Intercalation-enhanced electric polarization and chain formation of nano-layered particles

Microscopy observations show that suspensions of synthetic and natural nano-layered smectite clay particles submitted to a strong external electric field undergo a fast and extended structuring. This structuring results from the interaction between induced electric dipoles, and is only possible for particles with suitable polarization properties. Smectite clay colloids are observed to be particularly suitable, in contrast to similar suspensions of a non-swelling clay. Synchrotron X-ray scattering experiments provide the orientation distributions for the particles. These distributions are understood in terms of competing (i) homogenizing entropy and (ii) interaction between the particles and the local electric field; they show that clay particles polarize along their silica sheet. Furthermore, a change in the platelet separation inside nano-layered particles occurs under application of the electric field, indicating that intercalated ions and water molecules play a role in their electric polarization. The resulting induced dipole is structurally attached to the particle, and this causes particles to reorient and interact, resulting in the observed macroscopic structuring. The macroscopic properties of these electro-rheological smectite suspensions may be tuned by controlling the nature and quantity of the intercalated species, at the nanoscale.Comment: 7 pages, 5 figure

An Interdigitated Pixel PIN Detector for Energetic Particle Spectroscopy in Space

We describe a new two-dimensional position-sensitive detector, now under development, for use in space-borne energetic particle spectrometers. The novel feature of this device is the use of interdigitated pixels to provide both dimensions of position information from a single side of the detector, while a measurement of the energy deposition is derived from the opposite side. An advantage of this approach is that significant reductions in the complexity, power, and weight of the associated read-out electronics can be realized without sacrificing position or energy resolution

Two-Dimensional Helioseismic Power, Phase, and Coherence Spectra of {\it Solar Dynamics Observatory} Photospheric and Chromospheric Observables

While the {\it Helioseismic and Magnetic Imager} (HMI) onboard the {\it Solar Dynamics Observatory} (SDO) provides Doppler velocity [$V$], continuum intensity [$I_C$], and line-depth [$Ld$] observations, each of which is sensitive to the five-minute acoustic spectrum, the {\it Atmospheric Imaging Array} (AIA) also observes at wavelengths -- specifically the 1600 and 1700 Angstrom bands -- that are partly formed in the upper photosphere and have good sensitivity to acoustic modes. In this article we consider the characteristics of the spatio--temporal Fourier spectra in AIA and HMI observables for a 15-degree region around NOAA Active Region 11072. We map the spatio--temporal-power distribution for the different observables and the HMI Line Core [$I_L$], or Continuum minus Line Depth, and the phase and coherence functions for selected observable pairs, as a function of position and frequency. Five-minute oscillation power in all observables is suppressed in the sunspot and also in plage areas. Above the acoustic cut-off frequency, the behaviour is more complicated: power in HMI $I_C$ is still suppressed in the presence of surface magnetic fields, while power in HMI $I_L$ and the AIA bands is suppressed in areas of surface field but enhanced in an extended area around the active region, and power in HMI $V$ is enhanced in a narrow zone around strong-field concentrations and suppressed in a wider surrounding area. The relative phase of the observables, and their cross-coherence functions, are also altered around the active region. These effects may help us to understand the interaction of waves and magnetic fields in the different layers of the photosphere, and will need to be taken into account in multi-wavelength local helioseismic analysis of active regions.Comment: 18 pages, 15 figures, to be published in Solar Physic

Multiwavelength studies of MHD waves in the solar chromosphere: An overview of recent results

The chromosphere is a thin layer of the solar atmosphere that bridges the relatively cool photosphere and the intensely heated transition region and corona. Compressible and incompressible waves propagating through the chromosphere can supply significant amounts of energy to the interface region and corona. In recent years an abundance of high-resolution observations from state-of-the-art facilities have provided new and exciting ways of disentangling the characteristics of oscillatory phenomena propagating through the dynamic chromosphere. Coupled with rapid advancements in magnetohydrodynamic wave theory, we are now in an ideal position to thoroughly investigate the role waves play in supplying energy to sustain chromospheric and coronal heating. Here, we review the recent progress made in characterising, categorising and interpreting oscillations manifesting in the solar chromosphere, with an impetus placed on their intrinsic energetics.Comment: 48 pages, 25 figures, accepted into Space Science Review

