Periodic coupling strength-dependent multiple coherence resonance by time delay in Newman–Watts neuronal networks

Recently, multiple coherence resonance induced by time delay has been observed in neuronal networks with constant coupling strength. In this paper, by employing Newman–Watts Hodgkin–Huxley neuron networks with time-periodic coupling strength, we study how the temporal coherence of spiking behavior and coherence resonance by time delay change when the frequency of periodic coupling strength is varied. It is found that delay induced coherence resonance is dependent on periodic coupling strength and increases when the frequency of periodic coupling strength increases. Periodic coupling strength can also induce multiple coherence resonance, and the coherence resonance occurs when the frequency of periodic coupling strength is approximately multiple of the spiking frequency. These results show that for periodic coupling strength time delay can more frequently optimize the temporal coherence of spiking activity, and periodic coupling strength can repetitively optimize the temporal coherence of spiking activity as well. Frequency locking may be the mechanism for multiple coherence resonance induced by periodic coupling strength. These findings imply that periodic coupling strength is more efficient for enhancing the temporal coherence of spiking activity of neuronal networks, and thus it could play a more important role in improving the time precision of information processing and transmission in neural networks.     

Contrasting effects of invasive plants in plant–pollinator networks

The structural organization of mutualism networks, typified by interspecific positive interactions, is important to maintain community diversity. However, there is little information available about the effect of introduced species on the structure of such networks. We compared uninvaded and invaded ecological communities, to examine how two species of invasive plants with large and showy flowers (Carpobrotus affine acinaciformis and Opuntia stricta) affect the structure of Mediterranean plant–pollinator networks. To attribute differences in pollination to the direct presence of the invasive species, areas were surveyed that contained similar native plant species cover, diversity and floral composition, with or without the invaders. Both invasive plant species received significantly more pollinator visits than any native species and invaders interacted strongly with pollinators. Overall, the pollinator community richness was similar in invaded and uninvaded plots, and only a few generalist pollinators visited invasive species exclusively. Invasive plants acted as pollination super generalists. The two species studied were visited by 43% and 31% of the total insect taxa in the community, respectively, suggesting they play a central role in the plant–pollinator networks. Carpobrotus and Opuntia had contrasting effects on pollinator visitation rates to native plants: Carpobrotus facilitated the visit of pollinators to native species, whereas Opuntia competed for pollinators with native species, increasing the nestedness of the plant–pollinator network. These results indicate that the introduction of a new species to a community can have important consequences for the structure of the plant–pollinator network.     

Dose–response and threshold effects in cytotoxicity and apoptosis

Cell death can occur as an active, programmed event in response to cytotoxic injury or to endogenous growth limiting factors; the latter serve to maintain homeostasis of cell number in tissues. Cells seem to use different pathways for programmed death, as reflected by their different morphology and different biochemistry. Severe cell damage leading to incapacitation of essential cell functions such as ATP synthesis or the maintenance of membrane potential may lead to “necrosis”. In any event, the incidence and rate of cell death increase with increasing signal intensity. Cytotoxic injury requires a certain number of primary insults; cell death will therefore occur only beyond a definable threshold. Growth factor control of cell death is receptor-mediated with dose–response relations including threshold phenomena follow the general principles of receptor kinetics. The occurrence of programmed cell death during the stages of carcinogenesis introduces a reversible component into this disease. Therefore, there may exist thresholds of dose or durations of exposure to certain carcinogens below which irreversible disease is not generated.     

Measuring spike timing distance in the Hindmarsh–Rose neurons

In the present paper, a simple spike timing distance is defined which can be used to measure the degree of synchronization with the information only encoded in the precise timing of the spike trains. Via calculating the spike timing distance defined in this paper, the spike train similarity of uncoupled Hindmarsh–Rose neurons in bursting or spiking states with different initial conditions is investigated and the results are compared with other spike train distance measures. Later, the spike timing distance measure is applied to study the synchronization of coupled or common noise-stimulated neurons. Counterintuitively, the addition of weak coupling or common noise doesn’t enhance the degree of synchronization although after critical values, both of them can induce complete synchronizations. More interestingly, the common noise plays opposite roles for weak and strong enough couplings. Finally, it should be noted that the measure defined in this paper can be extended to measure large neuronal ensembles and the lag synchronization.     

