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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. 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...

  3. Bitwise dimensional co-clustering for analytical workloads

    NARCIS (Netherlands)

    Baumann, Stephan; Boncz, Peter; Sattler, Kai Uwe

    2016-01-01

    Analytical workloads in data warehouses often include heavy joins where queries involve multiple fact tables in addition to the typical star-patterns, dimensional grouping and selections. In this paper we propose a new processing and storage framework called bitwise dimensional co-clustering (BDCC)

  4. 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.

  5. 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.

  6. blockcluster: An R Package for Model-Based Co-Clustering

    Directory of Open Access Journals (Sweden)

    Parmeet Singh Bhatia

    2017-02-01

    Full Text Available Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or block clustering, is an important technique in two way data analysis. A new standard and efficient approach has been recently proposed based on the latent block model (Govaert and Nadif 2003 which takes into account the block clustering problem on both the individual and variable sets. This article presents our R package blockcluster for co-clustering of binary, contingency and continuous data based on these very models. In this document, we will give a brief review of the model-based block clustering methods, and we will show how the R package blockcluster can be used for co-clustering.

  7. 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.

  8. 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

    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...... sparse bipartite networks and achieve a speedup of two orders of magnitude compared to estimation based on conventional CPUs. In terms of scalability we find for networks with more than 100 million links that reliable inference can be achieved in less than an hour on a single GPU. To efficiently manage...

  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. 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...... and content preference simultaneously. In this paper we will present an algorithm using bipartite spectral clustering to co-cluster Web users and pages. The usage data of users visiting Web sites is modeled as a bipartite graph and the spectral clustering is then applied to the graph representation of usage...... data. The proposed approach is evaluated by experiments performed on real datasets, and the impact of using various clustering algorithms is also investigated. Experimental results have demonstrated the employed method can effectively reveal the subset aggregates of Web users and pages which...

  11. FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK

    Directory of Open Access Journals (Sweden)

    Katsuhiro Honda

    2017-01-01

    Full Text Available Cocluster structure analysis is a basic technique for revealing intrinsic structural information from cooccurrence data among objects and items, in which coclusters are composed of mutually familiar pairs of objects and items. In many real applications, it is also the case that we have not only cooccurrence information among objects and items but also intrinsic relation among items and other ingredients. For example, in food preference analysis, users’ preferences on foods should be found considering not only user-food cooccurrences but also the implicit relation among users and cooking ingredients. In this paper, two FCM-type fuzzy coclustering models, that is, FCCM and Fuzzy CoDoK, are extended for revealing intrinsic cocluster structures from three-mode cooccurrence data, where the aggregation degree of three elements in each cocluster is maximized through iterative updating of three types of fuzzy memberships for objects, items, and ingredients. The characteristic features of the proposed methods are demonstrated through a numerical experiment.

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

    International Nuclear Information System (INIS)

    Bai, Song; Liu, Zhiyi; Ying, Puyou; Wang, Jian; Li, Junlin

    2016-01-01

    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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Nano-spatial parameters from 3D to 2D lattice dimensionality by organic variant in [ZnCl4]- [R]+ hybrid materials: Structure, architecture-lattice dimensionality, microscopy, optical Eg and PL correlations

    Science.gov (United States)

    Kumar, Ajit; Verma, Sanjay K.; Alvi, P. A.; Jasrotia, Dinesh

    2016-04-01

    The nanospatial morphological features of [ZnCl]- [C5H4NCH3]+ hybrid derivative depicts 28 nm granular size and 3D spreader shape packing pattern as analyzed by FESEM and single crystal XRD structural studies. The organic moiety connect the inorganic components through N-H+…Cl- hydrogen bond to form a hybrid composite, the replacement of organic derivatives from 2-methylpyridine to 2-Amino-5-choloropyridine results the increase in granular size from 28nm to 60nm and unit cell packing pattern from 3D-2D lattice dimensionality along ac plane. The change in optical energy direct band gap value from 3.01eV for [ZnCl]- [C5H4NCH3]+ (HM1) to 3.42eV for [ZnCl]- [C5H5ClN2]+ (HM2) indicates the role of organic moiety in optical properties of hybrid materials. The photoluminescence emission spectra is observed in the wavelength range of 370 to 600 nm with maximum peak intensity of 9.66a.u. at 438 nm for (HM1) and 370 to 600 nm with max peak intensity of 9.91 a.u. at 442 nm for (HM2), indicating that the emission spectra lies in visible range. PL excitation spectra depicts the maximum excitation intensity [9.8] at 245.5 nm for (HM1) and its value of 9.9 a.u. at 294 nm, specify the excitation spectra lies in UV range. Photoluminescence excitation spectra is observed in the wavelength range of 280 to 350 nm with maximum peak intensity of 9.4 a.u. at 285.5 nm and 9.9 a.u. at 294 and 297 nm, indicating excitation in the UV spectrum. Single crystal growth process and detailed physiochemical characterization such as XRD, FESEM image analysis photoluminescence property reveals the structure stability with non-covalent interactions, lattice dimensionality (3D-2D) correlations interweaving into the design of inorganic-organic hybrid materials.