The interaction of HAb18G/CD147 with integrin α6β1 and its implications for the invasion potential of human hepatoma cells

<p>Abstract</p> <p>Background</p> <p>HAb18G/CD147 plays pivotal roles in invasion by hepatoma cells, but the underlying mechanism remains unclear. Our previous study demonstrated that overexpression of HAb18G/CD147 promotes invasion by interacting with integrin α3β1. However, it has never been investigated whether α3β1 is solely responsible for this process or if other integrin family members also interact with HAb18G/CD147 in human hepatoma cells.</p> <p>Methods</p> <p>Human SMMC-7721 and FHCC98 cells were cultured and transfected with siRNA fragments against HAb18G/CD147. The expression levels of HAb18G/CD147 and integrin α6β1 were determined by immunofluorescent double-staining and confocal imaging analysis. Co-immunoprecipitation and Western blot analyses were performed to examine the native conformations of HAb18G/CD147 and integrin α6β1. Invasion potential was evaluated with an invasion assay and gelatin zymography.</p> <p>Results</p> <p>We found that integrin α6β1 co-localizes and interacts with HAb18G/CD147 in human hepatoma cells. The enhancing effects of HAb18G/CD147 on invasion capacity and secretion of matrix metalloproteinases (MMPs) were partially blocked by integrin α6β1 antibodies (<it>P </it>< 0.01). Wortmannin, a specific phosphatidylinositol kinase (PI3K) inhibitor that reverses the effect of HAb18G/CD147 on the regulation of intracellular Ca²⁺mobilization, significantly reduced cell invasion potential and secretion of MMPs in human hepatoma cells (<it>P </it>< 0.05). Importantly, no additive effect between Wortmannin and α6β1 antibodies was observed, indicating that α6β1 and PI3K transmit the signal in an upstream-downstream relationship.</p> <p>Conclusion</p> <p>These results suggest that α6β1 interacts with HAb18G/CD147 to mediate tumor invasion and metastatic processes through the PI3K pathway.</p

Constitutional patriotism

Constitutional patriotism is a political theory that seeks to provide an explanation for the sense of ownership that most individuals have towards their national constitutional system. Specifically, constitutional patriotism assumes that free-thinking individuals involved in a discussion over the common good will reach an agreement that is perceived, at least by those involved in the debate, as having normative value. The awareness that such a deliberative process has historically been a part of the constitutional system also induces a sense of ownership of past historical accommodations of constitutional principles. The shared perception of being part of historically grounded institutions within a deliberative democracy is sometimes called the ‘normative surplus effect’ or ‘normative spill-over effect’ of the deliberative process. The theory, in its current form, was proposed by Jürgen Habermas and Jean-Werner Müller. Debates over the common good might take place informally or within the state’s institutions. Pell-mell informal debates, with few exceptions, have a limited effect on amending constitutional norms. Yet, the prerogative to openly discuss laws and policies legitimised by constitutional norms is normally sufficient to develop an inner sense of belonging to a constitutional system. Deliberative debates within public institutions (e.g. parliaments and courts) are more likely to change the functioning of a constitutional system, but they are, by way of comparison to informal political discussions, normally constrained by the system of rules that regulate representative democracy and the administration of justice. Thus, the theory of constitutional patriotism provides an explanatory model for the historical development of a democratic constitutional system. As one of the most persuasive explanatory theories of modern pluralist democracy, constitutional patriotism has attracted a series of well-articulated critiques. It has been suggested, for instance, that constitutional patriotism might not provide a plausible model of social integration for international organisations such as the European Union (EU). In this essay, I will provide an overview of the theory and a selection of its critiques

A systematic analysis of host factors reveals a Med23-interferon-λ regulatory axis against herpes simplex virus type 1 replication

