Clusters Of Structures Research Articles

Tissue heterogeneity in structure and conductivity contribute to cell survival during irreversible electroporation ablation by "electric field sinks".

Irreversible electroporation (IRE) is an emerging, minimally invasive technique for solid tumors ablation, under clinical investigation for cancer therapy. IRE affects only the cell membrane, killing cells while preserving the extracellular matrix structure. Current reports indicate tumors recurrence rate after IRE averaging 31% of the cases, of which 10% are local recurrences. The mechanisms for these recurrences are not known and new explanations for incomplete cell death are needed. Using finite elements method for electric field distribution, we show that presence of vascular structures with blood leads to the redistribution of electric fields leading to the areas with more than 60% reduced electric field strength in proximity to large blood vessels and clustered vessel structures. In an in vivo rat model of liver IRE ablation, we show that cells located in the proximity of larger vessel structures and in proximity of clustered vessel structures appear less affected by IRE ablation than cells in the tissue parenchyma or in the proximity of small, more isolated vessels. These findings suggest a role for “electric field sinks” in local tumors recurrences after IRE and emphasize the importance of the precise mapping of the targeted organ structure and conductivity for planning of electroporation procedures.

Growing scale-free networks with tunable distributions of triad motifs

Network motifs are local structural patterns and elementary functional units of complex networks in real world, which can have significant impacts on the global behavior of these systems. Many models are able to reproduce complex networks mimicking a series of global features of real systems, however the local features such as motifs in real networks have not been well represented. We propose a model to grow scale-free networks with tunable motif distributions through a combined operation of preferential attachment and triad motif seeding steps. Numerical experiments show that the constructed networks have adjustable distributions of the local triad motifs, meanwhile preserving the global features of power-law distributions of node degree, short average path lengths of nodes, and highly clustered structures.

LEGACY EXTRAGALACTIC UV SURVEY (LEGUS) WITH THEHUBBLE SPACE TELESCOPE. I. SURVEY DESCRIPTION

The Legacy ExtraGalactic UV Survey (LEGUS) is a Cycle 21 Treasury program on the Hubble Space Telescope, aimed at the investigation of star formation and its relation with galactic environment in nearby galaxies, from the scales of individual stars to those of ~kpc-size clustered structures. Five-band imaging, from the near-ultraviolet to the I-band, with the Wide Field Camera 3, plus parallel optical imaging with the Advanced Camera for Surveys, is being collected for selected pointings of 50 galaxies within the local 12 Mpc. The filters used for the observations with the Wide Field Camera 3 are: F275W(2,704 A), F336W(3,355 A), F438W(4,325 A), F555W(5,308 A), and F814W(8,024 A); the parallel observations with the Advanced Camera for Surveys use the filters: F435W(4,328 A), F606W(5,921 A), and F814W(8,057 A). The multi-band images are yielding accurate recent (<~50 Myr) star formation histories from resolved massive stars and the extinction-corrected ages and masses of star clusters and associations. The extensive inventories of massive stars and clustered systems will be used to investigate the spatial and temporal evolution of star formation within galaxies. This will, in turn, inform theories of galaxy evolution and improve the understanding of the physical underpinning of the gas-star formation relation and the nature of star formation at high redshift. This paper describes the survey, its goals and observational strategy, and the initial science results. Because LEGUS will provide a reference survey and a foundation for future observations with JWST and with ALMA, a large number of data products are planned for delivery to the community.

Effect of chain length distribution on thermal characteristics of model polytetrahydrofuran (PTHF) networks

A series of model polytetrahydrofuran (PTHF) networks were synthesized via end-linking reactions of α, ω-allyl PTHF oligomers with a stoichiometric tetrafunctional crosslinker. The telechelic PTHF oligomers were synthesized by living cationic ring-opening polymerization of tetrahydrofuran followed by a termination reaction with allyl alcohol. Networks thus prepared have well-controlled architecture in terms of the inter-crosslink chain length (Mc) and chain length distribution: resulting in unimodal, bimodal and clustered structures. Unimodal network was prepared by using polymer chains of same molecular weight, bimodal networks were synthesized by using two groups of polymer chains with different average molecular weights, and the clusters are prepared by incorporating clusters of networks with small molecular weight chains in a network matrix made of longer chains. Thermal characteristics of these model networks were investigated as a function of crosslink density, as well as inhomogeneities of crosslink distribution using DSC. We demonstrate that glass transition temperature (Tg) and crystallization behavior (melting temperature and crystallinity) of the networks are both strongly influenced by crosslink density (Mc). By comparing the unimodal, bimodal and clustered networks with similar average Mc, the effects of inhomogeneities in the crosslink distribution on the thermal properties were also investigated. Results show that inhomogeneities have trivial influence on Tg, but strongly affects the crystallization behavior. Moreover, the effects of the content ratio and length ratio between long and short chains, and the effects of cluster size and size distribution on the thermal characteristics were also studied.