  19. Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach

    Directory of Open Access Journals (Sweden)

    Sami Ullah

    2017-11-01

    Full Text Available Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square scanning windows to discover disease clusters. In certain situations, where the disease occurrences tend to cluster in very irregularly shaped areas, these algorithms are not feasible in practise for the detection of space-time clusters. To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. The proposed method detects space-time disease clusters by tracking the changes in space–time occurrence structure instead of an in-depth search over space. This method was utilised to detect potential clusters in the annual and monthly malaria data in Khyber Pakhtunkhwa Province, Pakistan from 2012 to 2016 visualising the results on a heat map. The results of the annual data analysis showed that the most likely hotspot emerged in three sub-regions in the years 2013-2014. The most likely hotspots in monthly data appeared in the month of July to October in each year and showed a strong periodic trend.

  20. Bitwise dimensional co-clustering for analytical workloads

    NARCIS (Netherlands)

    S. Baumann (Stephan); P.A. Boncz (Peter); K.-U. Sattler

    2016-01-01

    htmlabstractAnalytical workloads in data warehouses often include heavy joins where queries involve multiple fact tables in addition to the typical star-patterns, dimensional grouping and selections. In this paper we propose a new processing and storage framework called Bitwise Dimensional

  1. Spectral biclustering of microarray data: coclustering genes and conditions.

    Science.gov (United States)

    Kluger, Yuval; Basri, Ronen; Chang, Joseph T; Gerstein, Mark

    2003-04-01

    Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find "marker genes" that are differentially expressed in particular sets of "conditions." We have developed a method that simultaneously clusters genes and conditions, finding distinctive "checkerboard" patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data).

  2. 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

  3. 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…

  4. 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

  5. Ruthenium-platinum bimetallic catalysts supported on silica: characterization and study of benzene hydrogenation and CO methanation

    Energy Technology Data Exchange (ETDEWEB)

    Chakrabarty, D.K.; Rao, K.M.; Sundararaman, N.; Chandavar, K.

    1986-12-15

    Ru-Pt/SiO/sub 2/ bimetallic catalysts with varying Ru:Pt ratio have been prepared and studied with the aim to establish if they contain coclusters or isolated ruthenium and platinum particles. X-ray diffraction studies show that individual crystallites of ruthenium and platinum are present and no coclusters are formed. Metal dispersion has been determined by hydrogen chemisorption and surface composition of the catalysts has been obtained from XPS. It was found that preoxidation of the catalysts prior to reduction is essential for good platinum dispersion. The experimental turnover number (TN) for benzene hydrogenation on the bimetallic catalysts agrees very well with that of the weighted average on the individual metal catalysts and this may be taken as a kinetic evidence for the absence of coclusters. Carbon monoxide methanation activity of the bimetallic catalysts is quite similar to that of the supported platinum catalyst. 6 refs., 6 figs., 2 tabs.

  6. 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...

  7. 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...

  8. 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

  9. Combating Fraud in Online Social Networks: Detecting Stealthy Facebook Like Farms

    OpenAIRE

    Ikram, Muhammad; Onwuzurike, Lucky; Farooqi, Shehroze; De Cristofaro, Emiliano; Friedman, Arik; Jourjon, Guillaume; Kaafar, Mohammad Ali; Shafiq, M. Zubair

    2015-01-01

    As businesses increasingly rely on social networking sites to engage with their customers, it is crucial to understand and counter reputation manipulation activities, including fraudulently boosting the number of Facebook page likes using like farms. To this end, several fraud detection algorithms have been proposed and some deployed by Facebook that use graph co-clustering to distinguish between genuine likes and those generated by farm-controlled profiles. However, as we show in this paper,...