Herpes simplex virus type 1 (HSV-1) is a neurotropic virus causing vesicular oral or genital skin lesions, meningitis and other diseases particularly harmful in immunocompromised individuals. To comprehensively investigate the complex interaction between HSV-1 and its host we combined two genome-scale screens for host factors (HFs) involved in virus replication. A yeast two-hybrid screen for protein interactions and a RNA interference (RNAi) screen with a druggable genome small interfering RNA (siRNA) library confirmed existing and identified novel HFs which functionally influence HSV-1 infection. Bioinformatic analyses found the 358 HFs were enriched for several pathways and multi-protein complexes. Of particular interest was the identification of Med23 as a strongly anti-viral component of the largely pro-viral Mediator complex, which links specific transcription factors to RNA polymerase II. The anti-viral effect of Med23 on HSV-1 replication was confirmed in gain-of-function gene overexpression experiments, and this inhibitory effect was specific to HSV-1, as a range of other viruses including Vaccinia virus and Semliki Forest virus were unaffected by Med23 depletion. We found Med23 significantly upregulated expression of the type III interferon family (IFN-λ) at the mRNA and protein level by directly interacting with the transcription factor IRF7. The synergistic effect of Med23 and IRF7 on IFN-λ induction suggests this is the major transcription factor for IFN-λ expression. Genotypic analysis of patients suffering recurrent orofacial HSV-1 outbreaks, previously shown to be deficient in IFN-λ secretion, found a significant correlation with a single nucleotide polymorphism in the IFN-λ3 (IL28b) promoter strongly linked to Hepatitis C disease and treatment outcome. This paper describes a link between Med23 and IFN-λ, provides evidence for the crucial role of IFN-λ in HSV-1 immune control, and highlights the power of integrative genome-scale approaches to identify HFs critical for disease progression and outcome

Enhanced susceptibility to infections in a diabetic wound healing model

<p>Abstract</p> <p>Background</p> <p>Wound infection is a common complication in diabetic patients. The progressive spread of infections and development of drug-resistant strains underline the need for further insights into bacterial behavior in the host in order to develop new therapeutic strategies. The aim of our study was to develop a large animal model suitable for monitoring the development and effect of bacterial infections in diabetic wounds.</p> <p>Methods</p> <p>Fourteen excisional wounds were created on the dorsum of diabetic and non-diabetic Yorkshire pigs and sealed with polyurethane chambers. Wounds were either inoculated with 2 × 10⁸Colony-Forming Units (CFU) of <it>Staphylococcus aureus </it>or injected with 0.9% sterile saline. Blood glucose was monitored daily, and wound fluid was collected for bacterial quantification and measurement of glucose concentration. Tissue biopsies for microbiological and histological analysis were performed at days 4, 8, and 12. Wounds were assessed for reepithelialization and wound contraction.</p> <p>Results</p> <p>Diabetic wounds showed a sustained significant infection (>10⁵CFU/g tissue) compared to non-diabetic wounds (p < 0.05) over the whole time course of the experiment. <it>S. aureus</it>-inoculated diabetic wounds showed tissue infection with up to 8 × 10⁷CFU/g wound tissue. Non-diabetic wounds showed high bacterial counts at day 4 followed by a decrease and no apparent infection at day 12. Epidermal healing in <it>S. aureus</it>-inoculated diabetic wounds showed a significant delay compared with non-inoculated diabetic wounds (59% versus 84%; p < 0.05) and were highly significant compared with healing in non-diabetic wounds (97%; p < 0.001).</p> <p>Conclusion</p> <p>Diabetic wounds developed significantly more sustained infection than non-diabetic wounds. <it>S. aureus </it>inoculation leads to invasive infection and significant wound healing delay and promotes invasive co-infection with endogenous bacteria. This novel wound healing model provides the opportunity to closely assess infections during diabetic wound healing and to monitor the effect of therapeutical agents <it>in vivo</it>.</p

