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Sample records for cluster enzymes predicting

  1. Prediction of Wild-type Enzyme Characteristics

    DEFF Research Database (Denmark)

    Geertz-Hansen, Henrik Marcus

    of biotechnology, including enzyme discovery and characterization. This work presents two articles on sequence-based discovery and functional annotation of enzymes in environmental samples, and two articles on analysis and prediction of enzyme thermostability and cofactor requirements. The first article presents...... a sequence-based approach to discovery of proteolytic enzymes in metagenomes obtained from the Polar oceans. We show that microorganisms living in these extreme environments of constant low temperature harbour genes encoding novel proteolytic enzymes with potential industrial relevance. The second article...... presents a web server for the processing and annotation of functional metagenomics sequencing data, tailored to meet the requirements of non-bioinformaticians. The third article presents analyses of the molecular determinants of enzyme thermostability, and a feature-based prediction method of the melting...

  2. 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

  3. Genetics Home Reference: myopathy with deficiency of iron-sulfur cluster assembly enzyme

    Science.gov (United States)

    ... Myopathy with deficiency of iron-sulfur cluster assembly enzyme Printable PDF Open All Close All Enable Javascript ... Myopathy with deficiency of iron-sulfur cluster assembly enzyme is an inherited disorder that primarily affects muscles ...

  4. Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.

    Science.gov (United States)

    Noar, Roslyn D; Daub, Margaret E

    2016-01-01

    Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity) for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity) to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that they may encode

  5. Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.

    Directory of Open Access Journals (Sweden)

    Roslyn D Noar

    Full Text Available Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that

  6. Structure prediction of AlnOm clusters

    International Nuclear Information System (INIS)

    Smok, P

    2011-01-01

    Genetic algorithm simulations, using Buckingham potential to represent the anion-anion and cation-anion short-range interactions, were performed in order to predict the equilibrium positions of the Al and O ions in Al n O m clusters. In order to find the equilibrium structures of compounds a self-organizing genetic algorithm were constructed. The calculation were carried out for several clusters Al n O m , with different numbers of aluminium and oxygen atoms.

  7. Link prediction with node clustering coefficient

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

    2016-06-01

    Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

  8. 25. Steenbock symposium -- Biosynthesis and function of metal clusters for enzymes: Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    This symposium was held June 10--14, 1997 in Madison, Wisconsin. The purpose of this conference was to provide a multidisciplinary forum for exchange of state-of-the-art information on biochemistry of enzymes that have an affinity for metal clusters. Attention is focused on the following: metal clusters involved in energy conservation and remediation; tungsten, molybdenum, and cobalt-containing enzymes; Fe proteins, and Mo-binding proteins; nickel enzymes; and nitrogenase.

  9. Prediction of novel archaeal enzymes from sequence-derived features

    DEFF Research Database (Denmark)

    Jensen, Lars Juhl; Skovgaard, Marie; Brunak, Søren

    2002-01-01

    The completely sequenced archaeal genomes potentially encode, among their many functionally uncharacterized genes, novel enzymes of biotechnological interest. We have developed a prediction method for detection and classification of enzymes from sequence alone (available at http://www.cbs.dtu.dk/......The completely sequenced archaeal genomes potentially encode, among their many functionally uncharacterized genes, novel enzymes of biotechnological interest. We have developed a prediction method for detection and classification of enzymes from sequence alone (available at http......://www.cbs.dtu.dk/services/ArchaeaFun/). The method does not make use of sequence similarity; rather, it relies on predicted protein features like cotranslational and posttranslational modifications, secondary structure, and simple physical/chemical properties....

  10. Galectin-4 and small intestinal brush border enzymes form clusters

    DEFF Research Database (Denmark)

    Danielsen, E M; van Deurs, B

    1997-01-01

    that galectin-4 is indeed an intestinal brush border protein; we also localized galectin-4 throughout the cell, mainly associated with membraneous structures, including small vesicles, and to the rootlets of microvillar actin filaments. This was confirmed by subcellular fractionation, showing about half...... by a nonclassical pathway, and the brush border enzymes represent a novel class of natural ligands for a member of the galectin family. Newly synthesized galectin-4 is rapidly "trapped" by association with intracellular structures prior to its apical secretion, but once externalized, association with brush border......Detergent-insoluble complexes prepared from pig small intestine are highly enriched in several transmembrane brush border enzymes including aminopeptidase N and sucrase-isomaltase, indicating that they reside in a glycolipid-rich environment in vivo. In the present work galectin-4, an animal lectin...

  11. Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

    Directory of Open Access Journals (Sweden)

    Deanne W Sammond

    Full Text Available Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

  12. Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

    Science.gov (United States)

    Sammond, Deanne W; Kastelowitz, Noah; Himmel, Michael E; Yin, Hang; Crowley, Michael F; Bomble, Yannick J

    2016-01-01

    Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

  13. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  14. Sequence-based Screening for Rare Enzymes: New Insights into the World of AMDases Reveal a Conserved Motif and 58 Novel Enzymes Clustering in Eight Distinct Families.

    Directory of Open Access Journals (Sweden)

    Janine Maimanakos

    2016-08-01

    Full Text Available Arylmalonate-Decarboxylases (AMDases, EC 4.1.1.76 are very rare and mostly underexplored enzymes. Currently only four known and biochemically characterized representatives exist. However, their ability to decarboxylate α-disubstituted malonic acid derivatives to optically pure products without cofactors makes them attractive and promising candidates for the use as biocatalysts in industrial processes. Until now, AMDases could not be separated from other members of the aspartate/glutamate racemase superfamily based on their gene sequences. Within this work, a search algorithm was developed that enables a reliable prediction of AMDase activity for potential candidates. Based on specific sequence patterns and screening methods 58 novel AMDase candidate genes could be identified in this work. Thereby, AMDases with the conserved sequence pattern of Bordetella bronchiseptica’s prototype appeared to be limited to the classes of Alpha-, Beta- and Gammaproteobacteria. Amino acid homologies and comparison of gene surrounding sequences enabled the classification of eight enzyme clusters. Particularly striking is the accumulation of genes coding for different transporters of the TTT family, TRAP transporters and ABC transporters as well as genes coding for mandelate racemases/muconate lactonizing enzymes that might be involved in substrate uptake or degradation of AMDase products. Further, three novel AMDases were characterized which showed a high enantiomeric excess (>99% of the (R-enantiomer of flurbiprofen. These are the recombinant AmdA and AmdV from Variovorax sp. strains HH01 and HH02, originated from soil, and AmdP from Polymorphum gilvum found by a data base search. Altogether our findings give new insights into the class of AMDases and reveal many previously unknown enzyme candidates with high potential for bioindustrial processes.

  15. Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

    Energy Technology Data Exchange (ETDEWEB)

    Simmhan, Yogesh; Noor, Muhammad Usman

    2013-10-09

    Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

  16. Recent developments of the quantum chemical cluster approach for modeling enzyme reactions.

    Science.gov (United States)

    Siegbahn, Per E M; Himo, Fahmi

    2009-06-01

    The quantum chemical cluster approach for modeling enzyme reactions is reviewed. Recent applications have used cluster models much larger than before which have given new modeling insights. One important and rather surprising feature is the fast convergence with cluster size of the energetics of the reactions. Even for reactions with significant charge separation it has in some cases been possible to obtain full convergence in the sense that dielectric cavity effects from outside the cluster do not contribute to any significant extent. Direct comparisons between quantum mechanics (QM)-only and QM/molecular mechanics (MM) calculations for quite large clusters in a case where the results differ significantly have shown that care has to be taken when using the QM/MM approach where there is strong charge polarization. Insights from the methods used, generally hybrid density functional methods, have also led to possibilities to give reasonable error limits for the results. Examples are finally given from the most extensive study using the cluster model, the one of oxygen formation at the oxygen-evolving complex in photosystem II.

  17. Predicting healthcare outcomes in prematurely born infants using cluster analysis.

    Science.gov (United States)

    MacBean, Victoria; Lunt, Alan; Drysdale, Simon B; Yarzi, Muska N; Rafferty, Gerrard F; Greenough, Anne

    2018-05-23

    Prematurely born infants are at high risk of respiratory morbidity following neonatal unit discharge, though prediction of outcomes is challenging. We have tested the hypothesis that cluster analysis would identify discrete groups of prematurely born infants with differing respiratory outcomes during infancy. A total of 168 infants (median (IQR) gestational age 33 (31-34) weeks) were recruited in the neonatal period from consecutive births in a tertiary neonatal unit. The baseline characteristics of the infants were used to classify them into hierarchical agglomerative clusters. Rates of viral lower respiratory tract infections (LRTIs) were recorded for 151 infants in the first year after birth. Infants could be classified according to birth weight and duration of neonatal invasive mechanical ventilation (MV) into three clusters. Cluster one (MV ≤5 days) had few LRTIs. Clusters two and three (both MV ≥6 days, but BW ≥or <882 g respectively), had significantly higher LRTI rates. Cluster two had a higher proportion of infants experiencing respiratory syncytial virus LRTIs (P = 0.01) and cluster three a higher proportion of rhinovirus LRTIs (P < 0.001) CONCLUSIONS: Readily available clinical data allowed classification of prematurely born infants into one of three distinct groups with differing subsequent respiratory morbidity in infancy. © 2018 Wiley Periodicals, Inc.

  18. Proteolytic Enzymes Clustered in Specialized Plasma-Membrane Domains Drive Endothelial Cells' Migration.

    Directory of Open Access Journals (Sweden)

    Monica Salamone

    Full Text Available In vitro cultured endothelial cells forming a continuous monolayer establish stable cell-cell contacts and acquire a "resting" phenotype; on the other hand, when growing in sparse conditions these cells acquire a migratory phenotype and invade the empty area of the culture. Culturing cells in different conditions, we compared expression and clustering of proteolytic enzymes in cells having migratory versus stationary behavior. In order to observe resting and migrating cells in the same microscopic field, a continuous cell monolayer was wounded. Increased expression of proteolytic enzymes was evident in cell membranes of migrating cells especially at sprouting sites and in shed membrane vesicles. Gelatin zymography and western blotting analyses confirmed that in migrating cells, expression of membrane-bound and of vesicle-associated proteolytic enzymes are increased. The enzymes concerned include MMP-2, MMP-9, MT1-MMP, seprase, DPP4 (DiPeptidyl Peptidase 4 and uPA. Shed membrane vesicles were shown to exert degradative activity on ECM components and produce substrates facilitating cell migration. Vesicles shed by migrating cells degraded ECM components at an increased rate; as a result their effect on cell migration was amplified. Inhibiting either Matrix Metallo Proteases (MMPs or Serine Integral Membrane Peptidases (SIMPs caused a decrease in the stimulatory effect of vesicles, inhibiting the spontaneous migratory activity of cells; a similar result was also obtained when a monoclonal antibody acting on DPP4 was tested. We conclude that proteolytic enzymes have a synergistic stimulatory effect on cell migration and that their clustering probably facilitates the proteolytic activation cascades needed to produce maximal degradative activity on cell substrates during the angiogenic process.

  19. Proteolytic Enzymes Clustered in Specialized Plasma-Membrane Domains Drive Endothelial Cells' Migration.

    Science.gov (United States)

    Salamone, Monica; Carfì Pavia, Francesco; Ghersi, Giulio

    2016-01-01

    In vitro cultured endothelial cells forming a continuous monolayer establish stable cell-cell contacts and acquire a "resting" phenotype; on the other hand, when growing in sparse conditions these cells acquire a migratory phenotype and invade the empty area of the culture. Culturing cells in different conditions, we compared expression and clustering of proteolytic enzymes in cells having migratory versus stationary behavior. In order to observe resting and migrating cells in the same microscopic field, a continuous cell monolayer was wounded. Increased expression of proteolytic enzymes was evident in cell membranes of migrating cells especially at sprouting sites and in shed membrane vesicles. Gelatin zymography and western blotting analyses confirmed that in migrating cells, expression of membrane-bound and of vesicle-associated proteolytic enzymes are increased. The enzymes concerned include MMP-2, MMP-9, MT1-MMP, seprase, DPP4 (DiPeptidyl Peptidase 4) and uPA. Shed membrane vesicles were shown to exert degradative activity on ECM components and produce substrates facilitating cell migration. Vesicles shed by migrating cells degraded ECM components at an increased rate; as a result their effect on cell migration was amplified. Inhibiting either Matrix Metallo Proteases (MMPs) or Serine Integral Membrane Peptidases (SIMPs) caused a decrease in the stimulatory effect of vesicles, inhibiting the spontaneous migratory activity of cells; a similar result was also obtained when a monoclonal antibody acting on DPP4 was tested. We conclude that proteolytic enzymes have a synergistic stimulatory effect on cell migration and that their clustering probably facilitates the proteolytic activation cascades needed to produce maximal degradative activity on cell substrates during the angiogenic process.

