WorldWideScience

Sample records for cd28-enhanced nanospatial coclustering

  1. Co-clustering models, algorithms and applications

    CERN Document Server

    Govaert, Gérard

    2013-01-01

    Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixture

  2. A fuzzy co-clustering algorithm for biomedical data.

    Science.gov (United States)

    Liu, Yongli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

    2017-01-01

    Fuzzy co-clustering extends co-clustering by assigning membership functions to both the objects and the features, and is helpful to improve clustering accurarcy of biomedical data. In this paper, we introduce a new fuzzy co-clustering algorithm based on information bottleneck named ibFCC. The ibFCC formulates an objective function which includes a distance function that employs information bottleneck theory to measure the distance between feature data point and the feature cluster centroid. Many experiments were conducted on five biomedical datasets, and the ibFCC was compared with such prominent fuzzy (co-)clustering algorithms as FCM, FCCM, RFCC and FCCI. Experimental results showed that ibFCC could yield high quality clusters and was better than all these methods in terms of accuracy.

  3. Co-clustering for Weblogs in Semantic Space

    DEFF Research Database (Denmark)

    Zong, Yu; Xu, Guandong; Dolog, Peter

    2010-01-01

    Web clustering is an approach for aggregating web objects into various groups according to underlying relationships among them. Finding co-clusters of web objects in semantic space is an interesting topic in the context of web usage mining, which is able to capture the underlying user navigational...... interest and content preference simultaneously. In this paper we will present a novel web co-clustering algorithm named Co-Clustering in Semantic space (COCS) to simultaneously partition web users and pages via a latent semantic analysis approach. In COCS, we first, train the latent semantic space...... of weblog data by using Probabilistic Latent Semantic Analysis (PLSA) model, and then, project all weblog data objects into this semantic space with probability distribution to capture the relationship among web pages and web users, at last, propose a clustering algorithm to generate the co...

  4. Non-parametric co-clustering of large scale sparse bipartite networks on the GPU

    DEFF Research Database (Denmark)

    Hansen, Toke Jansen; Mørup, Morten; Hansen, Lars Kai

    2011-01-01

    Co-clustering is a problem of both theoretical and practical importance, e.g., market basket analysis and collaborative filtering, and in web scale text processing. We state the co-clustering problem in terms of non-parametric generative models which can address the issue of estimating the number...... of row and column clusters from a hypothesis space of an infinite number of clusters. To reach large scale applications of co-clustering we exploit that parameter inference for co-clustering is well suited for parallel computing. We develop a generic GPU framework for efficient inference on large scale......-life large scale collaborative filtering data and web scale text corpora, demonstrating that latent mesoscale structures extracted by the co-clustering problem as formulated by the Infinite Relational Model (IRM) are consistent across consecutive runs with different initializations and also relevant...

  5. Adapting Spectral Co-clustering to Documents and Terms Using Latent Semantic Analysis

    Science.gov (United States)

    Park, Laurence A. F.; Leckie, Christopher A.; Ramamohanarao, Kotagiri; Bezdek, James C.

    Spectral co-clustering is a generic method of computing co-clusters of relational data, such as sets of documents and their terms. Latent semantic analysis is a method of document and term smoothing that can assist in the information retrieval process. In this article we examine the process behind spectral clustering for documents and terms, and compare it to Latent Semantic Analysis. We show that both spectral co-clustering and LSA follow the same process, using different normalisation schemes and metrics. By combining the properties of the two co-clustering methods, we obtain an improved co-clustering method for document-term relational data that provides an increase in the cluster quality of 33.0%.

  6. Simultaneous Co-Clustering and Classification in Customers Insight

    Science.gov (United States)

    Anggistia, M.; Saefuddin, A.; Sartono, B.

    2017-04-01

    Building predictive model based on the heterogeneous dataset may yield many problems, such as less precise in parameter and prediction accuracy. Such problem can be solved by segmenting the data into relatively homogeneous groups and then build a predictive model for each cluster. The advantage of using this strategy usually gives result in simpler models, more interpretable, and more actionable without any loss in accuracy and reliability. This work concerns on marketing data set which recorded a customer behaviour across products. There are some variables describing customer and product as attributes. The basic idea of this approach is to combine co-clustering and classification simultaneously. The objective of this research is to analyse the customer across product characteristics, so the marketing strategy implemented precisely.

  7. Joint local and global consistency on interdocument and interword relationships for co-clustering.

    Science.gov (United States)

    Bao, Bing-Kun; Min, Weiqing; Li, Teng; Xu, Changsheng

    2015-01-01

    Co-clustering has recently received a lot of attention due to its effectiveness in simultaneously partitioning words and documents by exploiting the relationships between them. However, most of the existing co-clustering methods neglect or only partially reveal the interword and interdocument relationships. To fully utilize those relationships, the local and global consistencies on both word and document spaces need to be considered, respectively. Local consistency indicates that the label of a word/document can be predicted from its neighbors, while global consistency enforces a smoothness constraint on words/documents labels over the whole data manifold. In this paper, we propose a novel co-clustering method, called co-clustering via local and global consistency, to not only make use of the relationship between word and document, but also jointly explore the local and global consistency on both word and document spaces, respectively. The proposed method has the following characteristics: 1) the word-document relationships is modeled by following information-theoretic co-clustering (ITCC); 2) the local consistency on both interword and interdocument relationships is revealed by a local predictor; and 3) the global consistency on both interword and interdocument relationships is explored by a global smoothness regularization. All the fitting errors from these three-folds are finally integrated together to formulate an objective function, which is iteratively optimized by a convergence provable updating procedure. The extensive experiments on two benchmark document datasets validate the effectiveness of the proposed co-clustering method.

  8. a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

    Science.gov (United States)

    Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

    2017-09-01

    Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

  9. Mg-controlled formation of Mg–Ag co-clusters in initial aged Al–Cu–Mg–Ag alloys

    International Nuclear Information System (INIS)

    Bai, Song; Liu, Zhiyi; Zhou, Xuanwei; Xia, Peng; Zeng, Sumin

    2014-01-01

    Highlights: • The strongest age-hardening response was found in 0.81Mg alloy. • Quantitative APT study showed strong dependence of Mg–Ag co-clustering on Mg content. • A critical Mg content related to the greatest Mg–Ag co-clustering was revealed. • The evolution from Mg–Ag co-clusters to Ω phase was accelerated in 1.18Mg alloy. - Abstract: The effect of Mg variations on the number density, solute concentrations and sizes of Mg–Ag co-clusters at the early aging stage, as well as the age-hardening response of different Al–Cu–Mg–Ag alloys, was well investigated by a combination of Vickers hardness measurement, transmission electron microscopy (TEM) and atom probe tomography (APT). The strongest age-hardening response at 165 °C was found in 0.81Mg alloy, accompanied by the highest nucleation rate of Mg–Ag co-clusters after aging for 0.5 h. However, the least response was revealed in 0.39Mg alloy. By quantitative APT analysis, the observed trend in the total number density of Mg–Ag co-clusters suggested the following order: 0.81Mg alloy > 0.39Mg alloy > 1.18Mg alloy. This parabolic change in the total number density of Mg–Ag co-clusters with increasing Mg highlighted the existence of a critical Mg content, which contributed to the greatest nucleation kinetics of Mg–Ag co-clusters. As Mg increased from 0.39 to 0.81, the formation of small Mg–Ag co-clusters was significantly promoted, whereas the number density of large Mg–Ag co-clusters almost remained constant. Moreover, the remarkable enrichment of Cu within Mg–Ag co-clusters indicated that the accelerated evolution from Mg–Ag co-clusters to Ω phase was responsible for the lowest number density of Mg–Ag co-clusters in 1.18Mg alloy after aging at 165 °C for 0.5 h

  10. A novel analysis of spring phenological patterns over Europe based on co-clustering

    NARCIS (Netherlands)

    Wu, X.; Zurita-Milla, R.; Kraak, M.J.

    2016-01-01

    The study of phenological patterns and their dynamics provides insights into the impacts of climate change on terrestrial ecosystems. Here we present a novel analytical workflow, based on co-clustering, that enables the concurrent study of spatio-temporal patterns in spring phenology. The workflow

  11. Co-clustering Analysis of Weblogs Using Bipartite Spectral Projection Approach

    DEFF Research Database (Denmark)

    Xu, Guandong; Zong, Yu; Dolog, Peter

    2010-01-01

    Web clustering is an approach for aggregating Web objects into various groups according to underlying relationships among them. Finding co-clusters of Web objects is an interesting topic in the context of Web usage mining, which is able to capture the underlying user navigational interest...

  12. Investigation of modulus hardening of various co-clusters in aged Al-Cu-Mg-Ag alloy by atom probe tomography

    Energy Technology Data Exchange (ETDEWEB)

    Bai, Song [Key Laboratory of Nonferrous Metal Materials Science and Engineering, Ministry of Education, Central South University, Changsha 410083 (China); School of Material Science and Engineering, Central South University, Changsha 410083 (China); Liu, Zhiyi, E-mail: liuzhiyi@csu.edu.cn [Key Laboratory of Nonferrous Metal Materials Science and Engineering, Ministry of Education, Central South University, Changsha 410083 (China); School of Material Science and Engineering, Central South University, Changsha 410083 (China); Ying, Puyou; Wang, Jian; Li, Junlin [Key Laboratory of Nonferrous Metal Materials Science and Engineering, Ministry of Education, Central South University, Changsha 410083 (China); School of Material Science and Engineering, Central South University, Changsha 410083 (China)

    2016-06-21

    The modulus hardening capability of various co-clusters in a low Cu/Mg ratio Al-Cu-Mg-Ag alloy aged at 165 °C is investigated by quantitative atom probe tomography analysis. Prolonged aging from 5 min to 2 h leads to the simultaneous increase in the critical shear stress of both Mg-Ag and Cu-Mg co-clusters. Regardless of the higher shear modulus of Cu-Mg co-clusters, calculation results show that Mg-Ag co-clusters possess a greater modulus hardening capability than Cu-Mg co-clusters, suggesting its primary contribution to the rapid hardening at the early aging stage. As aging extends from 30 min to 2 h, the increment in the critical shear stress of Mg-Ag co-clusters is lower than that of Cu-Mg co-clusters due to the precipitation of high density Ω phase. In addition, the shear modulus of Mg-Ag co-clusters is generally independent on its size at each investigated condition.

