of our samples in the literature, we found verifications for 54 of our predicted direct physical interactions from only four of the biological interaction databases. As an example, we predicted that RAD50 with TRF2 have prostate cancer specific interaction that turned out to be having validation from the literature. It is known that RAD50 complex associates with TRF2 in the S phase of cell cycle, which suggests that this predicted interaction may promote telomere maintenance in tumor cells in order to allow tumor cells to divide indefinitely. Our enrichment analysis suggests that the identified tumor specific gene interactions may be potentially important in driving the growth in prostate cancer. Additionally, we found that the highest connected subnetwork of our predicted tumor specific network is enriched for all proliferation genes, which further suggests that the genes in this network may serve in the process of oncogenesis. Conclusions Our approach reveals disease specific interactions. It may help to make experimental follow-up studies more cost and time efficient by prioritizing disease relevant parts of the global gene network. PMID:21777411

Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

PubMed Central

Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

2016-01-01

Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

Structural basis for spectrin recognition by ankyrin.

PubMed

Ipsaro, Jonathan J; Mondragón, Alfonso

2010-05-20

Maintenance of membrane integrity and organization in the metazoan cell is accomplished through intracellular tethering of membrane proteins to an extensive, flexible protein network. Spectrin, the principal component of this network, is anchored to membrane proteins through the adaptor protein ankyrin. To elucidate the atomic basis for this interaction, we determined a crystal structure of human betaI-spectrin repeats 13 to 15 in complex with the ZU5-ANK domain of human ankyrin R. The structure reveals the role of repeats 14 to 15 in binding, the electrostatic and hydrophobic contributions along the interface, and the necessity for a particular orientation of the spectrin repeats. Using structural and biochemical data as a guide, we characterized the individual proteins and their interactions by binding and thermal stability analyses. In addition to validating the structural model, these data provide insight into the nature of some mutations associated with cell morphology defects, including those found in human diseases such as hereditary spherocytosis and elliptocytosis. Finally, analysis of the ZU5 domain suggests it is a versatile protein-protein interaction module with distinct interaction surfaces. The structure represents not only the first of a spectrin fragment in complex with its binding partner, but also that of an intermolecular complex involving a ZU5 domain.

CD4-gp120 interaction interface - a gateway for HIV-1 infection in human: molecular network, modeling and docking studies.

PubMed

Pandey, Deeksha; Podder, Avijit; Pandit, Mansi; Latha, Narayanan

2017-09-01

The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4-gp120 interaction interface has been studied through a comprehensive protein-protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.

Interactions of the Salience Network and Its Subsystems with the Default-Mode and the Central-Executive Networks in Normal Aging and Mild Cognitive Impairment.

PubMed

Chand, Ganesh B; Wu, Junjie; Hajjar, Ihab; Qiu, Deqiang

2017-09-01

Previous functional magnetic resonance imaging (fMRI) investigations suggest that the intrinsically organized large-scale networks and the interaction between them might be crucial for cognitive activities. A triple network model, which consists of the default-mode network, salience network, and central-executive network, has been recently used to understand the connectivity patterns of the cognitively normal brains versus the brains with disorders. This model suggests that the salience network dynamically controls the default-mode and central-executive networks in healthy young individuals. However, the patterns of interactions have remained largely unknown in healthy aging or those with cognitive decline. In this study, we assess the patterns of interactions between the three networks using dynamical causal modeling in resting state fMRI data and compare them between subjects with normal cognition and mild cognitive impairment (MCI). In healthy elderly subjects, our analysis showed that the salience network, especially its dorsal subnetwork, modulates the interaction between the default-mode network and the central-executive network (Mann-Whitney U test; p < 0.05), which was consistent with the pattern of interaction reported in young adults. In contrast, this pattern of modulation by salience network was disrupted in MCI (p < 0.05). Furthermore, the degree of disruption in salience network control correlated significantly with lower overall cognitive performance measured by Montreal Cognitive Assessment (r = 0.295; p < 0.05). This study suggests that a disruption of the salience network control, especially the dorsal salience network, over other networks provides a neuronal basis for cognitive decline and may be a candidate neuroimaging biomarker of cognitive impairment.

Topology association analysis in weighted protein interaction network for gene prioritization

NASA Astrophysics Data System (ADS)

Wu, Shunyao; Shao, Fengjing; Zhang, Qi; Ji, Jun; Xu, Shaojie; Sun, Rencheng; Sun, Gengxin; Du, Xiangjun; Sui, Yi

2016-11-01

Although lots of algorithms for disease gene prediction have been proposed, the weights of edges are rarely taken into account. In this paper, the strengths of topology associations between disease and essential genes are analyzed in weighted protein interaction network. Empirical analysis demonstrates that compared to other genes, disease genes are weakly connected with essential genes in protein interaction network. Based on this finding, a novel global distance measurement for gene prioritization with weighted protein interaction network is proposed in this paper. Positive and negative flow is allocated to disease and essential genes, respectively. Additionally network propagation model is extended for weighted network. Experimental results on 110 diseases verify the effectiveness and potential of the proposed measurement. Moreover, weak links play more important role than strong links for gene prioritization, which is meaningful to deeply understand protein interaction network.

How plants connect pollination and herbivory networks and their contribution to community stability.

PubMed

Sauve, Alix M C; Thébault, Elisa; Pocock, Michael J O; Fontaine, Colin

2016-04-01

Pollination and herbivory networks have mainly been studied separately, highlighting their distinct structural characteristics and the related processes and dynamics. However, most plants interact with both pollinators and herbivores, and there is evidence that both types of interaction affect each other. Here we investigated the way plants connect these mutualistic and antagonistic networks together, and the consequences for community stability. Using an empirical data set, we show that the way plants connect pollination and herbivory networks is not random and promotes community stability. Analyses of the structure of binary and quantitative networks show different results: the plants' generalism with regard to pollinators is positively correlated to their generalism with regard to herbivores when considering binary interactions, but not when considering quantitative interactions. We also show that plants that share the same pollinators do not share the same herbivores. However, the way plants connect pollination and herbivory networks promotes stability for both binary and quantitative networks. Our results highlight the relevance of considering the diversity of interaction types in ecological communities, and stress the need to better quantify the costs and benefits of interactions, as well as to develop new metrics characterizing the way different interaction types are combined within ecological networks.

Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

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

Shi, Cindy

2015-07-17

The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

Asp-Gly based peptides confined at the surface of cationic gemini surfactant aggregates.

PubMed

Brizard, Aurélie; Dolain, Christel; Huc, Ivan; Oda, Reiko

2006-04-11

Cationic gemini surfactants complexed with anionic oligoglycine-aspartate (called gemini peptides hereafter) were synthesized, and their aggregation behaviors were studied. The effects of the hydrophobic chain length (C10-C22) and the length of the oligoglycine (0-4) were investigated, and it was clearly shown by critical micellar concentration, Krafft temperature, and isothermal surface pressure measurements that the hydrophobic effect and interpeptidic interaction influence the aggregation behavior in a cooperative manner. Below their Krafft temperatures, some of them formed both hydro- and organogels with three-dimensional networks and the Fourier transform infrared measurements show the presence of interpeptidic hydrogen bonds.

Insights into structural and dynamical features of water at halloysite interfaces probed by DFT and classical molecular dynamics simulations.

PubMed

Presti, Davide; Pedone, Alfonso; Mancini, Giordano; Duce, Celia; Tiné, Maria Rosaria; Barone, Vincenzo

2016-01-21

Density functional theory calculations and classical molecular dynamics simulations have been used to investigate the structure and dynamics of water molecules on kaolinite surfaces and confined in the interlayer of a halloysite model of nanometric dimension. The first technique allowed us to accurately describe the structure of the tetrahedral-octahedral slab of kaolinite in vacuum and in interaction with water molecules and to assess the performance of two widely employed empirical force fields to model water/clay interfaces. Classical molecular dynamics simulations were used to study the hydrogen bond network structure and dynamics of water adsorbed on kaolinite surfaces and confined in the halloysite interlayer. The results are in nice agreement with the few experimental data available in the literature, showing a pronounced ordering and reduced mobility of water molecules at the hydrophilic octahedral surfaces of kaolinite and confined in the halloysite interlayer, with respect to water interacting with the hydrophobic tetrahedral surfaces and in the bulk. Finally, this investigation provides new atomistic insights into the structural and dynamical properties of water-clay interfaces, which are of fundamental importance for both natural processes and industrial applications.

Crystal structure and functional interpretation of the erythrocyte spectrin tetramerization domain complex

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

Ipsaro, Jonathan J.; Harper, Sandra L.; Messick, Troy E.

2010-09-07

As the principal component of the membrane skeleton, spectrin confers integrity and flexibility to red cell membranes. Although this network involves many interactions, the most common hemolytic anemia mutations that disrupt erythrocyte morphology affect the spectrin tetramerization domains. Although much is known clinically about the resulting conditions (hereditary elliptocytosis and pyropoikilocytosis), the detailed structural basis for spectrin tetramerization and its disruption by hereditary anemia mutations remains elusive. Thus, to provide further insights into spectrin assembly and tetramer site mutations, a crystal structure of the spectrin tetramerization domain complex has been determined. Architecturally, this complex shows striking resemblance to multirepeat spectrinmore » fragments, with the interacting tetramer site region forming a central, composite repeat. This structure identifies conformational changes in {alpha}-spectrin that occur upon binding to {beta}-spectrin, and it reports the first structure of the {beta}-spectrin tetramerization domain. Analysis of the interaction surfaces indicates an extensive interface dominated by hydrophobic contacts and supplemented by electrostatic complementarity. Analysis of evolutionarily conserved residues suggests additional surfaces that may form important interactions. Finally, mapping of hereditary anemia-related mutations onto the structure demonstrate that most, but not all, local hereditary anemia mutations map to the interacting domains. The potential molecular effects of these mutations are described.« less

Crystal Structure and Functional Interpretation of the Erythrocyte spectrin Tetramerization Domain Complex

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

J Ipsaro; S Harper; T Messick

2011-12-31

As the principal component of the membrane skeleton, spectrin confers integrity and flexibility to red cell membranes. Although this network involves many interactions, the most common hemolytic anemia mutations that disrupt erythrocyte morphology affect the spectrin tetramerization domains. Although much is known clinically about the resulting conditions (hereditary elliptocytosis and pyropoikilocytosis), the detailed structural basis for spectrin tetramerization and its disruption by hereditary anemia mutations remains elusive. Thus, to provide further insights into spectrin assembly and tetramer site mutations, a crystal structure of the spectrin tetramerization domain complex has been determined. Architecturally, this complex shows striking resemblance to multirepeat spectrinmore » fragments, with the interacting tetramer site region forming a central, composite repeat. This structure identifies conformational changes in {alpha}-spectrin that occur upon binding to {beta}-spectrin, and it reports the first structure of the {beta}-spectrin tetramerization domain. Analysis of the interaction surfaces indicates an extensive interface dominated by hydrophobic contacts and supplemented by electrostatic complementarity. Analysis of evolutionarily conserved residues suggests additional surfaces that may form important interactions. Finally, mapping of hereditary anemia-related mutations onto the structure demonstrate that most, but not all, local hereditary anemia mutations map to the interacting domains. The potential molecular effects of these mutations are described.« less

Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores

NASA Astrophysics Data System (ADS)

Bruun, Jesper; Brewe, Eric

2013-12-01

The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the position in a network, called centrality measures, can be understood in terms of interactions that happen in the context of a university physics course. We apply this discussion to an empirical data set of self-reported student interactions. In a weekly administered survey, first year university students enrolled in an introductory physics course at a Danish university indicated with whom they remembered having communicated within different interaction categories. For three categories pertaining to (1) communication about how to solve physics problems in the course (called the PS category), (2) communications about the nature of physics concepts (called the CD category), and (3) social interactions that are not strictly related to the content of the physics classes (called the ICS category) in the introductory mechanics course, we use the survey data to create networks of student interaction. For each of these networks, we calculate centrality measures for each student and correlate these measures with grades from the introductory course, grades from two subsequent courses, and the pretest Force Concept Inventory (FCI) scores. We find highly significant correlations (p<0.001) between network centrality measures and grades in all networks. We find the highest correlations between network centrality measures and future grades. In the network composed of interactions regarding problem solving (the PS network), the centrality measures hide and PageRank show the highest correlations (r=-0.32 and r=0.33, respectively) with future grades. In the CD network, the network measure target entropy shows the highest correlation (r=0.45) with future grades. In the network composed solely of noncontent related social interactions, these patterns of correlation are maintained in the sense that these network measures show the highest correlations and maintain their internal ranking. Using hierarchical linear regression, we find that a linear model that adds the network measures hide and target entropy, calculated on the ICS network, significantly improves a base model that uses only the FCI pretest scores from the beginning of the semester. Though one should not infer causality from these results, they do point to how social interactions in class are intertwined with academic interactions. We interpret this as an integral part of learning, and suggest that physics is a robust example.

Building a glaucoma interaction network using a text mining approach.

PubMed

Soliman, Maha; Nasraoui, Olfa; Cooper, Nigel G F

2016-01-01

The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of relations that could not be found in existing interaction databases and that were found to be new, in addition to a smaller subnetwork consisting of interconnected clusters of seven glaucoma genes. Future improvements can be applied towards obtaining a better version of this network.

Two-dimensional network stability of nucleobases and amino acids on graphite under ambient conditions: adenine, L-serine and L-tyrosine.

PubMed

Bald, Ilko; Weigelt, Sigrid; Ma, Xiaojing; Xie, Pengyang; Subramani, Ramesh; Dong, Mingdong; Wang, Chen; Mamdouh, Wael; Wang, Jianguo; Besenbacher, Flemming

2010-04-14

We have investigated the stability of two-dimensional self-assembled molecular networks formed upon co-adsorption of the DNA base, adenine, with each of the amino acids, L-serine and L-tyrosine, on a highly oriented pyrolytic graphite (HOPG) surface by drop-casting from a water solution. L-serine and L-tyrosine were chosen as model systems due to their different interaction with the solvent molecules and the graphite substrate, which is reflected in a high and low solubility in water, respectively, compared with adenine. Combined scanning tunneling microscopy (STM) measurements and density functional theory (DFT) calculations show that the self-assembly process is mainly driven by the formation of strong adenine-adenine hydrogen bonds. We find that pure adenine networks are energetically more stable than networks built up of either pure L-serine, pure L-tyrosine or combinations of adenine with L-serine or L-tyrosine, and that only pure adenine networks are stable enough to be observable by STM under ambient conditions.

Data Imputation in Epistatic MAPs by Network-Guided Matrix Completion

PubMed Central

Žitnik, Marinka; Zupan, Blaž

2015-01-01

Abstract Epistatic miniarray profile (E-MAP) is a popular large-scale genetic interaction discovery platform. E-MAPs benefit from quantitative output, which makes it possible to detect subtle interactions with greater precision. However, due to the limits of biotechnology, E-MAP studies fail to measure genetic interactions for up to 40% of gene pairs in an assay. Missing measurements can be recovered by computational techniques for data imputation, in this way completing the interaction profiles and enabling downstream analysis algorithms that could otherwise be sensitive to missing data values. We introduce a new interaction data imputation method called network-guided matrix completion (NG-MC). The core part of NG-MC is low-rank probabilistic matrix completion that incorporates prior knowledge presented as a collection of gene networks. NG-MC assumes that interactions are transitive, such that latent gene interaction profiles inferred by NG-MC depend on the profiles of their direct neighbors in gene networks. As the NG-MC inference algorithm progresses, it propagates latent interaction profiles through each of the networks and updates gene network weights toward improved prediction. In a study with four different E-MAP data assays and considered protein–protein interaction and gene ontology similarity networks, NG-MC significantly surpassed existing alternative techniques. Inclusion of information from gene networks also allowed NG-MC to predict interactions for genes that were not included in original E-MAP assays, a task that could not be considered by current imputation approaches. PMID:25658751

Dynamic Creative Interaction Networks and Team Creativity Evolution: A Longitudinal Study

ERIC Educational Resources Information Center

Jiang, Hui; Zhang, Qing-Pu; Zhou, Yang

2018-01-01

To assess the dynamical effects of creative interaction networks on team creativity evolution, this paper elaborates a theoretical framework that links the key elements of creative interaction networks, including node, edge and network structure, to creativity in teams. The process of team creativity evolution is divided into four phases,…

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

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

Robustness Elasticity in Complex Networks

PubMed Central

Matisziw, Timothy C.; Grubesic, Tony H.; Guo, Junyu

2012-01-01

Network robustness refers to a network’s resilience to stress or damage. Given that most networks are inherently dynamic, with changing topology, loads, and operational states, their robustness is also likely subject to change. However, in most analyses of network structure, it is assumed that interaction among nodes has no effect on robustness. To investigate the hypothesis that network robustness is not sensitive or elastic to the level of interaction (or flow) among network nodes, this paper explores the impacts of network disruption, namely arc deletion, over a temporal sequence of observed nodal interactions for a large Internet backbone system. In particular, a mathematical programming approach is used to identify exact bounds on robustness to arc deletion for each epoch of nodal interaction. Elasticity of the identified bounds relative to the magnitude of arc deletion is assessed. Results indicate that system robustness can be highly elastic to spatial and temporal variations in nodal interactions within complex systems. Further, the presence of this elasticity provides evidence that a failure to account for nodal interaction can confound characterizations of complex networked systems. PMID:22808060

Characterizing Topology of Probabilistic Biological Networks.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-09-06

Biological interactions are often uncertain events, that may or may not take place with some probability. Existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. Here, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. We develop a method that accurately describes the degree distribution of such networks. We also extend our method to accurately compute the joint degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. It also helps us find an adequate mathematical model using maximum likelihood estimation. Our results demonstrate that power law and log-normal models best describe degree distributions for probabilistic networks. The inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected.

Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

PubMed

Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

2016-11-30

Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

Topology of molecular interaction networks.

PubMed

Winterbach, Wynand; Van Mieghem, Piet; Reinders, Marcel; Wang, Huijuan; de Ridder, Dick

2013-09-16

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks.Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs.Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes.Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further.

Topology of molecular interaction networks

PubMed Central

2013-01-01

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks. Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs. Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes. Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further. PMID:24041013

Social networks dynamics revealed by temporal analysis: An example in a non-human primate (Macaca sylvanus) in "La Forêt des Singes".

PubMed

Sosa, Sebastian; Zhang, Peng; Cabanes, Guénaël

2017-06-01

This study applied a temporal social network analysis model to describe three affiliative social networks (allogrooming, sleep in contact, and triadic interaction) in a non-human primate species, Macaca sylvanus. Three main social mechanisms were examined to determine interactional patterns among group members, namely preferential attachment (i.e., highly connected individuals are more likely to form new connections), triadic closure (new connections occur via previous close connections), and homophily (individuals interact preferably with others with similar attributes). Preferential attachment was only observed for triadic interaction network. Triadic closure was significant in allogrooming and triadic interaction networks. Finally, gender homophily was seasonal for allogrooming and sleep in contact networks, and observed in each period for triadic interaction network. These individual-based behaviors are based on individual reactions, and their analysis can shed light on the formation of the affiliative networks determining ultimate coalition networks, and how these networks may evolve over time. A focus on individual behaviors is necessary for a global interactional approach to understanding social behavior rules and strategies. When combined, these social processes could make animal social networks more resilient, thus enabling them to face drastic environmental changes. This is the first study to pinpoint some of the processes underlying the formation of a social structure in a non-human primate species, and identify common mechanisms with humans. The approach used in this study provides an ideal tool for further research seeking to answer long-standing questions about social network dynamics. © 2017 Wiley Periodicals, Inc.

Carbon nanotube-templated assembly of regioregular poly(3-alkylthiophene) in solution

NASA Astrophysics Data System (ADS)

Zhu, Jiahua; Stevens, Eric; He, Youjun; Hong, Kunlun; Ivanov, Ilia

2016-09-01

Control of structural heterogeneity by rationally encoding of the molecular assemblies is a key enabling design of hierarchical, multifunctional materials of the future. Here we report the strategies to gain such control using solution- based assembly to construct a hybrid nano-assembly and a network hybrid structure of regioregular poly(3- alkylthiophene) - carbon nanotube (P3AT-CNT). The opto-electronic performance of conjugated polymer (P3AT) is defined by the structure of the aggregate in solution and in the solid film. Control of P3AT aggregation would allow formation of broad range of morphologies with very distinct electro-optical. We utilize interactive templating to confine the assembly behavior of conjugated polymers, replacing poorly controlled solution processing approach. Perfect crystalline surface of the single-walled and multi-walled carbon nanotube (SWCNT/MWCNT) acts as a template, seeding P3AT aggregation of the surface of the nanotube. The seed continues directional growth through pi-pi stacking leading to the formation of to well-defined P3AT-CNT morphologies, including comb-like nano-assemblies, super- structures and gel networks. Interconnected, highly-branched network structure of P3AT-CNT hybrids is of particular interest to enable efficient, long-range, balanced charge carrier transport. The structure and opto-electionic function of the intermediate assemblies and networks of P3AT/CNT hybrids are characterized by transmission election microscopy and UV-vis absorption.

Characterizing a four-qubit planar lattice for arbitrary error detection

NASA Astrophysics Data System (ADS)

Chow, Jerry M.; Srinivasan, Srikanth J.; Magesan, Easwar; Córcoles, A. D.; Abraham, David W.; Gambetta, Jay M.; Steffen, Matthias

2015-05-01

Quantum error correction will be a necessary component towards realizing scalable quantum computers with physical qubits. Theoretically, it is possible to perform arbitrarily long computations if the error rate is below a threshold value. The two-dimensional surface code permits relatively high fault-tolerant thresholds at the ~1% level, and only requires a latticed network of qubits with nearest-neighbor interactions. Superconducting qubits have continued to steadily improve in coherence, gate, and readout fidelities, to become a leading candidate for implementation into larger quantum networks. Here we describe characterization experiments and calibration of a system of four superconducting qubits arranged in a planar lattice, amenable to the surface code. Insights into the particular qubit design and comparison between simulated parameters and experimentally determined parameters are given. Single- and two-qubit gate tune-up procedures are described and results for simultaneously benchmarking pairs of two-qubit gates are given. All controls are eventually used for an arbitrary error detection protocol described in separate work [Corcoles et al., Nature Communications, 6, 2015].

Cooperativity of anion⋯π and π⋯π interactions regulates the self-assembly of a series of carbene proligands: Towards quantitative analysis of intermolecular interactions with Hirshfeld surface

NASA Astrophysics Data System (ADS)

Samanta, Tapastaru; Dey, Lingaraj; Dinda, Joydev; Chattopadhyay, Shyamal Kumar; Seth, Saikat Kumar

2014-06-01

The cooperative effect of weak non-covalent forces between anions and electron deficient aromatics by π⋯π stacking of a series of carbene proligands (1-3) have been thoroughly explored by crystallographic studies. Structural analysis revealed that the anion⋯π and π⋯π interactions along with intermolecular hydrogen bonding mutually cooperate to facilitate the assembling of the supramolecular framework. The π⋯π and corresponding anion⋯π interactions have been investigated in the title carbene proligands despite their association with counter ions. The presence of the anion in the vicinity of the π-system leads to the formation of anion⋯π/π⋯π/π⋯anion network for an inductive stabilization of the assemblies. To assess the dimensionality of the supramolecular framework consolidated by cooperative anion⋯π/π⋯π interactions and hydrogen bonding, different substituent effects in the carbene backbone have been considered to tune these interactions. These facts show that the supramolecular framework based on these cooperative weak forces may be robust enough for application in molecular recognition. The investigation of close intermolecular interactions between the molecules via Hirshfeld surface analyses is presented in order to reveal subtle differences and similarities in the crystal structures. The decomposition of the fingerprint plot area provides a percentage of each intermolecular interaction, allowing for a quantified analysis of close contacts within each crystal.

Putting the Capital 'A' in CoCoRAHS: A Pilot Program to Measure Albedo using the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Stampone, M. D.; Wake, C. P.; Dibb, J. E.

2012-12-01

The Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network, started in 1998 as a community-based network of volunteer weather observer in Colorado, is the single largest provider of daily precipitation observations in the United States. We embrace the CoCoRaHS mission to use low-cost measurement tools, provide training and education, and utilize an interactive website to collect high quality albedo data for research and education applications. We trained a select sub-set of CoCoRaHS's eighteen most enthusiastic, self-proclaimed 'weather nuts' in the state of New Hampshire to collect surface albedo, snow depth, and snow density measurements between 23-Nov-2011 and 15-Mar-2012. At less than 700 per observer, the low-cost albedo data falls within ±0.05 of albedo values collected from a First Class Kipp and Zonen Albedometer (CMA6) at local solar noon. CoCoRaHS albedo values range from 0.99 for fresh snow to 0.34 for shallow, aged snow. Snow-free albedo ranges from 0.09 to 0.39, depending on ground cover. Albedo is found to increase logarithmically with snow depth and decrease linearly with snow density. The latter relationship with snow density is inferred to be a proxy for increasing snow grain size as snowpack ages and compacts, supported by spectral albedo measurements collected with an ASD FieldSpec4 spectrometer. The newly established albedo network also serves as a development test bed for interactive online mapping and graphing applications for CoCoRaHS observers to investigate spatial and temporal patterns in albedo, snow depth, and snow density (www.cocorahs-albedo.org). The 2012-2013 field season will include low-cost infrared temperature guns (<40 each) to investigate the relationship between surface albedo and skin temperature. We have also recruited middle- and high-schools as volunteer observers and are working with the teachers to develop curriculum and lesson plans that utilize the low-cost measurement tools provided by CoCoRAHS. CoCoRAHS data will provide critical spatially distributed measurements of surface data that will be used to validate and improve land surface modeling of New Hampshire climate under different land cover scenarios. Building on the success of the first season, the newly established albedo network shows promise to put the capital 'A' in CoCoRAHS.Figure 1. (a) Map of Community Collaborative Rain, Hail, and Snow (CoCoRAHS) volunteers participating in the pilot albedo project, and (b) CoCoRAHS snow measurement kit.