Patch-size and isolation effects in the Fisher–Kolmogorov equation

We examine the classical problem of the existence of a threshold size for a patch to allow for survival of a given population in the case where the patch is not completely isolated. The surrounding habitat matrix is characterized by a non-zero carrying capacity. We show that a critical patch size cannot be strictly defined in this case. We also obtain the saturation density in such a patch as a function of the size of the patch and the relative carrying capacity of the outer region. We argue that this relative carrying capacity is a measure of the isolation of the patch. Our results are then compared with conclusions drawn from observations of the population dynamics of understorey birds in fragments of the Amazonian forest and shown to qualitatively agree with them, offering an explanation for the importance of dispersal and isolation in these observations. Finally, we show that a generalized critical patch size can be introduced resorting to threshold densities for the observation of a given species.     

Matching–centrality decomposition and the forecasting of new links in networks

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network.     

Native and invasive hosts play different roles in host–parasite networks

Parasites are often key players in biological invasions since they can mediate the impact of host invasions or can themselves become invasive species. However, the nature and extent of parasite-mediated invasions are often difficult to delineate. Here, we used individual-based, weighted bipartite networks to study the roles (degrees of interactions of individuals in a modular network according to their within- and among-module connections) played by native and invasive host individuals to their parasite communities. We studied two phylogenetically and ecologically close fish species, Mugil cephalus s.l. and Planiliza haematocheilus (Teleostei: Mugilidae). Planiliza haematocheilus is native to the Sea of Japan and invasive in the Sea of Azov whereas, M. cephalus s.l. is native to both seas. Based on the common evolutionary history that drives native host–parasite networks, we hypothesised that 1) native networks have higher modularity than invaded ones; and 2) invasive hosts in the invaded area play a peripheral role to structure parasite communities. We analysed the whole parasite community and subsets based on transmission strategy and host specificity of the parasite species to establish whether modularity and host roles are related to these features in the native and invaded areas. All networks were found to be modular. However, modularity tended to be higher in networks of the native area rather than those of the invaded area. Host individuals of both fish species played similar roles in the native area, whereas invasive hosts played a peripheral role in the networks of the invaded area. We propose that long-term monitoring of the roles of invasive hosts in parasite communities can be a useful proxy for estimating the maturity of the establishment of the invasive hosts in an ecosystem.     

Evolutionarily conserved motifs and modules in mitochondrial protein–protein interaction networks

Advances in organelle interactomics have led to new insights into organelle functions. In this study, we considered the common mitochondrial PIN of four evolutionarily distant eukaryotic species, namely Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans. By comparative interactomics analysis of mitochondrial PINs in these organisms, five conserved modules were identified. Modules comprise the main mitochondrial tasks, including proteins involved in translation process, mitochondrial import inner membrane proteins, TCA cycle enzymes, mitochondrial electron transport chain, and metabolic enzymes. Furthermore, we reemphasize that subgraphs of network, i.e., motifs and themes, may represent evolutionarily conserved topological units which are biologically significant.     