  13. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Science.gov (United States)

    Tokuda, Tomoki; Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  14. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Directory of Open Access Journals (Sweden)

    Tomoki Tokuda

    Full Text Available We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  15. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

    Science.gov (United States)

    Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

  16. Co-clustering directed graphs to discover asymmetries and directional communities.

    Science.gov (United States)

    Rohe, Karl; Qin, Tai; Yu, Bin

    2016-10-21

    In directed graphs, relationships are asymmetric and these asymmetries contain essential structural information about the graph. Directed relationships lead to a new type of clustering that is not feasible in undirected graphs. We propose a spectral co-clustering algorithm called di-sim for asymmetry discovery and directional clustering. A Stochastic co-Blockmodel is introduced to show favorable properties of di-sim To account for the sparse and highly heterogeneous nature of directed networks, di-sim uses the regularized graph Laplacian and projects the rows of the eigenvector matrix onto the sphere. A nodewise asymmetry score and di-sim are used to analyze the clustering asymmetries in the networks of Enron emails, political blogs, and the Caenorhabditis elegans chemical connectome. In each example, a subset of nodes have clustering asymmetries; these nodes send edges to one cluster, but receive edges from another cluster. Such nodes yield insightful information (e.g., communication bottlenecks) about directed networks, but are missed if the analysis ignores edge direction.

  17. Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

    Science.gov (United States)

    Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.

    2012-01-01

    Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…

  18. Magnetic domains in Co-cluster assembled films deposited by LECBD

    International Nuclear Information System (INIS)

    Dumas-Bouchiat, F.; Nagaraja, H.S.; Rossignol, F.; Champeaux, C.; Catherinot, A.

    2005-01-01

    Cobalt aggregates prepared using a cluster beam generator have been deposited on Si(100) substrate leading to thin films of randomly assembled Co nanoparticles which exhibit a spherical shape with a mono-dispersed diameter distribution centred around 9nm. Films with thickness ranging from 50 to 550nm are investigated using magnetic force microscopy (MFM) and results show the presence of twisted magnetic domains. An in-plane magnetic field applied during the growth of the layer leads to the formation of magnetic stripe domains but we observe a similar behaviour if an in-plane magnetic field is applied after the deposition. This indicates that probably the magnetic field applied during the film growth does not drive its magnetic structure. Finally, the measured variation of magnetic domain width D reveals a t dependence, where t is the film thickness, and is independent of the magnetic history of the films

  19. Enzyme clustering accelerates processing of intermediates through metabolic channeling

    Science.gov (United States)

    Castellana, Michele; Wilson, Maxwell Z.; Xu, Yifan; Joshi, Preeti; Cristea, Ileana M.; Rabinowitz, Joshua D.; Gitai, Zemer; Wingreen, Ned S.

    2015-01-01

    We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation. PMID:25262299

  20. The effect of natural pre-ageing on the mechanical properties of Rheo-High pressure die cast aluminium alloy 2139

    CSIR Research Space (South Africa)

    Chauke, L

    2015-07-01

    Full Text Available -high pressure die casting process (R-HPDC). Alloy 2139 is a Ag-containing aluminium alloy from the Al-Cu-Mg 2xxx series family. The addition of Ag enhances the age hardening response through the formation of co-clusters that act as precursors to the formation...

  1. Anti-glycosyl antibodies in lipid rafts of the enterocyte brush border: a possible host defense against pathogens

    DEFF Research Database (Denmark)

    Hansen, Gert Helge; Pedersen, Esben D K; Immerdal, Lissi

    2005-01-01

    a major part of the immunoglobulins at the lumenal surface of the gut. The antibodies were associated with lipid rafts at the brush border, and they frequently (52%) coclustered with the raft marker galectin 4. A lactose wash increased the susceptibility of the brush border toward lectin peanut agglutin...

  2. A tripartite clustering analysis on microRNA, gene and disease model.

    Science.gov (United States)

    Shen, Chengcheng; Liu, Ying

    2012-02-01

    Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

  3. Coincidence Doppler broadening and 3DAP study of the pre-precipitation stage of an Al-Li-Cu-Mg-Ag alloy

    International Nuclear Information System (INIS)

    Honma, T.; Yanagita, S.; Hono, K.; Nagai, Y.; Hasegawa, M.

    2004-01-01

    Pre-precipitation solute clustering in Al-Li-Cu-Mg-Ag and Al-Cu-Mg-Ag alloys has been investigated by coincidence Doppler broadening (CDB) spectroscopy of positron annihilation and three-dimensional atom probe (3DAP) analysis. Although Ag-Mg co-clusters form in the Al-Cu-Mg-Ag alloy in the early stage of aging, no evidence for the co-cluster formation was obtained from the Li containing alloy using 3DAP. While CDB spectra indicated that vacancies are associated with Ag after aging for 15 s in the Al-Cu-Mg-Ag alloy, vacancy-Ag association is suppressed in the Li containing alloy. Based on the 3DAP and CDB results, the reasons for the completely different clustering behaviors observed in these two similar alloys are discussed

  4. Understanding gene essentiality by finely characterizing hubs in the yeast protein interaction network.

    Science.gov (United States)

    Pang, Kaifang; Sheng, Huanye; Ma, Xiaotu

    2010-10-08

    The centrality-lethality rule, i.e., high-degree proteins or hubs tend to be more essential than low-degree proteins in the yeast protein interaction network, reveals that a protein's central position indicates its important function, but whether and why hubs tend to be more essential have been heavily debated. Here, we integrated gene expression and functional module data to classify hubs into four types: non-co-expressed non-co-cluster hubs, non-co-expressed co-cluster hubs, co-expressed non-co-cluster hubs and co-expressed co-cluster hubs. We found that all the four hub types are more essential than non-hubs, but they also show different enrichments in essential proteins. Non-co-expressed non-co-cluster hubs play key role in organizing different modules formed by the other three hub types, but they are less important to the survival of the yeast cell. Among the four hub types, co-expressed co-cluster hubs, which likely correspond to the core components of stable protein complexes, are the most essential. These results demonstrated that our classification of hubs into four types could better improve the understanding of gene essentiality. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. NSOM/QD-Based Visualization of GM1 Serving as Platforms for TCR/CD3 Mediated T-Cell Activation

    Directory of Open Access Journals (Sweden)

    Liyun Zhong

    2013-01-01

    Full Text Available Direct molecular imaging of nanoscale relationship between T-cell receptor complexes (TCR/CD3 and gangliosidosis GM1 before and after T-cell activation has not been reported. In this study, we made use of our expertise of near-field scanning optical microscopy(NSOM/immune-labeling quantum dots- (QD-based dual-color imaging system to visualize nanoscale profiles for distribution and organization of TCR/CD3, GM1, as well as their nanospatial relationship and their correlation with PKCθ signaling cascade during T-cell activation. Interestingly, after anti-CD3/anti-CD28 Ab co-stimulation, both TCR/CD3 and GM1 were clustered to form nanodomains; moreover, all of TCR/CD3 nanodomains were colocalized with GM1 nanodomains, indicating that the formation of GM1 nanodomains was greatly correlated with TCR/CD3 mediated signaling. Specially, while T-cells were pretreated with PKCθ signaling inhibitor rottlerin to suppress IL-2 cytokine production, no visible TCR/CD3 nanodomains appeared while a lot of GM1 nanodomains were still observed. However, while T-cells are pretreated with PKCαβ signaling inhibitor GÖ6976 to suppress calcium-dependent manner, all of TCR/CD3 nanodomains were still colocalized with GM1 nanodomains. These findings possibly support the notion that the formation of GM1 nanodomains indeed serves as platforms for the recruitment of TCR/CD3 nanodomains, and TCR/CD3 nanodomains are required for PKCθ signaling cascades and T-cell activation

  6. Differential association of GABABreceptors with their effector ion channels in Purkinje cells.

    Science.gov (United States)

    Luján, Rafael; Aguado, Carolina; Ciruela, Francisco; Cózar, Javier; Kleindienst, David; de la Ossa, Luis; Bettler, Bernhard; Wickman, Kevin; Watanabe, Masahiko; Shigemoto, Ryuichi; Fukazawa, Yugo

    2017-11-25

    Metabotropic GABA B receptors mediate slow inhibitory effects presynaptically and postsynaptically through the modulation of different effector signalling pathways. Here, we analysed the distribution of GABA B receptors using highly sensitive SDS-digested freeze-fracture replica labelling in mouse cerebellar Purkinje cells. Immunoreactivity for GABA B1 was observed on presynaptic and, more abundantly, on postsynaptic compartments, showing both scattered and clustered distribution patterns. Quantitative analysis of immunoparticles revealed a somato-dendritic gradient, with the density of immunoparticles increasing 26-fold from somata to dendritic spines. To understand the spatial relationship of GABA B receptors with two key effector ion channels, the G protein-gated inwardly rectifying K + (GIRK/Kir3) channel and the voltage-dependent Ca 2+ channel, biochemical and immunohistochemical approaches were performed. Co-immunoprecipitation analysis demonstrated that GABA B receptors co-assembled with GIRK and Ca V 2.1 channels in the cerebellum. Using double-labelling immunoelectron microscopic techniques, co-clustering between GABA B1 and GIRK2 was detected in dendritic spines, whereas they were mainly segregated in the dendritic shafts. In contrast, co-clustering of GABA B1 and Ca V 2.1 was detected in dendritic shafts but not spines. Presynaptically, although no significant co-clustering of GABA B1 and GIRK2 or Ca V 2.1 channels was detected, inter-cluster distance for GABA B1 and GIRK2 was significantly smaller in the active zone than in the dendritic shafts, and that for GABA B1 and Ca V 2.1 was significantly smaller in the active zone than in the dendritic shafts and spines. Thus, GABA B receptors are associated with GIRK and Ca V 2.1 channels in different subcellular compartments. These data provide a better framework for understanding the different roles played by GABA B receptors and their effector ion channels in the cerebellar network.