Multiple tipping points and optimal repairing in interacting networks

PubMed Central

Majdandzic, Antonio; Braunstein, Lidia A.; Curme, Chester; Vodenska, Irena; Levy-Carciente, Sary; Eugene Stanley, H.; Havlin, Shlomo

2016-01-01

Systems composed of many interacting dynamical networks—such as the human body with its biological networks or the global economic network consisting of regional clusters—often exhibit complicated collective dynamics. Three fundamental processes that are typically present are failure, damage spread and recovery. Here we develop a model for such systems and find a very rich phase diagram that becomes increasingly more complex as the number of interacting networks increases. In the simplest example of two interacting networks we find two critical points, four triple points, ten allowed transitions and two ‘forbidden' transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To test our model, we analyse an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model. PMID:26926803

1-{(E)-[(2E)-3-(4-Meth-oxy-phen-yl)-1-phenyl-prop-2-en-1-yl-idene]amino}-3-phenyl-urea: crystal structure and Hirshfeld surface analysis.

PubMed

Tan, Ming Yueh; Crouse, Karen A; Ravoof, Thahira B S A; Jotani, Mukesh M; Tiekink, Edward R T

2017-11-01

The title compound, C 23 H 21 N 3 O 2 , is constructed about an almost planar disubstituted amino-urea residue (r.m.s. deviation = 0.0201 Å), which features an intra-molecular amine-N-H⋯N(imine) hydrogen bond. In the 'all- trans ' chain connecting this to the terminal meth-oxy-benzene residue, the conformation about each of the imine and ethyl-ene double bonds is E . In the crystal, amide-N-H⋯O(carbon-yl) hydrogen bonds connect centrosymmetrically related mol-ecules into dimeric aggregates, which also incorporate ethyl-ene-C-H⋯O(amide) inter-actions. The dimers are linked by amine-phenyl-C-H⋯π(imine-phen-yl) and meth-oxy-benzene-C-H⋯π(amine-phen-yl) inter-actions to generate a three-dimensional network. The importance of C-H⋯π inter-actions in the mol-ecular packing is reflected in the relatively high contributions made by C⋯H/H⋯C contacts to the Hirshfeld surface, i.e . 31.6%.

User-interactive electronic skin for instantaneous pressure visualization

NASA Astrophysics Data System (ADS)

Wang, Chuan; Hwang, David; Yu, Zhibin; Takei, Kuniharu; Park, Junwoo; Chen, Teresa; Ma, Biwu; Javey, Ali

2013-10-01

Electronic skin (e-skin) presents a network of mechanically flexible sensors that can conformally wrap irregular surfaces and spatially map and quantify various stimuli. Previous works on e-skin have focused on the optimization of pressure sensors interfaced with an electronic readout, whereas user interfaces based on a human-readable output were not explored. Here, we report the first user-interactive e-skin that not only spatially maps the applied pressure but also provides an instantaneous visual response through a built-in active-matrix organic light-emitting diode display with red, green and blue pixels. In this system, organic light-emitting diodes (OLEDs) are turned on locally where the surface is touched, and the intensity of the emitted light quantifies the magnitude of the applied pressure. This work represents a system-on-plastic demonstration where three distinct electronic components—thin-film transistor, pressure sensor and OLED arrays—are monolithically integrated over large areas on a single plastic substrate. The reported e-skin may find a wide range of applications in interactive input/control devices, smart wallpapers, robotics and medical/health monitoring devices.

Quantum interference in plasmonic circuits.

PubMed

Heeres, Reinier W; Kouwenhoven, Leo P; Zwiller, Valery

2013-10-01

Surface plasmon polaritons (plasmons) are a combination of light and a collective oscillation of the free electron plasma at metal/dielectric interfaces. This interaction allows subwavelength confinement of light beyond the diffraction limit inherent to dielectric structures. As a result, the intensity of the electromagnetic field is enhanced, with the possibility to increase the strength of the optical interactions between waveguides, light sources and detectors. Plasmons maintain non-classical photon statistics and preserve entanglement upon transmission through thin, patterned metallic films or weakly confining waveguides. For quantum applications, it is essential that plasmons behave as indistinguishable quantum particles. Here we report on a quantum interference experiment in a nanoscale plasmonic circuit consisting of an on-chip plasmon beamsplitter with integrated superconducting single-photon detectors to allow efficient single plasmon detection. We demonstrate a quantum-mechanical interaction between pairs of indistinguishable surface plasmons by observing Hong-Ou-Mandel (HOM) interference, a hallmark non-classical interference effect that is the basis of linear optics-based quantum computation. Our work shows that it is feasible to shrink quantum optical experiments to the nanoscale and offers a promising route towards subwavelength quantum optical networks.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

User-interactive electronic skin for instantaneous pressure visualization.

PubMed

Wang, Chuan; Hwang, David; Yu, Zhibin; Takei, Kuniharu; Park, Junwoo; Chen, Teresa; Ma, Biwu; Javey, Ali

2013-10-01

Electronic skin (e-skin) presents a network of mechanically flexible sensors that can conformally wrap irregular surfaces and spatially map and quantify various stimuli. Previous works on e-skin have focused on the optimization of pressure sensors interfaced with an electronic readout, whereas user interfaces based on a human-readable output were not explored. Here, we report the first user-interactive e-skin that not only spatially maps the applied pressure but also provides an instantaneous visual response through a built-in active-matrix organic light-emitting diode display with red, green and blue pixels. In this system, organic light-emitting diodes (OLEDs) are turned on locally where the surface is touched, and the intensity of the emitted light quantifies the magnitude of the applied pressure. This work represents a system-on-plastic demonstration where three distinct electronic components--thin-film transistor, pressure sensor and OLED arrays--are monolithically integrated over large areas on a single plastic substrate. The reported e-skin may find a wide range of applications in interactive input/control devices, smart wallpapers, robotics and medical/health monitoring devices.

Solution Structure and Membrane Interaction of the Cytoplasmic Tail of HIV-1 gp41 Protein.

PubMed

Murphy, R Elliot; Samal, Alexandra B; Vlach, Jiri; Saad, Jamil S

2017-11-07

The cytoplasmic tail of gp41 (gp41CT) remains the last HIV-1 domain with an unknown structure. It plays important roles in HIV-1 replication such as mediating envelope (Env) intracellular trafficking and incorporation into assembling virions, mechanisms of which are poorly understood. Here, we present the solution structure of gp41CT in a micellar environment and characterize its interaction with the membrane. We show that the N-terminal 45 residues are unstructured and not associated with the membrane. However, the C-terminal 105 residues form three membrane-bound amphipathic α helices with distinctive structural features such as variable degree of membrane penetration, hydrophobic and basic surfaces, clusters of aromatic residues, and a network of cation-π interactions. This work fills a major gap by providing the structure of the last segment of HIV-1 Env, which will provide insights into the mechanisms of Gag-mediated Env incorporation as well as the overall Env mobility and conformation on the virion surface. Copyright © 2017 Elsevier Ltd. All rights reserved.

SH2 Domains Serve as Lipid-Binding Modules for pTyr-Signaling Proteins.

PubMed

Park, Mi-Jeong; Sheng, Ren; Silkov, Antonina; Jung, Da-Jung; Wang, Zhi-Gang; Xin, Yao; Kim, Hyunjin; Thiagarajan-Rosenkranz, Pallavi; Song, Seohyeon; Yoon, Youngdae; Nam, Wonhee; Kim, Ilshin; Kim, Eui; Lee, Dong-Gyu; Chen, Yong; Singaram, Indira; Wang, Li; Jang, Myoung Ho; Hwang, Cheol-Sang; Honig, Barry; Ryu, Sungho; Lorieau, Justin; Kim, You-Me; Cho, Wonhwa

2016-04-07

The Src-homology 2 (SH2) domain is a protein interaction domain that directs myriad phosphotyrosine (pY)-signaling pathways. Genome-wide screening of human SH2 domains reveals that ∼90% of SH2 domains bind plasma membrane lipids and many have high phosphoinositide specificity. They bind lipids using surface cationic patches separate from pY-binding pockets, thus binding lipids and the pY motif independently. The patches form grooves for specific lipid headgroup recognition or flat surfaces for non-specific membrane binding and both types of interaction are important for cellular function and regulation of SH2 domain-containing proteins. Cellular studies with ZAP70 showed that multiple lipids bind its C-terminal SH2 domain in a spatiotemporally specific manner and thereby exert exquisite spatiotemporal control over its protein binding and signaling activities in T cells. Collectively, this study reveals how lipids control SH2 domain-mediated cellular protein-protein interaction networks and suggest a new strategy for therapeutic modulation of pY-signaling pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Reprogramming hMSCs morphology with silicon/porous silicon geometric micro-patterns.

PubMed

Ynsa, M D; Dang, Z Y; Manso-Silvan, M; Song, J; Azimi, S; Wu, J F; Liang, H D; Torres-Costa, V; Punzon-Quijorna, E; Breese, M B H; Garcia-Ruiz, J P

2014-04-01

Geometric micro-patterned surfaces of silicon combined with porous silicon (Si/PSi) have been manufactured to study the behaviour of human Mesenchymal Stem Cells (hMSCs). These micro-patterns consist of regular silicon hexagons surrounded by spaced columns of silicon equilateral triangles separated by PSi. The results show that, at an early culture stage, the hMSCs resemble quiescent cells on the central hexagons with centered nuclei and actin/β-catenin and a microtubules network denoting cell adhesion. After 2 days, hMSCs adapted their morphology and cytoskeleton proteins from cell-cell dominant interactions at the center of the hexagonal surface. This was followed by an intermediate zone with some external actin fibres/β-catenin interactions and an outer zone where the dominant interactions are cell-silicon. Cells move into silicon columns to divide, migrate and communicate. Furthermore, results show that Runx2 and vitamin D receptors, both specific transcription factors for skeleton-derived cells, are expressed in cells grown on micropatterned silicon under all observed circumstances. On the other hand, non-phenotypic alterations are under cell growth and migration on Si/PSi substrates. The former consideration strongly supports the use of micro-patterned silicon surfaces to address pending questions about the mechanisms of human bone biogenesis/pathogenesis and the study of bone scaffolds.

Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

The Third Tibetan Plateau Atmospheric Scientific Experiment for Understanding the Earth-Atmosphere Coupled System

NASA Astrophysics Data System (ADS)

Zhao, P.; Xu, X.; Chen, F.; Guo, X.; Zheng, X.; Liu, L. P.; Hong, Y.; Li, Y.; La, Z.; Peng, H.; Zhong, L. Z.; Ma, Y.; Tang, S. H.; Liu, Y.; Liu, H.; Li, Y. H.; Zhang, Q.; Hu, Z.; Sun, J. H.; Zhang, S.; Dong, L.; Zhang, H.; Zhao, Y.; Yan, X.; Xiao, A.; Wan, W.; Zhou, X.

2016-12-01

The Third Tibetan Plateau atmospheric scientific experiment (TIPEX-III) was initiated jointly by the China Meteorological Administration, the National Natural Scientific Foundation, and the Chinese Academy of Sciences. This paper presents the background, scientific objectives, and overall experimental design of TIPEX-III. It was designed to conduct an integrated observation of the earth-atmosphere coupled system over the Tibetan Plateau (TP) from land surface, planetary boundary layer (PBL), troposphere, and stratosphere for eight to ten years by coordinating ground- and air-based measurement facilities for understanding spatial heterogeneities of complex land-air interactions, cloud-precipitation physical processes, and interactions between troposphere and stratosphere. TIPEX-III originally began in 2014, and is ongoing. It established multiscale land-surface and PBL observation networks over the TP and a tropospheric meteorological radiosonde network over the western TP, and executed an integrated observation mission for cloud-precipitation physical features using ground-based radar systems and aircraft campaigns and an observation task for atmospheric ozone, aerosol, and water vapor. The archive, management, and share policy of the observation data are also introduced herein. Some TIPEX-III data have been preliminarily applied to analyze the features of surface sensible and latent heat fluxes, cloud-precipitation physical processes, and atmospheric water vapor and ozone over the TP, and to improve the local precipitation forecast. Furthermore, TIPEX-III intends to promote greater scientific and technological cooperation with international research communities and broader organizations. Scientists working internationally are invited to participate in the field campaigns and to use the TIPEX-III data for their own research.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Biologically-Mediated Weathering of Minerals From Nanometre Scale to Environmental Systems

NASA Astrophysics Data System (ADS)

Brown, D. J.; Banwart, S. A.; Smits, M. M.; Leake, J. R.; Bonneville, S.; Benning, L. G.; Haward, S. J.; Ragnarsdottir, K.

2007-12-01

The Weathering Science Consortium is a multi-disciplinary project that aims to create a step change in understanding how biota control mineral weathering and soil formation (http://www.wun.ac.uk/wsc). Our hypothesis is that rates of biotic weathering are driven by the energy supply from plants to the organisms, controlling their biomass, surface area of contact with minerals and their capacity to interact chemically with minerals. Symbiotic fungal mycorrhiza of 90% of plant species are empowered with an available carbohydrate supply from plants that is unparalleled amongst soil microbes. They develop extensive mycelial networks that intimately contact minerals, which they weather aggressively. We hypothesise that mycorrhiza play a critical role through their focussing of photosynthate energy from plants into sub-surface weathering environments. Our work identifies how these fungal cells, and their secretions, interact with mineral surfaces and affect the rates of nutrient transfer from minerals to the organism. Investigating these living systems allows us to create new concepts and mathematical models that can describe biological weathering and be used in computer simulations of soil weathering dynamics. We are studying these biochemical interactions at 3 levels of observation: 1. At the molecular scale to understand interactions between living cells and minerals and to quantify the chemistry that breaks down the mineral structure; 2. At the soil grain scale to quantify the activity and spatial distribution of the fungi, roots and other organisms (e.g. bacteria) and their effects on the rates at which minerals are dissolved to release nutrients; 3. At soil profile scale to test models for the spatial distribution of active fungi and carbon energy and their seasonal variability and impact on mineral dissolution rates. Here we present early results from molecular and soil grain scale experiments. We have grown pure culture (Suillus bovinus, Paxillus involutus) mycorrhizal mycelial networks associated with pine trees in otherwise sterile (agar) and also non-sterile (peat) microcosms, which include mineral sections and powders of biotite, apatite and quartz. 14C labelling has been used to map C flux through the microcosms and to determine the transfer of photosynthate energy into the weathering arenas. We have used Vertical Scanning Interferometry (VSI) to assess volumetric alteration of mineral substrates in contact with fungi. Focused Ion Beam (FIB)- Transmission Electron Microscope (TEM) work provides evidence for increased mechanical forcing and possible alteration of biotite surfaces with greater fungi contact time. We also present real-time in situ observations of mineral-organic acid and mineral-exudate interactions using Atomic Force Microscopy (AFM).

Glycosyltransferase-programmed stereosubstitution (GPS) to create HCELL: engineering a roadmap for cell migration.

PubMed

Sackstein, Robert

2009-07-01

During evolution of the vertebrate cardiovascular system, the vast endothelial surface area associated with branching vascular networks mandated the development of molecular processes to efficiently and specifically recruit circulating sentinel host defense cells and tissue repair cells at localized sites of inflammation/tissue injury. The forces engendered by high-velocity blood flow commensurately required the evolution of specialized cell surface molecules capable of mediating shear-resistant endothelial adhesive interactions, thus literally capturing relevant cells from the blood stream onto the target endothelial surface and permitting subsequent extravasation. The principal effectors of these shear-resistant binding interactions comprise a family of C-type lectins known as 'selectins' that bind discrete sialofucosylated glycans on their respective ligands. This review explains the 'intelligent design' of requisite reagents to convert native CD44 into the sialofucosylated glycoform known as hematopoietic cell E-/L-selectin ligand (HCELL), the most potent E-selectin counter-receptor expressed on human cells, and will describe how ex vivo glycan engineering of HCELL expression may open the 'avenues' for the efficient vascular delivery of cells for a variety of cell therapies.

Food Web Designer: a flexible tool to visualize interaction networks.

PubMed

Sint, Daniela; Traugott, Michael

Species are embedded in complex networks of ecological interactions and assessing these networks provides a powerful approach to understand what the consequences of these interactions are for ecosystem functioning and services. This is mandatory to develop and evaluate strategies for the management and control of pests. Graphical representations of networks can help recognize patterns that might be overlooked otherwise. However, there is a lack of software which allows visualizing these complex interaction networks. Food Web Designer is a stand-alone, highly flexible and user friendly software tool to quantitatively visualize trophic and other types of bipartite and tripartite interaction networks. It is offered free of charge for use on Microsoft Windows platforms. Food Web Designer is easy to use without the need to learn a specific syntax due to its graphical user interface. Up to three (trophic) levels can be connected using links cascading from or pointing towards the taxa within each level to illustrate top-down and bottom-up connections. Link width/strength and abundance of taxa can be quantified, allowing generating fully quantitative networks. Network datasets can be imported, saved for later adjustment and the interaction webs can be exported as pictures for graphical display in different file formats. We show how Food Web Designer can be used to draw predator-prey and host-parasitoid food webs, demonstrating that this software is a simple and straightforward tool to graphically display interaction networks for assessing pest control or any other type of interaction in both managed and natural ecosystems from an ecological network perspective.

Evaluating the Spatio-Temporal Factors that Structure Network Parameters of Plant-Herbivore Interactions

PubMed Central

López-Carretero, Antonio; Díaz-Castelazo, Cecilia; Boege, Karina; Rico-Gray, Víctor

2014-01-01

Despite the dynamic nature of ecological interactions, most studies on species networks offer static representations of their structure, constraining our understanding of the ecological mechanisms involved in their spatio-temporal stability. This is the first study to evaluate plant-herbivore interaction networks on a small spatio-temporal scale. Specifically, we simultaneously assessed the effect of host plant availability, habitat complexity and seasonality on the structure of plant-herbivore networks in a coastal tropical ecosystem. Our results revealed that changes in the host plant community resulting from seasonality and habitat structure are reflected not only in the herbivore community, but also in the emergent properties (network parameters) of the plant-herbivore interaction network such as connectance, selectiveness and modularity. Habitat conditions and periods that are most stressful favored the presence of less selective and susceptible herbivore species, resulting in increased connectance within networks. In contrast, the high degree of selectivennes (i.e. interaction specialization) and modularity of the networks under less stressful conditions was promoted by the diversification in resource use by herbivores. By analyzing networks at a small spatio-temporal scale we identified the ecological factors structuring this network such as habitat complexity and seasonality. Our research offers new evidence on the role of abiotic and biotic factors in the variation of the properties of species interaction networks. PMID:25340790

Maximally informative pairwise interactions in networks

PubMed Central

Fitzgerald, Jeffrey D.; Sharpee, Tatyana O.

2010-01-01

Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here we present an approach for finding the optimal mappings between input signals and network states that allow the network to convey the maximal information about input signals drawn from a given distribution. This mapping also produces a set of linear equations for calculating the optimal Ising-model coupling constants, as well as geometric properties that indicate the applicability of the pairwise Ising model. We show that the optimal pairwise interactions are on average zero for Gaussian and uniformly distributed inputs, whereas they are nonzero for inputs approximating those in natural environments. These nonzero network interactions are predicted to increase in strength as the noise in the response functions of each network node increases. This approach also suggests ways for how interactions with unmeasured parts of the network can be inferred from the parameters of response functions for the measured network nodes. PMID:19905153

An Acetylation Switch Regulates SUMO-Dependent Protein Interaction Networks

PubMed Central

Ullmann, Rebecca; Chien, Christopher D.; Avantaggiati, Maria Laura; Muller, Stefan

2013-01-01

SUMMARY The attachment of the SUMO modifier to proteins controls cellular signaling pathways through noncovalent binding to SUMO-interaction motifs (SIMs). Canonical SIMs contain a core of hydrophobic residues that bind to a hydrophobic pocket on SUMO. Negatively charged residues of SIMs frequently contribute to binding by interacting with a basic surface on SUMO. Here we define acetylation within this basic interface as a central mechanism for the control of SUMO-mediated interactions. The acetyl-mediated neutralization of basic charges on SUMO prevents binding to SIMs in PML, Daxx, and PIAS family members but does not affect the interaction between RanBP2 and SUMO. Acetylation is controlled by HDACs and attenuates SUMO- and PIAS-mediated gene silencing. Moreover, it affects the assembly of PML nuclear bodies and restrains the recruitment of the corepressor Daxx to these structures. This acetyl-dependent switch thus expands the regulatory repertoire of SUMO signaling and determines the selectivity and dynamics of SUMO-SIM interactions. PMID:22578841

Social Networking Sites as Communication, Interaction, and Learning Environments: Perceptions and Preferences of Distance Education Students

ERIC Educational Resources Information Center

Bozkurt, Aras; Karadeniz, Abdulkadir; Kocdar, Serpil

2017-01-01

The advent of Web 2.0 technologies transformed online networks into interactive spaces in which user-generated content has become the core material. With the possibilities that emerged from Web 2.0, social networking sites became very popular. The capability of social networking sites promises opportunities for communication and interaction,…

Interaction Networks: Generating High Level Hints Based on Network Community Clustering

ERIC Educational Resources Information Center

Eagle, Michael; Johnson, Matthew; Barnes, Tiffany

2012-01-01

We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…

Public/Private Sector Interactions: The Implications for Networking. A Discussion Report Prepared by the Network Advisory Committee.

ERIC Educational Resources Information Center

Network Planning Paper, 1983

1983-01-01

At a 2-day meeting in October 1982, the Library of Congress Network Advisory Committee (NAC) members discussed the complex issues involved in public and private sector interactions and their relationship to networking activities. The report, "Public Sector/Private Sector Interaction in Providing Information Services," prepared by the…

A global interaction network maps a wiring diagram of cellular function

PubMed Central

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

Hydrologic connectivity as a framework for understanding biogeochemical flux through watersheds and along fluvial networks

NASA Astrophysics Data System (ADS)

Covino, Tim

2017-01-01

Hydrologic connections can link hillslopes to channel networks, streams to lakes, subsurface to surface, land to atmosphere, terrestrial to aquatic, and upstream to downstream. These connections can develop across vertical, lateral, and longitudinal dimensions and span spatial and temporal scales. Each of these dimensions and scales are interconnected, creating a mosaic of nested hydrologic connections and associated processes. In turn, these interacting and nested processes influence the transport, cycling, and transformation of organic material and inorganic nutrients through watersheds and along fluvial networks. Although hydrologic connections span dimensions and spatiotemporal scales, relationships between connectivity and carbon and nutrient dynamics are rarely evaluated within this framework. The purpose of this paper is to provide a cross-disciplinary view of hydrologic connectivity - highlighting the various forms of hydrologic connectivity that control fluxes of organic material and nutrients - and to help stimulate integration across scales and dimensions, and collaboration among disciplines.

Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

PubMed Central

Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

2014-01-01

Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

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.

Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

PubMed

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

Characterization of the bone marrow adipocyte niche with three-dimensional electron microscopy.

PubMed

Robles, Hero; Park, SungJae; Joens, Matthew S; Fitzpatrick, James A J; Craft, Clarissa S; Scheller, Erica L

2018-01-27

Unlike white and brown adipose tissues, the bone marrow adipocyte (BMA) exists in a microenvironment containing unique populations of hematopoietic and skeletal cells. To study this microenvironment at the sub-cellular level, we performed a three-dimensional analysis of the ultrastructure of the BMA niche with focused ion beam scanning electron microscopy (FIB-SEM). This revealed that BMAs display hallmarks of metabolically active cells including polarized lipid deposits, a dense mitochondrial network, and areas of endoplasmic reticulum. The distinct orientations of the triacylglycerol droplets suggest that fatty acids are taken up and/or released in three key areas - at the endothelial interface, into the hematopoietic milieu, and at the bone surface. Near the sinusoidal vasculature, endothelial cells send finger-like projections into the surface of the BMA which terminate near regions of lipid within the BMA cytoplasm. In some regions, perivascular cells encase the BMA with their flattened cellular projections, limiting contacts with other cells in the niche. In the hematopoietic milieu, BMAT adipocytes of the proximal tibia interact extensively with maturing cells of the myeloid/granulocyte lineage. Associations with erythroblast islands are also prominent. At the bone surface, the BMA extends organelle and lipid-rich cytoplasmic regions toward areas of active osteoblasts. This suggests that the BMA may serve to partition nutrient utilization between diverse cellular compartments, serving as an energy-rich hub of the stromal-reticular network. Lastly, though immuno-EM, we've identified a subset of bone marrow adipocytes that are innervated by the sympathetic nervous system, providing an additional mechanism for regulation of the BMA. In summary, this work reveals that the bone marrow adipocyte is a dynamic cell with substantial capacity for interactions with the diverse components of its surrounding microenvironment. These local interactions likely contribute to its unique regulation relative to peripheral adipose tissues. Copyright © 2018 Elsevier Inc. All rights reserved.

Top-down network analysis characterizes hidden termite-termite interactions.

PubMed

Campbell, Colin; Russo, Laura; Marins, Alessandra; DeSouza, Og; Schönrogge, Karsten; Mortensen, David; Tooker, John; Albert, Réka; Shea, Katriona

2016-09-01

The analysis of ecological networks is generally bottom-up, where networks are established by observing interactions between individuals. Emergent network properties have been indicated to reflect the dominant mode of interactions in communities that might be mutualistic (e.g., pollination) or antagonistic (e.g., host-parasitoid communities). Many ecological communities, however, comprise species interactions that are difficult to observe directly. Here, we propose that a comparison of the emergent properties from detail-rich reference communities with known modes of interaction can inform our understanding of detail-sparse focal communities. With this top-down approach, we consider patterns of coexistence between termite species that live as guests in mounds built by other host termite species as a case in point. Termite societies are extremely sensitive to perturbations, which precludes determining the nature of their interactions through direct observations. We perform a literature review to construct two networks representing termite mound cohabitation in a Brazilian savanna and in the tropical forest of Cameroon. We contrast the properties of these cohabitation networks with a total of 197 geographically diverse mutualistic plant-pollinator and antagonistic host-parasitoid networks. We analyze network properties for the networks, perform a principal components analysis (PCA), and compute the Mahalanobis distance of the termite networks to the cloud of mutualistic and antagonistic networks to assess the extent to which the termite networks overlap with the properties of the reference networks. Both termite networks overlap more closely with the mutualistic plant-pollinator communities than the antagonistic host-parasitoid communities, although the Brazilian community overlap with mutualistic communities is stronger. The analysis raises the hypothesis that termite-termite cohabitation networks may be overall mutualistic. More broadly, this work provides support for the argument that cryptic communities may be analyzed via comparison to well-characterized communities.

Self-organized nano-structuring of CoO islands on Fe(001)

NASA Astrophysics Data System (ADS)

Brambilla, A.; Picone, A.; Giannotti, D.; Riva, M.; Bussetti, G.; Berti, G.; Calloni, A.; Finazzi, M.; Ciccacci, F.; Duò, L.