  10. Differential association of GABAB receptors 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

    2018-04-01

    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.

  11. Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes.

    Science.gov (United States)

    Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Xu, Richard Yi Da; Luo, Xiangfeng

    2018-05-01

    Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co-clustering. However, the traditional SNMF typically assumes the number of latent factors (i.e., dimensionality of the factor matrices) to be fixed. This assumption makes it inflexible in practice. In this paper, we propose a doubly sparse nonparametric NMF framework to mitigate this issue by using dependent Indian buffet processes (dIBP). We apply a correlation function for the generation of two stick weights associated with each column pair of factor matrices while still maintaining their respective marginal distribution specified by IBP. As a consequence, the generation of two factor matrices will be columnwise correlated. Under this framework, two classes of correlation function are proposed: 1) using bivariate Beta distribution and 2) using Copula function. Compared with the single IBP-based NMF, this paper jointly makes two factor matrices nonparametric and sparse, which could be applied to broader scenarios, such as co-clustering. This paper is seen to be much more flexible than Gaussian process-based and hierarchial Beta process-based dIBPs in terms of allowing the two corresponding binary matrix columns to have greater variations in their nonzero entries. Our experiments on synthetic data show the merits of this paper compared with the state-of-the-art models in respect of factorization efficiency, sparsity, and flexibility. Experiments on real-world data sets demonstrate the efficiency of this paper in document-word co-clustering tasks.

  12. 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

  13. Lateral Organization of Influenza Virus Proteins in the Budozone Region of the Plasma Membrane.

    Science.gov (United States)

    Leser, George P; Lamb, Robert A

    2017-05-01

    Influenza virus assembles and buds at the plasma membrane of virus-infected cells. The viral proteins assemble at the same site on the plasma membrane for budding to occur. This involves a complex web of interactions among viral proteins. Some proteins, like hemagglutinin (HA), NA, and M2, are integral membrane proteins. M1 is peripherally membrane associated, whereas NP associates with viral RNA to form an RNP complex that associates with the cytoplasmic face of the plasma membrane. Furthermore, HA and NP have been shown to be concentrated in cholesterol-rich membrane raft domains, whereas M2, although containing a cholesterol binding motif, is not raft associated. Here we identify viral proteins in planar sheets of plasma membrane using immunogold staining. The distribution of these proteins was examined individually and pairwise by using the Ripley K function, a type of nearest-neighbor analysis. Individually, HA, NA, M1, M2, and NP were shown to self-associate in or on the plasma membrane. HA and M2 are strongly coclustered in the plasma membrane; however, in the case of NA and M2, clustering depends upon the expression system used. Despite both proteins being raft resident, HA and NA occupy distinct but adjacent membrane domains. M2 and M1 strongly cocluster, but the association of M1 with HA or NA is dependent upon the means of expression. The presence of HA and NP at the site of budding depends upon the coexpression of other viral proteins. Similarly, M2 and NP occupy separate compartments, but an association can be bridged by the coexpression of M1. IMPORTANCE The complement of influenza virus proteins necessary for the budding of progeny virions needs to accumulate at budozones. This is complicated by HA and NA residing in lipid raft-like domains, whereas M2, although an integral membrane protein, is not raft associated. Other necessary protein components such as M1 and NP are peripherally associated with the membrane. Our data define spatial relationships

  14. Collaborative Filtering Based on Sequential Extraction of User-Item Clusters

    Science.gov (United States)

    Honda, Katsuhiro; Notsu, Akira; Ichihashi, Hidetomo

    Collaborative filtering is a computational realization of “word-of-mouth” in network community, in which the items prefered by “neighbors” are recommended. This paper proposes a new item-selection model for extracting user-item clusters from rectangular relation matrices, in which mutual relations between users and items are denoted in an alternative process of “liking or not”. A technique for sequential co-cluster extraction from rectangular relational data is given by combining the structural balancing-based user-item clustering method with sequential fuzzy cluster extraction appraoch. Then, the tecunique is applied to the collaborative filtering problem, in which some items may be shared by several user clusters.