  7. Precipitation processes in Al-4Cu-(Mg, Cd) (wt.%) alloys

    Energy Technology Data Exchange (ETDEWEB)

    Sofyan, B.T.; Polmear, I.J. [Monash Univ., Vic. (Australia). School of Physics and Materials Engineering; Ringer, S.P. [Australian Key Centre for Microscopy and Microanalysis, Univ. of Sydney, NSW (Australia)

    2002-07-01

    The precipitation processes during elevated temperature ageing of Al-4Cu-(Mg, Cd) (wt.%) alloys have been studied using transmission electron microscopy and three dimensional atom probe (3DAP). Enhanced precipitation of {theta}' (Al{sub 2}Cu) was confirmed in Cd-containing alloys. Additions of Cd into the Al-Cu-Mg alloys also stimulated the precipitation of the {sigma} phase (Al{sub 5}Cu{sub 6}Mg{sub 2}). In the ternary Al-Cu-Cd alloy, elemental Cd particles were detected in a uniform dispersion throughout the matrix and were attached to {theta}', while in the Al-Cu-Mg-Cd alloy, co-clustering of Cd-Mg was observed at early stages of ageing. This result suggests that the enhanced precipitation and associated hardening in the quaternary Al-Cu-Mg-Cd alloy is initiated by the Cd-Mg co-clusters, through what is called as cluster-assisted nucleation. The nucleation mechanism in the ternary Al-Cu-Cd alloy is almost certainly the same, although the chemistry of the initiating cluster which assists nucleation is different, which is thought to be Cd clusters. (orig.)

  8. Functional and evolutionary correlates of gene constellations in the Drosophila melanogaster genome that deviate from the stereotypical gene architecture.

    Science.gov (United States)

    Li, Shuwei; Shih, Ching-Hua; Kohn, Michael H

    2010-05-24

    The biological dimensions of genes are manifold. These include genomic properties, (e.g., X/autosomal linkage, recombination) and functional properties (e.g., expression level, tissue specificity). Multiple properties, each generally of subtle influence individually, may affect the evolution of genes or merely be (auto-)correlates. Results of multidimensional analyses may reveal the relative importance of these properties on the evolution of genes, and therefore help evaluate whether these properties should be considered during analyses. While numerous properties are now considered during studies, most work still assumes the stereotypical solitary gene as commonly depicted in textbooks. Here, we investigate the Drosophila melanogaster genome to determine whether deviations from the stereotypical gene architecture correlate with other properties of genes. Deviations from the stereotypical gene architecture were classified as the following gene constellations: Overlapping genes were defined as those that overlap in the 5-prime, exonic, or intronic regions. Chromatin co-clustering genes were defined as genes that co-clustered within 20 kb of transcriptional territories. If this scheme is applied the stereotypical gene emerges as a rare occurrence (7.5%), slightly varied schemes yielded between approximately 1%-50%. Moreover, when following our scheme, paired-overlapping genes and chromatin co-clustering genes accounted for 50.1 and 42.4% of the genes analyzed, respectively. Gene constellation was a correlate of a number of functional and evolutionary properties of genes, but its statistical effect was approximately 1-2 orders of magnitude lower than the effects of recombination, chromosome linkage and protein function. Analysis of datasets on male reproductive proteins showed these were biased in their representation of gene constellations and evolutionary rate Ka/Ks estimates, but these biases did not overwhelm the biologically meaningful observation of high

  9. Functional and evolutionary correlates of gene constellations in the Drosophila melanogaster genome that deviate from the stereotypical gene architecture

    Directory of Open Access Journals (Sweden)

    Kohn Michael H

    2010-05-01

    Full Text Available Abstract Background The biological dimensions of genes are manifold. These include genomic properties, (e.g., X/autosomal linkage, recombination and functional properties (e.g., expression level, tissue specificity. Multiple properties, each generally of subtle influence individually, may affect the evolution of genes or merely be (auto-correlates. Results of multidimensional analyses may reveal the relative importance of these properties on the evolution of genes, and therefore help evaluate whether these properties should be considered during analyses. While numerous properties are now considered during studies, most work still assumes the stereotypical solitary gene as commonly depicted in textbooks. Here, we investigate the Drosophila melanogaster genome to determine whether deviations from the stereotypical gene architecture correlate with other properties of genes. Results Deviations from the stereotypical gene architecture were classified as the following gene constellations: Overlapping genes were defined as those that overlap in the 5-prime, exonic, or intronic regions. Chromatin co-clustering genes were defined as genes that co-clustered within 20 kb of transcriptional territories. If this scheme is applied the stereotypical gene emerges as a rare occurrence (7.5%, slightly varied schemes yielded between ~1%-50%. Moreover, when following our scheme, paired-overlapping genes and chromatin co-clustering genes accounted for 50.1 and 42.4% of the genes analyzed, respectively. Gene constellation was a correlate of a number of functional and evolutionary properties of genes, but its statistical effect was ~1-2 orders of magnitude lower than the effects of recombination, chromosome linkage and protein function. Analysis of datasets on male reproductive proteins showed these were biased in their representation of gene constellations and evolutionary rate Ka/Ks estimates, but these biases did not overwhelm the biologically meaningful

  10. In vitro membrane reconstitution of the T-cell receptor proximal signaling network.

    Science.gov (United States)

    Hui, Enfu; Vale, Ronald D

    2014-02-01

    T-cell receptor (TCR) phosphorylation is controlled by a complex network that includes Lck, a Src family kinase (SFK), the tyrosine phosphatase CD45 and the Lck-inhibitory kinase Csk. How these competing phosphorylation and dephosphorylation reactions are modulated to produce T-cell triggering is not fully understood. Here we reconstituted this signaling network using purified enzymes on liposomes, recapitulating the membrane environment in which they normally interact. We demonstrate that Lck's enzymatic activity can be regulated over an ~10-fold range by controlling its phosphorylation state. By varying kinase and phosphatase concentrations, we constructed phase diagrams that reveal ultrasensitivity in the transition from the quiescent to the phosphorylated state and demonstrate that co-clustering TCR and Lck or detaching Csk from the membrane can trigger TCR phosphorylation. Our results provide insight into the mechanism of TCR signaling as well as other signaling pathways involving SFKs.

  11. New insight into molecular phylogeny and epidemiology of Sporothrix schenckii species complex based on calmodulin-encoding gene analysis of Italian isolates.

    Science.gov (United States)

    Romeo, Orazio; Scordino, Fabio; Criseo, Giuseppe

    2011-09-01

    In this study, we investigated phylogenetic relationships among Italian Sporothrix schenckii isolates, by comparing their partial calmodulin sequences. In this analysis, we used 26 environmental strains of S. schenckii, plus two autochthonous clinical isolates. The results showed that our clinical strains grouped with S. schenckii sensu stricto isolates, whereas all 26 environmental isolates co-clustered with Sporothrix albicans (now regarded as a synonym of Sporothrix pallida), a non-pathogenic species closely related to S. schenckii. Furthermore, the group of environmental strains was found to be quite heterogeneous and further subdivided into two subgroups. The data reported here also showed that molecular methods, for specific identification of S. schenckii, developed before the description of its closely related species should be used with caution because of the possibility of false positive results, which could lead to inappropriate antifungal therapy. This study improves our understanding of the distribution of these new closely related Sporothrix species which also showed significant differences in antifungal susceptibilities.

  12. Future of phylogeny in HIV prevention.

    Science.gov (United States)

    Brenner, Bluma G; Wainberg, Mark A

    2013-07-01

    The success of the HIV Prevention Trials Network 052 trial has led to revisions in HIV-1 treatment guidelines. Antiretroviral therapy may reduce the risk of HIV-1 transmissions at the population level. The design of successful treatment as prevention interventions will be predicated on a comprehensive understanding of the spatial, temporal, and biological dynamics of heterosexual men who have sex with men and intravenous drug user epidemics. Viral phylogenetics can capture the underlying structure of transmission networks based on the genetic interrelatedness of viral sequences and cluster networks that could not be otherwise identified. This article describes the phylogenetic expansion of the Montreal men who have sex with men epidemic over the last decade. High rates of coclustering of primary infections are associated with 1 infection leading to 13 onward transmissions. Phylogeny substantiates the role of primary and recent stage infection in transmission dynamics, underlying the importance of timely diagnosis and immediate antiretroviral therapy initiation to avert transmission cascades.

  13. Continuous Autoregulatory Indices Derived from Multi-Modal Monitoring: Each One Is Not Like the Other.

    Science.gov (United States)

    Zeiler, Frederick A; Donnelly, Joseph; Menon, David K; Smielewski, Peter; Zweifel, Christian; Brady, Ken; Czosnyka, Marek

    2017-11-15

    We assess the relationships between various continuous measures of autoregulatory capacity in a cohort of adults with traumatic brain injury (TBI). We assessed relationships between autoregulatory indices derived from intracranial pressure (ICP: PRx, PAx, RAC), transcranial Doppler (TCD: Mx, Sx, Dx), brain tissue-oxygenation (ORx), and spatially resolved near infrared spectroscopy (NIRS resolved: TOx, THx). Relationships between indices were assessed using Pearson correlation coefficient, Friedman test, principal component analysis (PCA), agglomerative hierarchal clustering (AHC) and k-means cluster analysis (KMCA). All analytic techniques were repeated for a range of temporal resolutions of data, including minute-by-minute averages, moving means of 30 samples, and grand mean for each patient. Thirty-seven patients were studied. The PRx displayed strong association with PAx/RAC across all the analytical techniques: Pearson correlation (r = 0.682/r = 0.677, p indices (Mx, Dx) were correlated and co-clustered on PCA, AHC, and KMCA. The Sx was found to be more closely associated with ICP-derived indices on Pearson correlation, PCA, AHC, and KMCA. The NIRS indices displayed variable correlation with each other and with indices derived from ICP and TCD signals. Of interest, TOx and THx co-cluster with ICP-based indices on PCA and AHC. The ORx failed to display any meaningful correlations with other indices in neither of the analytical method used. Thirty-minute moving average and minute-by-minute data set displayed similar results across all the methods. The RAC, Mx, and Sx were the strongest predictors of outcome at six months. Continuously updating autoregulatory indices are not all correlated with one another. Caution must be advised when utilizing less commonly described autoregulation indices (i.e., ORx) for the clinical assessment of autoregulatory capacity, because they appear to not be related to commonly measured/establish indices, such as PRx