2016-01-01

The realization of nanometer-scale structures through bottom-up strategies can be accomplished by exploiting a buried network of dislocations. We show that, by following appropriate growth steps in ultra-high vacuum molecular beam epitaxy, it is possible to grow nano-structured films of CoO coupled to Fe(001) substrates, with tunable sizes (both the lateral size and the maximum height scale linearly with coverage). The growth mode is discussed in terms of the evolution of surface morphology and chemical interactions as a function of the CoO thickness. Scanning tunneling microscopy measurements reveal that square mounds of CoO with lateral dimensions of less than 25 nm and heights below 10 atomic layers are obtained by growing few-nanometers-thick CoO films on a pre-oxidized Fe(001) surface covered by an ultra-thin Co buffer layer. In the early stages of growth, a network of misfit dislocations develops, which works as a template for the CoO nano-structuring. From a chemical point of view, at variance with typical CoO/Fe interfaces, neither Fe segregation at the surface nor Fe oxidation at the buried interface are observed, as seen by Auger electron spectroscopy and X-ray Photoemission Spectroscopy, respectively.

Influences of brain development and ageing on cortical interactive networks.

PubMed

Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao

2011-02-01

To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

PubMed

Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Mapping the distribution of packing topologies within protein interiors shows predominant preference for specific packing motifs

PubMed Central

2011-01-01

Background Mapping protein primary sequences to their three dimensional folds referred to as the 'second genetic code' remains an unsolved scientific problem. A crucial part of the problem concerns the geometrical specificity in side chain association leading to densely packed protein cores, a hallmark of correctly folded native structures. Thus, any model of packing within proteins should constitute an indispensable component of protein folding and design. Results In this study an attempt has been made to find, characterize and classify recurring patterns in the packing of side chain atoms within a protein which sustains its native fold. The interaction of side chain atoms within the protein core has been represented as a contact network based on the surface complementarity and overlap between associating side chain surfaces. Some network topologies definitely appear to be preferred and they have been termed 'packing motifs', analogous to super secondary structures in proteins. Study of the distribution of these motifs reveals the ubiquitous presence of typical smaller graphs, which appear to get linked or coalesce to give larger graphs, reminiscent of the nucleation-condensation model in protein folding. One such frequently occurring motif, also envisaged as the unit of clustering, the three residue clique was invariably found in regions of dense packing. Finally, topological measures based on surface contact networks appeared to be effective in discriminating sequences native to a specific fold amongst a set of decoys. Conclusions Out of innumerable topological possibilities, only a finite number of specific packing motifs are actually realized in proteins. This small number of motifs could serve as a basis set in the construction of larger networks. Of these, the triplet clique exhibits distinct preference both in terms of composition and geometry. PMID:21605466

Variations in Social Network Type Membership Among Older African Americans, Caribbean Blacks, and Non-Hispanic Whites

PubMed Central

2017-01-01

Abstract Objectives: This study examined race differences in the probability of belonging to a specific social network typology of family, friends, and church members. Method: Samples of African Americans, Caribbean blacks, and non-Hispanic whites aged 55+ were drawn from the National Survey of American Life. Typology indicators related to social integration and negative interactions with family, friendship, and church networks were used. Latent class analysis was used to identify typologies, and latent class multinomial logistic regression was used to assess the influence of race, and interactions between race and age, and race and education on typology membership. Results: Four network typologies were identified: optimal (high social integration, low negative interaction), family-centered (high social integration within primarily the extended family network, low negative interaction), strained (low social integration, high negative interaction), and ambivalent (high social integration and high negative interaction). Findings for race and age and race and education interactions indicated that the effects of education and age on typology membership varied by race. Discussion: Overall, the findings demonstrate how race interacts with age and education to influence the probability of belonging to particular network types. A better understanding of the influence of race, education, and age on social network typologies will inform future research and theoretical developments in this area. PMID:28329871

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

User-Centric Secure Cross-Site Interaction Framework for Online Social Networking Services

ERIC Educational Resources Information Center

Ko, Moo Nam

2011-01-01

Social networking service is one of major technological phenomena on Web 2.0. Hundreds of millions of users are posting message, photos, and videos on their profiles and interacting with other users, but the sharing and interaction are limited within the same social networking site. Although users can share some content on a social networking site…

Assembly of Reconfigurable Colloidal Structures by Multidirectional Field-Induced Interactions.

PubMed

Bharti, Bhuvnesh; Velev, Orlin D

2015-07-28

Field-directed colloidal assembly has shown remarkable recent progress in increasing the complexity, degree of control, and multiscale organization of the structures. This has largely been achieved by using particles of complex shapes and polarizabilites (Janus, patchy, shaped, and faceted). We review the fundamentals of the interactions leading to the directed assembly of such structures, the ways to simulate the dynamics of the process, and the effect of particle size, shape, and properties on the type of structure obtained. We discuss how directional polarization interactions induced by external electric and magnetic fields can be used to assemble complex particles or particle mixtures into lattices of tailored structure. Examples of such systems include isotropic and anisotropic shaped particles with surface patches, which form networks and crystals of unusual symmetry by dipolar, quadrupolar, and multipolar interactions in external fields. The emerging trends in making reconfigurable and dynamic structures are discussed.

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

Strickland, Madeleine; Stanley, Ann Marie; Wang, Guangshun

Paralogous enzymes arise from gene duplication events that confer a novel function, although it is unclear how cross-reaction between the original and duplicate protein interaction network is minimized. We investigated HPr:EIsugar and NPr:EINtr, the initial complexes of paralogous phosphorylation cascades involved in sugar import and nitrogen regulation in bacteria, respectively. Although the HPr:EIsugar interaction has been well characterized, involving multiple complexes and transient interactions, the exact nature of the NPr:EINtr complex was unknown. We set out to identify the key features of the interaction by performing binding assays and elucidating the structure of NPr in complex with the phosphorylation domainmore » of EINtr (EINNtr), using a hybrid approach involving X-ray, homology, and sparse nuclear magnetic resonance. We found that the overall fold and active-site structure of the two complexes are conserved in order to maintain productive phosphorylation, however, the interface surface potential differs between the two complexes, which prevents cross-reaction.« less

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

Group-based strategy diffusion in multiplex networks with weighted values

NASA Astrophysics Data System (ADS)

Yu, Jianyong; Jiang, J. C.; Xiang, Leijun

2017-03-01

The information diffusion of multiplex social networks has received increasing interests in recent years. Actually, the multiplex networks are made of many communities, and it should be gotten more attention for the influences of community level diffusion, besides of individual level interactions. In view of this, this work explores strategy interactions and diffusion processes in multiplex networks with weighted values from a new perspective. Two different groups consisting of some agents with different influential strength are firstly built in each layer network, the authority and non-authority groups. The strategy interactions between different groups in intralayer and interlayer networks are performed to explore community level diffusion, by playing two classical strategy games, Prisoner's Dilemma and Snowdrift Game. The impact forces from the different groups and the reactive forces from individual agents are simultaneously taken into account in intralayer and interlayer interactions. This paper reveals and explains the evolutions of cooperation diffusion and the influences of interlayer interaction tight degrees in multiplex networks with weighted values. Some thresholds of critical parameters of interaction degrees and games parameters settings are also discussed in group-based strategy diffusion.

Does the Type of Event Influence How User Interactions Evolve on Twitter?

PubMed Central

del Val, Elena; Rebollo, Miguel; Botti, Vicente

2015-01-01

The number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes it possible to go a step further analyzing the dynamics of the interaction patterns. In this article, we present an analysis of the evolution of user interactions that take place in television, socio-political, conference, and keynote events on Twitter. Interactions have been modeled as networks that are annotated with the time markers. We study changes in the structural properties at both the network level and the node level. As a result of this analysis, we have detected patterns of network evolution and common structural features as well as differences among the events. PMID:25961305

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Structural stability of interaction networks against negative external fields

NASA Astrophysics Data System (ADS)

Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

2018-04-01

We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

DTIC Science & Technology

2011-03-10

more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...results give overviews on social interactions on a popular social network site . As each twitter account has different characteristics based on...the public and individuals post their private stories on their blogs and share their interests using social network sites . On the other hand, people

Vibrational Sum Frequency Generation Spectroscopy Study of Hydrous Species in Soda Lime Silica Float Glass.

PubMed

Luo, Jiawei; Banerjee, Joy; Pantano, Carlo G; Kim, Seong H

2016-06-21

It is generally accepted that the mechanical properties of soda lime silica (SLS) glass can be affected by the interaction between sodium ions and hydrous species (silanol groups and water molecules) in its surface region. While the amount of these hydrous species can be estimated from hydrogen profiles and infrared spectroscopy, their chemical environment in the glass network is still not well understood. This work employed vibrational sum frequency generation (SFG) spectroscopy to investigate the chemical environment of hydrous species in the surface region of SLS float glass. SLS float glass shows sharp peaks in the OH stretching vibration region in SFG spectra, while the OH stretch peaks of glasses that do not have leachable sodium ions and the OH peaks of water molecules in condensed phases are normally broad due to fast hydrogen bonding dynamics. The hydrous species responsible for the sharp SFG peaks for the SLS float glass were found to be thermodynamically more stable than physisorbed water molecules, did not exchange with D2O, and were associated with the sodium concentration gradient in the dealkalized subsurface region. These results suggested that the hydrous species reside in static solvation shells defined by the silicate network with relatively slow hydrogen bonding dynamics, compared to physisorbed water layers on top of the glass surface. A putative radial distribution of the hydrous species within the SLS glass network was estimated based on the OH SFG spectral features, which could be compared with theoretical distributions calculated from computational simulations.

Diversity of multilayer networks and its impact on collaborating epidemics

NASA Astrophysics Data System (ADS)

Min, Yong; Hu, Jiaren; Wang, Weihong; Ge, Ying; Chang, Jie; Jin, Xiaogang

2014-12-01

Interacting epidemics on diverse multilayer networks are increasingly important in modeling and analyzing the diffusion processes of real complex systems. A viral agent spreading on one layer of a multilayer network can interact with its counterparts by promoting (cooperative interaction), suppressing (competitive interaction), or inducing (collaborating interaction) its diffusion on other layers. Collaborating interaction displays different patterns: (i) random collaboration, where intralayer or interlayer induction has the same probability; (ii) concentrating collaboration, where consecutive intralayer induction is guaranteed with a probability of 1; and (iii) cascading collaboration, where consecutive intralayer induction is banned with a probability of 0. In this paper, we develop a top-bottom framework that uses only two distributions, the overlaid degree distribution and edge-type distribution, to model collaborating epidemics on multilayer networks. We then state the response of three collaborating patterns to structural diversity (evenness and difference of network layers). For viral agents with small transmissibility, we find that random collaboration is more effective in networks with higher diversity (high evenness and difference), while the concentrating pattern is more suitable in uneven networks. Interestingly, the cascading pattern requires a network with moderate difference and high evenness, and the moderately uneven coupling of multiple network layers can effectively increase robustness to resist cascading failure. With large transmissibility, however, we find that all collaborating patterns are more effective in high-diversity networks. Our work provides a systemic analysis of collaborating epidemics on multilayer networks. The results enhance our understanding of biotic and informative diffusion through multiple vectors.

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

PubMed Central

Friedman, Alexander; Slocum, Joshua F.; Tyulmankov, Danil; Gibb, Leif G.; Altshuler, Alex; Ruangwises, Suthee; Shi, Qinru; Toro Arana, Sebastian E.; Beck, Dirk W.; Sholes, Jacquelyn E. C.; Graybiel, Ann M.

2016-01-01

A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain. PMID:27222584

Mass balances of dissolved gases at river network scales across biomes.

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.; Sheehan, K.

2016-12-01

Estimating aquatic metabolism and gas fluxes at broad spatial scales is needed to evaluate the role of aquatic ecosystems in continental carbon cycles. We applied a river network model, FrAMES, to quantify the mass balances of dissolved oxygen at river network scales across five river networks in different biomes. The model accounts for hydrology; spatially varying re-aeration rates due to flow, slope, and water temperature; gas inputs via terrestrial runoff; variation in light due to canopy cover and water depth; benthic gross primary production; and benthic respiration. The model was parameterized using existing groundwater information and empirical relationships of GPP, R, and re-aeration, and was tested using dissolved oxygen patterns measured throughout river networks. We found that during summers, internal aquatic production dominates the river network mass balance of Kings Cr., Konza Prairie, KS (16.3 km2), whereas terrestrial inputs and aeration dominate the network mass balance at Coweeta Cr., Coweeta Forest, NC (15.7 km2). At network scales, both river networks are net heterotrophic, with Coweeta more so than Kings Cr. (P:R 0.6 vs. 0.7, respectively). The river network of Kings Creek showed higher network-scale GPP and R compared to Coweeta, despite having a lower drainage density because streams are on average wider so cumulative benthic surface areas are similar. Our findings suggest that the role of aquatic systems in watershed carbon balances will depend on interactions of drainage density, channel hydraulics, terrestrial vegetation, and biological activity.

Edge effects control helical wrapping of carbon nanotubes by polysaccharides

NASA Astrophysics Data System (ADS)

Liu, Yingzhe; Chipot, Christophe; Shao, Xueguang; Cai, Wensheng

2012-03-01

Carbon nanotubes (CNTs) wrapped by polysaccharide chains via noncovalent interactions have been shown to be soluble and dispersed in aqueous environments, and have several potential chemical and biomedical applications. The wrapping mechanism, in particular the role played by the end of the CNT, remains, however, unknown. In this work, a hybrid complex formed by an amylose (AMYL) chain and a single-walled carbon nanotube (SWNT) has been examined by means of atomistic molecular dynamics (MD) simulations to assess its propensity toward self-assembly, alongside its structural characteristics in water. To explore edge effects, the middle and end regions of the SWNT have been chosen as two initial wrapping sites, to which two relative orientations have been assigned, i.e. parallel and orthogonal. The present results prove that AMYL can wrap spontaneously around the tubular surface, starting from the end of the SWNT and driven by both favorable van der Waals attraction and hydrophobic interactions, and resulting in a perfectly compact, helical conformation stabilized by an interlaced hydrogen-bond network. Principal component analysis carried out over the MD trajectories reveals that stepwise burial of hydrophobic faces of pyranose rings controlled by hydrophobic interactions is a key step in the formation of the helix. Conversely, if wrapping proceeds from the middle of the SWNT, self-organization into a helical structure is not observed due to strong van der Waals attractions preventing the hydrophobic faces of the AMYL chain generating enough contacts with the tubular surface.Carbon nanotubes (CNTs) wrapped by polysaccharide chains via noncovalent interactions have been shown to be soluble and dispersed in aqueous environments, and have several potential chemical and biomedical applications. The wrapping mechanism, in particular the role played by the end of the CNT, remains, however, unknown. In this work, a hybrid complex formed by an amylose (AMYL) chain and a single-walled carbon nanotube (SWNT) has been examined by means of atomistic molecular dynamics (MD) simulations to assess its propensity toward self-assembly, alongside its structural characteristics in water. To explore edge effects, the middle and end regions of the SWNT have been chosen as two initial wrapping sites, to which two relative orientations have been assigned, i.e. parallel and orthogonal. The present results prove that AMYL can wrap spontaneously around the tubular surface, starting from the end of the SWNT and driven by both favorable van der Waals attraction and hydrophobic interactions, and resulting in a perfectly compact, helical conformation stabilized by an interlaced hydrogen-bond network. Principal component analysis carried out over the MD trajectories reveals that stepwise burial of hydrophobic faces of pyranose rings controlled by hydrophobic interactions is a key step in the formation of the helix. Conversely, if wrapping proceeds from the middle of the SWNT, self-organization into a helical structure is not observed due to strong van der Waals attractions preventing the hydrophobic faces of the AMYL chain generating enough contacts with the tubular surface. Electronic supplementary information (ESI) available: Table S1 shows the details of the systems for molecular dynamics simulations. Figure S1 shows time evolution of the distance RMSD over the heavy atoms of the AMYL chain with respect to the initial structure. The hydrogen-bond network including inter-residue and inter-turn hydrogen bonds monitored in the course of self-assembly is delineated in Figure S2. Figure S3 shows the equilibrium conformation of the initial right-handed AMYL chain wrapping the nanotube. See DOI: 10.1039/c2nr11979j

A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure.

PubMed

Kojic, M; Milosevic, M; Kojic, N; Kim, K; Ferrari, M; Ziemys, A

2014-02-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts.

A multiscale MD–FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure

PubMed Central

Kojic, M.; Milosevic, M.; Kojic, N.; Kim, K.; Ferrari, M.; Ziemys, A.

2014-01-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts. PMID:24578582

Cell-mediated fibre recruitment drives extracellular matrix mechanosensing in engineered fibrillar microenvironments

NASA Astrophysics Data System (ADS)

Baker, Brendon M.; Trappmann, Britta; Wang, William Y.; Sakar, Mahmut S.; Kim, Iris L.; Shenoy, Vivek B.; Burdick, Jason A.; Chen, Christopher S.

2015-12-01

To investigate how cells sense stiffness in settings structurally similar to native extracellular matrices, we designed a synthetic fibrous material with tunable mechanics and user-defined architecture. In contrast to flat hydrogel surfaces, these fibrous materials recapitulated cell-matrix interactions observed with collagen matrices including stellate cell morphologies, cell-mediated realignment of fibres, and bulk contraction of the material. Increasing the stiffness of flat hydrogel surfaces induced mesenchymal stem cell spreading and proliferation; however, increasing fibre stiffness instead suppressed spreading and proliferation for certain network architectures. Lower fibre stiffness permitted active cellular forces to recruit nearby fibres, dynamically increasing ligand density at the cell surface and promoting the formation of focal adhesions and related signalling. These studies demonstrate a departure from the well-described relationship between material stiffness and spreading established with hydrogel surfaces, and introduce fibre recruitment as a previously undescribed mechanism by which cells probe and respond to mechanics in fibrillar matrices.

Bioorthogonal in Situ Hydrogels Based on Polyether Polyols for New Biosensor Materials with High Sensitivity.

PubMed

Herrmann, Anna; Kaufmann, Lena; Dey, Pradip; Haag, Rainer; Schedler, Uwe

2018-04-04

Both noncovalent and covalent encapsulations of active biomolecules, for example, proteins and oligonucleotides, for a new biosensor matrix in an in situ bioorthogonal hydrogel formation via a strain-promoted azide-alkyne cycloaddition reaction were investigated. Unspecific interaction between the gel and the biomolecules as well as protein denaturation was prevented by the bioorthogonal gel components, which ensure a uniform aqueous environment in the hydrogel network. No leaching of the active biomolecules was observed. Additionally, a much higher and also adjustable loading of biomolecules in the hydrogel matrix was achieved compared to conventional biosensor surfaces, where the sensor molecules are immobilized on monolayers (2D surfaces) or brushlike structures (3D surfaces). Spotting experiments of the hydrogel confirm the possibility to use this new surface for microarray-based multiplex applications which require very high signal-to-noise ratios.

Atomic Origins of the Self-Healing Function in Cement–Polymer Composites

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

Nguyen, Manh-Thuong; Wang, Zheming; Rod, Kenton A.

Motivated by recent advances in self-healing cement and epoxy polymer composites, we present a combined ab initio molecular dynamics and sum frequency generation (SFG) spectroscopy study of a calcium-silicate-hydrate/polymer interface. On stable, low-defect surfaces, the polymer only weakly adheres through coordination and hydrogen bonding interactions and can be easily mobilized towards defected surfaces. Conversely, on fractured surfaces, the polymer strongly anchors through ionic Ca-O bonds resulting from the deprotonation of polymer hydroxyl groups. In addition, polymer S-S groups are turned away from the cement/polymer interface, allowing for the self-healing function within the polymer. The overall elasticity and healing properties ofmore » these composites stem from a flexible hydrogen bonding network that can readily adapt to surface morphology. The theoretical vibrational signals associated with the proposed cement-polymer interfacial chemistry were confirmed experimentally by SFG spectroscopy.« less

Molecular dynamics studies of interfacial water at the alumina surface.

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

Argyris, Dr. Dimitrios; Ho, Thomas; Cole, David

2011-01-01

Interfacial water properties at the alumina surface were investigated via all-atom equilibrium molecular dynamics simulations at ambient temperature. Al-terminated and OH-terminated alumina surfaces were considered to assess the structural and dynamic behavior of the first few hydration layers in contact with the substrates. Density profiles suggest water layering up to {approx}10 {angstrom} from the solid substrate. Planar density distribution data indicate that water molecules in the first interfacial layer are organized in well-defined patterns dictated by the atomic terminations of the alumina surface. Interfacial water exhibits preferential orientation and delayed dynamics compared to bulk water. Water exhibits bulk-like behavior atmore » distances greater than {approx}10 {angstrom} from the substrate. The formation of an extended hydrogen bond network within the first few hydration layers illustrates the significance of water?water interactions on the structural properties at the interface.« less

Atomic Origins of the Self-Healing Function in Cement-Polymer Composites.

PubMed

Nguyen, Manh-Thuong; Wang, Zheming; Rod, Kenton A; Childers, M Ian; Fernandez, Carlos; Koech, Phillip K; Bennett, Wendy D; Rousseau, Roger; Glezakou, Vassiliki-Alexandra

2018-01-24

Motivated by recent advances in self-healing cement and epoxy polymer composites, we present a combined ab initio molecular dynamics and sum frequency generation (SFG) vibrational spectroscopy study of a calcium-silicate-hydrate/polymer interface. On stable, low-defect surfaces, the polymer only weakly adheres through coordination and hydrogen bonding interactions and can be easily mobilized toward defected surfaces. Conversely, on fractured surfaces, the polymer strongly anchors through ionic Ca-O bonds resulting from the deprotonation of polymer hydroxyl groups. In addition, polymer S-S groups are turned away from the cement-polymer interface, allowing for the self-healing function within the polymer. The overall elasticity and healing properties of these composites stem from a flexible hydrogen bonding network that can readily adapt to surface morphology. The theoretical vibrational signals associated with the proposed cement-polymer interfacial chemistry were confirmed experimentally by SFG vibrational spectroscopy.

Network analysis applications in hydrology

NASA Astrophysics Data System (ADS)

Price, Katie

2017-04-01

Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

NASA Astrophysics Data System (ADS)

Han, Jing-Dong J.; Bertin, Nicolas; Hao, Tong; Goldberg, Debra S.; Berriz, Gabriel F.; Zhang, Lan V.; Dupuy, Denis; Walhout, Albertha J. M.; Cusick, Michael E.; Roth, Frederick P.; Vidal, Marc

2004-07-01

In apparently scale-free protein-protein interaction networks, or `interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the `hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: `party' hubs, which interact with most of their partners simultaneously, and `date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes-or modules -to each other, whereas party hubs function inside modules.

Gene essentiality and the topology of protein interaction networks

PubMed Central

Coulomb, Stéphane; Bauer, Michel; Bernard, Denis; Marsolier-Kergoat, Marie-Claude

2005-01-01

The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology. PMID:16087428

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Hazard Interactions and Interaction Networks (Cascades) within Multi-Hazard Methodologies

NASA Astrophysics Data System (ADS)

Gill, Joel; Malamud, Bruce D.

2016-04-01

Here we combine research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between 'multi-layer single hazard' approaches and 'multi-hazard' approaches that integrate such interactions. This synthesis suggests that ignoring interactions could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. We proceed to present an enhanced multi-hazard framework, through the following steps: (i) describe and define three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment; (ii) outline three types of interaction relationship (triggering, increased probability, and catalysis/impedance); and (iii) assess the importance of networks of interactions (cascades) through case-study examples (based on literature, field observations and semi-structured interviews). We further propose visualisation frameworks to represent these networks of interactions. Our approach reinforces the importance of integrating interactions between natural hazards, anthropogenic processes and technological hazards/disasters into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential, and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.

Community-level demographic consequences of urbanization: an ecological network approach.

PubMed

Rodewald, Amanda D; Rohr, Rudolf P; Fortuna, Miguel A; Bascompte, Jordi

2014-11-01

Ecological networks are known to influence ecosystem attributes, but we poorly understand how interspecific network structure affect population demography of multiple species, particularly for vertebrates. Establishing the link between network structure and demography is at the crux of being able to use networks to understand population dynamics and to inform conservation. We addressed the critical but unanswered question, does network structure explain demographic consequences of urbanization? We studied 141 ecological networks representing interactions between plants and nesting birds in forests across an urbanization gradient in Ohio, USA, from 2001 to 2011. Nest predators were identified by video-recording nests and surveyed from 2004 to 2011. As landscapes urbanized, bird-plant networks were more nested, less compartmentalized and dominated by strong interactions between a few species (i.e. low evenness). Evenness of interaction strengths promoted avian nest survival, and evenness explained demography better than urbanization, level of invasion, numbers of predators or other qualitative network metrics. Highly uneven networks had approximately half the nesting success as the most even networks. Thus, nest survival reflected how urbanization altered species interactions, particularly with respect to how nest placement affected search efficiency of predators. The demographic effects of urbanization were not direct, but were filtered through bird-plant networks. This study illustrates how network structure can influence demography at the community level and further, that knowledge of species interactions and a network approach may be requisite to understanding demographic responses to environmental change. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Physiological β-catenin signaling controls self-renewal networks and generation of stem-like cells from nasopharyngeal carcinoma.