Mixed effect frameworks in the analysis of longitudinal data

Longitudinal research generates data with correlated measurements and clustered data structures. The main interest in longitudinal studies is to find the change in outcome over time and to analyze the influence of predictor variables on the outcome. Model-based approach is a powerful tool to integrate the multiple measurements and complexity of such data. Mixed effect models provide the framework to identify the role of individual differences in responses, while incorporating information from multifactorial measures at the individual and group levels to advance our understanding of the underlying components influencing response. This methodology is flexible, could be extended to different data patterns and computes more accurate and stable estimates. Using a multilevel modeling approach, the hierarchical structure can be explicitly modeled. With the availability of standard statistical software for both classical and Bayesian approaches, its applicability has increased in various fields such as genome-wide association studies, understanding of disease/recovery process, disease-marker association and behavioral studies to understand personality traits and health outcomes. This review seeks to focus on the methodological approaches to model multiple failure time data, conceptual issues, arising due to correlation, heterogeneity, and clustering and estimation procedures. The article also emphasizes on their application in data analysis especially in immunology and rheumatology studies.

Vertex Ordering, Clustering, and Their Application to Graph Partitioning

We propose a new heuristic for vertex ordering and a method that splits the vertex ordering into clusters. We apply them to the graph partitioning problem. The application of these ideas incorporates reordering in genetic algorithms and the identification of clustered structures in graphs. Experimental tests on benchmark graphs showed that the new vertex-ordering scheme performed better than existing methods in terms of genetic algorithms, and that the clusters wer e successfully captured.

Using spherical wavelets to search for magnetically-induced alignment in the arrival directions of ultra-high energy cosmic rays

Due to the action of the intervening cosmic magnetic fields, ultra-high energy cosmic rays (UHECRs) can be deflected in such a way as to create clustered energy-ordered filamentary structures in the arrival direction of these particles, the so-called multiplets. In this work we propose a new method based on the spherical wavelet transform to identify multiplets in sky maps containing arrival directions of UHECRs. The method is illustrated in simulations with a multiplet embedded in isotropic backgrounds with different numbers of events. The efficiency of the algorithm is assessed through the calculation of Type I and II errors.

Effect of the microhydration on the tautomerism in the anticarcinogenic drug 5-fluorouracil and relationships with other 5-haloderivatives

The 5-fluorouracil (in short 5-FU) mutagenicity was investigated in the isolated state and in the hydrated form through an exhaustive quantum-chemical analysis. The most optimum tautomers of 5-FU were optimized and analyzed. Six of them were related to those of uracils molecule, with the same stability order. The effect of the halogen substitution in position 5 on the uracil ring in the stability of the different tautomers was analyzed. Solvent effects were considered using a variable number (1–10) of explicit water molecules surrounding 5-FU in order to simulate the first hydration shell. More than 100 cluster structures with water were analyzed. A comparative analysis in the different tautomers of the hydration effect on the molecular structure and energetics was carried out. For cases where literature data are available, the computed values were in good agreement with previous experimental and theoretical studies. Depending on the nature of the tautomers, cyclic, distributed, or clustered structures were formed. The deformation and interaction counterpoise (CP)-corrected energies between 5-FU and water molecules were determined. The maximum interaction was found in the enol form T2. The microhydrated environment stabilized remarkably the enol forms T3 and T5 (present in the corresponding nucleoside) more than the canonical keto T1, although this one continues being the most stable. Several relationships with 5-XU derivatives (X=F, Cl, Br, I) between the relative energy of tautomer T2 and the geometric parameters/atomic charges were underlined.

Assembly, Disassembly, and Anomalous Propulsion of Microscopic Helices

Controlling the motion of small objects in suspensions wirelessly is of fundamental interest and has potential applications in biomedicine for drug delivery and micromanipulation of small structures. Here we show that magnetic helical microstructures that propel themselves in the presence of rotating weak magnetic fields assemble into various configurations that exhibit locomotion and a change in swimming direction. The configuration is tuned dynamically, that is, assembly and disassembly occur, by the field input. We investigate a system that consists of two identical right-handed helices assembled at their center in order to model the motion of assembled swimmers. The swimming properties are dependent on both the component design and the assembly configuration. For particular designs and configurations, a reversal in swimming direction emerges, yet with other designs, a reversal in motion never appears. Understanding the locomotion of clustered chiral structures enables uni- and multidirectional navigation of this class of active suspensions.