  14. True Molecular Scale Visualization of Variable Clustering Properties of Ryanodine Receptors

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    Isuru Jayasinghe

    2018-01-01

    Full Text Available Summary: Signaling nanodomains rely on spatial organization of proteins to allow controlled intracellular signaling. Examples include calcium release sites of cardiomyocytes where ryanodine receptors (RyRs are clustered with their molecular partners. Localization microscopy has been crucial to visualizing these nanodomains but has been limited by brightness of markers, restricting the resolution and quantification of individual proteins clustered within. Harnessing the remarkable localization precision of DNA-PAINT (<10 nm, we visualized punctate labeling within these nanodomains, confirmed as single RyRs. RyR positions within sub-plasmalemmal nanodomains revealed how they are organized randomly into irregular clustering patterns leaving significant gaps occupied by accessory or regulatory proteins. RyR-inhibiting protein junctophilin-2 appeared highly concentrated adjacent to RyR channels. Analyzing these molecular maps showed significant variations in the co-clustering stoichiometry between junctophilin-2 and RyR, even between nearby nanodomains. This constitutes an additional level of complexity in RyR arrangement and regulation of calcium signaling, intrinsically built into the nanodomains. : Jayasinghe et al. resolve the distribution of single ryanodine receptors (RyRs within intracellular signaling domains in cardiac myocytes with DNA-PAINT, a super-resolution microscopy approach. Individual RyRs are resolved within irregular cluster arrays. Quantitative imaging reveals significant variation in the co-clustering stoichiometry between RyRs and the regulatory protein junctophilin-2. Keywords: nanodomains, DNA-PAINT, single-molecule localization microscopy, ryanodine receptor, super-resolution imaging, junctophilin, heart

  15. Protein Interacting with C Kinase 1 (PICK1) Reduces Reinsertion Rates of Interaction Partners Sorted to Rab11-dependent Slow Recycling Pathway*

    Science.gov (United States)

    Madsen, Kenneth L.; Thorsen, Thor S.; Rahbek-Clemmensen, Troels; Eriksen, Jacob; Gether, Ulrik

    2012-01-01

    The scaffolding protein PICK1 (protein interacting with C kinase 1) contains an N-terminal PSD-95/Discs large/ZO-1 (PDZ) domain and a central lipid-binding Bin/amphiphysin/Rvs (BAR) domain. PICK1 is thought to regulate trafficking of its PDZ binding partners but different and even opposing functions have been suggested. Here, we apply ELISA-based assays and confocal microscopy in HEK293 cells with inducible PICK1 expression to assess in an isolated system the ability of PICK1 to regulate trafficking of natural and engineered PDZ binding partners. The dopamine transporter (DAT), which primarily sorts to degradation upon internalization, did not form perinuclear clusters with PICK1, and PICK1 did not affect DAT internalization/recycling. However, transfer of the PICK1-binding DAT C terminus to the β2-adrenergic receptor, which sorts to recycling upon internalization, led to formation of PICK1 co-clusters in Rab11-positive compartments. Furthermore, PICK1 inhibited Rab11-mediated recycling of the receptor in a BAR and PDZ domain-dependent manner. In contrast, transfer of the DAT C terminus to the δ-opioid receptor, which sorts to degradation, did not result in PICK1 co-clusters or any change in internalization/recycling. Further support for a role of PICK1 determined by its PDZ cargo was obtained for the PICK1 interaction partner prolactin-releasing peptide receptor (GPR10). GPR10 co-localized with Rab11 and clustered with PICK1 upon constitutive internalization but co-localized with the late endosomal marker Rab7 and did not cluster with PICK1 upon agonist-induced internalization. Our data suggest a selective role of PICK1 in clustering and reducing the recycling rates of PDZ domain binding partners sorted to the Rab11-dependent recycling pathway. PMID:22303009

  16. A semi-parametric Bayesian model for unsupervised differential co-expression analysis

    Directory of Open Access Journals (Sweden)

    Medvedovic Mario

    2010-05-01

    Full Text Available Abstract Background Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined sets of biological samples, such analysis aims at identifying genes that are co-expressed in one, but not in the other set of samples. Results We developed a novel probabilistic framework for jointly uncovering contexts (i.e. groups of samples with specific co-expression patterns, and groups of genes with different co-expression patterns across such contexts. In contrast to current clustering and bi-clustering procedures, the implicit similarity measure in this model used for grouping biological samples is based on the clustering structure of genes within each sample and not on traditional measures of gene expression level similarities. Within this framework, biological samples with widely discordant expression patterns can be placed in the same context as long as the co-clustering structure of genes is concordant within these samples. To the best of our knowledge, this is the first method to date for unsupervised differential co-expression analysis in this generality. When applied to the problem of identifying molecular subtypes of breast cancer, our method identified reproducible patterns of differential co-expression across several independent expression datasets. Sample groupings induced by these patterns were highly informative of the disease outcome. Expression patterns of differentially co-expressed genes provided new insights into the complex nature of the ERα regulatory network. Conclusions We demonstrated that the use of the co-clustering structure as the similarity measure in the unsupervised analysis of sample gene expression profiles provides valuable information about expression regulatory networks.

  17. Dopamine D1 and adenosine A1 receptors form functionally interacting heteromeric complexes

    Science.gov (United States)

    Ginés, Silvia; Hillion, Joëlle; Torvinen, Maria; Le Crom, Stèphane; Casadó, Vicent; Canela, Enric I.; Rondin, Sofia; Lew, Jow Y.; Watson, Stanley; Zoli, Michele; Agnati, Luigi Francesco; Vernier, Philippe; Lluis, Carmen; Ferré, Sergi; Fuxe, Kjell; Franco, Rafael

    2000-01-01

    The possible molecular basis for the previously described antagonistic interactions between adenosine A1 receptors (A1R) and dopamine D1 receptors (D1R) in the brain have been studied in mouse fibroblast Ltk− cells cotransfected with human A1R and D1R cDNAs or with human A1R and dopamine D2 receptor (long-form) (D2R) cDNAs and in cortical neurons in culture. A1R and D1R, but not A1R and D2R, were found to coimmunoprecipitate in cotransfected fibroblasts. This selective A1R/D1R heteromerization disappeared after pretreatment with the D1R agonist, but not after combined pretreatment with D1R and A1R agonists. A high degree of A1R and D1R colocalization, demonstrated in double immunofluorescence experiments with confocal laser microscopy, was found in both cotransfected fibroblast cells and cortical neurons in culture. On the other hand, a low degree of A1R and D2R colocalization was observed in cotransfected fibroblasts. Pretreatment with the A1R agonist caused coclustering (coaggregation) of A1R and D1R, which was blocked by combined pretreatment with the D1R and A1R agonists in both fibroblast cells and in cortical neurons in culture. Combined pretreatment with D1R and A1R agonists, but not with either one alone, substantially reduced the D1R agonist-induced accumulation of cAMP. The A1R/D1R heteromerization may be one molecular basis for the demonstrated antagonistic modulation of A1R of D1R receptor signaling in the brain. The persistence of A1R/D1R heteromerization seems to be essential for the blockade of A1R agonist-induced A1R/D1R coclustering and for the desensitization of the D1R agonist-induced cAMP accumulation seen on combined pretreatment with D1R and A1R agonists, which indicates a potential role of A1R/D1R heteromers also in desensitization mechanisms and receptor trafficking. PMID:10890919

  18. Analysis of leukocyte binding to depletion filters: role of passive binding, interaction with platelets, and plasma components.

    Science.gov (United States)

    Henschler, R; Rüster, B; Steimle, A; Hansmann, H L; Walker, W; Montag, T; Seifried, E

    2005-08-01

    Since limited knowledge exists on the mechanisms which regulate cell binding to leukocyte removal filter surfaces, we investigated the binding patterns of leukocytes to individual layers of leukocyte depletion filters. After passage of 1 unit of whole blood, blotting of isolated filter layers on glass slides or elution of cells from filter layers revealed that most leukocytes were located within the first 10 of a total of 28 filter layers, peaking at layers 6 to 8, with granulocytes binding on average to earlier filter layers than lymphocytes. Leukocytes preincubated with inhibitors of actin activation showed unchanged distribution between filter layers, suggesting that cytoskeletal activation does not significantly contribute to their binding. When leukocytes were directly incubated with single filter layers, binding of up to 30% of input cells was recorded in the absence of Ca(2+). Immunohistological analyses showed colocalization of platelets and leukocytes, with co-clustering of platelets and leukocytes. Monocytes and to some degree lymphocytes but not granulocytes competed with platelets for filter binding. Precoating of filter layers with individual plasma components showed that hyaluronic acid, plasma type fibronectin, and fibrinogen all increased the binding of leukocytes compared with albumin coating. In conclusion, leukocytes can bind passively to filters in a process which does not require Ca(2+), which is independent of cytoskeletal activation and which may depend on individual plasma components. These results are of importance when new selective cell enrichment or depletion strategies through specific filters are envisaged.

  19. Application of Text Analytics to Extract and Analyze Material–Application Pairs from a Large Scientific Corpus

    Directory of Open Access Journals (Sweden)

    Nikhil Kalathil

    2018-01-01

    Full Text Available When assessing the importance of materials (or other components to a given set of applications, machine analysis of a very large corpus of scientific abstracts can provide an analyst a base of insights to develop further. The use of text analytics reduces the time required to conduct an evaluation, while allowing analysts to experiment with a multitude of different hypotheses. Because the scope and quantity of metadata analyzed can, and should, be large, any divergence from what a human analyst determines and what the text analysis shows provides a prompt for the human analyst to reassess any preliminary findings. In this work, we have successfully extracted material–application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used. Approximately 438,000 titles and abstracts of scientific papers published from 1992 to 2011 were used to examine 16 materials. This analysis used coclustering text analysis to associate individual materials with specific clean energy applications, evaluate the importance of materials to specific applications, and assess their importance to clean energy overall. Our analysis reproduced the judgments of experts in assigning material importance to applications. The validated methods were then used to map the replacement of one material with another material in a specific application (batteries.