PubMed

Cheng, Yue; Cheung, Arthur Kwok Leung; Ko, Josephine Mun Yee; Phoon, Yee Peng; Chiu, Pui Man; Lo, Paulisally Hau Yi; Waterman, Marian L; Lung, Maria Li

2013-09-27

A few reports suggested that low levels of Wnt signaling might drive cell reprogramming, but these studies could not establish a clear relationship between Wnt signaling and self-renewal networks. There are ongoing debates as to whether and how the Wnt/β-catenin signaling is involved in the control of pluripotency gene networks. Additionally, whether physiological β-catenin signaling generates stem-like cells through interactions with other pathways is as yet unclear. The nasopharyngeal carcinoma HONE1 cells have low expression of β-catenin and wild-type expression of p53, which provided a possibility to study regulatory mechanism of stemness networks induced by physiological levels of Wnt signaling in these cells. Introduction of increased β-catenin signaling, haploid expression of β-catenin under control by its natural regulators in transferred chromosome 3, resulted in activation of Wnt/β-catenin networks and dedifferentiation in HONE1 hybrid cell lines, but not in esophageal carcinoma SLMT1 hybrid cells that had high levels of endogenous β-catenin expression. HONE1 hybrid cells displayed stem cell-like properties, including enhancement of CD24(+) and CD44(+) populations and generation of spheres that were not observed in parental HONE1 cells. Signaling cascades were detected in HONE1 hybrid cells, including activation of p53- and RB1-mediated tumor suppressor pathways, up-regulation of Nanog-, Oct4-, Sox2-, and Klf4-mediated pluripotency networks, and altered E-cadherin expression in both in vitro and in vivo assays. qPCR array analyses further revealed interactions of physiological Wnt/β-catenin signaling with other pathways such as epithelial-mesenchymal transition, TGF-β, Activin, BMPR, FGFR2, and LIFR- and IL6ST-mediated cell self-renewal networks. Using β-catenin shRNA inhibitory assays, a dominant role for β-catenin in these cellular network activities was observed. The expression of cell surface markers such as CD9, CD24, CD44, CD90, and CD133 in generated spheres was progressively up-regulated compared to HONE1 hybrid cells. Thirty-four up-regulated components of the Wnt pathway were identified in these spheres. Wnt/β-catenin signaling regulates self-renewal networks and plays a central role in the control of pluripotency genes, tumor suppressive pathways and expression of cancer stem cell markers. This current study provides a novel platform to investigate the interaction of physiological Wnt/β-catenin signaling with stemness transition networks.

Mapping biological process relationships and disease perturbations within a pathway network.

PubMed

Stoney, Ruth; Robertson, David L; Nenadic, Goran; Schwartz, Jean-Marc

2018-01-01

Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network. Pathways represent spatial and temporal sets of context-dependent interactions, generating a high-level network when linked together, which incorporates contextual information without the need for molecular interaction data. Analysis of the pathway network revealed linked communities representing functional relationships, comparable to those found in molecular networks, including metabolism, signaling, immunity, and the cell cycle. We mapped a range of diseases onto this network and find that pathways associated with diseases tend to be functionally connected, highlighting the perturbed functions that result in disease phenotypes. We demonstrated that disease pathways cluster within the network. We then examined the distribution of cancer pathways and showed that cancer pathways tend to localize within the signaling, DNA processes and immune modules, although some cancer-associated nodes are found in other network regions. Altogether, we generated a high-confidence functional network, which avoids some of the shortcomings faced by conventional molecular models. Our representation provides an intuitive functional interpretation of cellular organization, which relies only on high-quality pathway and Gene Ontology data. The network is available at https://data.mendeley.com/datasets/3pbwkxjxg9/1.

Protein-protein interaction networks (PPI) and complex diseases

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

2014-01-01

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.

PubMed

Pancaldi, Vera; Carrillo-de-Santa-Pau, Enrique; Javierre, Biola Maria; Juan, David; Fraser, Peter; Spivakov, Mikhail; Valencia, Alfonso; Rico, Daniel

2016-07-08

Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements. Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks.

Interactions between neural networks: a mechanism for tuning chaos and oscillations.

PubMed

Wang, Lipo

2007-06-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

Kinetic stabilization of Bacillus licheniformis alpha-amylase through introduction of hydrophobic residues at the surface.

PubMed

Machius, Mischa; Declerck, Nathalie; Huber, Robert; Wiegand, Georg

2003-03-28

It is generally assumed that in proteins hydrophobic residues are not favorable at solvent-exposed sites, and that amino acid substitutions on the surface have little effect on protein thermostability. Contrary to these assumptions, we have identified hyperthermostable variants of Bacillus licheniformis alpha-amylase (BLA) that result from the incorporation of hydrophobic residues at the surface. Under highly destabilizing conditions, a variant combining five stabilizing mutations unfolds 32 times more slowly and at a temperature 13 degrees C higher than the wild-type. Crystal structure analysis at 1.7 A resolution suggests that stabilization is achieved through (a) extension of the concept of increased hydrophobic packing, usually applied to cavities, to surface indentations, (b) introduction of favorable aromatic-aromatic interactions on the surface, (c) specific stabilization of intrinsic metal binding sites, and (d) stabilization of a beta-sheet by introducing a residue with high beta-sheet forming propensity. All mutated residues are involved in forming complex, cooperative interaction networks that extend from the interior of the protein to its surface and which may therefore constitute "weak points" where BLA unfolding is initiated. This might explain the unexpectedly large effect induced by some of the substitutions on the kinetic stability of BLA. Our study shows that substantial protein stabilization can be achieved by stabilizing surface positions that participate in underlying cooperatively formed substructures. At such positions, even the apparently thermodynamically unfavorable introduction of hydrophobic residues should be explored.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks

PubMed Central

Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295

Interactivity vs. fairness in networked linux systems

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

Wu, Wenji; Crawford, Matt; /Fermilab

In general, the Linux 2.6 scheduler can ensure fairness and provide excellent interactive performance at the same time. However, our experiments and mathematical analysis have shown that the current Linux interactivity mechanism tends to incorrectly categorize non-interactive network applications as interactive, which can lead to serious fairness or starvation issues. In the extreme, a single process can unjustifiably obtain up to 95% of the CPU! The root cause is due to the facts that: (1) network packets arrive at the receiver independently and discretely, and the 'relatively fast' non-interactive network process might frequently sleep to wait for packet arrival. Thoughmore » each sleep lasts for a very short period of time, the wait-for-packet sleeps occur so frequently that they lead to interactive status for the process. (2) The current Linux interactivity mechanism provides the possibility that a non-interactive network process could receive a high CPU share, and at the same time be incorrectly categorized as 'interactive.' In this paper, we propose and test a possible solution to address the interactivity vs. fairness problems. Experiment results have proved the effectiveness of the proposed solution.« less

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

PubMed

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2017-03-14

Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of these gene interaction networks identified top ranked E. coli genes and 6 INO interaction types (e.g., regulation and gene expression). Vaccine-related E. coli gene-gene interaction network was constructed using ontology-based literature mining strategy, which identified important E. coli vaccine genes and their interactions with other genes through specific interaction types.

Network-based study reveals potential infection pathways of hepatitis-C leading to various diseases.

PubMed

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement.

Network-Based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement. PMID:24743187

The dissimilarity of species interaction networks.

PubMed

Poisot, Timothée; Canard, Elsa; Mouillot, David; Mouquet, Nicolas; Gravel, Dominique

2012-12-01

In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β-diversity. We emphasise that scaling up β-diversity of community composition to the β-diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions. © 2012 Blackwell Publishing Ltd/CNRS.

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

PubMed

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN.

System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

PubMed Central

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

Structure-Activity Relationship in TLR4 Mutations: Atomistic Molecular Dynamics Simulations and Residue Interaction Network Analysis

NASA Astrophysics Data System (ADS)

Anwar, Muhammad Ayaz; Choi, Sangdun

2017-03-01

Toll-like receptor 4 (TLR4), a vital innate immune receptor present on cell surfaces, initiates a signaling cascade during danger and bacterial intrusion. TLR4 needs to form a stable hexamer complex, which is necessary to dimerize the cytoplasmic domain. However, D299G and T399I polymorphism may abrogate the stability of the complex, leading to compromised TLR4 signaling. Crystallography provides valuable insights into the structural aspects of the TLR4 ectodomain; however, the dynamic behavior of polymorphic TLR4 is still unclear. Here, we employed molecular dynamics simulations (MDS), as well as principal component and residue network analyses, to decipher the structural aspects and signaling propagation associated with mutations in TLR4. The mutated complexes were less cohesive, displayed local and global variation in the secondary structure, and anomalous decay in rotational correlation function. Principal component analysis indicated that the mutated complexes also exhibited distinct low-frequency motions, which may be correlated to the differential behaviors of these TLR4 variants. Moreover, residue interaction networks (RIN) revealed that the mutated TLR4/myeloid differentiation factor (MD) 2 complex may perpetuate abnormal signaling pathways. Cumulatively, the MDS and RIN analyses elucidated the mutant-specific conformational alterations, which may help in deciphering the mechanism of loss-of-function mutations.

Linking Plant Specialization to Dependence in Interactions for Seed Set in Pollination Networks

PubMed Central

Tur, Cristina; Castro-Urgal, Rocío; Traveset, Anna

2013-01-01

Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled) can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them). Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i) linkage level (number of interactions), (ii) diversity of interactions, and (iii) closeness centrality (a measure of how much a species is connected to other plants via shared pollinators). Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent. PMID:24205187

Linking plant specialization to dependence in interactions for seed set in pollination networks.

PubMed

Tur, Cristina; Castro-Urgal, Rocío; Traveset, Anna

2013-01-01

Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled) can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them). Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i) linkage level (number of interactions), (ii) diversity of interactions, and (iii) closeness centrality (a measure of how much a species is connected to other plants via shared pollinators). Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent.

Harvesting electrostatic energy using super-hydrophobic surfaces

NASA Astrophysics Data System (ADS)

Pociecha, Dominik; Zylka, Pawel

2016-11-01

Almost all environments are now being extensively populated by miniaturized, nano-powered electronic sensor devices communicated together through wireless sensor networks building Internet of Things (IoT). Various energy harvesting techniques are being more and more frequently proposed for battery-less powering of such remote, unattended, implantable or wearable sensors or other low-power electronic gadgets. Energy harvesting relays on extracting energy from the ambient sources readily accessible at the sensor location and converting it into electrical power. The paper exploits possibility of generating electric energy safely accessible for nano-power electronics using tribo-electric and electrostatic induction phenomena displayed at super-hydrophobic surfaces impinged by water droplets. Mechanism of such interaction is discussed and illustrated by experimental results.

Lunar surface magnetometer experiment

NASA Technical Reports Server (NTRS)

Dyal, P.; Parkin, C. W.; Sonett, C. P.

1972-01-01

The Apollo 15 lunar-surface magnetometer (LSM) is one of a network of magnetometers that have been deployed on the moon to study intrinsic remanent magnetic fields and global magnetic response of the moon to large-scale solar and terrestrial magnetic fields. From these field measurements, properties of the lunar interior such as magnetic permeability, electrical conductivity, and temperature can be calculated. In addition, correlation with solar-wind-spectrometer data allows study of the the solar-wind plasma interaction with the moon and, in turn, investigation of the resulting absorption of gases and accretion of an ionosphere. These physical parameters and processes determined from magnetometer measurements must be accounted for by comprehensive theories of origin and evolution of the moon and solar system.

Fluxoids behavior in superconducting ladders

NASA Astrophysics Data System (ADS)

Sharon, Omri J.; Haham, Noam; Shaulov, Avner; Yeshurun, Yosef

2018-03-01

The nature of the interaction between fluxoids and between them and the external magnetic field is studied in one-dimensional superconducting networks. An Ising like expression is derived for the energy of a network revealing that fluxoids behave as repulsively interacting objects driven towards the network center by the effective applied field. Competition between these two interactions determines the equilibrium arrangement of fluxoids in the network as a function of the applied field. It is demonstrated that the fluxoids configurations are not always commensurate to the network symmetry. Incommensurate, degenerated configurations may be formed even in networks with an odd number of loops.

The interplay between pH sensitivity and label-free protein detection in immunologically modified nano-scaled field-effect transistor.

PubMed

Shalev, Gil; Rosenwaks, Yossi; Levy, Ilan

2012-01-15

We present experimental results in order to establish a correlation between pH sensitivity of immunologically modified nano-scaled field-effect transistor (NS-ImmunoFET) with their sensing capacity for label-free detection. The NS-ImmunoFETs are fabricated from silicon-on-insulator (SOI) wafers and are fully-depleted with thickness of ~20 nm. The data shows that higher sensitivity to pH entails enhanced sensitivity to analyte detection. This suggests that the mechanism of analyte detection as pure electrostatic perturbation induced by antibody-analyte interaction is over simplified. The fundamental assumption, in existing models for field-effect sensing mechanism assumes that the analyte molecules do not directly interact with the surface but rather stand 'deep' in the solution and away from the dielectric surface. Recent studies clearly provide contradicting evidence demonstrating that antibodies lie down flat on the surface. These observations led us to propose that the proteins that cover the gate area intimately interact with active sites on the surface thus forming a network of interacting sites. Since sensitivity to pH is directly correlated with the amount of amphoteric sites, we witness a direct correlation between sensitivity to pH and analyte detection. The highest and lowest threshold voltage shift for a label-free and specific detection of 6.5 nM IgG were 40 mV and 2.3 mV for NS-ImmunoFETs with pH sensitivity of 35 mV/decade and 15 mV/decade, respectively. Finally, physical modeling of the NS-ImmunoFET is presented and charge of a single IgG protein at pH 6 is calculated. The obtained value is consistent with charge of IgG protein cited in literature. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Alignment-free protein interaction network comparison

PubMed Central

Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

2014-01-01

Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information

PubMed Central

2013-01-01

Background In recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored. Results We provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes. Conclusions Although the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes. PMID:23663484

Probing the cross-effect of strains in non-linear elasticity of nearly regular polymer networks by pure shear deformation.

PubMed

Katashima, Takuya; Urayama, Kenji; Chung, Ung-il; Sakai, Takamasa

2015-05-07

The pure shear deformation of the Tetra-polyethylene glycol gels reveals the presence of an explicit cross-effect of strains in the strain energy density function even for the polymer networks with nearly regular structure including no appreciable amount of structural defect such as trapped entanglement. This result is in contrast to the expectation of the classical Gaussian network model (Neo Hookean model), i.e., the vanishing of the cross effect in regular networks with no trapped entanglement. The results show that (1) the cross effect of strains is not dependent on the network-strand length; (2) the cross effect is not affected by the presence of non-network strands; (3) the cross effect is proportional to the network polymer concentration including both elastically effective and ineffective strands; (4) no cross effect is expected exclusively in zero limit of network concentration in real polymer networks. These features indicate that the real polymer networks with regular network structures have an explicit cross-effect of strains, which originates from some interaction between network strands (other than entanglement effect) such as nematic interaction, topological interaction, and excluded volume interaction.

From watershed- to stream-reach-scale: the influence of multiple spatial scales on surface water-groundwater exchange

NASA Astrophysics Data System (ADS)

Caruso, Alice; Boano, Fulvio; Ridolfi, Luca

2015-04-01

Surface water bodies continuously interact with the subsurface and it is by now widely known that the hyporheic zone plays a key role in the mixing of river water with shallow groundwater. Hyporheic exchange occurs over a very wide range of spatial and temporal scales and the exchange processes at different scales interact and determine a complex system of nested flow cells. This intricacy results from the multiplicity of spatial scale that characterize landscape and river morphology. In the last years, many processes that regulate the surface-groundwater interactions have been elucidated and a more holistic view of groundwater and surface water has been adopted. However, despite several insights on the mechanisms of hyporheic exchange have been achieved, many important aspects remain to be clarified, i.e. how surface-groundwater interactions influence solute transport, microbial activity and biogeochemical transformations at the scale of entire watersheds. To date a deep knowledge of small-scale processes has been developed but what is lacking is a unifying overview of the role of surface water-groundwater exchange for the health of the whole water system at larger scales, i.e. the scale of the entire basin. In order to better understand the complex multiscale nature of spatial patterns of surface-subsurface exchange, we aim to assess the importance of the individual scales included in the range between watershed scale to stream reach scale. Hence, we study the large-scale subsurface flow field taking into account the surface-groundwater interactions induced by landscape topography from the basin scale to smaller scales ranging from tens of kilometers to tens of meters. The aim of this research is to analyze how individual topographic scales affect the flow field and to understand which ones are the most important and should be focused on. To study the impact of various scales of landscape topography we apply an analytical model that provides an exact solution of the underlying three dimensional groundwater flow and a numerical particle tracking routine that allows to obtain streamlines and residence time distributions from the flow field. Therefore, starting from a previously published mathematical tool we set the goal of investigating the interaction between the scales and clarifying their role. We consider real basin examples and describe subsurface flow at the landscape scale, identifying inflow patterns of groundwater to the river network, in order to obtain, in the near future, results to be used for conserving, managing and restoring of a riverine ecosystem.

Locally induced neuronal synchrony precisely propagates to specific cortical areas without rhythm distortion.

PubMed

Toda, Haruo; Kawasaki, Keisuke; Sato, Sho; Horie, Masao; Nakahara, Kiyoshi; Bepari, Asim K; Sawahata, Hirohito; Suzuki, Takafumi; Okado, Haruo; Takebayashi, Hirohide; Hasegawa, Isao

2018-05-16

Propagation of oscillatory spike firing activity at specific frequencies plays an important role in distributed cortical networks. However, there is limited evidence for how such frequency-specific signals are induced or how the signal spectra of the propagating signals are modulated during across-layer (radial) and inter-areal (tangential) neuronal interactions. To directly evaluate the direction specificity of spectral changes in a spiking cortical network, we selectively photostimulated infragranular excitatory neurons in the rat primary visual cortex (V1) at a supra-threshold level with various frequencies, and recorded local field potentials (LFPs) at the infragranular stimulation site, the cortical surface site immediately above the stimulation site in V1, and cortical surface sites outside V1. We found a significant reduction of LFP powers during radial propagation, especially at high-frequency stimulation conditions. Moreover, low-gamma-band dominant rhythms were transiently induced during radial propagation. Contrastingly, inter-areal LFP propagation, directed to specific cortical sites, accompanied no significant signal reduction nor gamma-band power induction. We propose an anisotropic mechanism for signal processing in the spiking cortical network, in which the neuronal rhythms are locally induced/modulated along the radial direction, and then propagate without distortion via intrinsic horizontal connections for spatiotemporally precise, inter-areal communication.

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

PubMed Central

Huber, Roland G.; Bond, Peter J.

2017-01-01

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

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

PubMed

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

2017-01-01

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

On the sufficiency of pairwise interactions in maximum entropy models of networks

NASA Astrophysics Data System (ADS)

Nemenman, Ilya; Merchan, Lina

Biological information processing networks consist of many components, which are coupled by an even larger number of complex multivariate interactions. However, analyses of data sets from fields as diverse as neuroscience, molecular biology, and behavior have reported that observed statistics of states of some biological networks can be approximated well by maximum entropy models with only pairwise interactions among the components. Based on simulations of random Ising spin networks with p-spin (p > 2) interactions, here we argue that this reduction in complexity can be thought of as a natural property of some densely interacting networks in certain regimes, and not necessarily as a special property of living systems. This work was supported in part by James S. McDonnell Foundation Grant No. 220020321.

Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

PubMed Central

Blonder, Benjamin; Dornhaus, Anna

2011-01-01

Background An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. Methodology/Findings Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. Conclusions/Significance Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales. PMID:21625450

Support surfaces for pressure ulcer prevention: A network meta-analysis

PubMed Central

Dumville, Jo C.; Cullum, Nicky

2018-01-01

Background Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult. Objectives To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness. Methods We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence. Main results We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence). Conclusions This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was of low or very low certainty, and more research is required to reduce these uncertainties. PMID:29474359

Support surfaces for pressure ulcer prevention: A network meta-analysis.

PubMed

Shi, Chunhu; Dumville, Jo C; Cullum, Nicky

2018-01-01

Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult. To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness. We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence. We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence). This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was of low or very low certainty, and more research is required to reduce these uncertainties.

Interactions between neural networks: a mechanism for tuning chaos and oscillations

PubMed Central

2007-01-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability. PMID:19003511

Construction of ontology augmented networks for protein complex prediction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Social networks predict selective observation and information spread in ravens

PubMed Central

Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

2016-01-01

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

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

Ba, Qian; Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing; Li, Junyang

2015-03-01

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong tomore » the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.« less

Functional modules by relating protein interaction networks and gene expression.

PubMed

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Functional modules by relating protein interaction networks and gene expression

PubMed Central

Tornow, Sabine; Mewes, H. W.

2003-01-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships. PMID:14576317

A human functional protein interaction network and its application to cancer data analysis

PubMed Central

2010-01-01

Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. PMID:20482850

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

PubMed

Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

2016-06-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

Understanding complex interactions using social network analysis.

PubMed

Pow, Janette; Gayen, Kaberi; Elliott, Lawrie; Raeside, Robert

2012-10-01

The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research. The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention. Review of literature and illustration of the application of the method of social network analysis using research examples. First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated. The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors. Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network. Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider. © 2012 Blackwell Publishing Ltd.

Rotation-libration in a hierarchic supramolecular rotor-stator system: arrhenius activation and retardation by local interaction.

PubMed

Wahl, Markus; Stöhr, Meike; Spillmann, Hannes; Jung, Thomas A; Gade, Lutz H

2007-04-07

Fourfold symmetric zinc-octaethylporphyrin (OEP) has been incorporated in the holes of the hexagonal molecular network generated by thermal dehydrogenation of 4,9-diaminoperylene-quinone-3,10-diimine (DPDI) on a Cu(111) surface and displayed hindered rotation; the reorganization between the potential minima, a rotation-libration, which is characterized by an activation energy of ED=0.17+/-0.03 eV, has been monitored in the STM tunnelling currents as a bi-state "switching".

PEGylated substrates of NSP4 protease: A tool to study protease specificity

NASA Astrophysics Data System (ADS)

Wysocka, Magdalena; Gruba, Natalia; Grzywa, Renata; Giełdoń, Artur; Bąchor, Remigiusz; Brzozowski, Krzysztof; Sieńczyk, Marcin; Dieter, Jenne; Szewczuk, Zbigniew; Rolka, Krzysztof; Lesner, Adam

2016-03-01

Herein we present the synthesis of a novel type of peptidomimetics composed of repeating diaminopropionic acid residues modified with structurally diverse heterobifunctional polyethylene glycol chains (abbreviated as DAPEG). Based on the developed compounds, a library of fluorogenic substrates was synthesized. Further library deconvolution towards human neutrophil serine protease 4 (NSP4) yielded highly sensitive and selective internally quenched peptidomimetic substrates. In silico analysis of the obtained peptidomimetics revealed the presence of an interaction network with distant subsites located on the enzyme surface.

Temporal changes in the structure of a plant-frugivore network are influenced by bird migration and fruit availability

PubMed Central

Andresen, Ellen; Díaz-Castelazo, Cecilia

2016-01-01

Background. Ecological communities are dynamic collections whose composition and structure change over time, making up complex interspecific interaction networks. Mutualistic plant–animal networks can be approached through complex network analysis; these networks are characterized by a nested structure consisting of a core of generalist species, which endows the network with stability and robustness against disturbance. Those mutualistic network structures can vary as a consequence of seasonal fluctuations and food availability, as well as the arrival of new species into the system that might disorder the mutualistic network structure (e.g., a decrease in nested pattern). However, there is no assessment on how the arrival of migratory species into seasonal tropical systems can modify such patterns. Emergent and fine structural temporal patterns are adressed here for the first time for plant-frugivorous bird networks in a highly seasonal tropical environment. Methods. In a plant-frugivorous bird community, we analyzed the temporal turnover of bird species comprising the network core and periphery of ten temporal interaction networks resulting from different bird migration periods. Additionally, we evaluated how fruit abundance and richness, as well as the arrival of migratory birds into the system, explained the temporal changes in network parameters such as network size, connectance, nestedness, specialization, interaction strength asymmetry and niche overlap. The analysis included data from 10 quantitative plant-frugivorous bird networks registered from November 2013 to November 2014. Results. We registered a total of 319 interactions between 42 plant species and 44 frugivorous bird species; only ten bird species were part of the network core. We witnessed a noteworthy turnover of the species comprising the network periphery during migration periods, as opposed to the network core, which did not show significant temporal changes in species composition. Our results revealed that migration and fruit richness explain the temporal variations in network size, connectance, nestedness and interaction strength asymmetry. On the other hand, fruit abundance only explained connectance and nestedness. Discussion. By means of a fine-resolution temporal analysis, we evidenced for the first time how temporal changes in the interaction network structure respond to the arrival of migratory species into the system and to fruit availability. Additionally, few migratory bird species are important links for structuring networks, while most of them were peripheral species. We showed the relevance of studying bird–plant interactions at fine temporal scales, considering changing scenarios of species composition with a quantitative network approach. PMID:27330852

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

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

Default Network Modulation and Large-Scale Network Interactivity in Healthy Young and Old Adults

PubMed Central

Schacter, Daniel L.

2012-01-01

We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands. PMID:22128194

DRoP: a water analysis program identifies Ras-GTP-specific pathway of communication between membrane-interacting regions and the active site.

PubMed

Kearney, Bradley M; Johnson, Christian W; Roberts, Daniel M; Swartz, Paul; Mattos, Carla

2014-02-06

Ras GTPase mediates several cellular signal transduction pathways and is found mutated in a large number of cancers. It is active in the GTP-bound state, where it interacts with effector proteins, and at rest in the GDP-bound state. The catalytic domain is tethered to the membrane, with which it interacts in a nucleotide-dependent manner. Here we present the program Detection of Related Solvent Positions (DRoP) for crystallographic water analysis on protein surfaces and use it to study Ras. DRoP reads and superimposes multiple Protein Data Bank coordinates, transfers symmetry-related water molecules to the position closest to the protein surface, and ranks the waters according to how well conserved and tightly clustered they are in the set of structures. Coloring according to this rank allows visualization of the results. The effector-binding region of Ras is hydrated with highly conserved water molecules at the interface between the P-loop, switch I, and switch II, as well as at the Raf-RBD binding pocket. Furthermore, we discovered a new conserved water-mediated H-bonding network present in Ras-GTP, but not in Ras-GDP, that links the nucleotide sensor residues R161 and R164 on helix 5 to the active site. The double mutant RasN85A/N86A, where the final link between helix 5 and the nucleotide is not possible, is a severely impaired enzyme, while the single mutant RasN86A, with partial connection to the active site, has a wild-type hydrolysis rate. DRoP was instrumental in determining the water-mediated connectivity networks that link two lobes of the catalytic domain in Ras. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Acoustic event location and background noise characterization on a free flying infrasound sensor network in the stratosphere

NASA Astrophysics Data System (ADS)

Bowman, Daniel C.; Albert, Sarah A.

2018-06-01

A variety of Earth surface and atmospheric sources generate low-frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth's surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphone stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while travelling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves at 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 s.

Acoustic Event Location and Background Noise Characterization on a Free Flying Infrasound Sensor Network in the Stratosphere

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

Bowman, Daniel C.; Albert, Sarah A.