Turn-Directed α-β Conformational Transition of α-syn12 Peptide at Different pH Revealed by Unbiased Molecular Dynamics Simulations

The transition from α-helical to β-hairpin conformations of α-syn12 peptide is characterized here using long timescale, unbiased molecular dynamics (MD) simulations in explicit solvent models at physiological and acidic pH values. Four independent normal MD trajectories, each 2500 ns, are performed at 300 K using the GROMOS 43A1 force field and SPC water model. The most clustered structures at both pH values are β-hairpin but with different turns and hydrogen bonds. Turn9-6 and four hydrogen bonds (HB9-6, HB6-9, HB11-4 and HB4-11) are formed at physiological pH; turn8-5 and five hydrogen bonds (HB8-5, HB5-8, HB10-3, HB3-10 and HB12-1) are formed at acidic pH. A common folding mechanism is observed: the formation of the turn is always before the formation of the hydrogen bonds, which means the turn is always found to be the major determinant in initiating the transition process. Furthermore, two transition paths are observed at physiological pH. One of the transition paths tends to form the most-clustered turn and improper hydrogen bonds at the beginning, and then form the most-clustered hydrogen bonds. Another transition path tends to form the most-clustered turn, and turn5-2 firstly, followed by the formation of part hydrogen bonds, then turn5-2 is extended and more hydrogen bonds are formed. The transition path at acidic pH is as the same as the first path described at physiological pH.

Are z ∼ 5 quasars found in the most massive high-redshift overdensities?★

Luminous high-redshift QSOs are thought to exist within the most massive dark matter haloes in the young Universe. As a consequence they are likely to be markers for biased, over-dense regions where early galaxies cluster, regions that eventually grow into the groups and clusters seen in the lower redshift universe. In this paper we explore the clustering of galaxies around z ~ 5 QSOs as traced by Lyman Break Galaxies (LBGs). We target the fields of three QSOs using the same optical imaging and spectroscopy techniques used in the ESO Remote Galaxy Survey (ERGS, Douglas et al. 2009, 2010), which was successful in identifying individual clustered structures of LBGs. We use the statistics of the redshift clustering in ERGS to show that two of the three fields show significant clustering of LBGs at the QSO redshifts. Neither of these fields is obviously over-dense in LBGs from the imaging alone; a possible reason why previous imaging-only studies of high-redshift QSO environments have given ambiguous results. This result shows that luminous QSOs at z ~ 5 are typically found in over-dense regions. The richest QSO field contains at least nine spectroscopically confirmed objects at the same redshift including the QSO itself, seven LBGs and a second fainter QSO. While this is a very strong observational signal of clustering at z ~ 5, it is of similar strength to that seen in two structures identified in the 'blank sky' ERGS fields. This indicates that, while over-dense, the QSO environments are not more extreme than other structures that can be identified at these redshifts. The three richest structures discovered in this work and in ERGS have properties consistent with that expected for proto-clusters and likely represent the early stages in the build-up of massive current-day groups and clusters.

Network Formation in the Presence of Contagious Risk

There are a number of domains where agents must collectively form a network in the face of the following trade-off: each agent receives benefits from the direct links it forms to others, but these links expose it to the risk of being hit by a cascading failure that might spread over multistep paths. Financial contagion, epidemic disease, the exposure of covert organizations to discovery, and electrical power networks are all settings in which such issues have been articulated. Here we formulate the problem in terms of strategic network formation, and provide asymptotically tight bounds on the welfare of both optimal and stable networks. We find that socially optimal networks are, in a precise sense, situated just beyond a phase transition in the behavior of the cascading failures, and that stable graphs lie slightly further beyond this phase transition, at a point where most of the available welfare has been lost. Our analysis enables us to explore such issues as the trade-offs between clustered and anonymous market structures, and it exposes a fundamental sense in which very small amounts of “over-linking” in networks with contagious risk can have strong consequences for the welfare of the participants.