A pig model of acute Staphylococcus aureus induced pyemia

<p>Abstract</p> <p>Background</p> <p>Sepsis caused by <it>Staphylococcus aureus </it>constitutes an important cause of morbidity and mortality in humans, and the incidence of this disease-entity is increasing. In this paper we describe the initial microbial dynamics and lesions in pigs experimentally infected with <it>S. aureus</it>, with the aim of mimicking human sepsis and pyemia.</p> <p>Methods</p> <p>The study was conducted in anaesthetized and intravenously inoculated pigs, and was based on bacteriological examination of blood and testing of blood for IL-6 and C-reactive protein. Following killing of the animals and necropsy bacteriological and histological examinations of different organs were performed 4, 5 or 6 h after inoculation.</p> <p>Results</p> <p>Clearance of bacteria from the blood was completed within the first 2 h in some of the pigs and the highest bacterial load was recorded in the lungs as compared to the spleen, liver and bones. This probably was a consequence of both the intravenous route of inoculation and the presence of pulmonary intravascular macrophages. Inoculation of bacteria induced formation of acute microabscesses in the lungs, spleen and liver, but not in the kidneys or bones. No generalized inflammatory response was recorded, i.e. IL-6 was not detected in the blood and C-reactive protein did not increase, probably because of the short time course of the study.</p> <p>Conclusion</p> <p>This study demonstrates the successful induction of acute pyemia (microabscesses), and forms a basis for future experiments that should include inoculation with strains of <it>S. aureus </it>isolated from man and an extension of the timeframe aiming at inducing sepsis, severe sepsis and septic shock.</p

Topology analysis and visualization of Potyvirus protein-protein interaction network