We present that a variety of Earth surface and atmospheric sources generate low frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth’s surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphonemore » stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while traveling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves in the 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Lastly, background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 seconds.« less

Acoustic Event Location and Background Noise Characterization on a Free Flying Infrasound Sensor Network in the Stratosphere

DOE PAGES

Bowman, Daniel C.; Albert, Sarah A.

2018-02-22

We present that a variety of Earth surface and atmospheric sources generate low frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth’s surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphonemore » stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while traveling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves in the 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Lastly, background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 seconds.« less

Tough bonding of hydrogels to diverse non-porous surfaces

NASA Astrophysics Data System (ADS)

Yuk, Hyunwoo; Zhang, Teng; Lin, Shaoting; Parada, German Alberto; Zhao, Xuanhe

2016-02-01

In many animals, the bonding of tendon and cartilage to bone is extremely tough (for example, interfacial toughness ~800 J m-2 refs ,), yet such tough interfaces have not been achieved between synthetic hydrogels and non-porous surfaces of engineered solids. Here, we report a strategy to design tough transparent and conductive bonding of synthetic hydrogels containing 90% water to non-porous surfaces of diverse solids, including glass, silicon, ceramics, titanium and aluminium. The design strategy is to anchor the long-chain polymer networks of tough hydrogels covalently to non-porous solid surfaces, which can be achieved by the silanation of such surfaces. Compared with physical interactions, the chemical anchorage results in a higher intrinsic work of adhesion and in significant energy dissipation of bulk hydrogel during detachment, which lead to interfacial toughness values over 1,000 J m-2. We also demonstrate applications of robust hydrogel-solid hybrids, including hydrogel superglues, mechanically protective hydrogel coatings, hydrogel joints for robotic structures and robust hydrogel-metal conductors.

Network representation of protein interactions: Theory of graph description and analysis.

PubMed

Kurzbach, Dennis

2016-09-01

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

PubMed Central

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Discharge-nitrate data clustering for characterizing surface-subsurface flow interaction and calibration of a hydrologic model

NASA Astrophysics Data System (ADS)

Shrestha, R. R.; Rode, M.

2008-12-01

Concentration of reactive chemicals has different chemical signatures in baseflow and surface runoff. Previous studies on nitrate export from a catchment indicate that the transport processes are driven by subsurface flow. Therefore nitrate signature can be used for understanding the event and pre-event contributions to streamflow and surface-subsurface flow interactions. The study uses flow and nitrate concentration time series data for understanding the relationship between these two variables. Unsupervised artificial neural network based learning method called self organizing map is used for the identification of clusters in the datasets. Based on the cluster results, five different pattern in the datasets are identified which correspond to (i) baseflow, (ii) subsurface flow increase, (iii) surface runoff increase, (iv) surface runoff recession, and (v) subsurface flow decrease regions. The cluster results in combination with a hydrologic model are used for discharge separation. For this purpose, a multi-objective optimization tool NSGA-II is used, where violation of cluster results is used as one of the objective functions. The results show that the use of cluster results as supplementary information for the calibration of a hydrologic model gives a plausible simulation of subsurface flow as well total runoff at the catchment outlet. The study is undertaken using data from the Weida catchment in the North-Eastern Germany, which is a sub-catchment of the Weisse Elster river in the Elbe river basin.

The Synchronization within and Interaction between the Default and Dorsal Attention Networks in Early Infancy

PubMed Central

Gilmore, John H.; Shen, Dinggang; Smith, Jeffery Keith; Zhu, Hongtu

2013-01-01

An anticorrelated interaction between the dorsal attention and the default-mode networks has been observed, although how these 2 networks establish such relationship remains elusive. Behavioral studies have reported the emergence of attention and default network–related functions and a preliminary competing relationship between them at early infancy. This study attempted to test the hypothesis—resting-state functional magnetic resonance imaging will demonstrate not only improved network synchronization of the dorsal attention and the default networks, respectively, during the first 2 years of life but also an anticorrelated network interaction pattern between the 2 networks at 1 year which will be further enhanced at 2 years old. Our results demonstrate that both networks start from an isolated region in neonates but evolve to highly synchronized networks at 1 year old. Paralleling the individual network maturation process, the anticorrelated behaviors are absent at birth but become apparent at 1 year and are further enhanced during the second year of life. Our studies elucidate not only the individual maturation process of the dorsal attention and default networks but also offer evidence that the maturation of the individual networks may be needed prior exhibiting the adult-like interaction patterns between the 2 networks. PMID:22368080

Distributed optical microsensors for hydrogen leak detection and related applications

NASA Astrophysics Data System (ADS)

Hunter, Scott R.; Patton, James F.; Sepaniak, Michael J.; Datskos, Panos G.; Smith, D. Barton

2010-04-01

Significant advances have recently been made to develop optically interrogated microsensor based chemical sensors with specific application to hydrogen vapor sensing and leak detection in the hydrogen economy. We have developed functionalized polymer-film and palladium/silver alloy coated microcantilever arrays with nanomechanical sensing for this application. The uniqueness of this approach is in the use of independent component analysis (ICA) and the classification techniques of neural networks to analyze the signals produced by an array of microcantilever sensors. This analysis identifies and quantifies the amount of hydrogen and other trace gases physisorbed on the arrays. Selectivity is achieved by using arrays of functionalized sensors with a moderate distribution of specificity among the sensing elements. The device consists of an array of beam-shaped transducers with molecular recognition phases (MRPs) applied to one surface of the transducers. Bending moments on the individual transducers can be detected by illuminating them with a laser or an LED and then reading the reflected light with an optical position sensitive detector (PSD) such as a CCD. Judicious selection of MRPs for the array provides multiple isolated interaction surfaces for sensing the environment. When a particular chemical agent binds to a transducer, the effective surface stresses of its modified and uncoated sides change unequally and the transducer begins to bend. The extent of bending depends upon the specific interactions between the microcantilever's MRP and the analyte. Thus, the readout of a multi-MRP array is a complex multidimensional signal that can be analyzed to deconvolve a multicomponent gas mixture. The use of this sensing and analysis technique in unattended networked arrays of sensors for various monitoring and surveillance applications is discussed.

Simultaneous and coordinated rotational switching of all molecular rotors in a network

DOE PAGES

Zhang, Y.; Kersell, H.; Stefak, R.; ...

2016-05-09

A range of artificial molecular systems have been created that can exhibit controlled linear and rotational motion. In the development of such systems, a key step is the addition of communication between molecules in a network. Here, we show that a two-dimensional array of dipolar molecular rotors can undergo simultaneous rotational switching by applying an electric field from the tip of a scanning tunnelling microscope. Several hundred rotors made from porphyrin-based double-decker complexes can be simultaneously rotated when in a hexagonal rotor network on a Cu(111) surface by applying biases above ±1 V at 80 K. The phenomenon is observedmore » only in a hexagonal rotor network due to the degeneracy of the ground state dipole rotational energy barrier of the system. Defects are essential to increase electric torque on the rotor network and to stabilize the switched rotor domains. At low biases and low initial rotator angles, slight reorientations of individual rotors can occur resulting in the rotator arms pointing in different directions. In conclusion, analysis reveals that the rotator arm directions here are not random, but are coordinated to minimize energy via cross talk among the rotors through dipolar interactions.« less

Revealing networks from dynamics: an introduction

NASA Astrophysics Data System (ADS)

Timme, Marc; Casadiego, Jose

2014-08-01

What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity.

Statistical physics of interacting neural networks

NASA Astrophysics Data System (ADS)

Kinzel, Wolfgang; Metzler, Richard; Kanter, Ido

2001-12-01

Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game-a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

Resolution of 2-chloromandelic acid with (R)-(+)-N-benzyl-1-phenylethylamine: chiral discrimination mechanism.

PubMed

Peng, Yangfeng; He, Quan; Rohani, Sohrab; Jenkins, Hilary

2012-05-01

During the resolution of 2-chloromandelic acid with (R)-(+)-N-benzyl-1-phenylethylamine, the crystals of the less soluble salt were grown, and their structure were determined and presented. The chiral discrimination mechanism was investigated by examining the weak intermolecular interactions (such as hydrogen bond, CH/π, and van der Waals interactions) and molecular packing mode in crystal structure of the less soluble diastereomeric salt. A one-dimensional double-chain hydrogen-bonding network and a "lock-and-key" supramolecular packing mode are disclosed. The investigation demonstrates that hydrophobic layers with corrugated surfaces can fit into the grooves of one another to realize a compact packing, when the molecular structure of resolving agent is much larger than that of the racemate. This "lock-and-key" assembly is recognized to be another characteristic of molecular packing contributing to the chiral discrimination, in addition to the well-known sandwich-like packing by hydrophobic layers with planar boundary surfaces. Copyright © 2012 Wiley Periodicals, Inc.

Submicron bidirectional all-optical plasmonic switches

PubMed Central

Chen, Jianjun; Li, Zhi; Zhang, Xiang; Xiao, Jinghua; Gong, Qihuang

2013-01-01

Ultra-small all-optical switches are of importance in highly integrated optical communication and computing networks. However, the weak nonlinear light-matter interactions in natural materials present an enormous challenge to realize efficiently switching for the ultra-short interaction lengths. Here, we experimentally demonstrate a submicron bidirectional all-optical plasmonic switch with an asymmetric T-shape single slit. Sharp asymmetric spectra as well as significant field enhancements (about 18 times that in the conventional slit case) occur in the symmetry-breaking structure. Consequently, both of the surface plasmon polaritons propagating in the opposite directions on the metal surface are all-optically controlled inversely at the same time with the on/off switching ratios of >6 dB for the device lateral dimension of <1 μm. Moreover, in such a submicron structure, the coupling of free-space light and the on-chip bidirectional switching are integrated together. This submicron bidirectional all-optical switch may find important applications in the highly integrated plasmonic circuits. PMID:23486232

Review: Milk Proteins as Nanocarrier Systems for Hydrophobic Nutraceuticals.

PubMed

Kimpel, Florian; Schmitt, Joachim J

2015-11-01

Milk proteins and milk protein aggregates are among the most important nanovehicles in food technology. Milk proteins have various functional properties that facilitate their ability to carry hydrophobic nutraceutical substances. The main functional transport properties that were examined in the reviewed studies are binding of molecules or ions, surface activity, aggregation, gelation, and interaction with other polymers. Hydrophobic binding has been investigated using caseins and isolated β-casein as well as whey proteins. Surface activity of caseins has been used to create emulsion-based carrier systems. Furthermore, caseins are able to self-assemble into micelles, which can incorporate molecules. Gelation and interaction with other polymers can be used to encapsulate molecules into protein networks. The release of transported substances mainly depends on pH and swelling behavior of the proteins. The targeted use of nanocarrier systems requires specific knowledge about the binding mechanisms between the proteins and the carried substances in a certain food matrix. © 2015 Institute of Food Technologists®

Combining Multiple Forms Of Visual Information To Specify Contact Relations In Spatial Layout

NASA Astrophysics Data System (ADS)

Sedgwick, Hal A.

1990-03-01

An expert system, called Layout2, has been described, which models a subset of available visual information for spatial layout. The system is used to examine detailed interactions between multiple, partially redundant forms of information in an environment-centered geometrical model of an environment obeying certain rather general constraints. This paper discusses the extension of Layout2 to include generalized contact relations between surfaces. In an environment-centered model, the representation of viewer-centered distance is replaced by the representation of environmental location. This location information is propagated through the representation of the environment by a network of contact relations between contiguous surfaces. Perspective information interacts with other forms of information to specify these contact relations. The experimental study of human perception of contact relations in extended spatial layouts is also discussed. Differences between human results and Layout2 results reveal limitations in the human ability to register available information; they also point to the existence of certain forms of information not yet formalized in Layout2.

Learning Analytics for Networked Learning Models

ERIC Educational Resources Information Center

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

Non-criticality of interaction network over system's crises: A percolation analysis.

PubMed

Shirazi, Amir Hossein; Saberi, Abbas Ali; Hosseiny, Ali; Amirzadeh, Ehsan; Toranj Simin, Pourya

2017-11-20

Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises.

Surface structural conformations of fibrinogen polypeptides for improved biocompatibility.

PubMed

Yaseen, Mohammed; Zhao, Xiubo; Freund, Amy; Seifalian, Alexander M; Lu, Jian R

2010-05-01

This work reports on how incorporation of silica nanocages into poly(urethane) copolymers (PU) affects conformational orientations of adsorbed fibrinogen and how different surfaces subsequently influenced HeLa cell attachment and proliferation. Incorporation of 2 wt% silica nanocages into poly(urethane) (PU4) substantially altered the surface topography of the films and some 50% of the surface was covered with the nanocages due to their preferential exposure. AFM studies revealed the deposition of a dense protein network on the soft polymeric domains of PU4 and much reduced fibrinogen adsorption on the hard nanocage domains. As on the bare SiO(2) control surface, fibrinogen molecules adsorbed on top of the hard nanocages mainly took the dominant trinodular structures in monomeric and dimeric forms. In addition, net positively charged long alpha chains were prone to being hidden beneath the D domains whilst gamma chains predominantly remained exposed. Dynamic interfacial adsorption as probed by spectroscopic ellipsometry revealed fast changes in interfacial conformation induced by electrostatic interactions between different segments of fibrinogen and the surface, consistent with the AFM imaging. On the PU surfaces without nanocage incorporation (PUA), however, adsorbed fibrinogen molecules formed beads-like chain networks, consistent with the structure featured on the soft PU4 domains, showing very different effects of surface chemical nature. Monoclonal antibodies specific to the alpha and gamma chains showed reduced alpha but increased gamma chain binding at the silicon oxide control and PU4 surfaces, whilst on the PUA, C18 and amine surfaces (organic surface controls) the opposite binding trend was detected with alpha chain binding dominant, showing different fibrinogen conformations. Cell attachment studies revealed differences in cell attachment and proliferation, consistent with the different polypeptide conformations on the two types of surfaces, showing a strong preference to the extent of exposure of gamma chains. Crown Copyright 2010. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

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

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

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

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

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

PubMed

Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

2008-10-01

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

Extending the Confrontation of Weather and Climate Models from Soil Moisture to Surface Flux Data

NASA Astrophysics Data System (ADS)

Dirmeyer, P.; Chen, L.; Wu, J.

2016-12-01

The atmosphere and land components of weather and climate models are typically developed separately and coupled as a last step before new model versions are released. Separate testing of land surface models (LSMs) and atmospheric models is often quite extensive in the development phase, but validation of coupled land-atmosphere behavior is often minimal if performed at all. This is partly because of this piecemeal model development approach and partly because the necessary in situ data to confront coupled land-atmosphere models (LAMs) has been meager until quite recently. Over the past 10-20 years there has been a growing number of networks of measurements of land surface states, surface fluxes, radiation and near-surface meteorology, although they have been largely uncoordinated and frequently incomplete across the range of variables necessary to validate LAMs. We extend recent work "confronting" a variety of LSMs and LAMs with in situ observations of soil moisture from cross-standardized networks to comparisons with measurements of surface latent and sensible heat fluxes at FLUXNET sites in a variety of climate regimes around the world. The motivation is to determine how well LSMs represent observed statistics of variability and co-variability, how much models differ from one another, and how those statistics change when the LSMs are coupled to atmospheric models. Furthermore, comparisons are made to several LAMs in both open-loop (free running) and reanalysis configurations. This shows to what extent data assimilation can constrain the processes involved in flux variability, and helps illuminate model development pathways to improve coupled land-atmosphere interactions in weather and climate models.

Nonlinear dynamics of ice-wedge networks and resulting sensitivity to severe cooling events.

PubMed

Plug, L J; Werner, B T

2002-06-27

Patterns of subsurface wedges of ice that form along cooling-induced tension fractures, expressed at the ground surface by ridges or troughs spaced 10 30 m apart, are ubiquitous in polar lowlands. Fossilized ice wedges, which are widespread at lower latitudes, have been used to infer the duration and mean temperature of cold periods within Proterozoic and Quaternary climates, and recent climate trends have been inferred from fracture frequency in active ice wedges. Here we present simulations from a numerical model for the evolution of ice-wedge networks over a range of climate scenarios, based on the interactions between thermal tensile stress, fracture and ice wedges. We find that short-lived periods of severe cooling permanently alter the spacing between ice wedges as well as their fracture frequency. This affects the rate at which the widths of ice wedges increase as well as the network's response to subsequent climate change. We conclude that wedge spacing and width in ice-wedge networks mainly reflect infrequent episodes of rapidly falling ground temperatures rather than mean conditions.

Super-resolution optical microscopy resolves network morphology of smart colloidal microgels.

PubMed

Bergmann, Stephan; Wrede, Oliver; Huser, Thomas; Hellweg, Thomas

2018-02-14

We present a new method to resolve the network morphology of colloidal particles in an aqueous environment via super-resolution microscopy. By localization of freely diffusing fluorophores inside the particle network we can resolve the three dimensional structure of one species of colloidal particles (thermoresponsive microgels) without altering their chemical composition through copolymerization with fluorescent monomers. Our approach utilizes the interaction of the fluorescent dye rhodamine 6G with the polymer network to achieve an indirect labeling. We calculate the 3D structure from the 2D images and compare the structure to previously published models for the microgel morphology, e.g. the fuzzy sphere model. To describe the differences in the data an extension of this model is suggested. Our method enables the tailor-made fabrication of colloidal particles which are used in various applications, such as paints or cosmetics, and are promising candidates for drug delivery, smart surface coatings, and nanocatalysis. With the precise knowledge of the particle morphology an understanding of the underlying structure-property relationships for various colloidal systems is possible.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Susceptibility of Phytomonas serpens to calpain inhibitors in vitro: interference on the proliferation, ultrastructure, cysteine peptidase expression and interaction with the invertebrate host.

PubMed

Oliveira, Simone Santiago Carvalho de; Gonçalves, Diego de Souza; Garcia-Gomes, Aline Dos Santos; Gonçalves, Inês Correa; Seabra, Sergio Henrique; Menna-Barreto, Rubem Figueiredo; Lopes, Angela Hampshire de Carvalho Santos; D'Avila-Levy, Claudia Masini; Santos, André Luis Souza Dos; Branquinha, Marta Helena

2017-01-01

A pleiotropic response to the calpain inhibitor MDL28170 was detected in the tomato parasite Phytomonas serpens. Ultrastructural studies revealed that MDL28170 caused mitochondrial swelling, shortening of flagellum and disruption of trans Golgi network. This effect was correlated to the inhibition in processing of cruzipain-like molecules, which presented an increase in expression paralleled by decreased proteolytic activity. Concomitantly, a calcium-dependent cysteine peptidase was detected in the parasite extract, the activity of which was repressed by pre-incubation of parasites with MDL28170. Flow cytometry and Western blotting analyses revealed the differential expression of calpain-like proteins (CALPs) in response to the pre-incubation of parasites with the MDL28170, and confocal fluorescence microscopy confirmed their surface location. The interaction of promastigotes with explanted salivary glands of the insect Oncopeltus fasciatus was reduced when parasites were pre-treated with MDL28170, which was correlated to reduced levels of surface cruzipain-like and gp63-like molecules. Treatment of parasites with anti-Drosophila melanogaster (Dm) calpain antibody also decreased the adhesion process. Additionally, parasites recovered from the interaction process presented higher levels of surface cruzipain-like and gp63-like molecules, with similar levels of CALPs cross-reactive to anti-Dm-calpain antibody. The results confirm the importance of exploring the use of calpain inhibitors in studying parasites' physiology.

Susceptibility of Phytomonas serpens to calpain inhibitors in vitro: interference on the proliferation, ultrastructure, cysteine peptidase expression and interaction with the invertebrate host

PubMed Central

de Oliveira, Simone Santiago Carvalho; Gonçalves, Diego de Souza; Garcia-Gomes, Aline dos Santos; Gonçalves, Inês Correa; Seabra, Sergio Henrique; Menna-Barreto, Rubem Figueiredo; Lopes, Angela Hampshire de Carvalho Santos; D’Avila-Levy, Claudia Masini; dos Santos, André Luis Souza; Branquinha, Marta Helena

2016-01-01

A pleiotropic response to the calpain inhibitor MDL28170 was detected in the tomato parasite Phytomonas serpens. Ultrastructural studies revealed that MDL28170 caused mitochondrial swelling, shortening of flagellum and disruption of trans Golgi network. This effect was correlated to the inhibition in processing of cruzipain-like molecules, which presented an increase in expression paralleled by decreased proteolytic activity. Concomitantly, a calcium-dependent cysteine peptidase was detected in the parasite extract, the activity of which was repressed by pre-incubation of parasites with MDL28170. Flow cytometry and Western blotting analyses revealed the differential expression of calpain-like proteins (CALPs) in response to the pre-incubation of parasites with the MDL28170, and confocal fluorescence microscopy confirmed their surface location. The interaction of promastigotes with explanted salivary glands of the insect Oncopeltus fasciatus was reduced when parasites were pre-treated with MDL28170, which was correlated to reduced levels of surface cruzipain-like and gp63-like molecules. Treatment of parasites with anti-Drosophila melanogaster (Dm) calpain antibody also decreased the adhesion process. Additionally, parasites recovered from the interaction process presented higher levels of surface cruzipain-like and gp63-like molecules, with similar levels of CALPs cross-reactive to anti-Dm-calpain antibody. The results confirm the importance of exploring the use of calpain inhibitors in studying parasites’ physiology. PMID:27925020

Perceptual asymmetry reveals neural substrates underlying stereoscopic transparency.

PubMed

Tsirlin, Inna; Allison, Robert S; Wilcox, Laurie M

2012-02-01

We describe a perceptual asymmetry found in stereoscopic perception of overlaid random-dot surfaces. Specifically, the minimum separation in depth needed to perceptually segregate two overlaid surfaces depended on the distribution of dots across the surfaces. With the total dot density fixed, significantly larger inter-plane disparities were required for perceptual segregation of the surfaces when the front surface had fewer dots than the back surface compared to when the back surface was the one with fewer dots. We propose that our results reflect an asymmetry in the signal strength of the front and back surfaces due to the assignment of the spaces between the dots to the back surface by disparity interpolation. This hypothesis was supported by the results of two experiments designed to reduce the imbalance in the neuronal response to the two surfaces. We modeled the psychophysical data with a network of inter-neural connections: excitatory within-disparity and inhibitory across disparity, where the spread of disparity was modulated according to figure-ground assignment. These psychophysical and computational findings suggest that stereoscopic transparency depends on both inter-neural interactions of disparity-tuned cells and higher-level processes governing figure ground segregation. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

NASA Astrophysics Data System (ADS)

Gill, Joel C.; Malamud, Bruce D.

2016-08-01

This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.

An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

PubMed Central

Holden, Brian J; Pinney, John W; Lovell, Simon C; Amoutzias, Grigoris D; Robertson, David L

2007-01-01

Background Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. Results Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. Conclusion We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available. PMID:17683601

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

PubMed

Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene-encoded proteins are attached to the core at more peripheral positions of the networks.

Brain network dysfunction in youth with obsessive-compulsive disorder induced by simple uni-manual behavior: The role of the dorsal anterior cingulate cortex

PubMed Central

Friedman, Amy L.; Burgess, Ashley; Ramaseshan, Karthik; Easter, Phil; Khatib, Dalal; Chowdury, Asadur; Arnold, Paul D.; Hanna, Gregory L.; Rosenberg, David R.; Diwadkar, Vaibhav A.

2017-01-01

In an effort to elucidate differences in functioning brain networks between youth with obsessive-compulsive disorder and controls, we used fMRI signals to analyze brain network interactions of the dorsal anterior cingulate cortex (dACC) during visually coordinated motor responses. Subjects made a uni-manual response to briefly presented probes, at periodic (allowing participants to maintain a “motor set”) or random intervals (demanding reactive responses). Network interactions were assessed using psycho-physiological interaction (PPI), a basic model of functional connectivity evaluating modulatory effects of the dACC in the context of each task condition. Across conditions, OCD were characterized by hyper-modulation by the dACC, with loci alternatively observed as both condition-general and condition-specific. Thus, dynamically driven task demands during simple uni-manual motor control induce compensatory network interactions in cortical-thalamic regions in OCD. These findings support previous research in OCD showing compensatory network interactions during complex memory tasks, but establish that these network effects are observed during basic sensorimotor processing. Thus, these patterns of network dysfunction may in fact be independent of the complexity of tasks used to induce brain network activity. Hypothesis-driven approaches coupled with sophisticated network analyses are a highly valuable approach in using fMRI to uncover mechanisms in disorders like OCD. PMID:27992792

Identification of infection- and defense-related genes via a dynamic host-pathogen interaction network using a Candida albicans-zebrafish infection model.

PubMed

Kuo, Zong-Yu; Chuang, Yung-Jen; Chao, Chun-Cheih; Liu, Fu-Chen; Lan, Chung-Yu; Chen, Bor-Sen

2013-01-01

Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs. Copyright © 2013 S. Karger AG, Basel.

Variations in Social Network Type Membership Among Older African Americans, Caribbean Blacks, and Non-Hispanic Whites.

PubMed

Nguyen, Ann W

2017-07-01

This study examined race differences in the probability of belonging to a specific social network typology of family, friends, and church members. Samples of African Americans, Caribbean blacks, and non-Hispanic whites aged 55+ were drawn from the National Survey of American Life. Typology indicators related to social integration and negative interactions with family, friendship, and church networks were used. Latent class analysis was used to identify typologies, and latent class multinomial logistic regression was used to assess the influence of race, and interactions between race and age, and race and education on typology membership. Four network typologies were identified: optimal (high social integration, low negative interaction), family-centered (high social integration within primarily the extended family network, low negative interaction), strained (low social integration, high negative interaction), and ambivalent (high social integration and high negative interaction). Findings for race and age and race and education interactions indicated that the effects of education and age on typology membership varied by race. Overall, the findings demonstrate how race interacts with age and education to influence the probability of belonging to particular network types. A better understanding of the influence of race, education, and age on social network typologies will inform future research and theoretical developments in this area. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Neutral Community Dynamics and the Evolution of Species Interactions.