  20. A mathematical programming approach for sequential clustering of dynamic networks

    Science.gov (United States)

    Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

    2016-02-01

    A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

  1. Crystal Structure of the Frizzled-Like Cysteine-Rich Domain of the Receptor Tyrosine Kinase MuSK

    Energy Technology Data Exchange (ETDEWEB)

    Stiegler, A.; Burden, S; Hubbard, S

    2009-01-01

    Muscle-specific kinase (MuSK) is an essential receptor tyrosine kinase for the establishment and maintenance of the neuromuscular junction (NMJ). Activation of MuSK by agrin, a neuronally derived heparan-sulfate proteoglycan, and LRP4 (low-density lipoprotein receptor-related protein-4), the agrin receptor, leads to clustering of acetylcholine receptors on the postsynaptic side of the NMJ. The ectodomain of MuSK comprises three immunoglobulin-like domains and a cysteine-rich domain (Fz-CRD) related to those in Frizzled proteins, the receptors for Wnts. Here, we report the crystal structure of the MuSK Fz-CRD at 2.1 {angstrom} resolution. The structure reveals a five-disulfide-bridged domain similar to CRDs of Frizzled proteins but with a divergent C-terminal region. An asymmetric dimer present in the crystal structure implicates surface hydrophobic residues that may function in homotypic or heterotypic interactions to mediate co-clustering of MuSK, rapsyn, and acetylcholine receptors at the NMJ.

  2. Infertility in the hyperplasic ovary of freshwater planarians: the role of programmed cell death.

    Science.gov (United States)

    Harrath, Abdel Halim; Semlali, Abdelhabib; Mansour, Lamjed; Ahmed, Mukhtar; Sirotkin, Alexander V; Al Omar, Suliman Y; Arfah, Maha; Al Anazi, Mohamed S; Alhazza, Ibrahim M; Nyengaard, Jens R; Alwasel, Saleh

    2014-11-01

    Ex-fissiparous planarians produce infertile cocoons or, in very rare cases, cocoons with very low fertility. Here, we describe the features of programmed cell death (PCD) occurring in the hyperplasic ovary of the ex-fissiparous freshwater planarian Dugesia arabica that may explain this infertility. Based on TEM results, we demonstrate a novel extensive co-clustering of cytoplasmic organelles, such as lysosomes and microtubules, and their fusion with autophagosomes during the early stage of oocyte cell death occurring through an autophagic pattern. During a later stage of cell death, the generation of apoptotic vesicles in the cytoplasm can be observed. The immunohistochemical labeling supports the ultrastructural results because it has been shown that the proapoptotic protein bax was more highly expressed in the hyperplasic ovary than in the normal one, whereas the anti-apoptotic protein bcl2 was slightly more highly expressed in the normal ovary compared to the hyperplasic one. TUNEL analysis of the hyperplasic ovary confirmed that the nuclei of the majority of differentiating oocytes were TUNEL-positive, whereas the nuclei of oogonia and young oocytes were TUNEL-negative; in the normal ovary, oocytes are TUNEL-negative. Considering all of these data, we suggest that the cell death mechanism of differentiating oocytes in the hyperplasic ovary of freshwater planarians is one of the most important factors that cause ex-fissiparous planarian infertility. We propose that autophagy precedes apoptosis during oogenesis, whereas apoptotic features can be observed later.

  3. Mechanisms controlling the artificial aging of Al-Mg-Si Alloys

    International Nuclear Information System (INIS)

    Pogatscher, S.; Antrekowitsch, H.; Leitner, H.; Ebner, T.; Uggowitzer, P.J.

    2011-01-01

    Highlights: → Artificial aging of Al-Mg-Si alloys in the range of 150 and 250 deg. C. → We study precipitation kinetics caused by various thermal histories. → Natural pre-aging affects kinetics at low artificial aging temperatures. → Natural pre-aging promotes kinetics at high artificial aging temperatures. → A vacancy-prison mechanism explains the effect of natural pre-aging. - Abstract: In this study the artificial aging behavior of the Al-Mg-Si alloy AA 6061 was investigated in the temperature range 150-250 deg. C using atom probe tomography, hardness and resistivity measurements for various thermal histories. It was found that the precipitation kinetics and age-hardening response of artificial aging at temperatures below 210 deg. C are lowered by prior natural aging but enhanced above this temperature. An analysis of hardness data was used to evaluate the temperature dependence of precipitation kinetics and dissolution processes. Supported by theoretical considerations, it is assumed that artificial aging of Al-Mg-Si alloys is controlled via the concentration of mobile vacancies. The 'vacancy-prison mechanism' proposed determines the mobile vacancy concentration in the case of natural pre-aging by temperature-dependent dissolution of co-clusters and solute-vacancy interactions.

  4. Thrombospondin-1 modulates vascular endothelial growth factor activity at the receptor level.

    Science.gov (United States)

    Zhang, Xuefeng; Kazerounian, Shideh; Duquette, Mark; Perruzzi, Carole; Nagy, Janice A; Dvorak, Harold F; Parangi, Sareh; Lawler, Jack

    2009-10-01

    Vascular endothelial growth factor (VEGF) is a well-established stimulator of vascular permeability and angiogenesis, whereas thrombospondin-1 (TSP-1) is a potent angiogenic inhibitor. In this study, we have found that the TSP-1 receptors CD36 and beta1 integrin associate with the VEGF receptor 2 (VEGFR2). The coclustering of receptors that regulate angiogenesis may provide the endothelial cell with a platform for integration of positive and negative signals in the plane of the membrane. Thus, this complex may represent a molecular switch that regulates angiogenesis and determines endothelial cell behavior. In this context, physiological levels of TSP-1 appear to support VEGFR2 function on both the cellular and tissue level, because phosphorylation of VEGFR2 and vascular permeability in response to VEGF are decreased in TSP-1-null mice and isolated endothelial cells. A therapeutic agent based on the antiangiogenic domain of TSP-1, designated 3TSR (for three TSP-1 type 1 repeats), has significant antiangiogenic and antitumor efficacy. Systemic treatment of wild-type mice with 3TSR significantly decreased VEGF-induced permeability. Consistent with this result, VEGF-stimulated phosphorylation of VEGFR2 was also significantly decreased in lung extracts from 3TSR-treated mice. Moreover, 3TSR significantly decreased VEGF-stimulated VEGFR2 phosphorylation in human dermal microvascular endothelial cells in culture. Taken together, the results indicate that TSP-1 and 3TSR modulate the function of VEGFR2.

  5. Symptom-Based Clustering in Chronic Rhinosinusitis Relates to History of Aspirin Sensitivity and Postsurgical Outcomes.

    Science.gov (United States)

    Divekar, Rohit; Patel, Neil; Jin, Jay; Hagan, John; Rank, Matthew; Lal, Devyani; Kita, Hirohito; O'Brien, Erin

    2015-01-01

    Symptoms burden in chronic rhinosinusitis (CRS) may be assessed by interviews or by means of validated tools such as the 22-item SinoNasal Outcome Test (SNOT-22). However, when only the total SNOT-22 scores are used, the pattern of symptom distribution and heterogeneity in patient symptoms is lost. To use a standardized symptom assessment tool (SNOT-22) on preoperative symptoms to understand symptom heterogeneity in CRS and to aid in characterization of distinguishing clinical features between subgroups. This was a retrospective review of 97 surgical patients with CRS. Symptom-based clusters were derived on the basis of presurgical SNOT-22 scores using unsupervised analysis and network graphs. Comparison between clusters was performed for clinical and demographic parameters, postsurgical symptom scores, and presence or absence of a history of aspirin sensitivity. Unsupervised analysis reveals coclustering of specific symptoms in the SNOT-22 tool. Using symptom-based clustering, patients with CRS were stratified into severe overall (mean total score, 90.8), severe sinonasal (score, 62), moderate sinonasal (score, 40), moderate nonsinonasal (score, 37) and mild sinonasal (score, 16) clusters. The last 2 clusters were associated with lack of history of aspirin sensitivity. The first cluster had a rapid relapse in symptoms postoperatively, and the last cluster demonstrated minimal symptomatic improvement after surgery. Symptom-based clusters in CRS reveal a distinct grouping of symptom burden that may relate to aspirin sensitivity and treatment outcomes. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  6. Postsynaptic GABABRs Inhibit L-Type Calcium Channels and Abolish Long-Term Potentiation in Hippocampal Somatostatin Interneurons

    Directory of Open Access Journals (Sweden)

    Sam A. Booker

    2018-01-01

    Full Text Available Summary: Inhibition provided by local GABAergic interneurons (INs activates ionotropic GABAA and metabotropic GABAB receptors (GABABRs. Despite GABABRs representing a major source of inhibition, little is known of their function in distinct IN subtypes. Here, we show that, while the archetypal dendritic-inhibitory somatostatin-expressing INs (SOM-INs possess high levels of GABABR on their somato-dendritic surface, they fail to produce significant postsynaptic inhibitory currents. Instead, GABABRs selectively inhibit dendritic CaV1.2 (L-type Ca2+ channels on SOM-IN dendrites, leading to reduced calcium influx and loss of long-term potentiation at excitatory input synapses onto these INs. These data provide a mechanism by which GABABRs can contribute to disinhibition and control the efficacy of extrinsic inputs to hippocampal networks. : Booker et al. show that GABAB receptors are highly expressed on somatostatin interneuron dendrites. Rather than activating Kir3 channels, they preferentially co-cluster with, and negatively couple to, L-type calcium channels inhibiting long-term potentiation at excitatory inputs. Keywords: GABAergic interneurons, feedback inhibition, GABAB receptors, dendrites, Cav1.2 channels, synaptic plasticity, hippocampus, electron microscopy, whole-cell recording, multi-photon imaging

  7. A fusion cytokine coupling GMCSF to IL9 induces heterologous receptor clustering and STAT1 hyperactivation through JAK2 promiscuity.