  20. Proteolytic Enzymes Clustered in Specialized Plasma-Membrane Domains Drive Endothelial Cells’ Migration

    Science.gov (United States)

    Salamone, Monica; Carfì Pavia, Francesco

    2016-01-01

    In vitro cultured endothelial cells forming a continuous monolayer establish stable cell-cell contacts and acquire a “resting” phenotype; on the other hand, when growing in sparse conditions these cells acquire a migratory phenotype and invade the empty area of the culture. Culturing cells in different conditions, we compared expression and clustering of proteolytic enzymes in cells having migratory versus stationary behavior. In order to observe resting and migrating cells in the same microscopic field, a continuous cell monolayer was wounded. Increased expression of proteolytic enzymes was evident in cell membranes of migrating cells especially at sprouting sites and in shed membrane vesicles. Gelatin zymography and western blotting analyses confirmed that in migrating cells, expression of membrane-bound and of vesicle-associated proteolytic enzymes are increased. The enzymes concerned include MMP-2, MMP-9, MT1-MMP, seprase, DPP4 (DiPeptidyl Peptidase 4) and uPA. Shed membrane vesicles were shown to exert degradative activity on ECM components and produce substrates facilitating cell migration. Vesicles shed by migrating cells degraded ECM components at an increased rate; as a result their effect on cell migration was amplified. Inhibiting either Matrix Metallo Proteases (MMPs) or Serine Integral Membrane Peptidases (SIMPs) caused a decrease in the stimulatory effect of vesicles, inhibiting the spontaneous migratory activity of cells; a similar result was also obtained when a monoclonal antibody acting on DPP4 was tested. We conclude that proteolytic enzymes have a synergistic stimulatory effect on cell migration and that their clustering probably facilitates the proteolytic activation cascades needed to produce maximal degradative activity on cell substrates during the angiogenic process. PMID:27152413

  1. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency...

  2. Enzyme

    Science.gov (United States)

    Enzymes are complex proteins that cause a specific chemical change in all parts of the body. For ... use them. Blood clotting is another example of enzymes at work. Enzymes are needed for all body ...

  3. Impulsivity facets’ predictive relations with DSM-5 PTSD symptom clusters

    Science.gov (United States)

    Roley, Michelle E.; Contractor, Ateka A.; Weiss, Nicole H.; Armour, Cherie; Elhai, Jon D.

    2017-01-01

    Objective Posttraumatic Stress Disorder (PTSD) has a well-established theoretical and empirical relation with impulsivity. Prior research has not used a multidimensional approach for measuring both PTSD and impulsivity constructs when assessing their relationship. Method The current study assessed the unique relationship of impulsivity facets on PTSD symptom clusters among a non-clinical sample of 412 trauma-exposed adults. Results Linear regression analyses revealed that impulsivity facets best accounted for PTSD’s arousal symptoms. The negative urgency facet of impulsivity was most predictive, as it was associated with all of PTSD’s symptom clusters. Sensation seeking did not predict PTSD’s intrusion symptoms, but did predict the other symptom clusters of PTSD. Lack of perseverance only predicted intrusion symptoms, while lack of premeditation only predicted PTSD’s mood/cognition symptoms. Conclusions Results extend theoretical and empirical research on the impulsivity-PTSD relationship, suggesting that impulsivity facets may serve as both risk and protective factors for PTSD symptoms. PMID:27243571

  4. Which clustering algorithm is better for predicting protein complexes?

    Directory of Open Access Journals (Sweden)

    Moschopoulos Charalampos N

    2011-12-01

    Full Text Available Abstract Background Protein-Protein interactions (PPI play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks. Results In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H and Tandem Affinity Purification (TAP methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases. Conclusions While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm

  5. Cluster analysis as a prediction tool for pregnancy outcomes.

    Science.gov (United States)

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  6. Comparison of Cluster Lensing Profiles with Lambda CDM Predictions

    Energy Technology Data Exchange (ETDEWEB)

    Broadhurst, Tom; /Tel Aviv U.; Umetsu, Keiichi; /Taipei, Inst. Astron. Astrophys.; Medezinski, Elinor; /Tel Aviv U.; Oguri, Masamune; /KIPAC, Menlo Park; Rephaeli, Yoel; /Tel Aviv U. /San Diego, CASS

    2008-05-21

    We derive lens distortion and magnification profiles of four well known clusters observed with Subaru. Each cluster is very well fitted by the general form predicted for Cold Dark Matter (CDM) dominated halos, with good consistency found between the independent distortion and magnification measurements. The inferred level of mass concentration is surprisingly high, 8 < c{sub vir} < 15 ( = 10.39 {+-} 0.91), compared to the relatively shallow profiles predicted by the {Lambda}CDM model, c{sub vir} = 5.06 {+-} 1.10 (for = 1.25 x 10{sup 15} M{sub {circle_dot}}/h). This represents a 4{sigma} discrepancy, and includes the relatively modest effects of projection bias and profile evolution derived from N-body simulations, which oppose each other with little residual effect. In the context of CDM based cosmologies, this discrepancy implies some modification of the widely assumed spectrum of initial density perturbations, so clusters collapse earlier (z {ge} 1) than predicted (z < 0.5) when the Universe was correspondingly denser.

  7. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

    Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

  8. DEEPre: sequence-based enzyme EC number prediction by deep learning

    KAUST Repository

    Li, Yu

    2017-10-20

    Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number.We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manuallycrafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre\\'s ability to capture the functional difference of enzyme isoforms.The server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre.

  9. DEEPre: sequence-based enzyme EC number prediction by deep learning

    KAUST Repository

    Li, Yu; Wang, Sheng; Umarov, Ramzan; Xie, Bingqing; Fan, Ming; Li, Lihua; Gao, Xin

    2017-01-01

    Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number.We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manuallycrafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre's ability to capture the functional difference of enzyme isoforms.The server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre.

  10. HotRegion: a database of predicted hot spot clusters.

    Science.gov (United States)

    Cukuroglu, Engin; Gursoy, Attila; Keskin, Ozlem

    2012-01-01

    Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

  11. PSPP: a protein structure prediction pipeline for computing clusters.

    Directory of Open Access Journals (Sweden)

    Michael S Lee

    2009-07-01

    Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

  12. In silico prediction of potential chemical reactions mediated by human enzymes.

    Science.gov (United States)

    Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

    2018-06-13

    Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

  13. EnzML: multi-label prediction of enzyme classes using InterPro signatures

    Directory of Open Access Journals (Sweden)

    De Ferrari Luna

    2012-04-01

    Full Text Available Abstract Background Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function. Results We present EnzML, a multi-label classification method that can efficiently account also for proteins with multiple enzymatic functions: 50,000 in UniProt. EnzML was evaluated using a standard set of 300,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commission (EC annotations. EnzML achieved more than 98% subset accuracy (exact match of all correct Enzyme Commission classes of a protein for the entire dataset and between 87 and 97% subset accuracy in reannotating eight entire proteomes: human, mouse, rat, mouse-ear cress, fruit fly, the S. pombe yeast, the E. coli bacterium and the M. jannaschii archaebacterium. To understand the role played by the dataset size, we compared the cross-evaluation results of smaller datasets, either constructed at random or from specific taxonomic domains such as archaea, bacteria, fungi, invertebrates, plants and vertebrates. The results were confirmed even when the redundancy in the dataset was reduced using UniRef100, UniRef90 or UniRef50 clusters. Conclusions InterPro signatures are a compact and powerful attribute space for the prediction of enzymatic function. This representation makes multi-label machine learning feasible in reasonable time (30 minutes to train on 300,747 instances with 10,852 attributes and 2,201 class values using the Mulan Binary Relevance Nearest Neighbours algorithm implementation (BR-kNN.

  14. Theoretical predictions for vehicular headways and their clusters

    Science.gov (United States)

    Krbálek, Milan

    2013-11-01

    This paper presents a derivation of analytical predictions for steady-state distributions of netto time gaps among clusters of vehicles moving inside a traffic stream. Using the thermodynamic socio-physical traffic model with short-ranged repulsion between particles (originally introduced in Krbálek and Helbing 2004 Physica A 333 370) we first derive the time-clearance distribution in the model and confront it with relation to the theoretical criteria for the acceptability of analytical clearance distributions. Consecutively, the approximating statistical distributions for the so-called time multi-clearances are calculated by means of the theory of functional convolutions. Moreover, all the theoretical surmises used during the above-mentioned calculations are evaluated by the statistical analysis of traffic data. The mathematical predictions acquired in this paper are thoroughly compared with relevant empirical quantities and discussed in the context of traffic theory.

  15. Ternary alloy material prediction using genetic algorithm and cluster expansion

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Chong [Iowa State Univ., Ames, IA (United States)

    2015-12-01

    This thesis summarizes our study on the crystal structures prediction of Fe-V-Si system using genetic algorithm and cluster expansion. Our goal is to explore and look for new stable compounds. We started from the current ten known experimental phases, and calculated formation energies of those compounds using density functional theory (DFT) package, namely, VASP. The convex hull was generated based on the DFT calculations of the experimental known phases. Then we did random search on some metal rich (Fe and V) compositions and found that the lowest energy structures were body centered cube (bcc) underlying lattice, under which we did our computational systematic searches using genetic algorithm and cluster expansion. Among hundreds of the searched compositions, thirteen were selected and DFT formation energies were obtained by VASP. The stability checking of those thirteen compounds was done in reference to the experimental convex hull. We found that the composition, 24-8-16, i.e., Fe3VSi2 is a new stable phase and it can be very inspiring to the future experiments.

  16. Prediction (early recognition) of emerging flu strain clusters

    Science.gov (United States)

    Li, X.; Phillips, J. C.

    2017-08-01

    Early detection of incipient dominant influenza strains is one of the key steps in the design and manufacture of an effective annual influenza vaccine. Here we report the most current results for pandemic H3N2 flu vaccine design. A 2006 model of dimensional reduction (compaction) of viral mutational complexity derives two-dimensional Cartesian mutational maps (2DMM) that exhibit an emergent dominant strain as a small and distinct cluster of as few as 10 strains. We show that recent extensions of this model can detect incipient strains one year or more in advance of their dominance in the human population. Our structural interpretation of our unexpectedly rich 2DMM involves sialic acid, and is based on nearly 6000 strains in a series of recent 3-year time windows. Vaccine effectiveness is predicted best by analyzing dominant mutational epitopes.

  17. Operational Numerical Weather Prediction systems based on Linux cluster architectures

    International Nuclear Information System (INIS)

    Pasqui, M.; Baldi, M.; Gozzini, B.; Maracchi, G.; Giuliani, G.; Montagnani, S.

    2005-01-01

    The progress in weather forecast and atmospheric science has been always closely linked to the improvement of computing technology. In order to have more accurate weather forecasts and climate predictions, more powerful computing resources are needed, in addition to more complex and better-performing numerical models. To overcome such a large computing request, powerful workstations or massive parallel systems have been used. In the last few years, parallel architectures, based on the Linux operating system, have been introduced and became popular, representing real high performance-low cost systems. In this work the Linux cluster experience achieved at the Laboratory far Meteorology and Environmental Analysis (LaMMA-CNR-IBIMET) is described and tips and performances analysed

  18. Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

    Science.gov (United States)

    Tolo, Isaiah; Thomas, Jonathan C.; Fischer, Rebecca S. B.; Brown, Eric L.; Gray, Barry M.

    2016-01-01

    Staphylococcus epidermidis is a ubiquitous colonizer of human skin and a common cause of medical device-associated infections. The extent to which the population genetic structure of S. epidermidis distinguishes commensal from pathogenic isolates is unclear. Previously, Bayesian clustering of 437 multilocus sequence types (STs) in the international database revealed a population structure of six genetic clusters (GCs) that may reflect the species' ecology. Here, we first verified the presence of six GCs, including two (GC3 and GC5) with significant admixture, in an updated database of 578 STs. Next, a single nucleotide polymorphism (SNP) assay was developed that accurately assigned 545 (94%) of 578 STs to GCs. Finally, the hypothesis that GCs could distinguish isolation sources was tested by SNP typing and GC assignment of 154 isolates from hospital patients with bacteremia and those with blood culture contaminants and from nonhospital carriage. GC5 was isolated almost exclusively from hospital sources. GC1 and GC6 were isolated from all sources but were overrepresented in isolates from nonhospital and infection sources, respectively. GC2, GC3, and GC4 were relatively rare in this collection. No association was detected between fdh-positive isolates (GC2 and GC4) and nonhospital sources. Using a machine learning algorithm, GCs predicted hospital and nonhospital sources with 80% accuracy and predicted infection and contaminant sources with 45% accuracy, which was comparable to the results seen with a combination of five genetic markers (icaA, IS256, sesD [bhp], mecA, and arginine catabolic mobile element [ACME]). Thus, analysis of population structure with subgenomic data shows the distinction of hospital and nonhospital sources and the near-inseparability of sources within a hospital. PMID:27076664

  19. How Do Social Capital and HIV/AIDS Outcomes Geographically Cluster and Which Sociocontextual Mechanisms Predict Differences Across Clusters?