Analysis of misinformation containment in online social networks

With their blistering expansion in recent years, popular online social sites such as Twitter, Facebook and Bebo, have become not only one of the most effective channels for viral marketing but also the major news sources for many people nowadays. Alongside these promising features, however, comes the threat of misinformation propagation which can lead to undesirable effects. Due to the sheer number of online social network (OSN) users and the highly clustered structures commonly shared by these kinds of networks, there is a substantial challenge to efficiently contain viral spread of misinformation in large-scale social networks. In this paper, we focus on how to limit viral propagation of misinformation in OSNs. Particularly, we study a set of problems, namely the βTI-Node Protectors problems, which aim to find the smallest set of highly influential nodes from which disseminating good information helps to contain the viral spread of misinformation, initiated from a set of nodes I, within a desired fraction (1-β) of the nodes in the entire network in T time steps. For this family of problems, we analyze and present solutions including their inapproximability results, greedy algorithms that provide better lower bounds on the number of selected nodes, and a community-based method for solving these problems. We further conduct a number of experiments on real-world traces, and the empirical results show that our proposed methods outperform existing alternative approaches in finding those important nodes that can help to contain the spread of misinformation effectively.

Nonlinear dynamic foundation and frame structure response observed in geotechnical centrifuge experiments

Soil–foundation–structure interaction (SFSI) and structure–soil–structure interaction (SSSI) influence the seismic response of a structure. Yet, consideration of nonlinear SFSI and SSSI in design practice is lacking. In this paper data from two centrifuge tests are examined. During each test, inelastic models of (1) a low-rise frame with shallowly embedded footings and (2) a mid-rise frame with a large basement are subjected to earthquake motions. In the first test, the structures are separated. In the second test, the structures are placed next to each other. Results show that the presence of the deep basement affects the moment–rotation behavior of the adjacent shallow footings, stiffening the response in the direction of loading towards the basement. This can be attributed to the additional restraint provided by the basement. Although the presence of the basement stiffens the response, it also limits the permanent displacements of the footing, which in turn limits physical damage to the superstructure. These results suggest that in addition to considering nonlinear SFSI effects, SSSI should be considered in the design of closely clustered structures.

The essential roles of protein–protein interaction in sigma-1 receptor functions

The essential roles of protein–protein interaction in sigma-1 receptor functions

Conformation of polyelectrolytes using cellular automata techniques

A cellular automata model of polyelectrolytes is studied using NetLogo, a multi-agent modelling environment based on the Java virtual machine. NetLogo allows easy construction of cellular automata models, is free to use and has a detailed documentation and examples library. In order to illustrate the working principles of NetLogo, we study polyelectrolyte conformations in a liquid salt solution using the so called cluster entropy S_C as an order parameter. Our results predict the correct evolution of polyelectrolyte conformations, from collapsed clustered structures, at low charge/high salt concentration conditions, to elongated chains, at high charge/low salt concentration, as had been reported in the literature. In both of these situations the cluster entropy is approximately zero S_C ≈ 0. In intermediate charge and salt concentration conditions the well-known pearl necklace structure is observed, in this case the values of S_{C} reach a maximum. The use of NetLogo modelling environment along the cluster entropy concept, permits quick and objective descriptions of the spatial properties of polyelectrolytes.

Evaluation of Riproximin Binding Properties Reveals a Novel Mechanism for Cellular Targeting

Riproximin is a cytotoxic type II ribosome-inactivating protein showing high selectivity for tumor cell lines. Its binding to cell surface glycans is crucial for subsequent internalization and cytotoxicity. In this paper, we describe a unique mechanism of interaction and discuss its implications for the cellular targeting and cytotoxicity of riproximin. On a carbohydrate microarray, riproximin specifically bound to two types of asialo-glycans, namely to bi- and triantennary complex N-glycan structures (NA2/NA3) and to repetitive N-acetyl-D-galactosamine (GalNAc), the so-called clustered Tn antigen, a cancer-specific O-glycan on mucins. Two glycoproteins showing high riproximin binding, the NA3-presenting asialofetuin and the clustered Tn-rich asialo-bovine submaxillary mucin, were subsequently chosen as model glycoproteins to mimic the binding interactions of riproximin with the two types of glycans. ELISA analyses were used to relate the two binding specificities of riproximin to its two sugar binding sites. The ability of riproximin to cross-link the two model proteins revealed that binding of the two types of glycoconjugates occurs within different binding sites. The biological implications of these binding properties were analyzed in cellular assays. The cytotoxicity of riproximin was found to depend on its specific and concomitant interaction with the two glycoconjugates as well as on dynamic avidity effects typical for lectins binding to multivalent glycoproteins. The presence of definite, cancer-related structures on the cells to be targeted determines the therapeutic potency of riproximin. Due to its cross-linking ability, riproximin is expected to show a high degree of specificity for cells exposing both NA2/NA3 and clustered Tn structures.