PubMed

Coelho, Marco Túlio P; Rangel, Thiago F

2018-04-01

A contemporary goal in ecology is to determine the ecological and evolutionary processes that generate recurring structural patterns in mutualistic networks. One of the great challenges is testing the capacity of neutral processes to replicate observed patterns in ecological networks, since the original formulation of the neutral theory lacks trophic interactions. Here, we develop a stochastic-simulation neutral model adding trophic interactions to the neutral theory of biodiversity. Without invoking ecological differences among individuals of different species, and assuming that ecological interactions emerge randomly, we demonstrate that a spatially explicit multitrophic neutral model is able to capture the recurrent structural patterns of mutualistic networks (i.e., degree distribution, connectance, nestedness, and phylogenetic signal of species interactions). Nonrandom species distribution, caused by probabilistic events of migration and speciation, create nonrandom network patterns. These findings have broad implications for the interpretation of niche-based processes as drivers of ecological networks, as well as for the integration of network structures with demographic stochasticity.

Empirical evaluation of neutral interactions in host-parasite networks.

PubMed

Canard, E F; Mouquet, N; Mouillot, D; Stanko, M; Miklisova, D; Gravel, D

2014-04-01

While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

AFM study of morphology and mechanical properties of a chimeric spider silk and bone sialoprotein protein for bone regeneration

PubMed Central

Gomes, Sílvia; Numata, Keiji; Leonor, Isabel B.; Mano, João F.; Reis, Rui L.; Kaplan, David L.

2011-01-01

Atomic force microscopy (AFM) was used to assess a new chimeric protein consisting of a fusion protein of the consensus repeat for Nephila clavipes spider dragline protein and bone sialoprotein (6mer+BSP). The elastic modulus of this protein in film form was assessed through force curves, and film surface roughness was also determined. The results showed a significant difference between the elastic modulus of the chimeric silk protein, 6mer+BSP, and control films consisting of only the silk component (6mer). The behaviour of the 6mer+BSP and 6mer proteins in aqueous solution in the presence of calcium (Ca) ions was also assessed to determine interactions between the inorganic and organic components related to bone interactions, anchoring and biomaterial network formation. The results demonstrated the formation of protein networks in the presence of Ca2+ ions, characteristics that may be important in the context of controlling materials assembly and properties related to bone-formation with this new chimeric silk-BSP protein. PMID:21370930

AFM study of morphology and mechanical properties of a chimeric spider silk and bone sialoprotein protein for bone regeneration.

PubMed

Gomes, Sílvia; Numata, Keiji; Leonor, Isabel B; Mano, João F; Reis, Rui L; Kaplan, David L

2011-05-09

Atomic force microscopy (AFM) was used to assess a new chimeric protein consisting of a fusion protein of the consensus repeat for Nephila clavipes spider dragline protein and bone sialoprotein (6mer+BSP). The elastic modulus of this protein in film form was assessed through force curves, and film surface roughness was also determined. The results showed a significant difference among the elastic modulus of the chimeric silk protein, 6mer+BSP, and control films consisting of only the silk component (6mer). The behavior of the 6mer+BSP and 6mer proteins in aqueous solution in the presence of calcium (Ca) ions was also assessed to determine interactions between the inorganic and organic components related to bone interactions, anchoring, and biomaterial network formation. The results demonstrated the formation of protein networks in the presence of Ca(2+) ions, characteristics that may be important in the context of controlling materials assembly and properties related to bone formation with this new chimeric silk-BSP protein.

A protein interaction network analysis for yeast integral membrane protein.

PubMed

Shi, Ming-Guang; Huang, De-Shuang; Li, Xue-Ling

2008-01-01

Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

A new 1D manganese(II) coordination polymer with end-to-end azide bridge and isonicotinoylhydrazone Schiff base ligand: Crystal structure, Hirshfeld surface, NBO and thermal analyses

NASA Astrophysics Data System (ADS)

Khani, S.; Montazerozohori, M.; Masoudiasl, A.; White, J. M.

2018-02-01

A new manganese (II) coordination polymer, [MnL2 (μ-1,3-N3)2]n, with co-ligands including azide anion and Schiff base based on isonicotinoylhydrazone has been synthesized and characterized. The crystal structure determination shows that the azide ligand acts as end-to-end (EE) bridging ligand and generates a one-dimensional coordination polymer. In this compound, each manganes (II) metal center is hexa-coordinated by four azide nitrogens and two pyridinic nitrogens for the formation of octahedral geometry. The analysis of crystal packing indicates that the 1D chain of [MnL2 (μ-1,3-N3)2]n, is stabilized as a 3D supramolecular network by intra- and inter-chain intermolecular interactions of X-H···Y (X = N and C, Y = O and N). Hirshfeld surface analysis and 2D fingerprint plots have been used for a more detailed investigation of intermolecular interactions. Also, natural bond orbital (NBO) analysis was performed to get information about atomic charge distributions, hybridizations and the strength of interactions. Finally, thermal analysis of compound showed its complete decomposition during three thermal steps.

Transient inter-cellular polymeric linker.

PubMed

Ong, Siew-Min; He, Lijuan; Thuy Linh, Nguyen Thi; Tee, Yee-Han; Arooz, Talha; Tang, Guping; Tan, Choon-Hong; Yu, Hanry

2007-09-01

Three-dimensional (3D) tissue-engineered constructs with bio-mimicry cell-cell and cell-matrix interactions are useful in regenerative medicine. In cell-dense and matrix-poor tissues of the internal organs, cells support one another via cell-cell interactions, supplemented by small amount of the extra-cellular matrices (ECM) secreted by the cells. Here we connect HepG2 cells directly but transiently with inter-cellular polymeric linker to facilitate cell-cell interaction and aggregation. The linker consists of a non-toxic low molecular-weight polyethyleneimine (PEI) backbone conjugated with multiple hydrazide groups that can aggregate cells within 30 min by reacting with the aldehyde handles on the chemically modified cell-surface glycoproteins. The cells in the cellular aggregates proliferated; and maintained the cortical actin distribution of the 3D cell morphology while non-aggregated cells died over 7 days of suspension culture. The aggregates lost distinguishable cell-cell boundaries within 3 days; and the ECM fibers became visible around cells from day 3 onwards while the inter-cellular polymeric linker disappeared from the cell surfaces over time. The transient inter-cellular polymeric linker can be useful for forming 3D cellular and tissue constructs without bulk biomaterials or extensive network of engineered ECM for various applications.

Gulf of Mexico Loop Current Interactions with the West Florida Shelf and its Influence on Harmful Algae Blooms

NASA Astrophysics Data System (ADS)

Liu, Y.; Weisberg, R. H.

2016-02-01

Interactions of the Loop Current (LC) system with the West Florida Shelf (WFS) are examined using 20+ years (1993 - 2015) of Ssalto/Duacs multi-mission altimetry data in the eastern Gulf of Mexico. Characteristic patterns of LC system sea surface height and surface geostrophic currents are extracted by an unsupervised neural network, Self-Organizing Map, along with their frequencies of occurrence. These current patterns suggest linkages with harmful algae bloom occurrences as recorded by in situ K. brevis cell counts. It is argued that LC system interactions with the shelf slope play an important role in WFS ecology through the upwelling of new inorganic nutrients across the shelf break. This is particularly important when the LC impinges on the southwest corner of the WFS slope, thereby impacting shallow water isobaths and setting the entire shelf circulation into motion. If such conditions persist, then deeper ocean waters with elevated nutrient content may broach the shelf and be transported landward. Resetting the nutrient state of the shelf by the coastal ocean circulation in response to deep-ocean forcing demonstrates the importance of physical oceanography in shelf ecology.

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

PubMed Central

Thibodeau, Asa; Márquez, Eladio J.; Luo, Oscar; Ruan, Yijun; Shin, Dong-Guk; Stitzel, Michael L.; Ucar, Duygu

2016-01-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/. PMID:27336171

Recycling Endosomes and Viral Infection.

PubMed

Vale-Costa, Sílvia; Amorim, Maria João

2016-03-08

Many viruses exploit specific arms of the endomembrane system. The unique composition of each arm prompts the development of remarkably specific interactions between viruses and sub-organelles. This review focuses on the viral-host interactions occurring on the endocytic recycling compartment (ERC), and mediated by its regulatory Ras-related in brain (Rab) GTPase Rab11. This protein regulates trafficking from the ERC and the trans-Golgi network to the plasma membrane. Such transport comprises intricate networks of proteins/lipids operating sequentially from the membrane of origin up to the cell surface. Rab11 is also emerging as a critical factor in an increasing number of infections by major animal viruses, including pathogens that provoke human disease. Understanding the interplay between the ERC and viruses is a milestone in human health. Rab11 has been associated with several steps of the viral lifecycles by unclear processes that use sophisticated diversified host machinery. For this reason, we first explore the state-of-the-art on processes regulating membrane composition and trafficking. Subsequently, this review outlines viral interactions with the ERC, highlighting current knowledge on viral-host binding partners. Finally, using examples from the few mechanistic studies available we emphasize how ERC functions are adjusted during infection to remodel cytoskeleton dynamics, innate immunity and membrane composition.

IAEA activities on atomic, molecular and plasma-material interaction data for fusion

NASA Astrophysics Data System (ADS)

Braams, Bastiaan J.; Chung, Hyun-Kyung

2013-09-01

The IAEA Atomic and Molecular Data Unit (http://www-amdis.iaea.org/) aims to provide internationally evaluated and recommended data for atomic, molecular and plasma-material interaction (A+M+PMI) processes in fusion research. The Unit organizes technical meetings and coordinates an A+M Data Centre Network (DCN) and a Code Centre Network (CCN). In addition the Unit organizes Coordinated Research Projects (CRPs), for which the objectives are mixed between development of new data and evaluation and recommendation of existing data. In the area of A+M data we are placing new emphasis in our meeting schedule on data evaluation and especially on uncertainties in calculated cross section data and the propagation of uncertainties through structure data and fundamental cross sections to effective rate coefficients. Following a recent meeting of the CCN it is intended to use electron scattering on Be, Ne and N2 as exemplars for study of uncertainties and uncertainty propagation in calculated data; this will be discussed further at the presentation. Please see http://www-amdis.iaea.org/CRP/ for more on our active and planned CRPs, which are concerned with atomic processes in core and edge plasma and with plasma interaction with beryllium-based surfaces and with irradiated tungsten.

Amyloid plaque structure and cell surface interactions of β-amyloid fibrils revealed by electron tomography

PubMed Central

Han, Shen; Kollmer, Marius; Markx, Daniel; Claus, Stephanie; Walther, Paul; Fändrich, Marcus

2017-01-01

The deposition of amyloid fibrils as plaques is a key feature of several neurodegenerative diseases including in particular Alzheimer’s. This disease is characterized, if not provoked, by amyloid aggregates formed from Aβ peptide that deposit inside the brain or are toxic to neuronal cells. We here used scanning transmission electron microscopy (STEM) to determine the fibril network structure and interactions of Aβ fibrils within a cell culture model of Alzheimer’s disease. STEM images taken from the formed Aβ amyloid deposits revealed three main types of fibril network structures, termed amorphous meshwork, fibril bundle and amyloid star. All three were infiltrated by different types of lipid inclusions from small-sized exosome-like structures (50–100 nm diameter) to large-sized extracellular vesicles (up to 300 nm). The fibrils also presented strong interactions with the surrounding cells such that fibril bundles extended into tubular invaginations of the plasma membrane. Amyloid formation in the cell model was previously found to have an intracellular origin and we show here that it functionally destroys the integrity of the intracellular membranes as it leads to lysosomal leakage. These data provide a mechanistic link to explain why intracellular fibril formation is toxic to the cell. PMID:28240273

Recycling Endosomes and Viral Infection

PubMed Central

Vale-Costa, Sílvia; Amorim, Maria João

2016-01-01

Many viruses exploit specific arms of the endomembrane system. The unique composition of each arm prompts the development of remarkably specific interactions between viruses and sub-organelles. This review focuses on the viral–host interactions occurring on the endocytic recycling compartment (ERC), and mediated by its regulatory Ras-related in brain (Rab) GTPase Rab11. This protein regulates trafficking from the ERC and the trans-Golgi network to the plasma membrane. Such transport comprises intricate networks of proteins/lipids operating sequentially from the membrane of origin up to the cell surface. Rab11 is also emerging as a critical factor in an increasing number of infections by major animal viruses, including pathogens that provoke human disease. Understanding the interplay between the ERC and viruses is a milestone in human health. Rab11 has been associated with several steps of the viral lifecycles by unclear processes that use sophisticated diversified host machinery. For this reason, we first explore the state-of-the-art on processes regulating membrane composition and trafficking. Subsequently, this review outlines viral interactions with the ERC, highlighting current knowledge on viral-host binding partners. Finally, using examples from the few mechanistic studies available we emphasize how ERC functions are adjusted during infection to remodel cytoskeleton dynamics, innate immunity and membrane composition. PMID:27005655

The tangled web of non-canonical Wnt signalling in neural migration.

PubMed

Clark, Charlotte E J; Nourse, C Cathrin; Cooper, Helen M

2012-01-01

In all multicellular animals, successful embryogenesis is dependent on the ability of cells to detect the status of the local environment and respond appropriately. The nature of the extracellular environment is communicated to the intracellular compartment by ligand/receptor interactions at the cell surface. The Wnt canonical and non-canonical signalling pathways are found in the most primitive metazoans, and they play an essential role in the most fundamental developmental processes in all multicellular organisms. Vertebrates have expanded the number of Wnts and Frizzled receptors and have additionally evolved novel Wnt receptor families (Ryk, Ror). The multiplicity of potential interactions between Wnts, their receptors and downstream effectors has exponentially increased the complexity of the signal transduction network. Signalling through each of the Wnt pathways, as well as crosstalk between them, plays a critical role in the establishment of the complex architecture of the vertebrate central nervous system. In this review, we explore the signalling networks triggered by non-canonical Wnt/receptor interactions, focussing on the emerging roles of the non-conventional Wnt receptors Ryk and Ror. We describe the role of these pathways in neural tube formation and axon guidance where Wnt signalling controls tissue polarity, coordinated cell migration and axon guidance via remodelling of the cytoskeleton. Copyright © 2012 S. Karger AG, Basel.

Solid-state structure of 1-(diaminomethylene)thiouron-1-ium propionate

NASA Astrophysics Data System (ADS)

Janczak, Jan

2017-10-01

The single crystals of 1-(diaminomethylene)thiouron-1-ium propionate suitable for the X-ray analysis were grown using a solution growth technique room temperature. The compound crystallises in the centrosymmetric C2/c space group of the monoclinic system. The conformation of the 1-(diaminomethylene)thiouron-1-ium cation is not strictly planar, but slightly twisted. Both planar arms of the cation are oppositely rotated by 2.1(1)° around the Csbnd N bonds involving the central N atom. The propionate(-) anion is also non-planar, the carboxylate group is turned by 4.3(1)° in relation to the planar carbon chain. The arrangement of oppositely charged components, i.e. 1-(diaminomethylene)thiouron-1-ium cations and propionate(-) anions in the crystal is mainly determined by ionic and Nsbnd H⋯O hydrogen bonding interactions forming two-dimensional network aligned to (100) plane. The neighbouring 2D layers interact via much weaker Nsbnd H⋯S hydrogen bonds forming three-dimensional hydrogen bonded network. Hirshfeld surface and the analysis of 2D fingerprint plots are illustrating both quantitatively and qualitatively interactions governing the supramolecular assemblies. The compound was also characterised by the FT-IR and Raman spectroscopy. The vibrational assignments have been supported by the isotopic frequency shift.

Disrupting the Networks of Cancer

PubMed Central

Camacho, Daniel F.; Pienta, Kenneth J.

2014-01-01

Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. PMID:22442061

Disrupting the networks of cancer.

PubMed

Camacho, Daniel F; Pienta, Kenneth J

2012-05-15

Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. ©2012 AACR.

Speech networks at rest and in action: interactions between functional brain networks controlling speech production.

PubMed

Simonyan, Kristina; Fuertinger, Stefan

2015-04-01

Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. Copyright © 2015 the American Physiological Society.

Condition-dependent functional connectivity: syntax networks in bilinguals

PubMed Central

Dodel, Silke; Golestani, Narly; Pallier, Christophe; ElKouby, Vincent; Le Bihan, Denis; Poline, Jean-Baptiste

2005-01-01

This paper introduces a method to study the variation of brain functional connectivity networks with respect to experimental conditions in fMRI data. It is related to the psychophysiological interaction technique introduced by Friston et al. and extends to networks of correlation modulation (CM networks). Extended networks containing several dozens of nodes are determined in which the links correspond to consistent correlation modulation across subjects. In addition, we assess inter-subject variability and determine networks in which the condition-dependent functional interactions can be explained by a subject-dependent variable. We applied the technique to data from a study on syntactical production in bilinguals and analysed functional interactions differentially across tasks (word reading or sentence production) and across languages. We find an extended network of consistent functional interaction modulation across tasks, whereas the network comparing languages shows fewer links. Interestingly, there is evidence for a specific network in which the differences in functional interaction across subjects can be explained by differences in the subjects' syntactical proficiency. Specifically, we find that regions, including ones that have previously been shown to be involved in syntax and in language production, such as the left inferior frontal gyrus, putamen, insula, precentral gyrus, as well as the supplementary motor area, are more functionally linked during sentence production in the second, compared with the first, language in syntactically more proficient bilinguals than in syntactically less proficient ones. Our approach extends conventional activation analyses to the notion of networks, emphasizing functional interactions between regions independently of whether or not they are activated. On the one hand, it gives rise to testable hypotheses and allows an interpretation of the results in terms of the previous literature, and on the other hand, it provides a basis for studying the structure of functional interactions as a whole, and hence represents a further step towards the notion of large-scale networks in functional imaging. PMID:16087437

Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

PubMed

Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

2011-11-01

A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

Cluster Approach to Network Interaction in Pedagogical University

ERIC Educational Resources Information Center

Chekaleva, Nadezhda V.; Makarova, Natalia S.; Drobotenko, Yulia B.

2016-01-01

The study presented in the article is devoted to the analysis of theory and practice of network interaction within the framework of education clusters. Education clusters are considered to be a novel form of network interaction in pedagogical education in Russia. The aim of the article is to show the advantages and disadvantages of the cluster…

Network Analysis Reveals a Common Host-Pathogen Interaction Pattern in Arabidopsis Immune Responses.

PubMed

Li, Hong; Zhou, Yuan; Zhang, Ziding

2017-01-01

Many plant pathogens secrete virulence effectors into host cells to target important proteins in host cellular network. However, the dynamic interactions between effectors and host cellular network have not been fully understood. Here, an integrative network analysis was conducted by combining Arabidopsis thaliana protein-protein interaction network, known targets of Pseudomonas syringae and Hyaloperonospora arabidopsidis effectors, and gene expression profiles in the immune response. In particular, we focused on the characteristic network topology of the effector targets and differentially expressed genes (DEGs). We found that effectors tended to manipulate key network positions with higher betweenness centrality. The effector targets, especially those that are common targets of an individual effector, tended to be clustered together in the network. Moreover, the distances between the effector targets and DEGs increased over time during infection. In line with this observation, pathogen-susceptible mutants tended to have more DEGs surrounding the effector targets compared with resistant mutants. Our results suggest a common plant-pathogen interaction pattern at the cellular network level, where pathogens employ potent local impact mode to interfere with key positions in the host network, and plant organizes an in-depth defense by sequentially activating genes distal to the effector targets.

Cdc42 and formin activity control non-muscle myosin dynamics during Drosophila heart morphogenesis

PubMed Central

Vogler, Georg; Liu, Jiandong; Iafe, Timothy W.; Migh, Ede; Mihály, József

2014-01-01

During heart formation, a network of transcription factors and signaling pathways guide cardiac cell fate and differentiation, but the genetic mechanisms orchestrating heart assembly and lumen formation remain unclear. Here, we show that the small GTPase Cdc42 is essential for Drosophila melanogaster heart morphogenesis and lumen formation. Cdc42 genetically interacts with the cardiogenic transcription factor tinman; with dDAAM which belongs to the family of actin organizing formins; and with zipper, which encodes nonmuscle myosin II. Zipper is required for heart lumen formation, and its spatiotemporal activity at the prospective luminal surface is controlled by Cdc42. Heart-specific expression of activated Cdc42, or the regulatory formins dDAAM and Diaphanous caused mislocalization of Zipper and induced ectopic heart lumina, as characterized by luminal markers such as the extracellular matrix protein Slit. Placement of Slit at the lumen surface depends on Cdc42 and formin function. Thus, Cdc42 and formins play pivotal roles in heart lumen formation through the spatiotemporal regulation of the actomyosin network. PMID:25267295

Network analysis reveals the recognition mechanism for complex formation of mannose-binding lectins

NASA Astrophysics Data System (ADS)

Jian, Yiren; Zhao, Yunjie; Zeng, Chen

The specific carbohydrate binding of lectin makes the protein a powerful molecular tool for various applications including cancer cell detection due to its glycoprotein profile on the cell surface. Most biologically active lectins are dimeric. To understand the structure-function relation of lectin complex, it is essential to elucidate the short- and long-range driving forces behind the dimer formation. Here we report our molecular dynamics simulations and associated dynamical network analysis on a particular lectin, i.e., the mannose-binding lectin from garlic. Our results, further supported by sequence coevolution analysis, shed light on how different parts of the complex communicate with each other. We propose a general framework for deciphering the recognition mechanism underlying protein-protein interactions that may have potential applications in signaling pathways.

Complement Involvement in Periodontitis: Molecular Mechanisms and Rational Therapeutic Approaches.

PubMed

Hajishengallis, George; Maekawa, Tomoki; Abe, Toshiharu; Hajishengallis, Evlambia; Lambris, John D

2015-01-01

The complement system is a network of interacting fluid-phase and cell surface-associated molecules that trigger, amplify, and regulate immune and inflammatory signaling pathways. Dysregulation of this finely balanced network can destabilize host-microbe homeostasis and cause inflammatory tissue damage. Evidence from clinical and animal model-based studies suggests that complement is implicated in the pathogenesis of periodontitis, a polymicrobial community-induced chronic inflammatory disease that destroys the tooth-supporting tissues. This review discusses molecular mechanisms of complement involvement in the dysbiotic transformation of the periodontal microbiome and the resulting destructive inflammation, culminating in loss of periodontal bone support. These mechanistic studies have additionally identified potential therapeutic targets. In this regard, interventional studies in preclinical models have provided proof-of-concept for using complement inhibitors for the treatment of human periodontitis.

Magneto-nanosensor platform for probing low-affinity protein–protein interactions and identification of a low-affinity PD-L1/PD-L2 interaction

PubMed Central

Lee, Jung-Rok; Bechstein, Daniel J. B.; Ooi, Chin Chun; Patel, Ashka; Gaster, Richard S.; Ng, Elaine; Gonzalez, Lino C.; Wang, Shan X.

2016-01-01

Substantial efforts have been made to understand the interactions between immune checkpoint receptors and their ligands targeted in immunotherapies against cancer. To carefully characterize the complete network of interactions involved and the binding affinities between their extracellular domains, an improved kinetic assay is needed to overcome limitations with surface plasmon resonance (SPR). Here, we present a magneto-nanosensor platform integrated with a microfluidic chip that allows measurement of dissociation constants in the micromolar-range. High-density conjugation of magnetic nanoparticles with prey proteins allows multivalent receptor interactions with sensor-immobilized bait proteins, more closely mimicking natural-receptor clustering on cells. The platform has advantages over traditional SPR in terms of insensitivity of signal responses to pH and salinity, less consumption of proteins and better sensitivities. Using this platform, we characterized the binding affinities of the PD-1—PD-L1/PD-L2 co-inhibitory receptor system, and discovered an unexpected interaction between the two known PD-1 ligands, PD-L1 and PD-L2. PMID:27447090

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

PubMed Central

Stetz, Gabrielle; Verkhivker, Gennady M.

2017-01-01

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

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

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2017-01-01

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

Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces.

PubMed

Engin, H Billur; Kreisberg, Jason F; Carter, Hannah

2016-01-01

Recently it has been shown that cancer mutations selectively target protein-protein interactions. We hypothesized that mutations affecting distinct protein interactions involving established cancer genes could contribute to tumor heterogeneity, and that novel mechanistic insights might be gained into tumorigenesis by investigating protein interactions under positive selection in cancer. To identify protein interactions under positive selection in cancer, we mapped over 1.2 million nonsynonymous somatic cancer mutations onto 4,896 experimentally determined protein structures and analyzed their spatial distribution. In total, 20% of mutations on the surface of known cancer genes perturbed protein-protein interactions (PPIs), and this enrichment for PPI interfaces was observed for both tumor suppressors (Odds Ratio 1.28, P-value < 10(-4)) and oncogenes (Odds Ratio 1.17, P-value < 10(-3)). To study this further, we constructed a bipartite network representing structurally resolved PPIs from all available human complexes in the Protein Data Bank (2,864 proteins, 3,072 PPIs). Analysis of frequently mutated cancer genes within this network revealed that tumor-suppressors, but not oncogenes, are significantly enriched with functional mutations in homo-oligomerization regions (Odds Ratio 3.68, P-Value < 10(-8)). We present two important examples, TP53 and beta-2-microglobulin, for which the patterns of somatic mutations at interfaces provide insights into specifically perturbed biological circuits. In patients with TP53 mutations, patient survival correlated with the specific interactions that were perturbed. Moreover, we investigated mutations at the interface of protein-nucleotide interactions and observed an unexpected number of missense mutations but not silent mutations occurring within DNA and RNA binding sites. Finally, we provide a resource of 3,072 PPI interfaces ranked according to their mutation rates. Analysis of this list highlights 282 novel candidate cancer genes that encode proteins participating in interactions that are perturbed recurrently across tumors. In summary, mutation of specific protein interactions is an important contributor to tumor heterogeneity and may have important implications for clinical outcomes.

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

Comparing species interaction networks along environmental gradients.

PubMed

Pellissier, Loïc; Albouy, Camille; Bascompte, Jordi; Farwig, Nina; Graham, Catherine; Loreau, Michel; Maglianesi, Maria Alejandra; Melián, Carlos J; Pitteloud, Camille; Roslin, Tomas; Rohr, Rudolf; Saavedra, Serguei; Thuiller, Wilfried; Woodward, Guy; Zimmermann, Niklaus E; Gravel, Dominique

2018-05-01

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients. © 2017 Cambridge Philosophical Society.

Synaptic activity induces input-specific rearrangements in a targeted synaptic protein interaction network.