    Science.gov (United States)

    Ransome, Yusuf; Dean, Lorraine T; Crawford, Natalie D; Metzger, David S; Blank, Michael B; Nunn, Amy S

    2017-09-01

    Place of residence has been associated with HIV transmission risks. Social capital, defined as features of social organization that improve efficiency of society by facilitating coordinated actions, often varies by neighborhood, and hypothesized to have protective effects on HIV care continuum outcomes. We examined whether the association between social capital and 2 HIV care continuum outcomes clustered geographically and whether sociocontextual mechanisms predict differences across clusters. Bivariate Local Moran's I evaluated geographical clustering in the association between social capital (participation in civic and social organizations, 2006, 2008, 2010) and [5-year (2007-2011) prevalence of late HIV diagnosis and linkage to HIV care] across Philadelphia, PA, census tracts (N = 378). Maps documented the clusters and multinomial regression assessed which sociocontextual mechanisms (eg, racial composition) predict differences across clusters. We identified 4 significant clusters (high social capital-high HIV/AIDS, low social capital-low HIV/AIDS, low social capital-high HIV/AIDS, and high social capital-low HIV/AIDS). Moran's I between social capital and late HIV diagnosis was (I = 0.19, z = 9.54, P social capital was lowest and HIV burden the highest, compared with clusters with high social capital and lowest HIV burden. The association between social participation and HIV care continuum outcomes cluster geographically in Philadelphia, PA. HIV prevention interventions should account for this phenomenon. Reducing geographic disparities will require interventions tailored to each continuum step and that address socioeconomic factors such as neighborhood median income.

  20. Crius: A Novel Fragment-Based Algorithm of De Novo Substrate Prediction for Enzymes.

    Science.gov (United States)

    Yao, Zhiqiang; Jiang, Shuiqin; Zhang, Lujia; Gao, Bei; He, Xiao; Zhang, John Z H; Wei, Dongzhi

    2018-05-03

    The study of enzyme substrate specificity is vital for developing potential applications of enzymes. However, the routine experimental procedures require lot of resources in the discovery of novel substrates. This article reports an in silico structure-based algorithm called Crius, which predicts substrates for enzyme. The results of this fragment-based algorithm show good agreements between the simulated and experimental substrate specificities, using a lipase from Candida antarctica (CALB), a nitrilase from Cyanobacterium syechocystis sp. PCC6803 (Nit6803), and an aldo-keto reductase from Gluconobacter oxydans (Gox0644). This opens new prospects of developing computer algorithms that can effectively predict substrates for an enzyme. This article is protected by copyright. All rights reserved. © 2018 The Protein Society.

  1. Prediction of Detailed Enzyme Functions and Identification of Specificity Determining Residues by Random Forests

    Science.gov (United States)

    Nagao, Chioko; Nagano, Nozomi; Mizuguchi, Kenji

    2014-01-01

    Determining enzyme functions is essential for a thorough understanding of cellular processes. Although many prediction methods have been developed, it remains a significant challenge to predict enzyme functions at the fourth-digit level of the Enzyme Commission numbers. Functional specificity of enzymes often changes drastically by mutations of a small number of residues and therefore, information about these critical residues can potentially help discriminate detailed functions. However, because these residues must be identified by mutagenesis experiments, the available information is limited, and the lack of experimentally verified specificity determining residues (SDRs) has hindered the development of detailed function prediction methods and computational identification of SDRs. Here we present a novel method for predicting enzyme functions by random forests, EFPrf, along with a set of putative SDRs, the random forests derived SDRs (rf-SDRs). EFPrf consists of a set of binary predictors for enzymes in each CATH superfamily and the rf-SDRs are the residue positions corresponding to the most highly contributing attributes obtained from each predictor. EFPrf showed a precision of 0.98 and a recall of 0.89 in a cross-validated benchmark assessment. The rf-SDRs included many residues, whose importance for specificity had been validated experimentally. The analysis of the rf-SDRs revealed both a general tendency that functionally diverged superfamilies tend to include more active site residues in their rf-SDRs than in less diverged superfamilies, and superfamily-specific conservation patterns of each functional residue. EFPrf and the rf-SDRs will be an effective tool for annotating enzyme functions and for understanding how enzyme functions have diverged within each superfamily. PMID:24416252

  2. Enzyme clusters during the metamorphic period of Ambystoma mexicanum: role of thyroid hormone

    NARCIS (Netherlands)

    Lamers, W. H.; Mooren, P. G.; de Graaf, A.

    1982-01-01

    Enzyme activities and DNA content have been measure in axolotl liver during the metamorphic period (4-8 months after spawning). Three different types of enzyme activity profiles were observed. In the type I profile (carbamoyl-phosphate synthase, arginase, ornithine transcarbamoylase, and glutamate

  3. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    Science.gov (United States)

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  4. A Deep Learning Prediction Model Based on Extreme-Point Symmetric Mode Decomposition and Cluster Analysis

    OpenAIRE

    Li, Guohui; Zhang, Songling; Yang, Hong

    2017-01-01

    Aiming at the irregularity of nonlinear signal and its predicting difficulty, a deep learning prediction model based on extreme-point symmetric mode decomposition (ESMD) and clustering analysis is proposed. Firstly, the original data is decomposed by ESMD to obtain the finite number of intrinsic mode functions (IMFs) and residuals. Secondly, the fuzzy c-means is used to cluster the decomposed components, and then the deep belief network (DBN) is used to predict it. Finally, the reconstructed ...

  5. Data characterizing the energetics of enzyme-catalyzed hydrolysis and transglycosylation reactions by DFT cluster model calculations

    Directory of Open Access Journals (Sweden)

    Jitrayut Jitonnom

    2018-04-01

    Full Text Available The data presented in this paper are related to the research article entitled “QM/MM modeling of the hydrolysis and transfructosylation reactions of fructosyltransferase from Aspergillus japonicas, an enzyme that produces prebiotic fructooligosaccharide” (Jitonnom et al., 2018 [1]. This paper presents the procedure and data for characterizing the whole relative energy profiles of hydrolysis and transglycosylation reactions whose elementary steps differ in chemical composition. The data also reflects the choices of the QM cluster model, the functional/basis set method and the equations in determining the reaction energetics.

  6. Tuberculosis outbreaks predicted by characteristics of first patients in a DNA fingerprint cluster.

    Science.gov (United States)

    Kik, Sandra V; Verver, Suzanne; van Soolingen, Dick; de Haas, Petra E W; Cobelens, Frank G; Kremer, Kristin; van Deutekom, Henk; Borgdorff, Martien W

    2008-07-01

    Some clusters of patients who have Mycobacterium tuberculosis isolates with identical DNA fingerprint patterns grow faster than others. It is unclear what predictors determine cluster growth. To assess whether the development of a tuberculosis (TB) outbreak can be predicted by the characteristics of its first two patients. Demographic and clinical data of all culture-confirmed patients with TB in the Netherlands from 1993 through 2004 were combined with DNA fingerprint data. Clusters were restricted to cluster episodes of 2 years to only detect newly arising clusters. Characteristics of the first two patients were compared between small (2-4 cases) and large (5 or more cases) cluster episodes. Of 5,454 clustered cases, 1,756 (32%) were part of a cluster episode of 2 years. Of 622 cluster episodes, 54 (9%) were large and 568 (91%) were small episodes. Independent predictors for large cluster episodes were as follows: less than 3 months' time between the diagnosis of the first two patients, one or both patients were young (<35 yr), both patients lived in an urban area, and both patients came from sub-Saharan Africa. In the Netherlands, patients in new cluster episodes should be screened for these risk factors. When the risk pattern applies, targeted interventions (e.g., intensified contact investigation) should be considered to prevent further cluster expansion.

  7. Predicting novel substrates for enzymes with minimal experimental effort with active learning.

    Science.gov (United States)

    Pertusi, Dante A; Moura, Matthew E; Jeffryes, James G; Prabhu, Siddhant; Walters Biggs, Bradley; Tyo, Keith E J

    2017-11-01

    Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes, developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of ~80% using ~33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  8. Predicting novel substrates for enzymes with minimal experimental effort with active learning

    Energy Technology Data Exchange (ETDEWEB)

    Pertusi, Dante A.; Moura, Matthew E.; Jeffryes, James G.; Prabhu, Siddhant; Walters Biggs, Bradley; Tyo, Keith E. J.

    2017-11-01

    Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes, developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of similar to 80% using similar to 33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways.

  9. Link-Prediction Enhanced Consensus Clustering for Complex Networks (Open Access)

    Science.gov (United States)

    2016-05-20

    RESEARCH ARTICLE Link-Prediction Enhanced Consensus Clustering for Complex Networks Matthew Burgess1*, Eytan Adar1,2, Michael Cafarella1 1Computer...consensus clustering algorithm to enhance community detection on incomplete networks. Our framework utilizes existing community detection algorithms that...types of complex networks exhibit community structure: groups of highly connected nodes. Communities or clusters often reflect nodes that share similar

  10. Descriptive and predictive assessment of enzyme activity and enzyme related processes in biorefinery using IR spectroscopy and chemometrics

    DEFF Research Database (Denmark)

    Baum, Andreas

    the understanding of the structural properties of the extracted pectin. Secondly, enzyme kinetics of biomass converting enzymes was examined in terms of measuring enzyme activity by spectral evolution profiling utilizing FTIR. Chemometric multiway methods were used to analyze the tensor datasets enabling the second......-order calibration advantage (reference Theory of Analytical chemistry). As PAPER 3 illustrates the method is universally applicable without the need of any external standards and was exemplified by performing quantitative enzyme activity determinations for glucose oxidase, pectin lyase and a cellolytic enzyme blend...... (Celluclast 1.5L). In PAPER 4, the concept is extended to quantify enzyme activity of two simultaneously acting enzymes, namely pectin lyase and pectin methyl esterase. By doing so the multiway methods PARAFAC, TUCKER3 and NPLS were compared and evaluated towards accuracy and precision....

  11. Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon

    Directory of Open Access Journals (Sweden)

    Moumita Saha

    2016-01-01

    Full Text Available Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models.

  12. STOCK MARKET PREDICTION USING CLUSTERING WITH META-HEURISTIC APPROACHES

    OpenAIRE

    Prasanna, S.; Ezhilmaran, D.

    2015-01-01

    Various examinations are performed to predict the stock values, yet not many points at assessing the predictability of the direction of stock index movement. Stock market prediction with data mining method is a standout amongst the most paramount issues to be researched and it is one of the interesting issues of stock market research over several decades. The approach of advanced data mining tools and refined database innovations has empowered specialists to handle the immense measure of data...

  13. STOCK MARKET PREDICTION USING CLUSTERING WITH META-HEURISTIC APPROACHES

    OpenAIRE

    Prasanna, S.; Ezhilmaran, D.

    2014-01-01

    Various examinations are performed to predict the stock values, yet not many points at assessing the predictability of the direction of stock index movement. Stock market prediction with data mining method is a standout amongst the most paramount issues to be researched and it is one of the interesting issues of stock market research over several decades. The approach of advanced data mining tools and refined database innovations has empowered specialists to handle the immense measure of data...

  14. Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

    Science.gov (United States)

    Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

    2017-11-01

    Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

    Energy Technology Data Exchange (ETDEWEB)

    Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard [Department of Physics, Carleton University, Ottawa, Ontario K1S 5B6 (Canada); Wells, R. Glenn; Birnie, David; Ruddy, Terrence D. [Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario K1Y 4W7 (Canada)

    2014-07-15

    Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster

  16. Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

    International Nuclear Information System (INIS)

    Lalonde, Michel; Wassenaar, Richard; Wells, R. Glenn; Birnie, David; Ruddy, Terrence D.

    2014-01-01

    Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster

  17. Hybrid Clustering-GWO-NARX neural network technique in predicting stock price

    Science.gov (United States)

    Das, Debashish; Safa Sadiq, Ali; Mirjalili, Seyedali; Noraziah, A.