  15. Secondary precipitation in an Al-Mg-Si-Cu alloy

    International Nuclear Information System (INIS)

    Buha, J.; Lumley, R.N.; Crosky, A.G.; Hono, K.

    2007-01-01

    Interruption of a conventional T6 heat treatment at 177 deg. C for the Al-Mg-Si-Cu alloy 6061 after a short period of time (20 min), by inserting a dwell period at a lower temperature (e.g. 65 deg. C), promotes secondary precipitation of Guinier-Preston (GP) zones. As a consequence, a much greater number of precursors to the β'' precipitates are produced so that a finer and denser dispersion of this phase is formed when T6 ageing is resumed. This change in microstructure causes significant and simultaneous improvements in tensile properties and fracture toughness. Secondary precipitation of GP zones occurs through a gradual evolution of a large number of Mg-Si(-Cu)-vacancy co-clusters formed during the initial ageing at 177 deg. C. The precise mechanism of secondary precipitation has been revealed by three-dimensional atom probe microscopy supplemented by transmission electron microscopy and differential scanning calorimetry

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

    Directory of Open Access Journals (Sweden)

    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

  17. 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

  18. Coupling aging immunity with a sedentary lifestyle: has the damage already been done?--a mini-review.

    Science.gov (United States)

    Simpson, Richard J; Guy, Keith

    2010-01-01

    The elderly population is at an unprecedented risk of infectious diseases and malignancy due to apparently inevitable age-related declines in immunity. The 'immune risk profile' (IRP) is an array of biomarkers that has been used to predict morbidity and mortality in older adults. As it is generally accepted that middle-aged and elderly individuals who habitually participate in moderate-intensity exercise are less likely to incur an infection than their sedentary counterparts, this review addresses current knowledge on the effects of regular exercise on aspects of adaptive immunity as they relate to the IRP. Findings from cross-sectional studies mostly show enhanced immunity in physically active compared to sedentary older adults. These include greater T-cell responsiveness to mitogens in vitro, a reduced frequency of antigen-experienced and senescent T-cells (i.e. CD45RO+/KLRG1+/CD57+/CD28-), enhanced IL-2 production and T-lymphocyte expression of the IL-2 receptor, longer chromosome telomere lengths in blood leukocytes and in vivo immune responses to vaccines and recall antigens. In contrast, the evidence from the available longitudinal studies that have used an exercise training intervention in previously sedentary elderly to improve similar immune responses is less compelling. Although this might indicate that exercise has limited immune restorative properties in previously sedentary elderly, there are still relatively few studies that have addressed specific IRP criteria and the large variation in experimental design among the longitudinal studies complicates the juxtaposition of these results. It is clear that a more substantial and focused research approach is required before physical exercise can be used in earnest as an effective immune restorative strategy in the elderly. This mini-review summarizes the major findings of these studies and proposes future avenues of research to investigate the effects of regular exercise on aspects of adaptive immunity in

  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. Response of Human Skin to Aesthetic Scarification

    Science.gov (United States)

    Gabriel, Vincent A.; McClellan, Elizabeth A.; Scheuermann, Richard H.

    2014-01-01

    This study was undertaken to investigate changes in RNA expression in previously healthy adult human skin following thermal injury induced by contact with hot metal that was undertaken as part of aesthetic scarification, a body modification practice. Subjects were recruited to have pre-injury skin and serial wound biopsies performed. 4 mm punch biopsies were taken prior to branding and 1 hour, 1 week, and 1, 2 and 3 months post injury. RNA was extracted and quality assured prior to the use of a whole-genome based bead array platform to describe expression changes in the samples using the pre-injury skin as a comparator. Analysis of the array data was performed using k-means clustering and a hypergeometric probability distribution without replacement and corrections for multiple comparisons were done. Confirmatory q-PCR was performed. Using a k of 10, several clusters of genes were shown to co-cluster together based on Gene Ontology classification with probabilities unlikely to occur by chance alone. OF particular interest were clusters relating to cell cycle, proteinaceous extracellular matrix and keratinization. Given the consistent expression changes at one week following injury in the cell cycle cluster, there is an opportunity to intervene early following burn injury to influence scar development. PMID:24582755

  1. 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.