Comparing the conservatism of ecological interactions in plant–pollinator and plant–herbivore networks

Conservatism in species interaction, meaning that related species tend to interact with similar partners, is an important feature of ecological interactions. Studies at community scale highlight variations in conservatism strength depending on the characteristics of the ecological interaction studied. However, the heterogeneity of datasets and methods used prevent to compare results between mutualistic and antagonistic networks. Here we perform such a comparison by taking plant–insect communities as a study case, with data on plant–herbivore and plant–pollinator networks. Our analysis reveals that plants acting as resources for herbivores exhibit the strongest conservatism in species interaction among the four interacting groups. Conservatism levels are similar for insect pollinators, insect herbivores and plants as interacting partners of pollinators, although insect pollinators tend to have a slightly higher conservatism than the two others. Our results thus clearly support the current view that within antagonistic networks, conservatism is stronger for species as resources than for species as consumer. Although the pattern tends to be opposite for plant–pollinator networks, our results suggest that asymmetry in conservatism is much less pronounced between the pollinators and the plant they interact with. We discuss these differences in conservatism strength in relation with the processes structuring plant–insect communities.     

Nestedness and τ-temperature in ecological networks

The τ-temperature is a measure of disorder of bipartite networks that is based on the total Manhattan distance of the adjacency matrix. Two properties of this measure are that it does not depend on permutations of lines or columns that have the same connectivity and it is completely determined by connectivities of lines and columns. The normalisation of τ is done by an uniform random matrix whose elements were previously sorted. τ shows no bias against uniform random matrices of several occupations, ρ, sizes, L, and shapes. The scaling of the total Manhattan distance of a random matrix is D_rand ∝ L³ρ while the same scaling for a full nested matrix is D_nest ∝ L³ρ^3/2. We test τ for a large set of empirical matrices to verify these scalings. The index τ correlates better with the temperature of Atmar than with the NODF index of nestedness. We conclude this work by discussing differences between nestedness indices and order/disorder indices.     

Constructing more informative plant–pollinator networks: visitation and pollen deposition networks in a heathland plant community

Interaction networks are widely used as tools to understand plant–pollinator communities, and to examine potential threats to plant diversity and food security if the ecosystem service provided by pollinating animals declines. However, most networks to date are based on recording visits to flowers, rather than recording clearly defined effective pollination events. Here we provide the first networks that explicitly incorporate measures of pollinator effectiveness (PE) from pollen deposition on stigmas per visit, and pollinator importance (PI) as the product of PE and visit frequency. These more informative networks, here produced for a low diversity heathland habitat, reveal that plant–pollinator interactions are more specialized than shown in most previous studies. At the studied site, the specialization index was lower for the visitation network than the PE network, which was in turn lower than for the PI network. Our study shows that collecting PE data is feasible for community-level studies in low diversity communities and that including information about PE can change the structure of interaction networks. This could have important consequences for our understanding of threats to pollination systems.     

Dispersion and polar flattening: noble gas–halogen complexes

High-level ab initio calculations on the complexes between noble gas atoms (He, Ne, Ar, Kr, and Xe) and dihalogen molecules (F₂, Cl₂, Br₂, and I₂) reveal trends, both in interaction energies and the energy difference between the linear and T-shaped structures, that can be explained well in terms of dispersion interactions enhanced by polar flattening of the halogens. The partial discrepancies with experimental findings are discussed.

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Graphical abstract The molecular electrostatic potential (red positive, blue negative) of Cl₂...Br₂ projected onto the 0.003 a.u. isodensity surface.

     

Metal–bipyridine complexes in DNA backbones and effects on thermal stability

Modified oligonucleotides are showing potential for multiple applications, including drug design, nanoscale building blocks, and biosensors. In an effort to expand the functionality available to DNA, we have placed chelating ligands directly into the backbone of DNA. Between one and three nucleosides were replaced with 2,2′-bipyridine phosphates in 23-mer duplexes of DNA. An array of metal ions were added (Fe²⁺, Co²⁺, Ni²⁺, Cu²⁺, Zn²⁺, and Pt²⁺) and the influences on duplex stability were examined by melting temperature studies. Titrations and UV–vis absorption spectroscopy were used to provide insights into the nature of the metal complexes formed. We found that Ni²⁺ binding to 2,2′-bipyridine typically provided the greatest increase in duplex stability relative to the other metal ions examined. For example, addition of Ni²⁺ to one 2,2′-bipyridine–DNA duplex increased the melting temperature by 13 °C, from 65.0 ± 0.3 to 78.4 ± 0.9 °C. These studies show that metal ions and backbone ligands can be used to regulate DNA structure and stability.     