PubMed

Lautz, Jonathan D; Brown, Emily A; VanSchoiack, Alison A Williams; Smith, Stephen E P

2018-05-27

Cells utilize dynamic, network level rearrangements in highly interconnected protein interaction networks to transmit and integrate information from distinct signaling inputs. Despite the importance of protein interaction network dynamics, the organizational logic underlying information flow through these networks is not well understood. Previously, we developed the quantitative multiplex co-immunoprecipitation platform, which allows for the simultaneous and quantitative measurement of the amount of co-association between large numbers of proteins in shared complexes. Here, we adapt quantitative multiplex co-immunoprecipitation to define the activity dependent dynamics of an 18-member protein interaction network in order to better understand the underlying principles governing glutamatergic signal transduction. We first establish that immunoprecipitation detected by flow cytometry can detect activity dependent changes in two known protein-protein interactions (Homer1-mGluR5 and PSD-95-SynGAP). We next demonstrate that neuronal stimulation elicits a coordinated change in our targeted protein interaction network, characterized by the initial dissociation of Homer1 and SynGAP-containing complexes followed by increased associations among glutamate receptors and PSD-95. Finally, we show that stimulation of distinct glutamate receptor types results in different modular sets of protein interaction network rearrangements, and that cells activate both modules in order to integrate complex inputs. This analysis demonstrates that cells respond to distinct types of glutamatergic input by modulating different combinations of protein co-associations among a targeted network of proteins. Our data support a model of synaptic plasticity in which synaptic stimulation elicits dissociation of preexisting multiprotein complexes, opening binding slots in scaffold proteins and allowing for the recruitment of additional glutamatergic receptors. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

PubMed

Takemoto, Kazuhiro; Aie, Kazuki

2017-05-25

Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks.

PubMed

Shtark, Mark B; Kozlova, Lyudmila I; Bezmaternykh, Dmitriy D; Mel'nikov, Mikhail Ye; Savelov, Andrey A; Sokhadze, Estate M

2018-06-01

Neural networks interaction was studied in healthy men (20-35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI-EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as "successful" in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these "successful" trainees. The experimental group (N = 23 total, N = 13 "successful") upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 "successful") beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

An Evolutionarily Conserved Innate Immunity Protein Interaction Network*

PubMed Central

De Arras, Lesly; Seng, Amara; Lackford, Brad; Keikhaee, Mohammad R.; Bowerman, Bruce; Freedman, Jonathan H.; Schwartz, David A.; Alper, Scott

2013-01-01

The innate immune response plays a critical role in fighting infection; however, innate immunity also can affect the pathogenesis of a variety of diseases, including sepsis, asthma, cancer, and atherosclerosis. To identify novel regulators of innate immunity, we performed comparative genomics RNA interference screens in the nematode Caenorhabditis elegans and mouse macrophages. These screens have uncovered many candidate regulators of the response to lipopolysaccharide (LPS), several of which interact physically in multiple species to form an innate immunity protein interaction network. This protein interaction network contains several proteins in the canonical LPS-responsive TLR4 pathway as well as many novel interacting proteins. Using RNAi and overexpression studies, we show that almost every gene in this network can modulate the innate immune response in mouse cell lines. We validate the importance of this network in innate immunity regulation in vivo using available mutants in C. elegans and mice. PMID:23209288

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.

The Use of CASES-97 Observations to Assess and Parameterize the Impact of Land-Surface Heterogeneity on Area-Average Surface Heat Fluxes for Large-Scale Coupled Atmosphere-Hydrology Models

NASA Technical Reports Server (NTRS)

Chen, Fei; Yates, David; LeMone, Margaret

2001-01-01

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we develop a multiscale data set. This data set, based on the Cooperative Atmosphere-Surface Exchange Study (CASES97) observations, includes atmospheric, surface, and sub-surface observations obtained from a dense observation network covering a large region on the order of 100 km. We use this data set to drive three land-surface models (LSMs) to generate multi-scale (with three resolutions of 1, 5, and 10 kilometers) gridded surface heat flux maps for the CASES area. Upon validating these flux maps with measurements from surface station and aircraft, we utilize them to investigate several approaches for estimating the area-integrated surface heat flux for the CASES97 domain of 71x74 square kilometers, which is crucial for land surface model development/validation and area water and energy budget studies. This research is aimed at understanding the relative contribution of random turbulence versus organized mesoscale circulations to the area-integrated surface flux at the scale of 100 kilometers, and identifying the most important effective parameters for characterizing the subgrid-scale variability for large-scale atmosphere-hydrology models.

Chemical-Gene Interactions from ToxCast Bioactivity Data ...

EPA Pesticide Factsheets

Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in the literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets. To evaluate the information gained from the ToxCast project, a ToxCast bioactivity network was created comprising ToxCast chemical-gene interactions based on assay data and compared to a chemical-gene association network from literature. The literature network was compiled from PubMed articles, excluding ToxCast publications, mapped to genes and chemicals. Genes were identified by curated associations available from NCBI while chemicals were identified by PubChem submissions. The frequencies of chemical-gene associations from the literature network were log-scaled and then compared to the ToxCast bioactivity network. In total, 140 times more chemical-gene associations were present in the ToxCast network in comparison to the literature-derived network highlighting the vast increase in chemical-gene interactions putatively elucidated by the ToxCast research program. There were 165 associations found in the literature network that were reproduced by ToxCast bioactivity data, and 336 associations in the literature network were not reproduced by the ToxCast bioactivity network. The literature network relies on the assumption that chemical-gene associations represent a true chemical-gene inte

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Hydration of a Large Anionic Charge Distribution - Naphthalene-Water Cluster Anions

NASA Astrophysics Data System (ADS)

Weber, J. Mathias; Adams, Christopher L.

2010-06-01

We report the infrared spectra of anionic clusters of naphthalene with up to three water molecules. Comparison of the experimental infrared spectra with theoretically predicted spectra from quantum chemistry calculations allow conclusions regarding the structures of the clusters under study. The first water molecule forms two hydrogen bonds with the π electron system of the naphthalene moiety. Subsequent water ligands interact with both the naphthalene and the other water ligands to form hydrogen bonded networks, similar to other hydrated anion clusters. Naphthalene-water anion clusters illustrate how water interacts with negative charge delocalized over a large π electron system. The clusters are interesting model systems that are discussed in the context of wetting of graphene surfaces and polyaromatic hydrocarbons.

Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility.

PubMed

Heffernan, Rhys; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

2017-09-15

The accuracy of predicting protein local and global structural properties such as secondary structure and solvent accessible surface area has been stagnant for many years because of the challenge of accounting for non-local interactions between amino acid residues that are close in three-dimensional structural space but far from each other in their sequence positions. All existing machine-learning techniques relied on a sliding window of 10-20 amino acid residues to capture some 'short to intermediate' non-local interactions. Here, we employed Long Short-Term Memory (LSTM) Bidirectional Recurrent Neural Networks (BRNNs) which are capable of capturing long range interactions without using a window. We showed that the application of LSTM-BRNN to the prediction of protein structural properties makes the most significant improvement for residues with the most long-range contacts (|i-j| >19) over a previous window-based, deep-learning method SPIDER2. Capturing long-range interactions allows the accuracy of three-state secondary structure prediction to reach 84% and the correlation coefficient between predicted and actual solvent accessible surface areas to reach 0.80, plus a reduction of 5%, 10%, 5% and 10% in the mean absolute error for backbone ϕ , ψ , θ and τ angles, respectively, from SPIDER2. More significantly, 27% of 182724 40-residue models directly constructed from predicted C α atom-based θ and τ have similar structures to their corresponding native structures (6Å RMSD or less), which is 3% better than models built by ϕ and ψ angles. We expect the method to be useful for assisting protein structure and function prediction. The method is available as a SPIDER3 server and standalone package at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

PubMed

Yang, Lei; Zhao, Xudong; Tang, Xianglong

2014-01-01

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

Functional Specialization in the Human Brain Estimated By Intrinsic Hemispheric Interaction

PubMed Central

Wang, Danhong; Buckner, Randy L.

2014-01-01

The human brain demonstrates functional specialization, including strong hemispheric asymmetries. Here specialization was explored using fMRI by examining the degree to which brain networks preferentially interact with ipsilateral as opposed to contralateral networks. Preferential within-hemisphere interaction was prominent in the heteromodal association cortices and minimal in the sensorimotor cortices. The frontoparietal control network exhibited strong within-hemisphere interactions but with distinct patterns in each hemisphere. The frontoparietal control network preferentially coupled to the default network and language-related regions in the left hemisphere but to attention networks in the right hemisphere. This arrangement may facilitate control of processing functions that are lateralized. Moreover, the regions most linked to asymmetric specialization also display the highest degree of evolutionary cortical expansion. Functional specialization that emphasizes processing within a hemisphere may allow the expanded hominin brain to minimize between-hemisphere connectivity and distribute domain-specific processing functions. PMID:25209275

Multiple regimes of robust patterns between network structure and biodiversity

NASA Astrophysics Data System (ADS)

Jover, Luis F.; Flores, Cesar O.; Cortez, Michael H.; Weitz, Joshua S.

2015-12-01

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities.

Multiple regimes of robust patterns between network structure and biodiversity

PubMed Central

Jover, Luis F.; Flores, Cesar O.; Cortez, Michael H.; Weitz, Joshua S.

2015-01-01

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities. PMID:26632996

Dense fibrillar collagen is a potent inducer of invadopodia via a specific signaling network

PubMed Central

Swatkoski, Stephen; Matsumoto, Kazue; Campbell, Catherine B.; Petrie, Ryan J.; Dimitriadis, Emilios K.; Li, Xin; Mueller, Susette C.; Bugge, Thomas H.; Gucek, Marjan

2015-01-01

Cell interactions with the extracellular matrix (ECM) can regulate multiple cellular activities and the matrix itself in dynamic, bidirectional processes. One such process is local proteolytic modification of the ECM. Invadopodia of tumor cells are actin-rich proteolytic protrusions that locally degrade matrix molecules and mediate invasion. We report that a novel high-density fibrillar collagen (HDFC) matrix is a potent inducer of invadopodia, both in carcinoma cell lines and in primary human fibroblasts. In carcinoma cells, HDFC matrix induced formation of invadopodia via a specific integrin signaling pathway that did not require growth factors or even altered gene and protein expression. In contrast, phosphoproteomics identified major changes in a complex phosphosignaling network with kindlin2 serine phosphorylation as a key regulatory element. This kindlin2-dependent signal transduction network was required for efficient induction of invadopodia on dense fibrillar collagen and for local degradation of collagen. This novel phosphosignaling mechanism regulates cell surface invadopodia via kindlin2 for local proteolytic remodeling of the ECM. PMID:25646088

Honeycomb structural composite polymer network of gelatin and functional cellulose ester for controlled release of omeprazole.

PubMed

Zhuang, Chen; Shi, Chengmei; Tao, Furong; Cui, Yuezhi

2017-12-01

The functionalized cellulose ester MCN was firstly synthesized and used to cross-link gelatin by amidation between -NH 2 in gelatin and active ester groups in MCN to form a composite polymer network Gel-MCN, which was confirmed by Van Slyke method, FTIR, XRD and TGA-DTG spectra. The model drug omeprazole was loaded in Gel-MCN composites mainly by electrostatic interaction and hydrogen bonds, which were certified by FTIR, XRD and TGA-DSC. Thermal stability, anti-biodegradability, mechanical property and surface hydrophobicity of the composites with different cross-linking extents and drug loading were systematically investigated. SEM images demonstrated the honeycomb structural cells of cross-linked gelatin networks and this ensured drug entrapment. The drug release mechanism was dominated by a combined effect of diffusion and degradation, and the release rate decreased with cross-linking degree increased. The developed drug delivery system had profound significance in improving pesticide effect and bioavailability of drugs. Copyright © 2017. Published by Elsevier B.V.

Surface-structured bacterial cellulose with guided assembly-based biolithography (GAB).

PubMed

Bottan, Simone; Robotti, Francesco; Jayathissa, Prageeth; Hegglin, Alicia; Bahamonde, Nicolas; Heredia-Guerrero, José A; Bayer, Ilker S; Scarpellini, Alice; Merker, Hannes; Lindenblatt, Nicole; Poulikakos, Dimos; Ferrari, Aldo

2015-01-27

A powerful replica molding methodology to transfer on-demand functional topographies to the surface of bacterial cellulose nanofiber textures is presented. With this method, termed guided assembly-based biolithography (GAB), a surface-structured polydimethylsiloxane (PDMS) mold is introduced at the gas-liquid interface of an Acetobacter xylinum culture. Upon bacterial fermentation, the generated bacterial cellulose nanofibers are assembled in a three-dimensional network reproducing the geometric shape imposed by the mold. Additionally, GAB yields directional alignment of individual nanofibers and memory of the transferred geometrical features upon dehydration and rehydration of the substrates. Scanning electron and atomic force microscopy are used to establish the good fidelity of this facile and affordable method. Interaction of surface-structured bacterial cellulose substrates with human fibroblasts and keratinocytes illustrates the efficient control of cellular activities which are fundamental in skin wound healing and tissue regeneration. The deployment of surface-structured bacterial cellulose substrates in model animals as skin wound dressing or body implant further proves the high durability and low inflammatory response to the material over a period of 21 days, demonstrating beneficial effects of surface structure on skin regeneration.

Effects of biotic and abiotic factors on the temporal dynamic of bat-fruit interactions

NASA Astrophysics Data System (ADS)

Laurindo, Rafael de Souza; Gregorin, Renato; Tavares, Davi Castro

2017-08-01

Mutualistic interactions between animals and plants vary over time and space based on the abundance of fruits or animals and seasonality. Little is known about this temporal dynamic and the influence of biotic and abiotic factors on the structure of interaction networks. We evaluated changes in the structure of network interactions between bats and fruits in relation to variations in rainfall. Our results suggest that fruit abundance is the main variable responsible for temporal changes in network attributes, such as network size, connectance, and number of interactions. In the same way, temperature positively affected the abundance of fruits and bats. An increase in temperature and alterations in rainfall patterns, due to human induced climate change, can cause changes in phenological patterns and fruit production, with negative consequences to biodiversity maintenance, ecological interactions, and ecosystem functioning.

DiffSLc: A graph centrality method to detect essential proteins of a protein-protein interaction network

USDA-ARS?s Scientific Manuscript database

Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures have been helpful in identifying critical genes and proteins in biomolecular networks. The proposed centrality measure DiffSLc uses the number of interactions of a protein and gen...

Integrating physical and genetic maps: from genomes to interaction networks

PubMed Central

Beyer, Andreas; Bandyopadhyay, Sourav; Ideker, Trey

2009-01-01

Physical and genetic mapping data have become as important to network biology as they once were to the Human Genome Project. Integrating physical and genetic networks currently faces several challenges: increasing the coverage of each type of network; establishing methods to assemble individual interaction measurements into contiguous pathway models; and annotating these pathways with detailed functional information. A particular challenge involves reconciling the wide variety of interaction types that are currently available. For this purpose, recent studies have sought to classify genetic and physical interactions along several complementary dimensions, such as ordered versus unordered, alleviating versus aggravating, and first versus second degree. PMID:17703239

The Influence of Gender, Age, Matriline and Hierarchical Rank on Individual Social Position, Role and Interactional Patterns in Macaca sylvanus at ‘La Forêt des Singes’: A Multilevel Social Network Approach

PubMed Central

Sosa, Sebastian

2016-01-01

A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank) on affiliative (allogrooming) and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e., centric, peripheral) and role (i.e., implication in the network cohesiveness) of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network. PMID:27148137

The Influence of Gender, Age, Matriline and Hierarchical Rank on Individual Social Position, Role and Interactional Patterns in Macaca sylvanus at 'La Forêt des Singes': A Multilevel Social Network Approach.

PubMed

Sosa, Sebastian

2016-01-01

A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank) on affiliative (allogrooming) and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e., centric, peripheral) and role (i.e., implication in the network cohesiveness) of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network.

Mental health and social networks in early adolescence: a dynamic study of objectively-measured social interaction behaviors.

PubMed

Pachucki, Mark C; Ozer, Emily J; Barrat, Alain; Cattuto, Ciro

2015-01-01

How are social interaction dynamics associated with mental health during early stages of adolescence? The goal of this study is to objectively measure social interactions and evaluate the roles that multiple aspects of the social environment--such as physical activity and food choice--may jointly play in shaping the structure of children's relationships and their mental health. The data in this study are drawn from a longitudinal network-behavior study conducted in 2012 at a private K-8 school in an urban setting in California. We recruited a highly complete network sample of sixth-graders (n = 40, 91% of grade, mean age = 12.3), and examined how two measures of distressed mental health (self-esteem and depressive symptoms) are positionally distributed in an early adolescent interaction network. We ascertained how distressed mental health shapes the structure of relationships over a three-month period, adjusting for relevant dimensions of the social environment. Cross-sectional analyses of interaction networks revealed that self-esteem and depressive symptoms are differentially stratified by gender. Specifically, girls with more depressive symptoms have interactions consistent with social inhibition, while boys' interactions suggest robustness to depressive symptoms. Girls higher in self-esteem tended towards greater sociability. Longitudinal network behavior models indicate that gender similarity and perceived popularity are influential in the formation of social ties. Greater school connectedness predicts the development of self-esteem, though social ties contribute to more self-esteem improvement among students who identify as European-American. Cross-sectional evidence shows associations between distressed mental health and students' network peers. However, there is no evidence that connected students' mental health status becomes more similar in their over time because of their network interactions. These findings suggest that mental health during early adolescence may be less subject to mechanisms of social influence than network research in even slightly older adolescents currently indicates. Copyright © 2014. Published by Elsevier Ltd.

Static Chemistry in Disks or Clouds

NASA Astrophysics Data System (ADS)

Semenov, D.; Wiebe, D.

2006-11-01

This FORTRAN77 code can be used to model static, time-dependent chemistry in ISM and circumstellar disks. Current version is based on the OSU'06 gas-grain astrochemical network with all updates to the reaction rates, and includes surface chemistry from Hasegawa & Herbst (1993) and Hasegawa, Herbst, and Leung (1992). Surface chemistry can be modeled either with the standard rate equation approach or modified rate equation approach (useful in disks). Gas-grain interactions include sticking of neutral molecules to grains, dissociative recombination of ions on grains as well as thermal, UV, X-ray, and CRP-induced desorption of frozen species. An advanced X-ray chemistry and 3 grain sizes with power-law size distribution are also included. An deuterium extension to this chemical model is available.

Mapping hydration dynamics around a protein surface

PubMed Central

Zhang, Luyuan; Wang, Lijuan; Kao, Ya-Ting; Qiu, Weihong; Yang, Yi; Okobiah, Oghaghare; Zhong, Dongping

2007-01-01

Protein surface hydration is fundamental to its structure and activity. We report here the direct mapping of global hydration dynamics around a protein in its native and molten globular states, using a tryptophan scan by site-specific mutations. With 16 tryptophan mutants and in 29 different positions and states, we observed two robust, distinct water dynamics in the hydration layer on a few (≈1–8 ps) and tens to hundreds of picoseconds (≈20–200 ps), representing the initial local relaxation and subsequent collective network restructuring, respectively. Both time scales are strongly correlated with protein's structural and chemical properties. These results reveal the intimate relationship between hydration dynamics and protein fluctuations and such biologically relevant water–protein interactions fluctuate on picosecond time scales. PMID:18003912

Nestedness across biological scales

PubMed Central

Marquitti, Flavia M. D.; Raimundo, Rafael L. G.; Sebastián-González, Esther; Coltri, Patricia P.; Perez, S. Ivan; Brandt, Débora Y. C.; Nunes, Kelly; Daura-Jorge, Fábio G.; Floeter, Sergio R.; Guimarães, Paulo R.

2017-01-01

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks. PMID:28166284

Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks

NASA Astrophysics Data System (ADS)

Liu, Quan-Hui; Wang, Wei; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-02-01

Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

Multiplex PageRank.

PubMed

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Construction of reliable protein-protein interaction networks with a new interaction generality measure.

PubMed

Saito, Rintaro; Suzuki, Harukazu; Hayashizaki, Yoshihide

2003-04-12

Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed. We developed a new 'interaction generality' measure (IG2) to assess the reliability of protein-protein interactions using only the topological properties of their interaction-network structure. Using yeast protein-protein interaction data, we showed that reliable protein-protein interactions had significantly lower IG2 values than less-reliable interactions, suggesting that IG2 values can be used to evaluate and filter interaction data to enable the construction of reliable protein-protein interaction networks.

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry.

PubMed

Pflieger, Delphine; Gonnet, Florence; de la Fuente van Bentem, Sergio; Hirt, Heribert; de la Fuente, Alberto

2011-01-01

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks. Copyright © 2010 Wiley Periodicals, Inc.

Radiological tele-immersion for next generation networks.

PubMed

Ai, Z; Dech, F; Rasmussen, M; Silverstein, J C

2000-01-01

Since the acquisition of high-resolution three-dimensional patient images has become widespread, medical volumetric datasets (CT or MR) larger than 100 MB and encompassing more than 250 slices are common. It is important to make this patient-specific data quickly available and usable to many specialists at different geographical sites. Web-based systems have been developed to provide volume or surface rendering of medical data over networks with low fidelity, but these cannot adequately handle stereoscopic visualization or huge datasets. State-of-the-art virtual reality techniques and high speed networks have made it possible to create an environment for clinicians geographically distributed to immersively share these massive datasets in real-time. An object-oriented method for instantaneously importing medical volumetric data into Tele-Immersive environments has been developed at the Virtual Reality in Medicine Laboratory (VRMedLab) at the University of Illinois at Chicago (UIC). This networked-VR setup is based on LIMBO, an application framework or template that provides the basic capabilities of Tele-Immersion. We have developed a modular general purpose Tele-Immersion program that automatically combines 3D medical data with the methods for handling the data. For this purpose a DICOM loader for IRIS Performer has been developed. The loader was designed for SGI machines as a shared object, which is executed at LIMBO's runtime. The loader loads not only the selected DICOM dataset, but also methods for rendering, handling, and interacting with the data, bringing networked, real-time, stereoscopic interaction with radiological data to reality. Collaborative, interactive methods currently implemented in the loader include cutting planes and windowing. The Tele-Immersive environment has been tested on the UIC campus over an ATM network. We tested the environment with 3 nodes; one ImmersaDesk at the VRMedLab, one CAVE at the Electronic Visualization Laboratory (EVL) on east campus, and a CT scan machine in UIC Hospital. CT data was pulled directly from the scan machine to the Tele-Immersion server in our Laboratory, and then the data was synchronously distributed by our Onyx2 Rack server to all the VR setups. Instead of permitting medical volume visualization at one VR device, by combining teleconferencing, tele-presence, and virtual reality, the Tele-Immersive environment will enable geographically distributed clinicians to intuitively interact with the same medical volumetric models, point, gesture, converse, and see each other. This environment will bring together clinicians at different geographic locations to participate in Tele-Immersive consultation and collaboration.

Integrated inference and evaluation of host–fungi interaction networks

PubMed Central

Remmele, Christian W.; Luther, Christian H.; Balkenhol, Johannes; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus T.

2015-01-01

Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of invasive mycoses in Europe. A key capability for host invasion and immune response evasion are specific molecular interactions between the fungal pathogen and its human host. Experimentally validated knowledge about these crucial interactions is rare in literature and even specialized host–pathogen databases mainly focus on bacterial and viral interactions whereas information on fungi is still sparse. To establish large-scale host–fungi interaction networks on a systems biology scale, we develop an extended inference approach based on protein orthology and data on gene functions. Using human and yeast intraspecies networks as template, we derive a large network of pathogen–host interactions (PHI). Rigorous filtering and refinement steps based on cellular localization and pathogenicity information of predicted interactors yield a primary scaffold of fungi–human and fungi–mouse interaction networks. Specific enrichment of known pathogenicity-relevant genes indicates the biological relevance of the predicted PHI. A detailed inspection of functionally relevant subnetworks reveals novel host–fungal interaction candidates such as the Candida virulence factor PLB1 and the anti-fungal host protein APP. Our results demonstrate the applicability of interolog-based prediction methods for host–fungi interactions and underline the importance of filtering and refinement steps to attain biologically more relevant interactions. This integrated network framework can serve as a basis for future analyses of high-throughput host–fungi transcriptome and proteome data. PMID:26300851

Controllability of Surface Water Networks

NASA Astrophysics Data System (ADS)

Riasi, M. Sadegh; Yeghiazarian, Lilit

2017-12-01

To sustainably manage water resources, we must understand how to control complex networked systems. In this paper, we study surface water networks from the perspective of structural controllability, a concept that integrates classical control theory with graph-theoretic formalism. We present structural controllability theory and compute four metrics: full and target controllability, control centrality and control profile (FTCP) that collectively determine the structural boundaries of the system's control space. We use these metrics to answer the following questions: How does the structure of a surface water network affect its controllability? How to efficiently control a preselected subset of the network? Which nodes have the highest control power? What types of topological structures dominate controllability? Finally, we demonstrate the structural controllability theory in the analysis of a wide range of surface water networks, such as tributary, deltaic, and braided river systems.

Information transfer in community structured multiplex networks

NASA Astrophysics Data System (ADS)

Solé Ribalta, Albert; Granell, Clara; Gómez, Sergio; Arenas, Alex

2015-08-01

The study of complex networks that account for different types of interactions has become a subject of interest in the last few years, specially because its representational power in the description of users interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.). The mathematical description of these interacting networks has been coined under the name of multilayer networks, where each layer accounts for a type of interaction. It has been shown that diffusive processes on top of these networks present a phenomenology that cannot be explained by the naive superposition of single layer diffusive phenomena but require the whole structure of interconnected layers. Nevertheless, the description of diffusive phenomena on multilayer networks has obviated the fact that social networks have strong mesoscopic structure represented by different communities of individuals driven by common interests, or any other social aspect. In this work, we study the transfer of information in multilayer networks with community structure. The final goal is to understand and quantify, if the existence of well-defined community structure at the level of individual layers, together with the multilayer structure of the whole network, enhances or deteriorates the diffusion of packets of information.

Unraveling spurious properties of interaction networks with tailored random networks.

PubMed

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Unraveling Spurious Properties of Interaction Networks with Tailored Random Networks

PubMed Central

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis. PMID:21850239

Decreased functional connectivity to posterior cingulate cortex in major depressive disorder.