  2. Epithelium-innate immune cell axis in mucosal responses to SIV.

    Science.gov (United States)

    Shang, L; Duan, L; Perkey, K E; Wietgrefe, S; Zupancic, M; Smith, A J; Southern, P J; Johnson, R P; Haase, A T

    2017-03-01

    In the SIV (simian immunodeficiency virus)-rhesus macaque model of HIV-1 (human immunodeficiency virus type I) transmission to women, one hallmark of the mucosal response to exposure to high doses of SIV is CD4 T-cell recruitment that fuels local virus expansion in early infection. In this study, we systematically analyzed the cellular events and chemoattractant profiles in cervical tissues that precede CD4 T-cell recruitment. We show that vaginal exposure to the SIV inoculum rapidly induces chemokine expression in cervical epithelium including CCL3, CCL20, and CXCL8. The chemokine expression is associated with early recruitment of macrophages and plasmacytoid dendritic cells that are co-clustered underneath the cervical epithelium. Production of chemokines CCL3 and CXCL8 by these cells in turn generates a chemokine gradient that is spatially correlated with the recruitment of CD4 T cells. We further show that the protection of SIVmac239Δnef vaccination against vaginal challenge is correlated with the absence of this epithelium-innate immune cell-CD4 T-cell axis response in the cervical mucosa. Our results reveal a critical role for cervical epithelium in initiating early mucosal responses to vaginal infection, highlight an important role for macrophages in target cell recruitment, and provide further evidence of a paradoxical dampening effect of a protective vaccine on these early mucosal responses.

  3. A novel framework to alleviate the sparsity problem in context-aware recommender systems

    Science.gov (United States)

    Yu, Penghua; Lin, Lanfen; Wang, Jing

    2017-04-01

    Recommender systems have become indispensable for services in the era of big data. To improve accuracy and satisfaction, context-aware recommender systems (CARSs) attempt to incorporate contextual information into recommendations. Typically, valid and influential contexts are determined in advance by domain experts or feature selection approaches. Most studies have focused on utilizing the unitary context due to the differences between various contexts. Meanwhile, multi-dimensional contexts will aggravate the sparsity problem, which means that the user preference matrix would become extremely sparse. Consequently, there are not enough or even no preferences in most multi-dimensional conditions. In this paper, we propose a novel framework to alleviate the sparsity issue for CARSs, especially when multi-dimensional contextual variables are adopted. Motivated by the intuition that the overall preferences tend to show similarities among specific groups of users and conditions, we first explore to construct one contextual profile for each contextual condition. In order to further identify those user and context subgroups automatically and simultaneously, we apply a co-clustering algorithm. Furthermore, we expand user preferences in a given contextual condition with the identified user and context clusters. Finally, we perform recommendations based on expanded preferences. Extensive experiments demonstrate the effectiveness of the proposed framework.

  4. 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.

  5. Ensemble Clustering Classification Applied to Competing SVM and One-Class Classifiers Exemplified by Plant MicroRNAs Data

    Directory of Open Access Journals (Sweden)

    Yousef Malik

    2016-12-01

    Full Text Available The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN. In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that EC-kNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.

  6. Cholera toxin entry into pig enterocytes occurs via a lipid raft- and clathrin-dependent mechanism

    DEFF Research Database (Denmark)

    Hansen, Gert H; Dalskov, Stine-Mathilde; Rasmussen, Christina Rehné

    2005-01-01

    The small intestinal brush border is composed of lipid raft microdomains, but little is known about their role in the mechanism whereby cholera toxin gains entry into the enterocyte. The present work characterized the binding of cholera toxin B subunit (CTB) to the brush border and its internaliz......The small intestinal brush border is composed of lipid raft microdomains, but little is known about their role in the mechanism whereby cholera toxin gains entry into the enterocyte. The present work characterized the binding of cholera toxin B subunit (CTB) to the brush border and its...... accompanied the toxin internalization whereas no formation of caveolae was observed. CTB was strongly associated with the buoyant, detergent-insoluble fraction of microvillar membranes. Neither CTB's raft association nor uptake via clathrin-coated pits was affected by methyl-beta-cyclodextrin, indicating...... that membrane cholesterol is not required for toxin binding and entry. The ganglioside GM(1) is known as the receptor for CTB, but surprisingly the toxin also bound to sucrase-isomaltase and coclustered with this glycosidase in apical membrane pits. CTB binds to lipid rafts of the brush border...