    2017-09-01

    Prediction of stock price is one of the most challenging tasks due to nonlinear nature of the stock data. Though numerous attempts have been made to predict the stock price by applying various techniques, yet the predicted price is not always accurate and even the error rate is high to some extent. Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. The study uses stock data from prominent stock market i.e. New York Stock Exchange (NYSE), NASDAQ and emerging stock market i.e. Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. The prediction performance gained through experimentation is compared and assessed to guide the investors in making investment decision. The result through this technique is indeed promising as it has shown almost precise prediction and improved error rate. We have applied the hybrid Clustering-GWO-NARX neural network technique in predicting stock price. We intend to work with the effect of various factors in stock price movement and selection of parameters. We will further investigate the influence of company news either positive or negative in stock price movement. We would be also interested to predict the Stock indices.

  18. Muscle enzyme release does not predict muscle function impairment after triathlon.

    Science.gov (United States)

    Margaritis, I; Tessier, F; Verdera, F; Bermon, S; Marconnet, P

    1999-06-01

    We sought to determine the effects of a long distance triathlon (4 km swim, 120 km bike-ride, and 30 km run) on the four-day kinetics of the biochemical markers of muscle damage, and whether they were quantitatively linked with muscle function impairment and soreness. Data were collected from 2 days before until 4 days after the completion of the race. Twelve triathletes performed the triathlon and five did not. Maximal voluntary contraction (MVC), muscle soreness (DOMS) and total serum CK, CK-MB, LDH, AST and ALT activities were assessed. Significant changes after triathlon completion were found for all muscle damage indirect markers over time (p triathlon. Long distance triathlon race caused muscle damage, but extent, as well as muscle recovery cannot be evaluated by the magnitude of changes in serum enzyme activities. Muscle enzyme release cannot be used to predict the magnitude of the muscle function impairment caused by muscle damage.

  19. A cluster expansion model for predicting activation barrier of atomic processes

    International Nuclear Information System (INIS)

    Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit

    2013-01-01

    We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog

  20. High endothelin-converting enzyme-1 expression independently predicts poor survival of patients with esophageal squamous cell carcinoma.

    Science.gov (United States)

    Wu, Ching-Fang; Lee, Ching-Tai; Kuo, Yao-Hung; Chen, Tzu-Haw; Chang, Chi-Yang; Chang, I-Wei; Wang, Wen-Lun

    2017-09-01

    Patients with esophageal squamous cell carcinoma have poor survival and high recurrence rate, thus an effective prognostic biomarker is needed. Endothelin-converting enzyme-1 is responsible for biosynthesis of endothelin-1, which promotes growth and invasion of human cancers. The role of endothelin-converting enzyme-1 in esophageal squamous cell carcinoma is still unknown. Therefore, this study investigated the significance of endothelin-converting enzyme-1 expression in esophageal squamous cell carcinoma clinically. We enrolled patients with esophageal squamous cell carcinoma who provided pretreated tumor tissues. Tumor endothelin-converting enzyme-1 expression was evaluated by immunohistochemistry and was defined as either low or high expression. Then we evaluated whether tumor endothelin-converting enzyme-1 expression had any association with clinicopathological findings or predicted survival of patients with esophageal squamous cell carcinoma. Overall, 54 of 99 patients with esophageal squamous cell carcinoma had high tumor endothelin-converting enzyme-1 expression, which was significantly associated with lymph node metastasis ( p = 0.04). In addition, tumor endothelin-converting enzyme-1 expression independently predicted survival of patients with esophageal squamous cell carcinoma, and the 5-year survival was poorer in patients with high tumor endothelin-converting enzyme-1 expression ( p = 0.016). Among patients with locally advanced and potentially resectable esophageal squamous cell carcinoma (stage II and III), 5-year survival was poorer with high tumor endothelin-converting enzyme-1 expression ( p = 0.003). High tumor endothelin-converting enzyme-1 expression also significantly predicted poorer survival of patients in this population. In patients with esophageal squamous cell carcinoma, high tumor endothelin-converting enzyme-1 expression might indicate high tumor invasive property. Therefore, tumor endothelin-converting enzyme-1 expression

  1. FLOCK cluster analysis of mast cell event clustering by high-sensitivity flow cytometry predicts systemic mastocytosis.

    Science.gov (United States)

    Dorfman, David M; LaPlante, Charlotte D; Pozdnyakova, Olga; Li, Betty

    2015-11-01

    In our high-sensitivity flow cytometric approach for systemic mastocytosis (SM), we identified mast cell event clustering as a new diagnostic criterion for the disease. To objectively characterize mast cell gated event distributions, we performed cluster analysis using FLOCK, a computational approach to identify cell subsets in multidimensional flow cytometry data in an unbiased, automated fashion. FLOCK identified discrete mast cell populations in most cases of SM (56/75 [75%]) but only a minority of non-SM cases (17/124 [14%]). FLOCK-identified mast cell populations accounted for 2.46% of total cells on average in SM cases and 0.09% of total cells on average in non-SM cases (P < .0001) and were predictive of SM, with a sensitivity of 75%, a specificity of 86%, a positive predictive value of 76%, and a negative predictive value of 85%. FLOCK analysis provides useful diagnostic information for evaluating patients with suspected SM, and may be useful for the analysis of other hematopoietic neoplasms. Copyright© by the American Society for Clinical Pathology.

  2. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  3. Clustering gene expression data based on predicted differential effects of GV interaction.

    Science.gov (United States)

    Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

    2005-02-01

    Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

  4. Terrestrial irradiation-sunshine duration clustering and prediction

    International Nuclear Information System (INIS)

    Sen, Zekai; Oeztopal, Ahmet

    2003-01-01

    The relationship between terrestrial irradiance and sunshine duration is not crisp and there are scatters around a general trend, which most often is expressed to occur in the form of a linear expression. This study presents a way of grouping the solar irradiation-sunshine duration data into convenient seasonal subgroups and then makes predictions within each of the groups quantitatively. In the classical Angstroem or other approaches, the seasonal variations are not considered, and therefore, rather global parameter estimations are obtained. However, the seasonal methodology of this paper provides more detailed interpretations in addition to seasonal effects and parameter estimations

  5. Magnetically triggered clustering of biotinylated iron oxide nanoparticles in the presence of streptavidinylated enzymes

    International Nuclear Information System (INIS)

    Hodenius, Michael; De Cuyper, Marcel; Hieronymus, Thomas; Zenke, Martin; Becker, Christiane; Elling, Lothar; Bornemann, Jörg; Wong, John E; Richtering, Walter; Himmelreich, Uwe

    2012-01-01

    This work deals with the production and characterization of water-compatible, iron oxide based nanoparticles covered with functional poly(ethylene glycol) (PEG)–biotin surface groups (SPIO–PEG–biotin). Synthesis of the functionalized colloids occurred by incubating the oleate coated particles used as precursor magnetic fluid with anionic liposomes containing 14 mol% of a phospholipid–PEG–biotin conjugate. The latter was prepared by coupling dimyristoylphosphatidylethanolamine (DC 14:0 PE) to activated α-biotinylamido-ω –N-hydroxy-succinimidcarbonyl–PEG (NHS–PEG–biotin). Physical characterization of the oleate and PEG–biotin iron oxide nanocolloids revealed that they appear as colloidal stable clusters with a hydrodynamic diameter of 160 nm and zeta potentials of − 39 mV (oleate coated particles) and − 14 mV (PEG–biotin covered particles), respectively, as measured by light scattering techniques. Superconducting quantum interference device (SQUID) measurements revealed specific saturation magnetizations of 62–73 emu g −1 Fe 3 O 4 and no hysteresis was observed at 300 K. MR relaxometry at 3 T revealed very high r 2 relaxivities and moderately high r 1 values. Thus, both nanocolloids can be classified as small, superparamagnetic, negative MR contrast agents. The capacity to functionalize the particles was illustrated by binding streptavidin alkaline phosphatase (SAP). It was found, however, that these complexes become highly aggregated after capturing them on the magnetic filter device during high-gradient magnetophoresis, thereby reducing the accessibility of the SAP. (paper)

  6. Mass distribution and multiple fragmentation events in high energy cluster-cluster collisions: evidence for a predicted phase transition

    International Nuclear Information System (INIS)

    Farizon, B.; Farizon, M.; Gaillard, M.J.; Genre, R.; Louc, S.; Martin, J.; Senn, G.; Scheier, P.; Maerk, T.D.

    1996-09-01

    Fragment size distributions including multiple fragmentation events have been measured for high energy H 25 + cluster ions (60 keV/amu) colliding with a neutral C 60 target. In contrast to earlier collision experiments with a helium target the present studies do not show a U-shaped fragment mass distribution, but a single power-law falloff with increasing fragment mass. This behaviour is similar to what is known for the intermediate regime in nuclear collision physics and thus confirms a recently predicted scaling from nuclear to molecular collisions

  7. Carbonate reservoir characterization with lithofacies clustering and porosity prediction

    International Nuclear Information System (INIS)

    Al Moqbel, Abdulrahman; Wang, Yanghua

    2011-01-01

    One of the objectives in reservoir characterization is to quantitatively or semi-quantitatively map the spatial distribution of its heterogeneity and related properties. With the availability of 3D seismic data, artificial neural networks are capable of discovering the nonlinear relationship between seismic attributes and reservoir parameters. For a target carbonate reservoir, we adopt a two-stage approach to conduct characterization. First, we use an unsupervised neural network, the self-organizing map method, to classify the reservoir lithofacies. Then we apply a supervised neural network, the back-propagation algorithm, to quantitatively predict the porosity of the carbonate reservoir. Based on porosity maps at different time levels, we interpret the target reservoir vertically related to three depositional phases corresponding to, respectively, a lowstand system tract before sea water immersion, a highstand system tract when water covers organic deposits and a transition zone for the sea level falling. The highstand system is the most prospective zone, given the organic content deposited during this stage. The transition zone is also another prospective feature in the carbonate depositional system due to local build-ups

  8. Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data

    Directory of Open Access Journals (Sweden)

    Hendrik Treutler

    2016-10-01

    Full Text Available Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92 % of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0.

  9. Symptom clusters predict mortality among dialysis patients in Norway: a prospective observational cohort study.

    Science.gov (United States)

    Amro, Amin; Waldum, Bård; von der Lippe, Nanna; Brekke, Fredrik Barth; Dammen, Toril; Miaskowski, Christine; Os, Ingrid

    2015-01-01

    Patients with end-stage renal disease on dialysis have reduced survival rates compared with the general population. Symptoms are frequent in dialysis patients, and a symptom cluster is defined as two or more related co-occurring symptoms. The aim of this study was to explore the associations between symptom clusters and mortality in dialysis patients. In a prospective observational cohort study of dialysis patients (n = 301), Kidney Disease and Quality of Life Short Form and Beck Depression Inventory questionnaires were administered. To generate symptom clusters, principal component analysis with varimax rotation was used on 11 kidney-specific self-reported physical symptoms. A Beck Depression Inventory score of 16 or greater was defined as clinically significant depressive symptoms. Physical and mental component summary scores were generated from Short Form-36. Multivariate Cox regression analysis was used for the survival analysis, Kaplan-Meier curves and log-rank statistics were applied to compare survival rates between the groups. Three different symptom clusters were identified; one included loading of several uremic symptoms. In multivariate analyses and after adjustment for health-related quality of life and depressive symptoms, the worst perceived quartile of the "uremic" symptom cluster independently predicted all-cause mortality (hazard ratio 2.47, 95% CI 1.44-4.22, P = 0.001) compared with the other quartiles during a follow-up period that ranged from four to 52 months. The two other symptom clusters ("neuromuscular" and "skin") or the individual symptoms did not predict mortality. Clustering of uremic symptoms predicted mortality. Assessing co-occurring symptoms rather than single symptoms may help to identify dialysis patients at high risk for mortality. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  10. Classification via Clustering for Predicting Final Marks Based on Student Participation in Forums

    Science.gov (United States)

    Lopez, M. I.; Luna, J. M.; Romero, C.; Ventura, S.

    2012-01-01

    This paper proposes a classification via clustering approach to predict the final marks in a university course on the basis of forum data. The objective is twofold: to determine if student participation in the course forum can be a good predictor of the final marks for the course and to examine whether the proposed classification via clustering…

  11. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  12. PINGU: PredIction of eNzyme catalytic residues usinG seqUence information.