A new measure based on degree distribution that links information theory and network graph analysis

BackgroundDetailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths.ResultsWe captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system’s capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric.ConclusionsThe new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties.

Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

Clustered connectivity promotes synchronous burst initiation in vitro

Event Abstract Back to Event Clustered connectivity promotes synchronous burst initiation in vitro Samora Okujeni1, 2, 3*, Nila Mönig2, 3, Steffen Kandler1, 2, 3, Oliver Weihberger1, 2 and Ulrich Egert1, 2 1 Albert-Ludwigs University of Freiburg, Bernstein Center Freiburg, Germany 2 Albert-Ludwigs University of Freiburg, Department of Microsystems Engineering, IMTEK, Germany 3 Albert-Ludwigs University of Freiburg, Department of Biology III, Germany Synchronous bursting events (SBE) are widely observed in developing neuronal systems suggesting that the capability to spontaneously initiate these dynamics reflects a crucial intermediate feature of forming networks. Consistently, SBE dynamics similarly and robustly also emerge as the predominant type of activity in networks of cultured neurons in vitro. We speculate that this might hint towards general neuronal mechanisms guiding network self-organization with the aim to establish these dynamics. Interestingly, theoretical models have shown that hierarchical network structures embedding clusters of strongly inter-connected neurons are optimal for initiating and sustaining spontaneous activity (Kaiser 2010) and clustered network structure typically emerges in networks forming in vitro (Kriegstein 1983). We hypothesize that activity-dependent structural plasticity, being a principle driving force of network self-organization, establishes clustered network structures and thereby promotes spontaneous activity levels. Previous studies showed that protein kinase C (PKC) inhibition promotes dendritic outgrowth and arborization (Metzger 2000), and impairs pruning (Kano 1995), linking this protein closely to structural plasticity. To test our hypothesis we thus inhibited PKC in developing networks of cortical neurons in vitro. We show that developmental inhibition of PKC in cortical cell cultures increased dendritic outgrowth, impaired neurite fasciculation and clustering, and abolished network pruning. This resulted in more homogeneous and potentially better connected networks. Consistently, SBEs propagated faster and in more regular wave fronts. Yet, following our hypothesis, SBEs were triggered from fewer sites and at lower rates suggesting that these homogeneous networks embedded fewer SBE initiation zones. We tested if the homogeneous networks were able to support higher SBE rates providing additional input by electrical stimulation. Interestingly, homogeneous networks achieved comparable rates when electrically stimulated compared to the more clustered control networks. This data suggests that activity-dependent structural plasticity promotes network clustering and thereby spontaneous SBE levels during development. Based on recent evidence for a reciprocal scaling between synaptic strength and number of neuronal partners in vitro (Wilson 2007), we propose that locally more confined synaptic targeting within neuronal clusters promotes stronger and more recurrent coupling of neurons. The resulting connectivity structure could thereby more easily amplify spontaneous excitation locally beyond a critical threshold necessary for SBE initiation. In summary, our results indicate that activity-dependent structural plasticity promotes neuronal clustering and thereby the ability of in vitro networks to spontaneously initiate SBEs. We propose that this might reflect a general strategy pursued by neuronal networks to establish this crucial activity pattern during development. Acknowledgements Supported by the German BMBF (FKZ 01GQ0420) and by the EC (NEURO, No. 12788). Keywords: burst, Cluster, connectivity, in vitro, network, Neuron, PKC, structural plasticity Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Other Citation: Okujeni S, Mönig N, Kandler S, Weihberger O and Egert U (2012). Clustered connectivity promotes synchronous burst initiation in vitro. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00112 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 18 Sep 2012; Published Online: 12 Sep 2012. * Correspondence: Mr. Samora Okujeni, Albert-Ludwigs University of Freiburg, Bernstein Center Freiburg, Freiburg, 79104, Germany, okujeni@bcf.uni-freiburg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Samora Okujeni Nila Mönig Steffen Kandler Oliver Weihberger Ulrich Egert Google Samora Okujeni Nila Mönig Steffen Kandler Oliver Weihberger Ulrich Egert Google Scholar Samora Okujeni Nila Mönig Steffen Kandler Oliver Weihberger Ulrich Egert PubMed Samora Okujeni Nila Mönig Steffen Kandler Oliver Weihberger Ulrich Egert Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.