  7. 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.

  8. Making of a Synapse: Recurrent Roles of Drebrin A at Excitatory Synapses Throughout Life.

    Science.gov (United States)

    Aoki, Chiye; Sherpa, Ang D

    2017-01-01

    Mature excitatory synapses are composed of more than 1500 proteins postsynaptically and hundreds more that operate presynaptically. Among them, drebrin is an F-actin-binding protein that increases noticeably during juvenile synaptogenesis. Electron microscopic analysis reveals that drebrin is highly enriched specifically on the postsynaptic side of excitatory synapses. Since dendritic spines are structures specialized for excitatory synaptic transmission, the function of drebrin was probed by analyzing the ultrastructural characteristics of dendritic spines of animals with genetic deletion of drebrin A (DAKO), the adult isoform of drebrin. Electron microscopic analyses revealed that these brains are surprisingly intact, in that axo-spinous synaptic junctions are well-formed and not significantly altered in number. This normal ultrastructure may be because drebrin E, the alternate embryonic isoform, compensates for the genetic deletion of drebrin A. However, DAKO results in the loss of homeostatic plasticity of N-methyl-D-aspartate receptors (NMDARs). The NMDAR activation-dependent trafficking of the NR2A subunit-containing NMDARs from dendritic shafts into spine head cytoplasm is greatly diminished within brains of DAKO. Conversely, within brains of wild-type rodents, spines respond to NMDAR blockade with influx of F-actin, drebrin A, and NR2A subunits of NMDARs. These observations indicate that drebrin A facilitates the trafficking of NMDAR cargos in an F-actin-dependent manner to mediate homeostatic plasticity. Analysis of the brains of transgenic mice used as models of Alzheimer's disease (AD) reveals that the loss of drebrin from dendritic spines predates the emergence of synaptic dysfunction and cognitive impairment, suggesting that this form of homeostatic plasticity contributes toward cognition. Two studies suggest that the nature of drebrin's interaction with NMDARs is dependent on the receptor's subunit composition. Drebrin A can be found co-clustering

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  11. Spatial distribution of HIV, HCV, and co-infections among drug users in the southwestern border areas of China (2004-2014): a cohort study of a national methadone maintenance treatment program.

    Science.gov (United States)

    Li, Mingli; Li, Rongjian; Shen, Zhiyong; Li, Chunying; Liang, Nengxiu; Peng, Zhenren; Huang, Wenbo; He, Chongwei; Zhong, Feng; Tang, Xianyan; Lan, Guanghua

    2017-09-30

    A methadone maintenance treatment (MMT) program to curb the dual epidemics of HIV/AIDS and drug use has been administered by China since 2004. Little is known regarding the geographic heterogeneity of HIV and hepatitis C virus (HCV) infections among MMT clients in the resource-constrained context of Chinese provinces, such as Guangxi. This study aimed to characterize the geographic distribution patterns and co-clustered epidemic factors of HIV, HCV and co-infections at the county level among drug users receiving MMT in Guangxi Zhuang Autonomous Region, located in the southwestern border area of China. Baseline data on drug users' demographic, behavioral and biological characteristics in the MMT clinics of Guangxi Zhuang Autonomous Region during the period of March 2004 to December 2014 were obtained from national HIV databases. Residential addresses were entered into a geographical information system (GIS) program and analyzed for spatial clustering of HIV, HCV and co-infections among MMT clients at the county level using geographic autocorrelation analysis and geographic scan statistics. A total of 31,015 MMT clients were analyzed, and the prevalence of HIV, HCV and co-infections were 13.05%, 72.51% and 11.96% respectively. Both the geographic autocorrelation analysis and geographic scan statistics showed that HIV, HCV and co-infections in Guangxi Zhuang Autonomous Region exhibited significant geographic clustering at the county level, and the Moran's I values were 0.33, 0.41 and 0.30, respectively (P areas surrounding P county. HIV, HCV and co-infections among MMT clients in Guangxi Zhuang Autonomous Region all presented substantial geographic heterogeneity at the county level with a number of overlapping significant clusters. The areas surrounding P county were effective in enrolling high-risk clients in their MMT programs which, in turn, might enable people who inject drugs to inject less, share fewer syringes, and receive referrals for HIV or HCV treatment in

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

    Directory of Open Access Journals (Sweden)

    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

  13. Local calcium signalling is mediated by mechanosensitive ion channels in mesenchymal stem cells

    International Nuclear Information System (INIS)

    Chubinskiy-Nadezhdin, Vladislav I.; Vasileva, Valeria Y.; Pugovkina, Natalia A.; Vassilieva, Irina O.; Morachevskaya, Elena A.; Nikolsky, Nikolay N.; Negulyaev, Yuri A.