Predicting single spikes and spike patterns with the Hindmarsh–Rose model

Most simple neuron models are only able to model traditional spiking behavior. As physiologists discover and classify different electrical phenotypes, computational neuroscientists become interested in using simple phenomenological models that can exhibit these different types of spiking patterns. The Hindmarsh–Rose model is a three-dimensional relaxation oscillator which can show both spiking and bursting patterns and has a chaotic regime. We test the predictive powers of the Hindmarsh–Rose model on two different test databases. We show that the Hindmarsh–Rose model can predict the spiking response of rat layer 5 neocortical pyramidal neurons on a stochastic input signal with a precision comparable to the best known spiking models. We also show that the Hindmarsh–Rose model can capture qualitatively the electrical footprints in a database of different types of neocortical interneurons. When the model parameters are fit from sub-threshold measurements only, the model still captures well the electrical phenotype, which suggests that the sub-threshold signals contain information about the firing patterns of the different neurons.     

On the functional and structural characterization of hubs in protein–protein interaction networks

A number of interesting issues have been addressed on biological networks about their global and local properties. The connection between the topological properties of proteins in Protein–Protein Interaction (PPI) networks and their biological relevance has been investigated focusing on hubs, i.e. proteins with a large number of interacting partners. We will survey the literature trying to answer the following questions: Do hub proteins have special biological properties? Do they tend to be more essential than non-hub proteins? Are they more evolutionarily conserved? Do they play a central role in modular organization of the protein interaction network? Are there structural properties that characterize hub proteins?     

Integration of lectin–glycan recognition systems and immune cell networks in CNS inflammation

Multiple sclerosis (MS) is a progressive degenerative disorder of the central nervous system (CNS), characterized by inflammation, demyelination and axonal loss. While the majority of MS patients experience relapsing-remitting symptoms followed by a secondary progressive phase, about 10–15% patients exhibit a primary progressive disease involving continuous progression from its onset. Here we review the role of lectin–glycan recognition systems, including those concerning siglecs, C-type lectins and galectins in the pathogenesis of MS and experimental autoimmune encephalomyelitis. Particularly, we will focus on the role of galectins in the fate of T cells, dendritic cells and CNS cell populations. Understanding the regulatory circuits governed by lectin–glycan interactions and their association with disease-associated cytokine networks will contribute to develop novel therapeutic strategies in MS.     

181 Integrative analysis of gene expression and protein–protein interaction networks in Glioblastoma

Glioblastoma multiforme (GBM) is the most malignant of all the brain tumors with very low median survival time of one year, as per Central Brain Tumor Registry of the USA, 2001. Efforts are ongoing to understand this disease pathogenesis in complete details. Global gene expression changes in GBM pathogenesis have been studied by several groups using microarray technology (e.g. Carro et al., 2010). One of the many approaches to ‘understand the control mechanisms underlying the observed changes in the activity of a biological process’ (Cline et al., 2007) is integration of gene expression and protein–protein interactions (PPI) datasets. Among several examples, aberrant activation of Wnt/β-catenin signaling pathway as well as sonic hedgehog (SHH) signaling pathway is reported in GBMs (Klaus & Birchmeier, 2008). Further, these two pathways are also involved in proliferation and clonogenicity of glioma cancer stem cells (Li et al., 2009), which are thought to play a role in glioma initiation, proliferation, and invasion, and are one of the important points of intervention. Hedgehog–Gli1 signaling is also found to regulate the expression of stemness genes. In this paper, analyses of the relationship between the significant differential expression of these and other genes and the connectivity as well as topological features of a PPI network would be discussed. This way, genes potentially overlooked when relying solely on expression profiles may be identified which can be biologically relevant as possible drug target/s or disease biomarker/s.