    Directory of Open Access Journals (Sweden)

    Pingxin Li

    Full Text Available Cytokine receptors are randomly distributed on the cell surface membrane and are activated upon binding of their extracellular ligands to mediate downstream cellular activities. We hypothesized that pharmaceutical clustering of ligand-bound, activated receptors may lead to heretofore unrealized gain-of-function with therapeutically desirable properties. We here describe an engineered bifunctional cytokine borne of the fusion of Granulocyte Macrophage Colony Stimulating Factor (GMCSF and Interleukin-9 (IL9 (hereafter GIFT9 fusokine and demonstrate that it chaperones co-clustering of the functionally unrelated GMCSF receptor (GMCSFR and IL9 receptor (IL9R on cell surface of target cells. We demonstrate that GIFT9 treatment of MC/9 cells leads to transhyperphosphorylation of IL9R-associated STAT1 by GMCSFR-associated JAK2. We also show that IL9R-associated JAK1 and JAK3 augment phosphorylation of GMCSFR-linked STAT5. The functional relevance of these synergistic JAK/STAT transphosphorylation events translates to an increased mitogenic response by GMCSFR/IL9R-expressing primary marrow mast cells. The notion of inducing heterologous receptor clustering by engineered fusokines such as GIFT9 opens the door to a novel type of biopharmaceutical platform where designer fusokines modulate cell physiology through clustering of targeted receptor complexes.

  8. Scalable non-negative matrix tri-factorization.

    Science.gov (United States)

    Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

    2017-01-01

    Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.

  9. Prolonged mitotic arrest induced by Wee1 inhibition sensitizes breast cancer cells to paclitaxel

    Science.gov (United States)

    Lewis, Cody W.; Jin, Zhigang; Macdonald, Dawn; Wei, Wenya; Qian, Xu Jing; Choi, Won Shik; He, Ruicen; Sun, Xuejun; Chan, Gordon

    2017-01-01

    Wee1 kinase is a crucial negative regulator of Cdk1/cyclin B1 activity and is required for normal entry into and exit from mitosis. Wee1 activity can be chemically inhibited by the small molecule MK-1775, which is currently being tested in phase I/II clinical trials in combination with other anti-cancer drugs. MK-1775 promotes cancer cells to bypass the cell-cycle checkpoints and prematurely enter mitosis. In our study, we show premature mitotic cells that arise from MK-1775 treatment exhibited centromere fragmentation, a morphological feature of mitotic catastrophe that is characterized by centromeres and kinetochore proteins that co-cluster away from the condensed chromosomes. In addition to stimulating early mitotic entry, MK-1775 treatment also delayed mitotic exit. Specifically, cells treated with MK-1775 following release from G1/S or prometaphase arrested in mitosis. MK-1775 induced arrest occurred at metaphase and thus, cells required 12 times longer to transition into anaphase compared to controls. Consistent with an arrest in mitosis, MK-1775 treated prometaphase cells maintained high cyclin B1 and low phospho-tyrosine 15 Cdk1. Importantly, MK-1775 induced mitotic arrest resulted in cell death regardless the of cell-cycle phase prior to treatment suggesting that Wee1 inhibitors are also anti-mitotic agents. We found that paclitaxel enhances MK-1775 mediated cell killing. HeLa and different breast cancer cell lines (T-47D, MCF7, MDA-MB-468 and MDA-MB-231) treated with different concentrations of MK-1775 and low dose paclitaxel exhibited reduced cell survival compared to mono-treatments. Our data highlight a new potential strategy for enhancing MK-1775 mediated cell killing in breast cancer cells. PMID:29088738

  10. Viruses affecting lentil (Lens culinaris Medik. in Greece; incidence and genetic variability of Bean leafroll virus and Pea enation mosaic virus

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    Elisavet K. CHATZIVASSILIOU

    2016-07-01

    Full Text Available In Greece, lentil (Lens culinaris Medik. crops are mainly established with non-certified seeds of local landraces, implying high risks for seed transmitted diseases. During April and May of the 2007–2012 growing seasons, surveys were conducted in eight regions of Greece (Attiki, Evros, Fthiotida, Korinthos, Kozani, Larissa, Lefkada and Viotia to monitor virus incidence in lentil fields. A total of 1216 lentil samples, from plants exhibiting symptoms suggestive of virus infection, were analyzed from 2007 to 2009, using tissue-blot immunoassays (TBIA. Pea seed-borne mosaic virus (PSbMV overall incidence was 4.9%, followed by Alfalfa mosaic virus (AMV (2.4% and Bean yellow mosaic virus (BYMV (1.0%. When 274 of the samples were tested for the presence of luteoviruses, 38.8% were infected with Bean leafroll virus (BLRV. Since BLRV was not identified in the majority of the samples collected from 2007 to 2009, representative symptomatic plants (360 samples were collected in further surveys performed from 2010 to 2012 and tested by ELISA. Two viruses prevailed in those samples: BLRV (36.1% was associated with stunting, yellowing, and reddening symptoms and Pea enation mosaic virus-1 (PEMV-1 (35.0% was associated with mosaic and mottling symptoms. PSbMV (2.2%, AMV (2.2%, BYMV (3.9% and CMV (2.8% were also detected. When the molecular variability was analyzed for representative isolates, collected from the main Greek lentil production areas, five BLRV isolates showed 95% identity for the coat protein (CP gene and 99% for the 3’ end region. Three Greek PEMV isolates co-clustered with an isolate from Germany when their CP sequence was compared with isolates with no mutation in the aphid transmission gene. Overall, limited genetic variability was detected among Greek isolates of BLRV and PEMV.

  11. Subgenotype A1 of HBV--tracing human migrations in and out of Africa.

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    Kramvis, Anna; Paraskevis, Dimitrios

    2013-01-01

    HBV subgenotype A1 is the dominant genotype A strain in Africa, with molecular characteristics differentiating it from A2, which prevails elsewhere. Outside Africa, A1 is confined to areas with migration history from Africa, including India and Latin America. The aim of this study was to reconstruct A1 phylogeny on a spatial scale in order to determine whether A1 can be used to track human migrations. A phylogenetic comparison of A1 was established using neighbour-joining analysis of complete genomes, and the Bayesian method, implemented in BEAST, was performed on the S region of isolates from 22 countries. Migration events were estimated by ancestral state reconstruction using the criterion of parsimony. From the tree reconstruction, nucleotide divergence calculations and migration analysis, it was evident that Africa was the source of dispersal of A1 globally, and its dispersal to Asia and Latin America occurred at a similar time period. Strains from South Africa were the most divergent, clustering in both the African and Asian/American clades and a South African subclade was the origin of A1. The effect of the 9th to 19th century trade and slave routes on the dispersal of A1 was evident and certain unexpected findings, such as the co-clustering of Somalian and Latin American strains, and the dispersal of A1 from India to Haiti, correlated with historical evidence. Phylogeographic analyses of subgenotype A1 can be used to trace human migrations in and out of Africa and the plausible sites of origin and migration routes are presented.

  12. The influence of temperament and character profiles on specialty choice and well-being in medical residents

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    Martin Sievert

    2016-09-01

    Full Text Available Background Multiple factors influence the decision to enter a career in medicine and choose a specialty. Previous studies have looked at personality differences in medicine but often were unable to describe the heterogeneity that exists within each specialty. Our study used a person-centered approach to characterize the complex relations between the personality profiles of resident physicians and their choice of specialty. Methods 169 resident physicians at a large Midwestern US training hospital completed the Temperament and Character Inventory (TCI and the Satisfaction with Life Scale (SWLS. Clusters of personality profiles were identified without regard to medical specialty, and then the personality clusters were tested for association with their choice of specialty by co-clustering analysis. Life satisfaction was tested for association with personality traits and medical specialty by linear regression and analysis of variance. Results We identified five clusters of people with distinct personality profiles, and found that these were associated with particular medical specialties Physicians with an “investigative” personality profile often chose pathology or internal medicine, those with a “commanding” personality often chose general surgery, “rescuers” often chose emergency medicine, the “dependable” often chose pediatrics, and the “compassionate” often chose psychiatry. Life satisfaction scores were not enhanced by personality-specialty congruence, but were related strongly to self-directedness regardless of specialty. Conclusions The personality profiles of physicians were strongly associated with their medical specialty choices. Nevertheless, the relationships were complex: physicians with each personality profile went into a variety of medical specialties, and physicians in each medical specialty had variable personality profiles. The plasticity and resilience of physicians were more important for their life

  13. The influence of temperament and character profiles on specialty choice and well-being in medical residents.

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    Sievert, Martin; Zwir, Igor; Cloninger, Kevin M; Lester, Nigel; Rozsa, Sandor; Cloninger, C Robert

    2016-01-01

    Multiple factors influence the decision to enter a career in medicine and choose a specialty. Previous studies have looked at personality differences in medicine but often were unable to describe the heterogeneity that exists within each specialty. Our study used a person-centered approach to characterize the complex relations between the personality profiles of resident physicians and their choice of specialty. 169 resident physicians at a large Midwestern US training hospital completed the Temperament and Character Inventory (TCI) and the Satisfaction with Life Scale (SWLS). Clusters of personality profiles were identified without regard to medical specialty, and then the personality clusters were tested for association with their choice of specialty by co-clustering analysis. Life satisfaction was tested for association with personality traits and medical specialty by linear regression and analysis of variance. We identified five clusters of people with distinct personality profiles, and found that these were associated with particular medical specialties Physicians with an "investigative" personality profile often chose pathology or internal medicine, those with a "commanding" personality often chose general surgery, "rescuers" often chose emergency medicine, the "dependable" often chose pediatrics, and the "compassionate" often chose psychiatry. Life satisfaction scores were not enhanced by personality-specialty congruence, but were related strongly to self-directedness regardless of specialty. The personality profiles of physicians were strongly associated with their medical specialty choices. Nevertheless, the relationships were complex: physicians with each personality profile went into a variety of medical specialties, and physicians in each medical specialty had variable personality profiles. The plasticity and resilience of physicians were more important for their life satisfaction than was matching personality to the prototype of a particular specialty.

  14. The population genetics of Pseudomonas aeruginosa isolates from different patient populations exhibits high-level host specificity.