    2017-01-01

    Mechanical forces are implicated in key physiological processes in stem cells, including proliferation, differentiation and lineage switching. To date, there is an evident lack of understanding of how external mechanical cues are coupled with calcium signalling in stem cells. Mechanical reactions are of particular interest in adult mesenchymal stem cells because of their promising potential for use in tissue remodelling and clinical therapy. Here, single channel patch-clamp technique was employed to search for cation channels involved in mechanosensitivity in mesenchymal endometrial-derived stem cells (hMESCs). Functional expression of native mechanosensitive stretch-activated channels (SACs) and calcium-sensitive potassium channels of different conductances in hMESCs was shown. Single current analysis of stretch-induced channel activity revealed functional coupling of SACs and BK channels in plasma membrane. The combination of cell-attached and inside-out experiments have indicated that highly localized Ca 2+ entry via SACs triggers BK channel activity. At the same time, SK channels are not coupled with SACs despite of high calcium sensitivity as compared to BK. Our data demonstrate novel mechanism controlling BK channel activity in native cells. We conclude that SACs and BK channels are clusterized in functional mechanosensitive domains in the plasma membrane of hMESCs. Co-clustering of ion channels may significantly contribute to mechano-dependent calcium signalling in stem cells. - Highlights: • Stretch-induced channel activity in human mesenchymal stem cells was analyzed. • Functional expression of SACs and Ca 2+ -sensitive BK and SK channels was shown. • Local Ca 2+ influx via stretch-activated channels triggers BK channel activity. • SK channels are not coupled with SACs despite higher sensitivity to [Ca 2+ ] i . • Functional clustering of SACs and BK channels in stem cell membrane is proposed.

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

    Directory of Open Access Journals (Sweden)

    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

  15. 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.

  16. Threonine 89 Is an Important Residue of Profilin-1 That Is Phosphorylatable by Protein Kinase A.

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    David Gau

    Full Text Available Dynamic regulation of actin cytoskeleton is at the heart of all actin-based cellular events. In this study, we sought to identify novel post-translational modifications of Profilin-1 (Pfn1, an important regulator of actin polymerization in cells.We performed in vitro protein kinase assay followed by mass-spectrometry to identify Protein Kinase A (PKA phosphorylation sites of Pfn1. By two-dimensional gel electrophoresis (2D-GE analysis, we further examined the changes in the isoelectric profile of ectopically expressed Pfn1 in HEK-293 cells in response to forskolin (FSK, an activator of cAMP/PKA pathway. Finally, we combined molecular dynamics simulations (MDS, GST pull-down assay and F-actin analyses of mammalian cells expressing site-specific phosphomimetic variants of Pfn1 to predict the potential consequences of phosphorylation of Pfn1.We identified several PKA phosphorylation sites of Pfn1 including Threonine 89 (T89, a novel site. Consistent with PKA's ability to phosphorylate Pfn1 in vitro, FSK stimulation increased the pool of the most negatively charged form of Pfn1 in HEK-293 cells which can be attenuated by PKA inhibitor H89. MDS predicted that T89 phosphorylation destabilizes an intramolecular interaction of Pfn1, potentially increasing its affinity for actin. The T89D phosphomimetic mutation of Pfn1 elicits several changes that are hallmarks of proteins folded into alternative three-dimensional conformations including detergent insolubility, protein aggregation and accelerated proteolysis, suggesting that T89 is a structurally important residue of Pfn1. Expression of T89D-Pfn1 induces actin:T89D-Pfn1 co-clusters and dramatically reduces overall actin polymerization in cells, indicating an actin-sequestering action of T89D-Pfn1. Finally, rendering T89 non-phosphorylatable causes a positive charge shift in the isoelectric profile of Pfn1 in a 2D gel electrophoresis analysis of cell extracts, a finding that is consistent with

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

    Science.gov (United States)

    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

  18. 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