Background: One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new perspective is allowing the identification of direct and indirect viral targets. Such information is available for several members of the Potyviridae family, one of the largest and more important families of plant viruses. Results: After collecting information on virus protein-protein interactions from different potyviruses, we have processed it and used it for inferring a protein-protein interaction network. All proteins are connected into a single network component. Some proteins show a high degree and are highly connected while others are much less connected, with the network showing a significant degree of dissortativeness. We have attempted to integrate this virus protein-protein interaction network into the largest protein-protein interaction network of Arabidopsis thaliana, a susceptible laboratory host. To make the interpretation of data and results easier, we have developed a new approach for visualizing and analyzing the dynamic spread on the host network of the local perturbations induced by viral proteins. We found that local perturbations can reach the entire host protein-protein interaction network, although the efficiency of this spread depends on the particular viral proteins. By comparing the spread dynamics among viral proteins, we found that some proteins spread their effects fast and efficiently by attacking hubs in the host network while other proteins exert more local effects. Conclusions: Our findings confirm that potyvirus protein-protein interaction networks are highly connected, with some proteins playing the role of hubs. Several topological parameters depend linearly on the protein degree. Some viral proteins focus their effect in only host hubs while others diversify its effect among several proteins at the first step. Future new data will help to refine our model and to improve our predictions.This work was supported by the Spanish Ministerio de Economia y Competitividad grants BFU2012-30805 (to SFE), DPI2011-28112-C04-02 (to AF) and DPI2011-28112-C04-01 (to JP). The first two authors are recipients of fellowships from the Spanish Ministerio de Economia y Competitividad: BES-2012-053772 (to GB) and BES-2012-057812 (to AF-F).Bosque, G.; Folch Fortuny, A.; Picó Marco, JA.; Ferrer, A.; Elena Fito, SF. (2014). Topology analysis and visualization of Potyvirus protein-protein interaction network. BMC Systems Biology. 129(8):1-15. doi:10.1186/s12918-014-0129-8S1151298Gibbs A, Ohshima K: Potyviruses and the digital revolution. Annu Rev Phytopathol. 2010, 48: 205-223. 10.1146/annurev-phyto-073009-114404.Spence NJ, Phiri NA, Hughes SL, Mwaniki A, Simons S, Oduor G, Chacha D, Kuria A, Ndirangu S, Kibata GN, Marris GC: Economic impact of turnip mosaic virus, cauliflower mosaic virus and beet mosaic virus in three Kenyan vegetables. Plant Pathol. 2007, 56: 317-323. 10.1111/j.1365-3059.2006.01498.x.Ward CW, Shukla DD: Taxonomy of potyviruses: current problems and some solutions. Intervirology. 1991, 32: 269-296.Riechmann JL, Laín S, García JA: Highlights and prospects of potyvirus molecular biology. J Gen Virol. 1992, 73 (Pt 1): 1-16. 10.1099/0022-1317-73-1-1.Elena SF, Rodrigo G: Towards an integrated molecular model of plant-virus interactions. Curr Opin Virol. 2012, 2: 719-724. 10.1016/j.coviro.2012.09.004.Wei T, Zhang C, Hong J, Xiong R, Kasschau KD, Zhou X, Carrington JC, Wang A: Formation of complexes at plasmodesmata for potyvirus intercellular movement is mediated by the viral protein P3N-PIPO. PLoS Pathog. 2010, 6: e1000962-10.1371/journal.ppat.1000962.Chung BY-W, Miller WA, Atkins JF, Firth AE: An overlapping essential gene in the Potyviridae. Proc Natl Acad Sci. 2008, 105: 5897-5902. 10.1073/pnas.0800468105.Allison R, Johnston RE, Dougherty WG: The nucleotide sequence of the coding region of tobacco etch virus genomic RNA: evidence for the synthesis of a single polyprotein. Virology. 1986, 154: 9-20. 10.1016/0042-6822(86)90425-3.Domier LL, Franklin KM, Shahabuddin M, Hellmann GM, Overmeyer JH, Hiremath ST, Siaw MF, Lomonossoff GP, Shaw JG, Rhoads RE: The nucleotide sequence of tobacco vein mottling virus RNA. Nucleic Acids Res. 1986, 14: 5417-5430. 10.1093/nar/14.13.5417.Revers F, Le Gall O, Candresse T, Maule AJ: New advances in understanding the molecular biology of plant/potyvirus interactions. Mol Plant Microbe Interact. 