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    Rosa van Mansfeld

    Full Text Available OBJECTIVE: To determine whether highly prevalent P. aeruginosa sequence types (ST in Dutch cystic fibrosis (CF patients are specifically linked to CF patients we investigated the population structure of P. aeruginosa from different clinical backgrounds. We first selected the optimal genotyping method by comparing pulsed-field gel electrophoresis (PFGE, multilocus sequence typing (MLST and multilocus variable number tandem-repeat analysis (MLVA. METHODS: Selected P. aeruginosa isolates (n = 60 were genotyped with PFGE, MLST and MLVA to determine the diversity index (DI and congruence (adjusted Rand and Wallace coefficients. Subsequently, isolates from patients admitted to two different ICUs (n = 205, from CF patients (n = 100 and from non-ICU, non-CF patients (n = 58, of which 19 were community acquired were genotyped with MLVA to determine distribution of genotypes and genetic diversity. RESULTS: Congruence between the typing methods was >79% and DIs were similar and all >0.963. Based on costs, ease, speed and possibilities to compare results between labs an adapted MLVA scheme called MLVA9-Utrecht was selected as the preferred typing method. In 363 clinical isolates 252 different MLVA types (MTs were identified, indicating a highly diverse population (DI  = 0.995; CI  = 0.993-0.997. DI levels were similarly high in the diverse clinical sources (all >0.981 and only eight genotypes were shared. MTs were highly specific (>80% for the different patient populations, even for similar patient groups (ICU patients in two distinct geographic regions, with only three of 142 ICU genotypes detected in both ICUs. The two major CF clones were unique to CF patients. CONCLUSION: The population structure of P. aeruginosa isolates is highly diverse and population specific without evidence for a core lineage in which major CF, hospital or community clones co-cluster. The two genotypes highly prevalent among Dutch CF patients appeared unique to CF patients

  15. Bi-Force: large-scale bicluster editing and its application to gene expression data biclustering.

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    Sun, Peng; Speicher, Nora K; Röttger, Richard; Guo, Jiong; Baumbach, Jan

    2014-05-01

    The explosion of the biological data has dramatically reformed today's biological research. The need to integrate and analyze high-dimensional biological data on a large scale is driving the development of novel bioinformatics approaches. Biclustering, also known as 'simultaneous clustering' or 'co-clustering', has been successfully utilized to discover local patterns in gene expression data and similar biomedical data types. Here, we contribute a new heuristic: 'Bi-Force'. It is based on the weighted bicluster editing model, to perform biclustering on arbitrary sets of biological entities, given any kind of pairwise similarities. We first evaluated the power of Bi-Force to solve dedicated bicluster editing problems by comparing Bi-Force with two existing algorithms in the BiCluE software package. We then followed a biclustering evaluation protocol in a recent review paper from Eren et al. (2013) (A comparative analysis of biclustering algorithms for gene expressiondata. Brief. Bioinform., 14:279-292.) and compared Bi-Force against eight existing tools: FABIA, QUBIC, Cheng and Church, Plaid, BiMax, Spectral, xMOTIFs and ISA. To this end, a suite of synthetic datasets as well as nine large gene expression datasets from Gene Expression Omnibus were analyzed. All resulting biclusters were subsequently investigated by Gene Ontology enrichment analysis to evaluate their biological relevance. The distinct theoretical foundation of Bi-Force (bicluster editing) is more powerful than strict biclustering. We thus outperformed existing tools with Bi-Force at least when following the evaluation protocols from Eren et al. Bi-Force is implemented in Java and integrated into the open source software package of BiCluE. The software as well as all used datasets are publicly available at http://biclue.mpi-inf.mpg.de. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. The cellular robustness by genetic redundancy in budding yeast.

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    Jingjing Li

    2010-11-01

    Full Text Available The frequent dispensability of duplicated genes in budding yeast is heralded as a hallmark of genetic robustness contributed by genetic redundancy. However, theoretical predictions suggest such backup by redundancy is evolutionarily unstable, and the extent of genetic robustness contributed from redundancy remains controversial. It is anticipated that, to achieve mutual buffering, the duplicated paralogs must at least share some functional overlap. However, counter-intuitively, several recent studies reported little functional redundancy between these buffering duplicates. The large yeast genetic interactions released recently allowed us to address these issues on a genome-wide scale. We herein characterized the synthetic genetic interactions for ∼500 pairs of yeast duplicated genes originated from either whole-genome duplication (WGD or small-scale duplication (SSD events. We established that functional redundancy between duplicates is a pre-requisite and thus is highly predictive of their backup capacity. This observation was particularly pronounced with the use of a newly introduced metric in scoring functional overlap between paralogs on the basis of gene ontology annotations. Even though mutual buffering was observed to be prevalent among duplicated genes, we showed that the observed backup capacity is largely an evolutionarily transient state. The loss of backup capacity generally follows a neutral mode, with the buffering strength decreasing in proportion to divergence time, and the vast majority of the paralogs have already lost their backup capacity. These observations validated previous theoretic predictions about instability of genetic redundancy. However, departing from the general neutral mode, intriguingly, our analysis revealed the presence of natural selection in stabilizing functional overlap between SSD pairs. These selected pairs, both WGD and SSD, tend to have decelerated functional evolution, have higher propensities of co-clustering

  17. Coral: an integrated suite of visualizations for comparing clusterings

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    Filippova Darya

    2012-10-01

    Full Text Available Abstract Background Clustering has become a standard analysis for many types of biological data (e.g interaction networks, gene expression, metagenomic abundance. In practice, it is possible to obtain a large number of contradictory clusterings by varying which clustering algorithm is used, which data attributes are considered, how algorithmic parameters are set, and which near-optimal clusterings are chosen. It is a difficult task to sift though such a large collection of varied clusterings to determine which clustering features are affected by parameter settings or are artifacts of particular algorithms and which represent meaningful patterns. Knowing which items are often clustered together helps to improve our understanding of the underlying data and to increase our confidence about generated modules. Results We present Coral, an application for interactive exploration of large ensembles of clusterings. Coral makes all-to-all clustering comparison easy, supports exploration of individual clusterings, allows tracking modules across clusterings, and supports identification of core and peripheral items in modules. We discuss how each visual component in Coral tackles a specific question related to clustering comparison and provide examples of their use. We also show how Coral could be used to visually and quantitatively compare clusterings with a ground truth clustering. Conclusion As a case study, we compare clusterings of a recently published protein interaction network of Arabidopsis thaliana. We use several popular algorithms to generate the network’s clusterings. We find that the clusterings vary significantly and that few proteins are consistently co-clustered in all clusterings. This is evidence that several clusterings should typically be considered when evaluating modules of genes, proteins, or sequences, and Coral can be used to perform a comprehensive analysis of these clustering ensembles.

  18. Isolating stem cells in the inter-follicular epidermis employing synchrotron radiation-based Fourier-transform infrared microspectroscopy and focal plane array imaging.

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    Patel, Imran I; Harrison, Wesley J; Kerns, Jemma G; Filik, Jacob; Wehbe, Katia; Carmichael, Paul L; Scott, Andrew D; Philpott, Mike P; Frogley, Mark D; Cinque, Gianfelice; Martin, Francis L

    2012-10-01

    Normal function and physiology of the epidermis is maintained by the regenerative capacity of this tissue via adult stem cells (SCs). However, definitive identifying markers for SCs remain elusive. Infrared (IR) spectroscopy exploits the ability of cellular biomolecules to absorb in the mid-IR region (λ = 2.5-25 μm), detecting vibrational transitions of chemical bonds. In this study, we exploited the cell's inherent biochemical composition to discriminate SCs of the inter-follicular skin epidermis based on IR-derived markers. Paraffin-embedded samples of human scalp skin (n = 4) were obtained, and 10-μm thick sections were mounted for IR spectroscopy. Samples were interrogated in transmission mode using synchrotron radiation-based Fourier-transform IR (FTIR) microspectroscopy (15 × 15 μm) and also imaged employing globar-source FTIR focal plane array (FPA) imaging (5.4 × 5.4 μm). Dependent on the location of derived spectra, wavenumber-absorbance/intensity relationships were examined using unsupervised principal component analysis. This approach showed clear separation and spectral differences dependent on cell type. Spectral biomarkers concurrently associated with segregation of SCs, transit-amplifying cells and terminally-differentiated cells of epidermis were primarily PO(2)(-) vibrational modes (1,225 and 1,080 cm(-1)), related to DNA conformational alterations. FPA imaging coupled with hierarchical cluster analysis also indicated the presence of specific basal layer cells potentially originating from the follicular bulge, suggested by co-clustering of spectra. This study highlights PO (2) (-) vibrational modes as potential putative SC markers.

  19. Interaction patterns of trauma providers are associated with length of stay.

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    Chen, You; Patel, Mayur B; McNaughton, Candace D; Malin, Bradley A

    2018-02-22

    Trauma-related hospitalizations drive a high percentage of health care expenditure and inpatient resource consumption, which is directly related to length of stay (LOS). Robust and reliable interactions among health care employees can reduce LOS. However, there is little known about whether certain patterns of interactions exist and how they relate to LOS and its variability. The objective of this study is to learn interaction patterns and quantify the relationship to LOS within a mature trauma system and long-standing electronic medical record (EMR). We adapted a spectral co-clustering methodology to infer the interaction patterns of health care employees based on the EMR of 5588 hospitalized adult trauma survivors. The relationship between interaction patterns and LOS was assessed via a negative binomial regression model. We further assessed the influence of potential confounders by age, number of health care encounters to date, number of access action types care providers committed to patient EMRs, month of admission, phenome-wide association study codes, procedure codes, and insurance status. Three types of interaction patterns were discovered. The first pattern exhibited the most collaboration between employees and was associated with the shortest LOS. Compared to this pattern, LOS for the second and third patterns was 0.61 days (P = 0.014) and 0.43 days (P = 0.037) longer, respectively. Although the 3 interaction patterns dealt with different numbers of patients in each admission month, our results suggest that care was provided for similar patients. The results of this study indicate there is an association between LOS and the extent to which health care employees interact in the care of an injured patient. The findings further suggest that there is merit in ascertaining the content of these interactions and the factors that induce these differences in interaction patterns within a trauma system.