    Directory of Open Access Journals (Sweden)

    Priyadarshini P Pai

    Full Text Available Identification of catalytic residues can help unveil interesting attributes of enzyme function for various therapeutic and industrial applications. Based on their biochemical roles, the number of catalytic residues and sequence lengths of enzymes vary. This article describes a prediction approach (PINGU for such a scenario. It uses models trained using physicochemical properties and evolutionary information of 650 non-redundant enzymes (2136 catalytic residues in a support vector machines architecture. Independent testing on 200 non-redundant enzymes (683 catalytic residues in predefined prediction settings, i.e., with non-catalytic per catalytic residue ranging from 1 to 30, suggested that the prediction approach was highly sensitive and specific, i.e., 80% or above, over the incremental challenges. To learn more about the discriminatory power of PINGU in real scenarios, where the prediction challenge is variable and susceptible to high false positives, the best model from independent testing was used on 60 diverse enzymes. Results suggested that PINGU was able to identify most catalytic residues and non-catalytic residues properly with 80% or above accuracy, sensitivity and specificity. The effect of false positives on precision was addressed in this study by application of predicted ligand-binding residue information as a post-processing filter. An overall improvement of 20% in F-measure and 0.138 in Correlation Coefficient with 16% enhanced precision could be achieved. On account of its encouraging performance, PINGU is hoped to have eventual applications in boosting enzyme engineering and novel drug discovery.

  13. K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

    Directory of Open Access Journals (Sweden)

    Lv Tao

    2017-01-01

    Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.

  14. Biocatalyst including porous enzyme cluster composite immobilized by two-step crosslinking and its utilization as enzymatic biofuel cell

    Science.gov (United States)

    Chung, Yongjin; Christwardana, Marcelinus; Tannia, Daniel Chris; Kim, Ki Jae; Kwon, Yongchai

    2017-08-01

    An enzyme cluster composite (TPA/GOx) formed from glucose oxidase (GOx) and terephthalaldehyde (TPA) that is coated onto polyethyleneimine (PEI) and carbon nanotubes (CNTs) is suggested as a new catalyst ([(TPA/GOx)/PEI]/CNT). In this catalyst, TPA promotes inter-GOx links by crosslinking to form a large and porous structure, and the TPA/GOx composite is again crosslinked with PEI/CNT to increase the amount of immobilized GOx. Such a two-step crosslinking (i) increases electron transfer because of electron delocalization by π conjugation and (ii) reduces GOx denaturation because of the formation of strong chemical bonds while its porosity facilitates mass transfer. With these features, an enzymatic biofuel cell (EBC) employing the new catalyst is fabricated and induces an excellent maximum power density (1.62 ± 0.08 mW cm-2), while the catalytic activity of the [(TPA/GOx)/PEI]/CNT catalyst is outstanding. This is clear evidence that the two-step crosslinking and porous structure caused by adoption of the TPA/GOx composite affect the performance enhancement of EBC.

  15. A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2004-06-01

    Full Text Available Abstract Background The PathoLogic program constructs Pathway/Genome databases by using a genome's annotation to predict the set of metabolic pathways present in an organism. PathoLogic determines the set of reactions composing those pathways from the enzymes annotated in the organism's genome. Most annotation efforts fail to assign function to 40–60% of sequences. In addition, large numbers of sequences may have non-specific annotations (e.g., thiolase family protein. Pathway holes occur when a genome appears to lack the enzymes needed to catalyze reactions in a pathway. If a protein has not been assigned a specific function during the annotation process, any reaction catalyzed by that protein will appear as a missing enzyme or pathway hole in a Pathway/Genome database. Results We have developed a method that efficiently combines homology and pathway-based evidence to identify candidates for filling pathway holes in Pathway/Genome databases. Our program not only identifies potential candidate sequences for pathway holes, but combines data from multiple, heterogeneous sources to assess the likelihood that a candidate has the required function. Our algorithm emulates the manual sequence annotation process, considering not only evidence from homology searches, but also considering evidence from genomic context (i.e., is the gene part of an operon? and functional context (e.g., are there functionally-related genes nearby in the genome? to determine the posterior belief that a candidate has the required function. The method can be applied across an entire metabolic pathway network and is generally applicable to any pathway database. The program uses a set of sequences encoding the required activity in other genomes to identify candidate proteins in the genome of interest, and then evaluates each candidate by using a simple Bayes classifier to determine the probability that the candidate has the desired function. We achieved 71% precision at a

  16. An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

    Science.gov (United States)

    Nidheesh, N; Abdul Nazeer, K A; Ameer, P M

    2017-12-01

    Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids. We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids. We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others. There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Framework for Optimizing Cluster Selection using Geo-assisted Movement Prediction

    DEFF Research Database (Denmark)

    Kristensen, Thomas Sander; Madsen, Jacob Theilgaard; Pedersen, Michael Sølvkjær

    2012-01-01

    Due to the availability of satellite- and radio-based location systems in most new devices, it is possible to use geographical location of a node for network management and communication protocol optimization. It is a common belief that usage of location information can bring performance benefits...... movement prediction and inaccurate location estimation on its performance. The proposed algorithm is compared with two reference algorithms: when a considered node associates with either the first discovered cluster or the nearest cluster. Evaluation shows significant performance benefits in terms...

  18. DYNAMIC MODELLING AND ADVANCED PREDICTIVE CONTROL OF A CONTINUOUS PROCESS OF ENZYME PURIFICATION

    Directory of Open Access Journals (Sweden)

    Dechechi E.C.

    1997-01-01

    Full Text Available A dynamic mathematical model, simulation and computer control of a Continuous Affinity Recycle Extraction (CARE process, a protein purification technique based on protein adsorption on solid-phase adsorbents is described in this work. This process, consisting of three reactors, is a multivariable process with considerable time delay in the on-line analyses of the controlled variable. An advanced predictive control configuration, specifically the Dynamic Matrix Control (DMC, was applied. The DMC algorithm was applied in process schemes where the aim was to maintain constant the enzyme concentration in the outlet of the third reactor. The performance of the DMC controller was analyzed in the feed-flow disturbances and the results are presented.

  19. clusters

    Indian Academy of Sciences (India)

    2017-09-27

    Sep 27, 2017 ... Author for correspondence (zh4403701@126.com). MS received 15 ... lic clusters using density functional theory (DFT)-GGA of the DMOL3 package. ... In the process of geometric optimization, con- vergence thresholds ..... and Postgraduate Research & Practice Innovation Program of. Jiangsu Province ...

  20. clusters

    Indian Academy of Sciences (India)

    environmental as well as technical problems during fuel gas utilization. ... adsorption on some alloys of Pd, namely PdAu, PdAg ... ried out on small neutral and charged Au24,26,27, Cu,28 ... study of Zanti et al.29 on Pdn (n = 1–9) clusters.

  1. Unmatter Entities inside Nuclei, Predicted by the Brightsen Nucleon Cluster Model

    Directory of Open Access Journals (Sweden)

    Smarandache F.

    2006-01-01

    Full Text Available Applying the R. A. Brightsen Nucleon Cluster Model of the atomic nucleus we discuss how unmatter entities (the conjugations of matter and antimatter may be formed as clusters inside a nucleus. The model supports a hypothesis that antimatter nucleon clusters are present as a parton (sensu Feynman superposition within the spatial confinement of the proton (1H1, the neutron, and the deuteron (1H2. If model predictions can be confirmed both mathematically and experimentally, a new physics is suggested. A proposed experiment is connected to othopositronium annihilation anomalies, which, being related to one of known unmatter entity, orthopositronium (built on electron and positron, opens a way to expand the Standard Model.

  2. Gravitational redshift of galaxies in clusters as predicted by general relativity.

    Science.gov (United States)

    Wojtak, Radosław; Hansen, Steen H; Hjorth, Jens

    2011-09-28

    The theoretical framework of cosmology is mainly defined by gravity, of which general relativity is the current model. Recent tests of general relativity within the Lambda Cold Dark Matter (ΛCDM) model have found a concordance between predictions and the observations of the growth rate and clustering of the cosmic web. General relativity has not hitherto been tested on cosmological scales independently of the assumptions of the ΛCDM model. Here we report an observation of the gravitational redshift of light coming from galaxies in clusters at the 99 per cent confidence level, based on archival data. Our measurement agrees with the predictions of general relativity and its modification created to explain cosmic acceleration without the need for dark energy (the f(R) theory), but is inconsistent with alternative models designed to avoid the presence of dark matter. © 2011 Macmillan Publishers Limited. All rights reserved

  3. Number of Clusters and the Quality of Hybrid Predictive Models in Analytical CRM

    Directory of Open Access Journals (Sweden)

    Łapczyński Mariusz

    2014-08-01

    Full Text Available Making more accurate marketing decisions by managers requires building effective predictive models. Typically, these models specify the probability of customer belonging to a particular category, group or segment. The analytical CRM categories refer to customers interested in starting cooperation with the company (acquisition models, customers who purchase additional products (cross- and up-sell models or customers intending to resign from the cooperation (churn models. During building predictive models researchers use analytical tools from various disciplines with an emphasis on their best performance. This article attempts to build a hybrid predictive model combining decision trees (C&RT algorithm and cluster analysis (k-means. During experiments five different cluster validity indices and eight datasets were used. The performance of models was evaluated by using popular measures such as: accuracy, precision, recall, G-mean, F-measure and lift in the first and in the second decile. The authors tried to find a connection between the number of clusters and models' quality.

  4. piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

    Science.gov (United States)

    Ray, Rishav; Pandey, Priyanka

    2017-12-19

    With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Prediction of strontium bromide laser efficiency using cluster and decision tree analysis

    Directory of Open Access Journals (Sweden)

    Iliev Iliycho

    2018-01-01

    Full Text Available Subject of investigation is a new high-powered strontium bromide (SrBr2 vapor laser emitting in multiline region of wavelengths. The laser is an alternative to the atom strontium lasers and electron free lasers, especially at the line 6.45 μm which line is used in surgery for medical processing of biological tissues and bones with minimal damage. In this paper the experimental data from measurements of operational and output characteristics of the laser are statistically processed by means of cluster analysis and tree-based regression techniques. The aim is to extract the more important relationships and dependences from the available data which influence the increase of the overall laser efficiency. There are constructed and analyzed a set of cluster models. It is shown by using different cluster methods that the seven investigated operational characteristics (laser tube diameter, length, supplied electrical power, and others and laser efficiency are combined in 2 clusters. By the built regression tree models using Classification and Regression Trees (CART technique there are obtained dependences to predict the values of efficiency, and especially the maximum efficiency with over 95% accuracy.

  6. A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm.

    Directory of Open Access Journals (Sweden)

    Daniel M de Brito

    Full Text Available Genomic Islands (GIs are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP--Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.

  7. Prediction of interindividual variation in drug plasma levels in vivo from individual enzyme kinetic data and physiologically based pharmacokinetic modeling

    NARCIS (Netherlands)

    Bogaards, J.J.P.; Hissink, E.M.; Briggs, M.; Weaver, R.; Jochemsen, R.; Jackson, P.; Bertrand, M.; Bladeren, P. van

    2000-01-01

    A strategy is presented to predict interindividual variation in drug plasma levels in vivo by the use of physiologically based pharmacokinetic modeling and human in vitro metabolic parameters, obtained through the combined use of microsomes containing single cytochrome P450 enzymes and a human liver

  8. FUZZY CLUSTERING BASED BAYESIAN FRAMEWORK TO PREDICT MENTAL HEALTH PROBLEMS AMONG CHILDREN

    Directory of Open Access Journals (Sweden)

    M R Sumathi

    2017-04-01

    Full Text Available According to World Health Organization, 10-20% of children and adolescents all over the world are experiencing mental disorders. Correct diagnosis of mental disorders at an early stage improves the quality of life of children and avoids complicated problems. Various expert systems using artificial intelligence techniques have been developed for diagnosing mental disorders like Schizophrenia, Depression, Dementia, etc. This study focuses on predicting basic mental health problems of children, like Attention problem, Anxiety problem, Developmental delay, Attention Deficit Hyperactivity Disorder (ADHD, Pervasive Developmental Disorder(PDD, etc. using the machine learning techniques, Bayesian Networks and Fuzzy clustering. The focus of the article is on learning the Bayesian network structure using a novel Fuzzy Clustering Based Bayesian network structure learning framework. The performance of the proposed framework was compared with the other existing algorithms and the experimental results have shown that the proposed framework performs better than the earlier algorithms.