1999, 12: 367-376. 10.1094/MPMI.1999.12.5.367.Urcuqui-Inchima S, Haenni AL, Bernardi F: Potyvirus proteins: a wealth of functions. Virus Res. 2001, 74: 157-175. 10.1016/S0168-1702(01)00220-9.Merits A, Rajamäki M-L, Lindholm P, Runeberg-Roos P, Kekarainen T, Puustinen P, Mäkeläinen K, Valkonen JPT, Saarma M: Proteolytic processing of potyviral proteins and polyprotein processing intermediates in insect and plant cells. J Gen Virol. 2002, 83: 1211-1221.Adams MJ, Antoniw JF, Beaudoin F: Overview and analysis of the polyprotein cleavage sites in the family Potyviridae. Mol Plant Pathol. 2005, 6: 471-487. 10.1111/j.1364-3703.2005.00296.x.Zheng H, Yan F, Lu Y, Sun L, Lin L, Cai L, Hou M, Chen J: Mapping the self-interacting domains of TuMV HC-Pro and the subcellular localization of the protein. Virus Genes. 2011, 42: 110-116. 10.1007/s11262-010-0538-8.Culver JN, Padmanabhan MS: Virus-induced disease: altering host physiology one interaction at a time. Annu Rev Phytopathol. 2007, 45: 221-243. 10.1146/annurev.phyto.45.062806.094422.De Las Rivas J, Fontanillo C: Protein-protein interactions essentials: key concepts to building and analyzing interactome networks. PLoS Comput Biol. 2010, 6: e1000807-10.1371/journal.pcbi.1000807.Bornke F: Protein Interaction Networks. Anal Biol Netw. Edited by: Junker BH, Schreiber F. 2008, John Wiley & Sons, Inc, Hoboken, NJ, USA, 207-232. 10.1002/9780470253489.ch9.Phizicky EM, Fields S: Protein-protein interactions: methods for detection and analysis. Microbiol Rev. 1995, 59: 94-123.Brückner A, Polge C, Lentze N, Auerbach D, Schlattner U: Yeast two-hybrid, a powerful tool for systems biology. Int J Mol Sci. 2009, 10: 2763-2788. 10.3390/ijms10062763.Fields S, Song O: A novel genetic system to detect protein-protein interactions. Nature. 1989, 340: 245-246. 10.1038/340245a0.Ho Y, Gruhler A, Heilbut A, Bader GD, Moore L, Adams S-L, Millar A, Taylor P, Bennett K, Boutilier K, Yang L, Wolting C, Donaldson I, Schandorff S, Shewnarane J, Vo M, Taggart J, Goudreault M, Muskat B, Alfarano C, Dewar D, Lin Z, Michalickova K, Willems AR, Sassi H, Nielsen PA, Rasmussen KJ, Andersen JR, Johansen LE, Hansen LH, et al: Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature. 2002, 415: 180-183. 10.1038/415180a.Hu C-D, Chinenov Y, Kerppola TK: Visualization of interactions among bZIP and Rel family proteins in living cells using bimolecular fluorescence complementation. Mol Cell. 2002, 9: 789-798. 10.1016/S1097-2765(02)00496-3.Kodama Y, Hu C-D: An improved bimolecular fluorescence complementation assay with a high signal-to-noise ratio. Biotechniques. 2010, 49: 793-805. 10.2144/000113519.Rual J-F, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N, Klitgord N, Simon C, Boxem M, Milstein S, Rosenberg J, Goldberg DS, Zhang LV, Wong SL, Franklin G, Li S, Albala JS, Lim J, Fraughton C, Llamosas E, Cevik S, Bex C, Lamesch P, Sikorski RS, Vandenhaute J, Zoghbi HY, et al: Towards a proteome-scale map of the human protein-protein interaction network. Nature. 2005, 437: 1173-1178. 10.1038/nature04209.Venkatesan K, Rual J-F, Vazquez A, Stelzl U, Lemmens I, Hirozane-Kishikawa T, Hao T, Zenkner M, Xin X, Goh K-I, Yildirim MA, Simonis N, Heinzmann K, Gebreab F, Sahalie JM, Cevik S, Simon C, de Smet A-S, Dann E, Smolyar A, Vinayagam A, Yu H, Szeto D, Borick H, Dricot A, Klitgord N, Murray RR, Lin C, Lalowski M, Timm J, et al: An empirical framework for binary interactome mapping. Nat Methods. 2008, 6: 83-90. 10.1038/nmeth.1280.Uetz P, Giot L, Cagney G, Mansfield TA, Judson RS, Knight JR, Lockshon D, Narayan V, Srinivasan M, Pochart P, Qureshi-Emili A, Li Y, Godwin B, Conover D, Kalbfleisch T, Vijayadamodar G, Yang M, Johnston M, Fields S, Rothberg JM: A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature. 2000, 403: 623-627. 10.1038/35001009.Ito T, Chiba T, Ozawa R, Yoshida M, Hattori M, Sakaki Y: A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc Natl Acad Sci. 2001, 98: 4569-4574. 10.1073/pnas.061034498.Uetz P, Dong Y-A, Zeretzke C, Atzler C, Baiker A, Berger B, Rajagopala SV, Roupelieva M, Rose D, Fossum E, Haas J: Herpesviral protein networks and their interaction with the human proteome. Science. 2006, 311: 239-242. 