  20. Kv2 Ion Channels Determine the Expression and Localization of the Associated AMIGO-1 Cell Adhesion Molecule in Adult Brain Neurons

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    Hannah I. Bishop

    2018-01-01

    Full Text Available Voltage-gated K+ (Kv channels play important roles in regulating neuronal excitability. Kv channels comprise four principal α subunits, and transmembrane and/or cytoplasmic auxiliary subunits that modify diverse aspects of channel function. AMIGO-1, which mediates homophilic cell adhesion underlying neurite outgrowth and fasciculation during development, has recently been shown to be an auxiliary subunit of adult brain Kv2.1-containing Kv channels. We show that AMIGO-1 is extensively colocalized with both Kv2.1 and its paralog Kv2.2 in brain neurons across diverse mammals, and that in adult brain, there is no apparent population of AMIGO-1 outside of that colocalized with these Kv2 α subunits. AMIGO-1 is coclustered with Kv2 α subunits at specific plasma membrane (PM sites associated with hypolemmal subsurface cisternae at neuronal ER:PM junctions. This distinct PM clustering of AMIGO-1 is not observed in brain neurons of mice lacking Kv2 α subunit expression. Moreover, in heterologous cells, coexpression of either Kv2.1 or Kv2.2 is sufficient to drive clustering of the otherwise uniformly expressed AMIGO-1. Kv2 α subunit coexpression also increases biosynthetic intracellular trafficking and PM expression of AMIGO-1 in heterologous cells, and analyses of Kv2.1 and Kv2.2 knockout mice show selective loss of AMIGO-1 expression and localization in neurons lacking the respective Kv2 α subunit. Together, these data suggest that in mammalian brain neurons, AMIGO-1 is exclusively associated with Kv2 α subunits, and that Kv2 α subunits are obligatory in determining the correct pattern of AMIGO-1 expression, PM trafficking and clustering.

  1. The genome sequence of Caenorhabditis briggsae: a platform for comparative genomics.

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    Lincoln D Stein

    2003-11-01

    Full Text Available The soil nematodes Caenorhabditis briggsae and Caenorhabditis elegans diverged from a common ancestor roughly 100 million years ago and yet are almost indistinguishable by eye. They have the same chromosome number and genome sizes, and they occupy the same ecological niche. To explore the basis for this striking conservation of structure and function, we have sequenced the C. briggsae genome to a high-quality draft stage and compared it to the finished C. elegans sequence. We predict approximately 19,500 protein-coding genes in the C. briggsae genome, roughly the same as in C. elegans. Of these, 12,200 have clear C. elegans orthologs, a further 6,500 have one or more clearly detectable C. elegans homologs, and approximately 800 C. briggsae genes have no detectable matches in C. elegans. Almost all of the noncoding RNAs (ncRNAs known are shared between the two species. The two genomes exhibit extensive colinearity, and the rate of divergence appears to be higher in the chromosomal arms than in the centers. Operons, a distinctive feature of C. elegans, are highly conserved in C. briggsae, with the arrangement of genes being preserved in 96% of cases. The difference in size between the C. briggsae (estimated at approximately 104 Mbp and C. elegans (100.3 Mbp genomes is almost entirely due to repetitive sequence, which accounts for 22.4% of the C. briggsae genome in contrast to 16.5% of the C. elegans genome. Few, if any, repeat families are shared, suggesting that most were acquired after the two species diverged or are undergoing rapid evolution. Coclustering the C. elegans and C. briggsae proteins reveals 2,169 protein families of two or more members. Most of these are shared between the two species, but some appear to be expanding or contracting, and there seem to be as many as several hundred novel C. briggsae gene families. The C. briggsae draft sequence will greatly improve the annotation of the C. elegans genome. Based on similarity to C

  2. Screening and hit evaluation of a chemical library against blood-stage Plasmodium falciparum.

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    Avery, Vicky M; Bashyam, Sridevi; Burrows, Jeremy N; Duffy, Sandra; Papadatos, George; Puthukkuti, Shyni; Sambandan, Yuvaraj; Singh, Shivendra; Spangenberg, Thomas; Waterson, David; Willis, Paul

    2014-05-27

    In view of the need to continuously feed the pipeline with new anti-malarial agents adapted to differentiated and more stringent target product profiles (e.g., new modes of action, transmission-blocking activity or long-duration chemo-protection), a chemical library consisting of more than 250,000 compounds has been evaluated in a blood-stage Plasmodium falciparum growth inhibition assay and further assessed for chemical diversity and novelty. The selection cascade used for the triaging of hits from the chemical library started with a robust three-step in vitro assay followed by an in silico analysis of the resulting confirmed hits. Upon reaching the predefined requirements for selectivity and potency, the set of hits was subjected to computational analysis to assess chemical properties and diversity. Furthermore, known marketed anti-malarial drugs were co-clustered acting as 'signposts' in the chemical space defined by the hits. Then, in cerebro evaluation of the chemical structures was performed to identify scaffolds that currently are or have been the focus of anti-malarial medicinal chemistry programmes. Next, prioritization according to relaxed physicochemical parameters took place, along with the search for structural analogues. Ultimately, synthesis of novel chemotypes with desired properties was performed and the resulting compounds were subsequently retested in a P. falciparum growth inhibition assay. This screening campaign led to a 1.25% primary hit rate, which decreased to 0.77% upon confirmatory repeat screening. With the predefined potency (EC₅₀  10) criteria, 178 compounds progressed to the next steps where chemical diversity, physicochemical properties and novelty assessment were taken into account. This resulted in the selection of 15 distinct chemical series. A selection cascade was applied to prioritize hits resulting from the screening of a medium-sized chemical library against blood-stage P. falciparum. Emphasis was placed on chemical

  3. Involvement of raft aggregates enriched in Fas/CD95 death-inducing signaling complex in the antileukemic action of edelfosine in Jurkat cells.

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    Gajate, Consuelo; Gonzalez-Camacho, Fernando; Mollinedo, Faustino

    2009-01-01

    Recent evidence suggests that co-clustering of Fas/CD95 death receptor and lipid rafts plays a major role in death receptor-mediated apoptosis. By a combination of genetic, biochemical, and ultrastructural approaches, we provide here compelling evidence for the involvement of lipid raft aggregates containing recruited Fas/CD95 death receptor, Fas-associated death domain-containing protein (FADD), and procaspase-8 in the induction of apoptosis in human T-cell leukemia Jurkat cells by the antitumor drug edelfosine, the prototype compound of a promising family of synthetic antitumor lipids named as synthetic alkyl-lysophospholipid analogues. Co-immunoprecipitation assays revealed that edelfosine induced the generation of the so-called death-inducing signaling complex (DISC), made up of Fas/CD95, FADD, and procaspase-8, in lipid rafts. Electron microscopy analyses allowed to visualize the formation of raft clusters and their co-localization with DISC components Fas/CD95, FADD, and procaspase-8 following edelfosine treatment of Jurkat cells. Silencing of Fas/CD95 by RNA interference, transfection with a FADD dominant-negative mutant that blocks Fas/CD95 signaling, and specific inhibition of caspase-8 prevented the apoptotic response triggered by edelfosine, hence demonstrating the functional role of DISC in drug-induced apoptosis. By using radioactive labeled edelfosine and a fluorescent analogue, we found that edelfosine accumulated in lipid rafts, forming edelfosine-rich membrane raft clusters in Jurkat leukemic T-cells. Disruption of these membrane raft domains abrogated drug uptake and drug-induced DISC assembly and apoptosis. Thus, edelfosine uptake into lipid rafts was critical for the onset of both co-aggregation of DISC in membrane rafts and subsequent apoptotic cell death. This work shows the involvement of DISC clusters in lipid raft aggregates as a supramolecular and physical entity responsible for the induction of apoptosis in leukemic cells by the antitumor

  4. Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle

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    Liu Liwen

    2009-09-01

    Full Text Available Abstract Background Fission yeast Schizosaccharomyces pombe and budding yeast Saccharomyces cerevisiae are among the original model organisms in the study of the cell-division cycle. Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast. It has only been partially characterized. As a result, important regulatory cascades in budding yeast have no known or complete counterpart in fission yeast. Results By integrating genome-wide data from multiple time course cell cycle microarray experiments we reconstructed a gene regulatory network. Based on the network, we discovered in addition to previously known regulatory hubs in M phase, a new putative regulatory hub in the form of the HMG box transcription factor SPBC19G7.04. Further, we inferred periodic activities of several less known transcription factors over the course of the cell cycle, identified over 500 putative regulatory targets and detected many new phase-specific and conserved cis-regulatory motifs. In particular, we show that SPBC19G7.04 has highly significant periodic activity that peaks in early M phase, which is coordinated with the late G2 activity of the forkhead transcription factor fkh2. Finally, using an enhanced Bayesian algorithm to co-cluster the expression data, we obtained 31 clusters of co-regulated genes 1 which constitute regulatory modules from different phases of the cell cycle, 2 whose phase order is coherent across the 10 time course experiments, and 3 which lead to identification of phase-specific control elements at both the transcriptional and post-transcriptional levels in S. pombe. In particular, the ribosome biogenesis clusters expressed in G2 phase reveal new, highly conserved RNA motifs. Conclusion Using a systems-level analysis of the phase-specific nature of the S. pombe cell cycle gene regulation, we have provided new testable evidence for post-transcriptional regulation in the G2 phase of the fission yeast cell cycle

  5. ICP Versus Laser Doppler Cerebrovascular Reactivity Indices to Assess Brain Autoregulatory Capacity.

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    Zeiler, F A; Donnelly, J; Cardim, D; Menon, D K; Smielewski, P; Czosnyka, M

    2017-10-17

    /Lx_a. Both Sx/Sx-a and the ICP-derived indices appear to be dissociated with LDF-based cerebrovascular reactivity, leaving Mx/Mx-a as a better surrogate for the assessment of cortical small vessel/MV cerebrovascular reactivity. Sx/Sx_a cocluster/covary with ICP-derived indices, as seen in our previous work.