  9. QSAR and docking studies of anthraquinone derivatives by similarity cluster prediction.

    Science.gov (United States)

    Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V

    2016-01-01

    Forty anthraquinone derivatives have been downloaded from PubChem database and investigated in a quantitative structure-activity relationships (QSAR) study. The models describing log P and LD50 of this set were built up on the hypermolecule scheme that mimics the investigated receptor space; the models were validated by the leave-one-out procedure, in the external test set and in a new version of prediction by using similarity clusters. Molecular docking approach using Lamarckian Genetic Algorithm was made on this class of anthraquinones with respect to 3Q3B receptor. The best scored molecules in the docking assay were used as leaders in the similarity clustering procedure. It is demonstrated that the LD50 data of this set of anthraquinones are related to the binding energies of anthraquinone ligands to the 3Q3B receptor.

  10. [Current seroprevalence, vaccination and predictive value of liver enzymes for hepatitis B among refugees in Germany].

    Science.gov (United States)

    Hampel, Annika; Solbach, Philipp; Cornberg, Markus; Schmidt, Reinhold E; Behrens, Georg M N; Jablonka, Alexandra

    2016-05-01

    Currently only vague estimates exist for the seroprevalence and vaccination status for viral hepatitis B (HBV) in refugees arriving in Germany during the current refugee crisis. To assess the prevalence of hepatitis B in refugees arriving in northern Germany in 2015. In a cross-sectional study in 793 patients from all age groups tests for serological markers of hepatitis B virus infection (HBsAg, anti-HBc) and liver enzymes (ALT, AST, bilirubin, γGT, alkaline phosphatase) were performed in August 2015 at six reception centers in northern Germany. In 258 patients anti-HBs antibodies were assessed additionally. Of the tested refugees, 76.7 % were male, the median age was 28.8 ± 11.4 years, and 7.8 % were children under the age of 18. The overall prevalence of HBsAg and total anti-HBc was 2.3 % and 14.0 % respectively (2.5 % and 14.5 % in men; 1.2 % and 13.5 % in women). Prevalence was highest in 35 to 49-year-old patients for HBsAg (3.1 %) and for refugees over 50 years for anti-HBc (38 %). No immunity to Hepatitis B was found in 62 %, 18.6 % had been vaccinated against Hepatitis B, while 50 % of children aged up to 15 years (n = 12) had been vaccinated. Positive predictive values of elevated AST and ALT for detection of HBsAg was 0 and 0.016, respectively. Only two patients with a positive HBsAg had elevated transaminases. This study showed a high prevalence of HBsAg in a German refugee sample in comparison to the general German population. Liver enzymes are not an appropriate tool for screening for hepatitis B virus infection.

  11. PREDICTED SIZES OF PRESSURE-SUPPORTED HI CLOUDS IN THE OUTSKIRTS OF THE VIRGO CLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Burkhart, Blakesley; Loeb, Abraham [Harvard-Smithsonian Center for Astrophysics, 60 Garden St. Cambridge, MA (United States)

    2016-06-10

    Using data from the ALFALFA AGES Arecibo HI survey of galaxies and the Virgo cluster X-ray pressure profiles from XMM-Newton , we investigate the possibility that starless dark HI clumps, also known as “dark galaxies,” are supported by external pressure in the surrounding intercluster medium. We find that the starless HI clump masses, velocity dispersions, and positions allow these clumps to be in pressure equilibrium with the X-ray gas near the virial radius of the Virgo cluster. We predict the sizes of these clumps to range from 1 to 10 kpc, in agreement with the range of sizes found for spatially resolved HI starless clumps outside of Virgo. Based on the predicted HI surface density of the Virgo sources, as well as a sample of other similar resolved ALFALFA HI dark clumps with follow-up optical/radio observations, we predict that most of the HI dark clumps are on the cusp of forming stars. These HI sources therefore mark the transition between starless HI clouds and dwarf galaxies with stars.

  12. Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours

    DEFF Research Database (Denmark)

    Yamada, Takuji; Waller, Alison S.; Raes, Jeroen

    2012-01-01

    Despite the current wealth of sequencing data, one-third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently a...... Systems Biology 8: 581; published online 8 May 2012; doi:10.1038/msb.2012.13...

  13. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Science.gov (United States)

    Zhang, Ying; Moges, Semu; Block, Paul

    2018-01-01

    Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  14. Influence of nutrient restriction and melatonin supplementation of pregnant ewes on maternal and fetal pancreatic digestive enzymes and insulin-containing clusters.

    Science.gov (United States)

    Keomanivong, F E; Lemley, C O; Camacho, L E; Yunusova, R; Borowicz, P P; Caton, J S; Meyer, A M; Vonnahme, K A; Swanson, K C

    2016-03-01

    Primiparous ewes (n=32) were assigned to dietary treatments in a 2×2 factorial arrangement to determine effects of nutrient restriction and melatonin supplementation on maternal and fetal pancreatic weight, digestive enzyme activity, concentration of insulin-containing clusters and plasma insulin concentrations. Treatments consisted of nutrient intake with 60% (RES) or 100% (ADQ) of requirements and melatonin supplementation at 0 (CON) or 5 mg/day (MEL). Treatments began on day 50 of gestation and continued until day 130. On day 130, blood was collected under general anesthesia from the uterine artery, uterine vein, umbilical artery and umbilical vein for plasma insulin analysis. Ewes were then euthanized and the pancreas removed from the ewe and fetus, trimmed of mesentery and fat, weighed and snap-frozen until enzyme analysis. In addition, samples of pancreatic tissue were fixed in 10% formalin solution for histological examination including quantitative characterization of size and distribution of insulin-containing cell clusters. Nutrient restriction decreased (P⩽0.001) maternal pancreatic mass (g) and α-amylase activity (U/g, kU/pancreas, U/kg BW). Ewes supplemented with melatonin had increased pancreatic mass (P=0.03) and α-amylase content (kU/pancreas and U/kg BW). Melatonin supplementation decreased (P=0.002) maternal pancreatic insulin-positive tissue area (relative to section of tissue), and size of the largest insulin-containing cell cluster (P=0.04). Nutrient restriction decreased pancreatic insulin-positive tissue area (P=0.03) and percent of large (32 001 to 512 000 µm2) and giant (⩾512 001 µm2) insulin-containing cell clusters (P=0.04) in the fetus. Insulin concentrations in plasma from the uterine vein, umbilical artery and umbilical vein were greater (P⩽0.01) in animals receiving 100% requirements. When comparing ewes to fetuses, ewes had a greater percentage of medium insulin-containing cell clusters (2001 to 32 000 µm2) while fetuses

  15. Psychological Factors Predict Local and Referred Experimental Muscle Pain: A Cluster Analysis in Healthy Adults

    Science.gov (United States)

    Lee, Jennifer E.; Watson, David; Frey-Law, Laura A.

    2012-01-01

    Background Recent studies suggest an underlying three- or four-factor structure explains the conceptual overlap and distinctiveness of several negative emotionality and pain-related constructs. However, the validity of these latent factors for predicting pain has not been examined. Methods A cohort of 189 (99F; 90M) healthy volunteers completed eight self-report negative emotionality and pain-related measures (Eysenck Personality Questionnaire-Revised; Positive and Negative Affect Schedule; State-Trait Anxiety Inventory; Pain Catastrophizing Scale; Fear of Pain Questionnaire; Somatosensory Amplification Scale; Anxiety Sensitivity Index; Whiteley Index). Using principal axis factoring, three primary latent factors were extracted: General Distress; Catastrophic Thinking; and Pain-Related Fear. Using these factors, individuals clustered into three subgroups of high, moderate, and low negative emotionality responses. Experimental pain was induced via intramuscular acidic infusion into the anterior tibialis muscle, producing local (infusion site) and/or referred (anterior ankle) pain and hyperalgesia. Results Pain outcomes differed between clusters (multivariate analysis of variance and multinomial regression), with individuals in the highest negative emotionality cluster reporting the greatest local pain (p = 0.05), mechanical hyperalgesia (pressure pain thresholds; p = 0.009) and greater odds (2.21 OR) of experiencing referred pain compared to the lowest negative emotionality cluster. Conclusion Our results provide support for three latent psychological factors explaining the majority of the variance between several pain-related psychological measures, and that individuals in the high negative emotionality subgroup are at increased risk for (1) acute local muscle pain; (2) local hyperalgesia; and (3) referred pain using a standardized nociceptive input. PMID:23165778

  16. Operational mesoscale atmospheric dispersion prediction using high performance parallel computing cluster for emergency response

    International Nuclear Information System (INIS)

    Srinivas, C.V.; Venkatesan, R.; Muralidharan, N.V.; Das, Someshwar; Dass, Hari; Eswara Kumar, P.

    2005-08-01

    An operational atmospheric dispersion prediction system is implemented on a cluster super computer for 'Online Emergency Response' for Kalpakkam nuclear site. The numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48 hour forecast of the local weather and radioactive plume dispersion due to hypothetical air borne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. Results of MM5 run time performance for 1-day prediction are reported on all the machines available for testing. A reduction of 5 times in runtime is achieved using 9 dual Xeon nodes (18 physical/36 logical processors) compared to a single node sequential run. Based on the above run time results a cluster computer facility with 9-node Dual Xeon is commissioned at IGCAR for model operation. The run time of a triple nested domain MM5 is about 4 h for 24 h forecast. The system has been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions and using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Slight improvement is noticed in rainfall, winds, geopotential heights and the vertical atmospheric structure while using NCEP data probably because of its high spatial and temporal resolution. (author)

  17. Prediction of line failure fault based on weighted fuzzy dynamic clustering and improved relational analysis

    Science.gov (United States)

    Meng, Xiaocheng; Che, Renfei; Gao, Shi; He, Juntao

    2018-04-01

    With the advent of large data age, power system research has entered a new stage. At present, the main application of large data in the power system is the early warning analysis of the power equipment, that is, by collecting the relevant historical fault data information, the system security is improved by predicting the early warning and failure rate of different kinds of equipment under certain relational factors. In this paper, a method of line failure rate warning is proposed. Firstly, fuzzy dynamic clustering is carried out based on the collected historical information. Considering the imbalance between the attributes, the coefficient of variation is given to the corresponding weights. And then use the weighted fuzzy clustering to deal with the data more effectively. Then, by analyzing the basic idea and basic properties of the relational analysis model theory, the gray relational model is improved by combining the slope and the Deng model. And the incremental composition and composition of the two sequences are also considered to the gray relational model to obtain the gray relational degree between the various samples. The failure rate is predicted according to the principle of weighting. Finally, the concrete process is expounded by an example, and the validity and superiority of the proposed method are verified.

  18. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  19. Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

    Science.gov (United States)

    Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

    2018-04-01

    Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

  20. Renal function predicts long-term outcome on enzyme replacement therapy in patients with Fabry disease.

    Science.gov (United States)

    Lenders, Malte; Schmitz, Boris; Stypmann, Jörg; Duning, Thomas; Brand, Stefan-Martin; Kurschat, Christine; Brand, Eva

    2017-12-01

    Renal and cardiac involvement is responsible for substantial morbidity and mortality in Fabry disease (FD). We analysed the incidence of FD-related renal, cardiac and neurologic end points in patients with FD on long-term enzyme replacement therapy (ERT). A retrospective analysis of prospectively collected data from two German FD centres was performed. The impact of renal and cardiac function at ERT-naïve baseline on end point development despite ERT was analysed. Fifty-four patients (28 females) receiving ERT (mean 81 ± 21 months) were investigated. Forty per cent of patients were diagnosed with clinical end points before ERT initiation and 50% of patients on ERT developed new clinical end points. In patients initially diagnosed with an end point before ERT initiation, the risk for an additional end point on ERT was increased {hazard ratio [HR] 3.83 [95% confidence interval (CI) 1.61-9.08]; P = 0.0023}. A decreased glomerular filtration rate (eGFR) ≤75 mL/min/1.73 m2 in ERT-naïve patients at baseline was associated with an increased risk for cardiovascular end points [HR 3.59 (95% CI 1.15-11.18); P = 0.0273] as well as for combined renal, cardiac and neurologic end points on ERT [HR 4.77 (95% CI 1.93-11.81); P = 0.0007]. In patients with normal kidney function, left ventricular hypertrophy at baseline predicted a decreased end point-free survival [HR 6.90 (95% CI 2.04-23.27); P = 0.0018]. The risk to develop an end point was independent of sex. In addition to age, even moderately impaired renal function determines FD progression on ERT. In patients with FD, renal and cardiac protection is warranted to prevent patients from deleterious manifestations of the disease. © The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  1. A Model Study on the Possible Effects of an External Electrical Field on Enzymes Having Dinuclear Iron Cluster [2Fe-2S

    Directory of Open Access Journals (Sweden)

    Lemi Türker

    2012-01-01

    Full Text Available Hydrogenases which catalyze the H2 ↔ 2H+ + 2e− reaction are metalloenzymes that can be divided into two classes, the NiFe and Fe enzymes, on the basis of their metal content. Iron-sulfur clusters [2Fe-2S] and [4Fe-4S] are common in ironhydrogenases. In the present model study, [2Fe-2S] cluster has been considered to visualize the effect of external electric field on various quantum chemical properties of it. In the model, all the cysteinyl residues are in the amide form. The PM3 type semiempirical calculations have been performed for the geometry optimization of the model structure in the absence and presence of the external field. Then, single point DFT calculations (B3LYP/6-31+G(d have been carried out. Depending on the direction of the field, the chemical reactivity of the model enzyme varies which suggests that an external electric field could, under proper conditions, improve the enzymatic hydrogen production.