10.1126/science.1116804.Fossum E, Friedel CC, Rajagopala SV, Titz B, Baiker A, Schmidt T, Kraus T, Stellberger T, Rutenberg C, Suthram S, Bandyopadhyay S, Rose D, von Brunn A, Uhlmann M, Zeretzke C, Dong Y-A, Boulet H, Koegl M, Bailer SM, Koszinowski U, Ideker T, Uetz P, Zimmer R, Haas J: Evolutionarily conserved herpesviral protein interaction networks. PLoS Pathog. 2009, 5: e1000570-10.1371/journal.ppat.1000570.Rodrigo G, Carrera J, Ruiz-Ferrer V, del Toro FJ, Llave C, Voinnet O, Elena SF: A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens. PLoS One. 2012, 7: e40526-10.1371/journal.pone.0040526.Newman MEJ: The structure and function of complex networks. SIAM Rev. 2003, 45: 167-256. 10.1137/S003614450342480.Watts DJ, Strogatz SH: Collective dynamics of "small-world" networks. Nature. 1998, 393: 440-442. 10.1038/30918.Albert R, Barabási A-L: Statistical mechanics of complex networks. Rev Mod Phys. 2002, 74: 47-97. 10.1103/RevModPhys.74.47.Boccaletti S, Latora V, Moreno Y, Chávez M, Hwang D: Complex networks: structure and dynamics. Phys Rep. 2006, 424: 175-308. 10.1016/j.physrep.2005.10.009.Barabási A-L, Oltvai ZN: Network biology: understanding the cell's functional organization. Nat Rev Genet. 2004, 5: 101-113. 10.1038/nrg1272.Albert R, DasGupta B, Hegde R, Sivanathan GS, Gitter A, Gürsoy G, Paul P, Sontag E: Computationally efficient measure of topological redundancy of biological and social networks. Phys Rev E. 2011, 84: 036117-10.1103/PhysRevE.84.036117.Cho D-Y, Kim Y-A, Przytycka TM: Chapter 5: network biology approach to complex diseases. PLoS Comput Biol. 2012, 8: e1002820-10.1371/journal.pcbi.1002820.Russell RB, Aloy P: Targeting and tinkering with interaction networks. Nat Chem Biol. 2008, 4: 666-673. 10.1038/nchembio.119.Winterbach W, Mieghem PV, Reinders M, Wang H, de Ridder D: Topology of molecular interaction networks. BMC Syst Biol. 2013, 7: 90-10.1186/1752-0509-7-90.Pržulj N: Protein-protein interactions: making sense of networks via graph-theoretic modeling. Bioessays. 2011, 33: 115-123. 10.1002/bies.201000044.Yook S-H, Oltvai ZN, Barabási A-L: Functional and topological characterization of protein interaction networks. Proteomics. 2004, 4: 928-942. 10.1002/pmic.200300636.Pržulj N, Wigle DA, Jurisica I: Functional topology in a network of protein interactions. Bioinformatics. 2004, 20: 340-348. 10.1093/bioinformatics/btg415.Elena SF, Carrera J, Rodrigo G: A systems biology approach to the evolution of plant-virus interactions. Curr Opin Plant Biol. 2011, 14: 372-377. 10.1016/j.pbi.2011.03.013.Zilian E, Maiss E: Detection of plum pox potyviral protein-protein interactions in planta using an optimized mRFP-based bimolecular fluorescence complementation system. J Gen Virol. 2011, 92: 2711-2723. 10.1099/vir.0.033811-0.Lin L, Shi Y, Luo Z, Lu Y, Zheng H, Yan F, Chen J, Chen J, Adams MJ, Wu Y: Protein-protein interactions in two potyviruses using the yeast two-hybrid system. Virus Res. 2009, 142: 36-40. 10.1016/j.virusres.2009.01.006.Guo D, Rajamäki M-L, Saarma M, Valkonen JPT: Towards a protein interaction map of potyviruses: protein interaction matrixes of two potyviruses based on the yeast two-hybrid system. J Gen Virol. 2001, 82: 935-939.Shen WT, Wang MQ, Yan P, Gao L, Zhou P: Protein interaction matrix of papaya ringspot virus type P based on a yeast two-hybrid system. Acta Virol. 2010, 54: 49-54. 10.4149/av_2010_01_49.Kang S, Ws L, Kh K: A protein interaction map of soybean mosaic virus strain G7H based on the yeast two-hybrid system. Mol Cells. 2004, 18: 122-126.Yambao MLM, Masuta C, Nakahara K, Uyeda I: The central and C-terminal domains of VPg of Clover yellow vein virus are important for VPg-HCPro and VPg-VPg interactions. J Gen Virol. 2003, 84: 2861-2869. 10.1099/vir.0.19312-0.Evidence for network evolution in an Arabidopsis interactome map. Science. 2011, 333: 601-607. 10.1126/science.1203877.Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13: 2498-2504. 10.1101/gr.1239303.Fouss F, Francoisse K, Yen L, Pirotte A, Saerens M: An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification. Neural Netw Off J Int Neural Netw Soc. 2012, 31: 53-72. 10.1016/j.neunet.2012.03.001.Bass JIF, Diallo A, Nelson J, Soto JM, Myers CL, Walhout AJM: Using networks to measure similarity between genes: association index selection. Nat Methods. 2013, 10: 1169-1176. 10.1038/nmeth.2728.Newman MEJ: Assortative mixing in networks. Phys Rev Lett. 2002, 89: 208701-10.1103/PhysRevLett.89.208701