PubMed

Yang, Rui; Gao, Chengge; Wu, Xiaoping; Yang, Junle; Li, Shengbin; Cheng, Hu

2016-09-30

The default mode network (DMN) and its interaction with other key networks such as the salience network and executive network are keys to understand psychiatric and neurological disorders including major depressive disorder (MDD). In this study, we combined independent component analysis and seed based connectivity analysis to study the posterior default mode network between 20 patients with MDD and 25 normal controls, as well as pre-treatment and post-treatment conditions of the patients. Both correlated and anti-correlated networks centered at the posterior cingulate cortex (PCC) were examined (PCC+ and PCC-). Our results showed aberrant functional connectivity of the PCC+ and PCC- networks between patients and normal controls. Specifically, normal controls exhibited significantly higher connectivity between the PCC and frontal/temporal regions for the PCC+ network and stronger connectivity strength between the PCC and the insula/middle frontal cortex for the PCC- network. The overall connectivity strength of the PCC+ and PCC- networks was also significantly lower in MDD. Because the PCC is a hub in the DMN that interacts with other networks, our result suggested a stronger interaction between the DMN and the salience network but a weak interaction between the DMN and the executive network in MDD. The treatment using sertraline did increase the functional connectivity strength, especially in the PCC+ network. Despite a large inter-subject variability in the overall connectivity strengths and change of the PCC network in response to the treatment, a high correlation between change of connectivity strength and the Hamilton depression score was observed for both the PCC+ and PCC- network. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Understanding protein-nanoparticle interaction: a new gateway to disease therapeutics.

PubMed

Giri, Karuna; Shameer, Khader; Zimmermann, Michael T; Saha, Sounik; Chakraborty, Prabir K; Sharma, Anirudh; Arvizo, Rochelle R; Madden, Benjamin J; Mccormick, Daniel J; Kocher, Jean-Pierre A; Bhattacharya, Resham; Mukherjee, Priyabrata

2014-06-18

Molecular identification of protein molecules surrounding nanoparticles (NPs) may provide useful information that influences NP clearance, biodistribution, and toxicity. Hence, nanoproteomics provides specific information about the environment that NPs interact with and can therefore report on the changes in protein distribution that occurs during tumorigenesis. Therefore, we hypothesized that characterization and identification of protein molecules that interact with 20 nm AuNPs from cancer and noncancer cells may provide mechanistic insights into the biology of tumor growth and metastasis and identify new therapeutic targets in ovarian cancer. Hence, in the present study, we systematically examined the interaction of the protein molecules with 20 nm AuNPs from cancer and noncancerous cell lysates. Time-resolved proteomic profiles of NP-protein complexes demonstrated electrostatic interaction to be the governing factor in the initial time-points which are dominated by further stabilization interaction at longer time-points as determined by ultraviolet-visible spectroscopy (UV-vis), dynamic light scattering (DLS), ζ-potential measurements, transmission electron microscopy (TEM), and tandem mass spectrometry (MS/MS). Reduction in size, charge, and number of bound proteins were observed as the protein-NP complex stabilized over time. Interestingly, proteins related to mRNA processing were overwhelmingly represented on the NP-protein complex at all times. More importantly, comparative proteomic analyses revealed enrichment of a number of cancer-specific proteins on the AuNP surface. Network analyses of these proteins highlighted important hub nodes that could potentially be targeted for maximal therapeutic advantage in the treatment of ovarian cancer. The importance of this methodology and the biological significance of the network proteins were validated by a functional study of three hubs that exhibited variable connectivity, namely, PPA1, SMNDC1, and PI15. Western blot analysis revealed overexpression of these proteins in ovarian cancer cells when compared to normal cells. Silencing of PPA1, SMNDC1, and PI15 by the siRNA approach significantly inhibited proliferation of ovarian cancer cells and the effect correlated with the connectivity pattern obtained from our network analyses.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

PubMed Central

Acencio, Marcio Luis; Bovolenta, Luiz Augusto; Camilo, Esther; Lemke, Ney

2013-01-01

Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI). This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved in cancer research interested in detecting signaling networks most prone to contribute with the emergence of malignant phenotype. PMID:24204854

Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

PubMed

Ammenwerth, Elske; Hackl, Werner O

2017-01-01

Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

An interactive graphics program for manipulation and display of panel method geometry

NASA Technical Reports Server (NTRS)

Hall, J. F.; Neuhart, D. H.; Walkley, K. B.

1983-01-01

Modern aerodynamic panel methods that handle large, complex geometries have made evident the need to interactively manipulate, modify, and view such configurations. With this purpose in mind, the GEOM program was developed. It is a menu driven, interactive program that uses the Tektronix PLOT 10 graphics software to display geometry configurations which are characterized by an abutting set of networks. These networks are composed of quadrilateral panels which are described by the coordinates of their corners. GEOM is divided into fourteen executive controlled functions. These functions are used to build configurations, scale and rotate networks, transpose networks defining M and N lines, graphically display selected networks, join and split networks, create wake networks, produce symmetric images of networks, repanel and rename networks, display configuration cross sections, and output network geometry in two formats. A data base management system is used to facilitate data transfers in this program. A sample session illustrating various capabilities of the code is included as a guide to program operation.

Systematic Evaluation of Molecular Networks for Discovery of Disease Genes.

PubMed

Huang, Justin K; Carlin, Daniel E; Yu, Michael Ku; Zhang, Wei; Kreisberg, Jason F; Tamayo, Pablo; Ideker, Trey

2018-04-25

Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation, gene expression profiling, or genome-wide association studies. While all networks have some ability to recover disease genes, we observe a wide range of performance with STRING, ConsensusPathDB, and GIANT networks having the best performance overall. A general tendency is that performance scales with network size, suggesting that new interaction discovery currently outweighs the detrimental effects of false positives. Correcting for size, we find that the DIP network provides the highest efficiency (value per interaction). Based on these results, we create a parsimonious composite network with both high efficiency and performance. This work provides a benchmark for selection of molecular networks in human disease research. Copyright © 2018 Elsevier Inc. All rights reserved.

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

The strong ground motion in Mexico City: array and borehole data analysis.

NASA Astrophysics Data System (ADS)

Roullé, A.; Chávez-García, F. J.

2003-04-01

Site response at Mexico City has been intensively studied for the last 15 years, since the disastrous 1985 earthquakes. After those events, more than 100 accelerographs were installed, and their data have been extremely useful in quantifying amplification and in the subsequent upgrading of the building code. However, detailed analysis of the wavefield has been hampered by the lack of absolute time in the records and the large spacing between stations in terms of dominant wavelengths. In 2001, thanks to the support of CONACYT, Mexico, a new dense accelerographic network was installed in the lake bed zone of Mexico City. The entire network, including an existing network of 3 surface and 2 borehole stations operated by CENAPRED, consists in 12 surface and 4 borehole stations (at 30, 102 and 50 meters). Each station has a 18 bits recorder and a GPS receiver so that the complete network is a 3D array with absolute time. The main objective of this array is to provide data that can help us to better understand the wavefield that propagates in Mexico City during large earthquakes. Last year, a small event of magnitude 6.0 was partially recorded by 6 of the 12 surface stations and all the borehole stations. We analysed the surface data using different array processing techniques such as f-k methods and MUSIC algorithm and the borehole ones using a cross-correlation method. For periods inferior to the site resonance period, the soft clay layer with very low propagation velocities (less than 500 m/s) and a possible multipathing rule the wavefield pattern. For the large period range, the dominant surface wave comes from the epicentral direction and propagates with a quicker velocity (more than 1500 m/s) that corresponds to the velocity of deep layers. The analysis of borehole data shows the presence of different quick wavetrains in the short period range that could correspond to the first harmonic modes of Rayleigh waves. To complete this study, four others events recorded in 1994 by a temporal dense network installed in the firm rock zone of Mexico City were analysed using the same techniques. The results confirm the presence of a diffracting zone south of the valley. These results confirm the hypothesis of a possible interaction between the soft clay layers resonance and diffracted wavetrains of Rayleigh waves to explain both the amplification and the long duration of strong ground motion in Mexico City.

Evaluating factors that predict the structure of a commensalistic epiphyte–phorophyte network

PubMed Central

Sáyago, Roberto; Lopezaraiza-Mikel, Martha; Quesada, Mauricio; Álvarez-Añorve, Mariana Yolotl; Cascante-Marín, Alfredo; Bastida, Jesus Ma.

2013-01-01

A central issue in ecology is the understanding of the establishment of biotic interactions. We studied the factors that affect the assembly of the commensalistic interactions between vascular epiphytes and their host plants. We used an analytical approach that considers all individuals and species of epiphytic bromeliads and woody hosts and non-hosts at study plots. We built models of interaction probabilities among species to assess if host traits and abundance and spatial overlap of species predict the quantitative epiphyte–host network. Species abundance, species spatial overlap and host size largely predicted pairwise interactions and several network metrics. Wood density and bark texture of hosts also contributed to explain network structure. Epiphytes were more common on large hosts, on abundant woody species, with denser wood and/or rougher bark. The network had a low level of specialization, although several interactions were more frequent than expected by the models. We did not detect a phylogenetic signal on the network structure. The effect of host size on the establishment of epiphytes indicates that mature forests are necessary to preserve diverse bromeliad communities. PMID:23407832

Dynamics of deceptive interactions in social networks.

PubMed

Barrio, Rafael A; Govezensky, Tzipe; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

2015-11-06

In this paper, we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model, we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and, in this sense, they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society. © 2015 The Author(s).

Fluctuating interaction network and time-varying stability of a natural fish community

NASA Astrophysics Data System (ADS)

Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

2018-02-01

Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

Evolution of cooperation on complex networks with synergistic and discounted group interactions

NASA Astrophysics Data System (ADS)

Zhou, Lei; Li, Aming; Wang, Long

2015-06-01

In the real world individuals often engage in group interactions and their payoffs are determined by many factors, including the typical nonlinear interactions, i.e., synergy and discounting. Previous literatures assume that individual payoffs are either synergistically enhanced or discounted with the additional cooperators. Such settings ignore the interplay of these two factors, which is in sharp contrast with the fact that they ubiquitously coexist. Here we investigate how the coexistence and periodical switching of synergistic and discounted group interactions affect the evolution of cooperation on various complex networks. We show that scale-free networks facilitate the emergence of cooperation in terms of fixation probability for group interactions. With nonlinear interactions the heterogeneity of the degree acts as a double-edged sword: below the neutral drift it is the best for cooperation while above the neutral drift it instead provides the least opportunity for cooperators to be fixed. The advantages of the heterogeneity fade as interactive attributes switch between synergy and discounting, which suggests that the heterogeneity of population structures cannot favor cooperators in group interactions even with simple nonlinear interactions. Nonetheless, scale-free networks always guarantee cooperators the fastest rate of fixation. Our work implies that even very simple nonlinear group interactions could greatly shape the fixation probability and fixation time of cooperators in structured populations indicated by complex networks.

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.

Microglia recapitulate a hematopoietic master regulator network in the aging human frontal cortex

PubMed Central

Wehrspaun, Claudia C.; Haerty, Wilfried; Ponting, Chris P.

2015-01-01

Microglia form the immune system of the brain. Previous studies in cell cultures and animal models suggest altered activation states and cellular senescence in the aged brain. Instead, we analyzed 3 transcriptome data sets from the postmortem frontal cortex of 381 control individuals to show that microglia gene markers assemble into a transcriptional module in a gene coexpression network. These markers predominantly represented M1 and M1/M2b activation phenotypes. Expression of genes in this module generally declines over the adult life span. This decrease was more pronounced in microglia surface receptors for microglia and/or neuron crosstalk than in markers for activation state phenotypes. In addition to these receptors for exogenous signals, microglia are controlled by brain-expressed regulatory factors. We identified a subnetwork of transcription factors, including RUNX1, IRF8, PU.1, and TAL1, which are master regulators (MRs) for the age-dependent microglia module. The causal contributions of these MRs on the microglia module were verified using publicly available ChIP-Seq data. Interactions of these key MRs were preserved in a protein-protein interaction network. Importantly, these MRs appear to be essential for regulating microglia homeostasis in the adult human frontal cortex in addition to their crucial roles in hematopoiesis and myeloid cell-fate decisions during embryogenesis. PMID:26002684

Spectro-microscopic study of the formation of supramolecular networks

NASA Astrophysics Data System (ADS)

Sadowski, Jerzy T.

2015-03-01

Metal-organic frameworks (MOFs) are emerging as a new class of materials for CO2 capture. There are many fundamental questions, including the optimum pore size and arrangement of the molecules in the structure to achieve highest CO2 uptake. As only the surface is of interest for potential applications such as heterogeneous catalysis, nano-templating, and sensing, 2D analogs of MOFs can serve as good model systems. Utilizing capabilities of LEEM/PEEM for non-destructive interrogation of the real-time molecular self-assembly, we investigated supramolecular systems based on carboxylic acid-metal complexes, such as trimesic and mellitic acid, doped with transition metals. Such 2D networks act as host systems for transition-metal phthalocyanines (MPc; M = Fe, Ti, Sc) and the electrostatic interactions of CO2 molecules with transition metal ions, can be tuned by controlling the type of TM ion and the size of the pore in the host network. The understanding of directed self-assembly by controlling the molecule-substrate interaction can enable us to engineer the pore size and density, and thus tune the host's chemical activity. Research carried out at the Center for Functional Nanomaterials and National Synchrotron Light Source, Brookhaven National Laboratory, which are supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Contract No. DE-AC02-98CH10.

An overview to networks and its applications

NASA Astrophysics Data System (ADS)

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

2010-07-01

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

Carnegie Mellon's STUDIO for Creative Inquiry [and] The Interdisciplinary Teaching Network (ITeN) [and] Interactive Fiction [and] The Networked Virtual Art Museum.

ERIC Educational Resources Information Center

Holden, Lynn; And Others

1992-01-01

Explains the STUDIO for Creative Inquiry, an interdisciplinary center at Carnegie Mellon University that supports experimental activities in the arts, and its Interdisciplinary Teaching Network. Three STUDIO projects are described: the Ancient Egypt Prototype application of the network; an interactive fiction system based on artificial…

The Geomorphological Effects of Old Routes

NASA Astrophysics Data System (ADS)

Martinek, Jan; Bíl, Michal

2017-04-01

The communication network in rural areas in the historical Czech Lands predominantly consisted of unpaved routes prior to the eighteenth century. Certain parts of the network were transformed gradually into the current roads and are now being used by motor traffic. The majority of the old routes form, however, an abandoned network the remnants of which (abandoned during the Middle Ages or even earlier) are currently being discovered. Certain segments of used unpaved routes were, over the course of time, transformed into holloways (sunken lanes) and consequently also abandoned. The degree of incision of the holloway into the soil was determined by local geological conditions. Routes, which were abandoned due to more difficult transport in holloways, have distinct linear forms and can often be found as a grouping of parallel holloways. This indicates that these routes were frequently used or localized on low-resistant ground. Analyses of the precise digital elevation models, derived from LIDAR data, can reveal the distinct pattern of an old route network quite often interacting with other geomorphological phenomena (e.g., landslides, streams) or old human constructions (e.g., fortified settlements). We will present several cases where old paths interacted with landslides. These facts can consequently be used for dating the purposes of both the landslides and the old path sections. General erosion impacts, the degree of incision of the old transportation lines, can also be quantified through analyses of digital elevation models taking into consideration the former and new, incised, surface. We will demonstrate the methodology used for these analyses and the preliminary results.

Microfluidic approaches for the fabrication of gradient crosslinked networks based on poly(ethylene glycol) and hyperbranched polymers for manipulation of cell interactions

PubMed Central

Pedron, S; Peinado, C; Bosch, P; Benton, J A; Anseth, K S

2011-01-01

High-throughput methods allow rapid examination of parameter space to characterize materials and develop new polymeric formulations for biomaterials applications. One limitation is the difficulty of preparing libraries and performing high-throughput screening with conventional instrumentation and sample preparation. Here, we describe the fabrication of substrate materials with controlled gradients in composition by a rapid method of micromixing followed by a photopolymerization reaction. Specifically, poly(ethylene glycol) dimethacrylate was copolymerized with a hyperbranched multimethacrylate (P1000MA or H30MA) in a gradient manner. The extent of methacrylate conversion and the final network composition were determined by near-infrared spectroscopy, and mechanical properties were measured by nanoindentation. A relationship was observed between the elastic modulus and network crosslinking density. Roughness and hydrophilicity were increased on surfaces with a higher concentration of P1000MA. These results likely relate to a phase segregation process of the hyperbranched macromer that occurs during the photopolymerization reaction. On the other hand, the decrease in the final conversion in H30MA polymerization reactions was attributed to the lower termination rate as a consequence of the softening of the network. Valvular interstitial cell attachment was evaluated on these gradient substrates as a demonstration of studying cell morphology as a function of the local substrate properties. Data revealed that the presence of P1000MA affects cell–material interaction with a higher number of adhered cells and more cell spreading on gradient regions with a higher content of the multifunctional crosslinker. PMID:21105168

Integrated Water Flow Model (IWFM), A Tool For Numerically Simulating Linked Groundwater, Surface Water And Land-Surface Hydrologic Processes

NASA Astrophysics Data System (ADS)

Dogrul, E. C.; Brush, C. F.; Kadir, T. N.

2006-12-01

The Integrated Water Flow Model (IWFM) is a comprehensive input-driven application for simulating groundwater flow, surface water flow and land-surface hydrologic processes, and interactions between these processes, developed by the California Department of Water Resources (DWR). IWFM couples a 3-D finite element groundwater flow process and 1-D land surface, lake, stream flow and vertical unsaturated-zone flow processes which are solved simultaneously at each time step. The groundwater flow system is simulated as a multilayer aquifer system with a mixture of confined and unconfined aquifers separated by semiconfining layers. The groundwater flow process can simulate changing aquifer conditions (confined to unconfined and vice versa), subsidence, tile drains, injection wells and pumping wells. The land surface process calculates elemental water budgets for agricultural, urban, riparian and native vegetation classes. Crop water demands are dynamically calculated using distributed soil properties, land use and crop data, and precipitation and evapotranspiration rates. The crop mix can also be automatically modified as a function of pumping lift using logit functions. Surface water diversions and groundwater pumping can each be specified, or can be automatically adjusted at run time to balance water supply with water demand. The land-surface process also routes runoff to streams and deep percolation to the unsaturated zone. Surface water networks are specified as a series of stream nodes (coincident with groundwater nodes) with specified bed elevation, conductance and stage-flow relationships. Stream nodes are linked to form stream reaches. Stream inflows at the model boundary, surface water diversion locations, and one or more surface water deliveries per location are specified. IWFM routes stream flows through the network, calculating groundwater-surface water interactions, accumulating inflows from runoff, and allocating available stream flows to meet specified or calculated deliveries. IWFM utilizes a very straight-forward input file structure, allowing rapid development of complex simulations. A key feature of IWFM is a new algorithm for computation of groundwater flow across element faces. Enhancements to version 3.0 include automatic time-tracking of input and output data sets, linkage with the HEC-DSS database, and dynamic crop allocation using logit functions. Utilities linking IWFM to the PEST automated calibration suite are also available. All source code, executables and documentation are available for download from the DWR web site. IWFM is currently being used to develop hydrologic simulations of California's Central Valley (C2VSIM); the west side of California's San Joaquin Valley (WESTSIM); Butte County, CA; Solano County, CA; Merced County, CA; and the Oregon side of the Walla Walla River Basin.

Analytical Expressions for Thermo-Osmotic Permeability of Clays

NASA Astrophysics Data System (ADS)

Gonçalvès, J.; Ji Yu, C.; Matray, J.-M.; Tremosa, J.

2018-01-01

In this study, a new formulation for the thermo-osmotic permeability of natural pore solutions containing monovalent and divalent cations is proposed. The mathematical formulation proposed here is based on the theoretical framework supporting thermo-osmosis which relies on water structure alteration in the pore space of surface-charged materials caused by solid-fluid electrochemical interactions. The ionic content balancing the surface charge of clay minerals causes a disruption in the hydrogen bond network when more structured water is present at the clay surface. Analytical expressions based on our heuristic model are proposed and compared to the available data for NaCl solutions. It is shown that the introduction of divalent cations reduces the thermo-osmotic permeability by one third compared to the monovalent case. The analytical expressions provided here can be used to advantage for safety calculations in deep underground nuclear waste repositories.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V

2006-12-12

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

PubMed

Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

2012-01-01

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

The Correlation Fractal Dimension of Complex Networks

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Liu, Zhenzhen; Wang, Mogei

2013-05-01

The fractality of complex networks is studied by estimating the correlation dimensions of the networks. Comparing with the previous algorithms of estimating the box dimension, our algorithm achieves a significant reduction in time complexity. For four benchmark cases tested, that is, the Escherichia coli (E. Coli) metabolic network, the Homo sapiens protein interaction network (H. Sapiens PIN), the Saccharomyces cerevisiae protein interaction network (S. Cerevisiae PIN) and the World Wide Web (WWW), experiments are provided to demonstrate the validity of our algorithm.

Latent Factors in Student-Teacher Interaction Factor Analysis

ERIC Educational Resources Information Center

Le, Thu; Bolt, Daniel; Camburn, Eric; Goff, Peter; Rohe, Karl

2017-01-01

Classroom interactions between students and teachers form a two-way or dyadic network. Measurements such as days absent, test scores, student ratings, or student grades can indicate the "quality" of the interaction. Together with the underlying bipartite graph, these values create a valued student-teacher dyadic interaction network. To…

apterous A specifies dorsal wing patterns and sexual traits in butterflies

PubMed Central

2018-01-01

Butterflies have evolved different colour patterns on their dorsal and ventral wing surfaces to serve different signalling functions, yet the developmental mechanisms controlling surface-specific patterning are still unknown. Here, we mutate both copies of the transcription factor apterous in Bicyclus anynana butterflies using CRISPR/Cas9 and show that apterous A, expressed dorsally, functions both as a repressor and modifier of ventral wing colour patterns, as well as a promoter of dorsal sexual ornaments in males. We propose that the surface-specific diversification of wing patterns in butterflies proceeded via the co-option of apterous A or its downstream effectors into various gene regulatory networks involved in the differentiation of discrete wing traits. Further, interactions between apterous and sex-specific factors such as doublesex may have contributed to the origin of sexually dimorphic surface-specific patterns. Finally, we discuss the evolution of eyespot number diversity in the family Nymphalidae within the context of developmental constraints due to apterous regulation. PMID:29467265

Hydrogen-assisted versus hydroxyl-assisted CO dissociation over Co-doped Cu(111): A DFT study

NASA Astrophysics Data System (ADS)

Zha, Hao; Dong, Xiuqin; Yu, Yingzhe; Zhang, Minhua

2018-03-01

First principle based density functional theory (DFT) was used to calculate the step-by-step hydrogenation and dissociation reaction network of carbon monoxide (CO) over Co-doped Cu(111) surface as a model for understanding the lateral interaction of surface hydroxyl species (OH) on these reactions. We discussed the Csbnd O bond length and the adsorption energy changes of reaction intermediates under different adsorption circumstances for purpose of making out the effect of surface hydroxyl on the reaction selectivity. Reaction intermediates co-adsorbed with H atom and hydroxyl could undergo H-assisted or OH-assisted routes. The calculations show that the OH-assisted route prefers with the formation of COH, CHOH and CH2OH while general H-assisted route prefers with the formation of HCO, CH2O and CH3O. Considering the rather low activation barrier of COH, CHOH and CH2OH to form CHX, the existence of hydroxyl on the surface is in favor of boosting the CHX and suppressing the methanol.

Networks 90: Polymer Networks Group Meeting (10th) and IUPAC international Symposium on Polymer Networks (10th) Held in Jerusalem on 20-25 May 1990. Programme and Abstracts

DTIC Science & Technology

1990-05-25

INCLUDING ORIENTATIONAL INTERACTIONS BETWEEN CHAIN SEGMENTS B. Deloche, E.T. Samulski (France, USA) CHAIN SEGMENT ORDERING IN STRAINED BIMODAL P-2 PDMS...theory of elastomers is difficult because it requires a detailed study of many body interactions . A theory of elasticity must address the following: (1...a Kirchhoff matrix which describes the connectivity of the network (Kc) or the linear chains (Ku). The nonbonded interactions are handled with the

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

PubMed

Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

A Preliminary Examination of the Relationship Between Social Networking Interactions, Internet Use, and Thwarted Belongingness.

PubMed

Moberg, Fallon B; Anestis, Michael D

2015-01-01

Joiner's (2005) interpersonal-psychological theory of suicide hypothesizes that suicidal desire develops in response to the joint presence of thwarted belongingness and perceived burdensomeness. To consider the potential influence of online interactions and behaviors on these outcomes. To address this, we administered an online protocol assessing suicidal desire and online interactions in a sample of 305 undergraduates (83.6% female). We hypothesized negative interactions on social networking sites and a preference for online social interactions would be associated with thwarted belongingness. We also conducted an exploratory analysis examining the associations between Internet usage and perceived burdensomeness. Higher levels of negative interactions on social networking sites, but no other variables, significantly predicted thwarted belongingness. Our exploratory analysis showed that none of our predictors were associated with perceived burdensomeness after accounting for demographics, depression, and thwarted belongingness. Our findings indicate that a general tendency to have negative interactions on social networking sites could possibly impact suicidal desire and that these effects are significant above and beyond depression symptoms. Furthermore, no other aspect of problematic Internet use significantly predicted our outcomes in multivariate analyses, indicating that social networking in particular may have a robust effect on thwarted belongingness.

Synchronization unveils the organization of ecological networks with positive and negative interactions

NASA Astrophysics Data System (ADS)

Girón, Andrea; Saiz, Hugo; Bacelar, Flora S.; Andrade, Roberto F. S.; Gómez-Gardeñes, Jesús

2016-06-01

Network science has helped to understand the organization principles of the interactions among the constituents of large complex systems. However, recently, the high resolution of the data sets collected has allowed to capture the different types of interactions coexisting within the same system. A particularly important example is that of systems with positive and negative interactions, a usual feature appearing in social, neural, and ecological systems. The interplay of links of opposite sign presents natural difficulties for generalizing typical concepts and tools applied to unsigned networks and, moreover, poses some questions intrinsic to the signed nature of the network, such as how are negative interactions balanced by positive ones so to allow the coexistence and survival of competitors/foes within the same system? Here, we show that synchronization phenomenon is an ideal benchmark for uncovering such balance and, as a byproduct, to assess which nodes play a critical role in the overall organization of the system. We illustrate our findings with the analysis of synthetic and real ecological networks in which facilitation and competitive interactions coexist.