  2. A Knowledge-Based System for Display and Prediction of O-Glycosylation Network Behaviour in Response to Enzyme Knockouts.

    Directory of Open Access Journals (Sweden)

    Andrew G McDonald

    2016-04-01

    Full Text Available O-linked glycosylation is an important post-translational modification of mucin-type protein, changes to which are important biomarkers of cancer. For this study of the enzymes of O-glycosylation, we developed a shorthand notation for representing GalNAc-linked oligosaccharides, a method for their graphical interpretation, and a pattern-matching algorithm that generates networks of enzyme-catalysed reactions. Software for generating glycans from the enzyme activities is presented, and is also available online. The degree distributions of the resulting enzyme-reaction networks were found to be Poisson in nature. Simple graph-theoretic measures were used to characterise the resulting reaction networks. From a study of in-silico single-enzyme knockouts of each of 25 enzymes known to be involved in mucin O-glycan biosynthesis, six of them, β-1,4-galactosyltransferase (β4Gal-T4, four glycosyltransferases and one sulfotransferase, play the dominant role in determining O-glycan heterogeneity. In the absence of β4Gal-T4, all Lewis X, sialyl-Lewis X, Lewis Y and Sda/Cad glycoforms were eliminated, in contrast to knockouts of the N-acetylglucosaminyltransferases, which did not affect the relative abundances of O-glycans expressing these epitopes. A set of 244 experimentally determined mucin-type O-glycans obtained from the literature was used to validate the method, which was able to predict up to 98% of the most common structures obtained from human and engineered CHO cell glycoforms.

  3. Measurement of circulating transcripts and gene cluster analysis predicts and defines therapeutic efficacy of peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors

    International Nuclear Information System (INIS)

    Bodei, L.; Kidd, M.; Modlin, I.M.; Severi, S.; Nicolini, S.; Paganelli, G.; Drozdov, I.; Kwekkeboom, D.J.; Krenning, E.P.; Baum, R.P.

    2016-01-01

    Peptide receptor radionuclide therapy (PRRT) is an effective method for treating neuroendocrine tumors (NETs). It is limited, however, in the prediction of individual tumor response and the precise and early identification of changes in tumor size. Currently, response prediction is based on somatostatin receptor expression and efficacy by morphological imaging and/or chromogranin A (CgA) measurement. The aim of this study was to assess the accuracy of circulating NET transcripts as a measure of PRRT efficacy, and moreover to identify prognostic gene clusters in pretreatment blood that could be interpolated with relevant clinical features in order to define a biological index for the tumor and a predictive quotient for PRRT efficacy. NET patients (n = 54), M: F 37:17, median age 66, bronchial: n = 13, GEP-NET: n = 35, CUP: n = 6 were treated with 177 Lu-based-PRRT (cumulative activity: 6.5-27.8 GBq, median 18.5). At baseline: 47/54 low-grade (G1/G2; bronchial typical/atypical), 31/49 18 FDG positive and 39/54 progressive. Disease status was assessed by RECIST1.1. Transcripts were measured by real-time quantitative reverse transcription PCR (qRT-PCR) and multianalyte algorithmic analysis (NETest); CgA by enzyme-linked immunosorbent assay (ELISA). Gene cluster (GC) derivations: regulatory network, protein:protein interactome analyses. Statistical analyses: chi-square, non-parametric measurements, multiple regression, receiver operating characteristic and Kaplan-Meier survival. The disease control rate was 72 %. Median PFS was not achieved (follow-up: 1-33 months, median: 16). Only grading was associated with response (p < 0.01). At baseline, 94 % of patients were NETest-positive, while CgA was elevated in 59 %. NETest accurately (89 %, χ 2 = 27.4; p = 1.2 x 10 -7 ) correlated with treatment response, while CgA was 24 % accurate. Gene cluster expression (growth-factor signalome and metabolome) had an AUC of 0.74 ± 0.08 (z-statistic = 2.92, p < 0.004) for predicting

  4. Measurement of circulating transcripts and gene cluster analysis predicts and defines therapeutic efficacy of peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors

    Energy Technology Data Exchange (ETDEWEB)

    Bodei, L. [European Institute of Oncology, Division of Nuclear Medicine, Milan (Italy); LuGenIum Consortium, Milan, Rotterdam, Bad Berka, London, Italy, Netherlands, Germany (Country Unknown); Kidd, M. [Wren Laboratories, Branford, CT (United States); Modlin, I.M. [LuGenIum Consortium, Milan, Rotterdam, Bad Berka, London, Italy, Netherlands, Germany (Country Unknown); Yale School of Medicine, New Haven, CT (United States); Severi, S.; Nicolini, S.; Paganelli, G. [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Nuclear Medicine and Radiometabolic Units, Meldola (Italy); Drozdov, I. [Bering Limited, London (United Kingdom); Kwekkeboom, D.J.; Krenning, E.P. [LuGenIum Consortium, Milan, Rotterdam, Bad Berka, London, Italy, Netherlands, Germany (Country Unknown); Erasmus Medical Center, Nuclear Medicine Department, Rotterdam (Netherlands); Baum, R.P. [LuGenIum Consortium, Milan, Rotterdam, Bad Berka, London, Italy, Netherlands, Germany (Country Unknown); Zentralklinik Bad Berka, Theranostics Center for Molecular Radiotherapy and Imaging, Bad Berka (Germany)

    2016-05-15

    Peptide receptor radionuclide therapy (PRRT) is an effective method for treating neuroendocrine tumors (NETs). It is limited, however, in the prediction of individual tumor response and the precise and early identification of changes in tumor size. Currently, response prediction is based on somatostatin receptor expression and efficacy by morphological imaging and/or chromogranin A (CgA) measurement. The aim of this study was to assess the accuracy of circulating NET transcripts as a measure of PRRT efficacy, and moreover to identify prognostic gene clusters in pretreatment blood that could be interpolated with relevant clinical features in order to define a biological index for the tumor and a predictive quotient for PRRT efficacy. NET patients (n = 54), M: F 37:17, median age 66, bronchial: n = 13, GEP-NET: n = 35, CUP: n = 6 were treated with {sup 177}Lu-based-PRRT (cumulative activity: 6.5-27.8 GBq, median 18.5). At baseline: 47/54 low-grade (G1/G2; bronchial typical/atypical), 31/49 {sup 18}FDG positive and 39/54 progressive. Disease status was assessed by RECIST1.1. Transcripts were measured by real-time quantitative reverse transcription PCR (qRT-PCR) and multianalyte algorithmic analysis (NETest); CgA by enzyme-linked immunosorbent assay (ELISA). Gene cluster (GC) derivations: regulatory network, protein:protein interactome analyses. Statistical analyses: chi-square, non-parametric measurements, multiple regression, receiver operating characteristic and Kaplan-Meier survival. The disease control rate was 72 %. Median PFS was not achieved (follow-up: 1-33 months, median: 16). Only grading was associated with response (p < 0.01). At baseline, 94 % of patients were NETest-positive, while CgA was elevated in 59 %. NETest accurately (89 %, χ{sup 2} = 27.4; p = 1.2 x 10{sup -7}) correlated with treatment response, while CgA was 24 % accurate. Gene cluster expression (growth-factor signalome and metabolome) had an AUC of 0.74 ± 0.08 (z-statistic = 2.92, p < 0

  5. Prediction of drop time and impact velocity of rod cluster control assembly

    International Nuclear Information System (INIS)

    Choi, Kee Sung; Yim, Jeong Sik; Kim, Il Kon; Kim, Kyu Tae

    1992-01-01

    This paper deals with the drop modelling of rod cluster control assembly(RCCA) and the prediction of drop time and impact velocity of RCCA at scram event. On the scram, RCCA, dropping into the guide thimble of fuel assembly by the gravity, is subject to retarding forces such as hydraulic resistance, mechanical friction and buoyancy. Considering these retarding forces RCCA dynamic equation is derived and computerized it to solve the equation in conjunction with fluid equation which is coupled with the motion of the RCCA. Because the equation is nonlinear, coupled with fluid equations, the program is written in FORTRAN using numerical method in order to calculate the drop distance and velocity with time increment. To verify the program, its results are compared with those of other fuel vendors. Predicting identical tendency as other fuel vendors and the deviation is insignificant in values this program is expected to be used for predicting the drop time and impact velocity of RCCA when the parameters affecting the control rod drop time and impact velocity changes are occurred

  6. Cluster approach to the prediction of thermodynamic and transport properties of ionic liquids

    Science.gov (United States)

    Seeger, Zoe L.; Kobayashi, Rika; Izgorodina, Ekaterina I.

    2018-05-01

    The prediction of physicochemical properties of ionic liquids such as conductivity and melting point would substantially aid the targeted design of ionic liquids for specific applications ranging from solvents for extraction of valuable chemicals to biowaste to electrolytes in alternative energy devices. The previously published study connecting the interaction energies of single ion pairs (1 IP) of ionic liquids to their thermodynamic and transport properties has been extended to larger systems consisting of two ion pairs (2 IPs), in which many-body and same-ion interactions are included. Routinely used cations, of the imidazolium and pyrrolidinium families, were selected in the study coupled with chloride, tetrafluoroborate, and dicyanamide. Their two ion pair clusters were subjected to extensive configuration screening to establish most stable structures. Interaction energies of these clusters were calculated at the spin-ratio scaled MP2 (SRS-MP2) level for the correlation interaction energy, and a newly developed scaled Hartree-Fock method for the rest of energetic contributions to interaction energy. A full geometry screening for each cation-anion combination resulted in 192 unique structures, whose stability was assessed using two criteria—widely used interaction energy and total electronic energy. Furthermore, the ratio of interaction energy to its dispersion component was correlated with experimentally observed melting points in 64 energetically favourable structures. These systems were also used to test the correlation of the dispersion contribution to interaction energy with measured conductivity.

  7. THE INFRARED PROPERTIES OF EMBEDDED SUPER STAR CLUSTERS: PREDICTIONS FROM THREE-DIMENSIONAL RADIATIVE TRANSFER MODELS

    International Nuclear Information System (INIS)

    Whelan, David G.; Johnson, Kelsey E.; Indebetouw, Remy; Whitney, Barbara A.; Wood, Kenneth

    2011-01-01

    With high-resolution infrared data becoming available that can probe the formation of high-mass stellar clusters for the first time, appropriate models that make testable predictions of these objects are necessary. We utilize a three-dimensional radiative transfer code, including a hierarchically clumped dusty envelope, to study the earliest stages of super star cluster (SSC) evolution. We explore a range of parameter space in geometric sequences that mimic the hypothesized evolution of an embedded SSC. The inclusion of a hierarchically clumped medium can make the envelope porous, in accordance with previous models and supporting observational evidence. The infrared luminosity inferred from observations can differ by a factor of two from the true value in the clumpiest envelopes depending on the viewing angle. The infrared spectral energy distribution also varies with viewing angle for clumpy envelopes, creating a range in possible observable infrared colors and magnitudes, silicate feature depths, and dust continua. General observable features of cluster evolution differ between envelopes that are relatively opaque or transparent to mid-infrared photons. For optically thick envelopes, evolution is marked by a gradual decline of the 9.8 μm silicate absorption feature depth and a corresponding increase in the visual/ultraviolet flux. For the optically thin envelopes, clusters typically begin with a strong hot dust component and silicates in emission, and these features gradually fade until the mid-infrared polycyclic aromatic hydrocarbon features are predominant. For the models with a smooth dust distribution, the Spitzer MIPS or Herschel PACS [70]-[160] color is a good probe of the stellar mass relative to the total mass or star formation efficiency (SFE). Likewise, the IRAC/MIPS [3.6]-[24] color can be used to constrain the R in and R out values of the envelope. However, clumpiness confuses the general trends seen in the smooth dust distribution models, making it

  8. The clustering of z > 7 galaxies: predictions from the BLUETIDES simulation

    Science.gov (United States)

    Bhowmick, Aklant K.; Di Matteo, Tiziana; Feng, Yu; Lanusse, Francois

    2018-03-01

    We study the clustering of the highest z galaxies (from ˜0.1 to a few tens Mpc scales) using the BLUETIDES simulation and compare it to current observational constraints from Hubble legacy and Hyper Suprime Cam (HSC) fields (at z = 6-7.2). With a box length of 400 Mpc h-1 on each side and 0.7 trillion particles, BLUETIDES is the largest volume high-resolution cosmological hydrodynamic simulation to date ideally suited for studies of high-z galaxies. We find that galaxies with magnitude mUV < 27.7 have a bias (bg) of 8.1 ± 1.2 at z = 8, and typical halo masses MH ≳ 6 × 1010 M⊙. Given the redshift evolution between z = 8 and z = 10 [bg ∝ (1 + z)1.6], our inferred values of the bias and halo masses are consistent with measured angular clustering at z ˜ 6.8 from these brighter samples. The bias of fainter galaxies (in the Hubble legacy field at H160 ≲ 29.5) is 5.9 ± 0.9 at z = 8 corresponding to halo masses MH ≳ 1010 M⊙. We investigate directly the 1-halo term in the clustering and show that it dominates on scales r ≲ 0.1 Mpc h-1 (Θ ≲ 3 arcsec) with non-linear effect at transition scales between the one-halo and two-halo term affecting scales 0.1 Mpc h-1≲ r ≲ 20 Mpc h-1 (3 arcsec ≲ Θ ≲ 90 arcsec). Current clustering measurements probe down to the scales in the transition between one-halo and two-halo regime where non-linear effects are important. The amplitude of the one-halo term implies that occupation numbers for satellites in BLUETIDES are somewhat higher than standard halo occupation distributions adopted in these analyses (which predict amplitudes in the one-halo regime suppressed by a factor 2-3). That possibly implies a higher number of galaxies detected by JWST (at small scales and even fainter magnitudes) observing these fields.

  9. Influence of nano-cluster compounds of rhenium drugs on the activity of liver enzymes in a tumor model

    Directory of Open Access Journals (Sweden)

    J. V. Suponko

    2010-06-01

    Full Text Available Enzymes’ level in rat’s hepatocytes under Guerin's carcinoma T8 development as well as after injection of rhenium compounds and cis-platin has been studied. It has been determined that the decrease of enzymatic activity to the level of the animals of control group was observed at the simultaneous injection of cis-platin and cluster rhenium compounds in nanoliposomal and water-soluble forms. That confirms possible hepatoprotective properties of the rhenium compounds. It has been shown that hepatoprotective properties of rhenium cluster compounds mostly don’t depend on the form of their injection and are detected regardless of anticancer properties. Rhenium-platinum system with β-alanine ligand in aqueous solution, has been found. Its injection is accompanied by the hepatoprotective effect.

  10. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2018-01-01

    Full Text Available Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS values of up to 0.5 and 33 %, respectively. The general skill (after bias correction of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  11. Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear

    Science.gov (United States)

    Kindschuh, Sarah R.; Cain, James W.; Daniel, David; Peyton, Mark A.

    2016-01-01

    The capacity to describe and quantify predation by large carnivores expanded considerably with the advent of GPS technology. Analyzing clusters of GPS locations formed by carnivores facilitates the detection of predation events by identifying characteristics which distinguish predation sites. We present a performance assessment of GPS cluster analysis as applied to the predation and scavenging of an omnivore, the American black bear (Ursus americanus), on ungulate prey and carrion. Through field investigations of 6854 GPS locations from 24 individual bears, we identified 54 sites where black bears formed a cluster of locations while predating or scavenging elk (Cervus elaphus), mule deer (Odocoileus hemionus), or cattle (Bos spp.). We developed models for three data sets to predict whether a GPS cluster was formed at a carnivory site vs. a non-carnivory site (e.g., bed sites or non-ungulate foraging sites). Two full-season data sets contained GPS locations logged at either 3-h or 30-min intervals from April to November, and a third data set contained 30-min interval data from April through July corresponding to the calving period for elk. Longer fix intervals resulted in the detection of fewer carnivory sites. Clusters were more likely to be carnivory sites if they occurred in open or edge habitats, if they occurred in the early season, if the mean distance between all pairs of GPS locations within the cluster was less, and if the cluster endured for a longer period of time. Clusters were less likely to be carnivory sites if they were initiated in the morning or night compared to the day. The top models for each data set performed well and successfully predicted 71–96% of field-verified carnivory events, 55–75% of non–carnivory events, and 58–76% of clusters overall. Refinement of this method will benefit from further application across species and ecological systems.

  12. Comparison of loline alkaloid gene clusters across fungal endophytes: predicting the co-regulatory sequence motifs and the evolutionary history.

    Science.gov (United States)

    Kutil, Brandi L; Greenwald, Charles; Liu, Gang; Spiering, Martin J; Schardl, Christopher L; Wilkinson, Heather H

    2007-10-01

    LOL, a fungal secondary metabolite gene cluster found in Epichloë and Neotyphodium species, is responsible for production of insecticidal loline alkaloids. To analyze the genetic architecture and to predict the evolutionary history of LOL, we compared five clusters from four fungal species (single clusters from Epichloë festucae, Neotyphodium sp. PauTG-1, Neotyphodium coenophialum, and two clusters we previously characterized in Neotyphodium uncinatum). Using PhyloCon to compare putative lol gene promoter regions, we have identified four motifs conserved across the lol genes in all five clusters. Each motif has significant similarity to known fungal transcription factor binding sites in the TRANSFAC database. Conservation of these motifs is further support for the hypothesis that the lol genes are co-regulated. Interestingly, the history of asexual Neotyphodium spp. includes multiple interspecific hybridization events. Comparing clusters from three Neotyphodium species and E. festucae allowed us to determine which Epichloë ancestors are the most likely contributors of LOL in these asexual species. For example, while no present day Epichloë typhina isolates are known to produce lolines, our data support the hypothesis that the E. typhina ancestor(s) of three asexual endophyte species contained a LOL gene cluster. Thus, these data support a model of evolution in which the polymorphism in loline alkaloid production phenotypes among endophyte species is likely due to the loss of the trait over time.

  13. [Predicting Incidence of Hepatitis E in Chinausing Fuzzy Time Series Based on Fuzzy C-Means Clustering Analysis].

    Science.gov (United States)

    Luo, Yi; Zhang, Tao; Li, Xiao-song

    2016-05-01

    To explore the application of fuzzy time series model based on fuzzy c-means clustering in forecasting monthly incidence of Hepatitis E in mainland China. Apredictive model (fuzzy time series method based on fuzzy c-means clustering) was developed using Hepatitis E incidence data in mainland China between January 2004 and July 2014. The incidence datafrom August 2014 to November 2014 were used to test the fitness of the predictive model. The forecasting results were compared with those resulted from traditional fuzzy time series models. The fuzzy time series model based on fuzzy c-means clustering had 0.001 1 mean squared error (MSE) of fitting and 6.977 5 x 10⁻⁴ MSE of forecasting, compared with 0.0017 and 0.0014 from the traditional forecasting model. The results indicate that the fuzzy time series model based on fuzzy c-means clustering has a better performance in forecasting incidence of Hepatitis E.

  14. Post-traumatic stress symptom clusters in acute whiplash associated disorder and their prediction of chronic pain-related disability

    Directory of Open Access Journals (Sweden)

    Annick Maujean

    2017-12-01

    Conclusion:. Given that only the hyperarousal/numbing symptom cluster predicted long-term neck pain-related disability, this finding may have implications in terms of diagnosis, assessment, and management of the psychological impact of whiplash-injured individuals following a MVC.

  15. Short-Term Predictive Validity of Cluster Analytic and Dimensional Classification of Child Behavioral Adjustment in School

    Science.gov (United States)

    Kim, Sangwon; Kamphaus, Randy W.; Baker, Jean A.

    2006-01-01

    A constructive debate over the classification of child psychopathology can be stimulated by investigating the validity of different classification approaches. We examined and compared the short-term predictive validity of cluster analytic and dimensional classifications of child behavioral adjustment in school using the Behavior Assessment System…

  16. Incremental Criterion Validity of the WJ-III COG Clinical Clusters: Marginal Predictive Effects beyond the General Factor

    Science.gov (United States)

    McGill, Ryan J.

    2015-01-01

    The current study examined the incremental validity of the clinical clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ-III COG) for predicting scores on the Woodcock-Johnson III Tests of Achievement (WJ-III ACH). All participants were children and adolescents (N = 4,722) drawn from the nationally representative WJ-III…

  17. Prediction of severe hypoglycaemia by angiotensin-converting enzyme activity and genotype in type 1 diabetes

    DEFF Research Database (Denmark)

    Pedersen-Bjerggaard, U.; Agerholm-Larsen, B.; Pramming, S.

    2003-01-01

    AIMS/HYPOTHESIS: We have previously shown a strong relationship between high angiotensin-converting enzyme (ACE) activity, presence of the deletion (D) allele of the ACEgene and recall of severe hypoglycaemic events in patients with Type 1 diabetes. This study was carried out to assess...... this relationship prospectively. METHODS: We followed 171 adult outpatients with Type 1 diabetes in a one-year observational study with the recording of severe hypoglycaemia. Participants were characterised by serum ACE activity and ACE genotype and not treated with ACE inhibitors or angiotensin II receptor...... antagonists. RESULTS: There was a positive relationship between serum ACE activity and rate of severe hypoglycaemia with a 2.7 times higher rate in the fourth quartile of ACE activity compared to the first quartile (p=0.0007). A similar relationship was observed for the subset of episodes with coma (2.9 times...

  18. Cluster abundance in chameleon f ( R ) gravity I: toward an accurate halo mass function prediction

    Energy Technology Data Exchange (ETDEWEB)

    Cataneo, Matteo; Rapetti, David [Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, 2100 Copenhagen (Denmark); Lombriser, Lucas [Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ (United Kingdom); Li, Baojiu, E-mail: matteoc@dark-cosmology.dk, E-mail: drapetti@dark-cosmology.dk, E-mail: llo@roe.ac.uk, E-mail: baojiu.li@durham.ac.uk [Institute for Computational Cosmology, Department of Physics, Durham University, South Road, Durham DH1 3LE (United Kingdom)

    2016-12-01

    We refine the mass and environment dependent spherical collapse model of chameleon f ( R ) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N -body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f ( R ) halo abundance with respect to that of General Relativity (GR) within a precision of ∼< 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f ( R ) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.

  19. The cluster analysis based on non-teacher artificial neural network for the danger prediction of coal spontaneous fire

    Energy Technology Data Exchange (ETDEWEB)

    Wang, D.; Wang, J. [China University of Mining and Technology (China)

    1999-04-01

    This paper focuses on the problem of predicting the danger level of spontaneous fire in coal mines. Firstly, the inadequacy of the present artificial neural networks prediction model is analysed. Then a new cluster model based on non-teacher neural network is constructed according to the danger judgement standards given by experts. On this basis, by adopting the error square sum criterion and its algorithm, the corresponding prediction software is developed and applied in two working faces of Chaili Coal Mine. The forecasting result is importantly significant for the prevention of spontaneous fire. 4 refs., 1 fig., 1 tab.

  20. Prediction of chemotherapeutic response in bladder cancer using K-means clustering of dynamic contrast-enhanced (DCE)-MRI pharmacokinetic parameters.

    Science.gov (United States)

    Nguyen, Huyen T; Jia, Guang; Shah, Zarine K; Pohar, Kamal; Mortazavi, Amir; Zynger, Debra L; Wei, Lai; Yang, Xiangyu; Clark, Daniel; Knopp, Michael V

    2015-05-01

    To apply k-means clustering of two pharmacokinetic parameters derived from 3T dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the chemotherapeutic response in bladder cancer at the mid-cycle timepoint. With the predetermined number of three clusters, k-means clustering was performed on nondimensionalized Amp and kep estimates of each bladder tumor. Three cluster volume fractions (VFs) were calculated for each tumor at baseline and mid-cycle. The changes of three cluster VFs from baseline to mid-cycle were correlated with the tumor's chemotherapeutic response. Receiver-operating-characteristics curve analysis was used to evaluate the performance of each cluster VF change as a biomarker of chemotherapeutic response in bladder cancer. The k-means clustering partitioned each bladder tumor into cluster 1 (low kep and low Amp), cluster 2 (low kep and high Amp), cluster 3 (high kep and low Amp). The changes of all three cluster VFs were found to be associated with bladder tumor response to chemotherapy. The VF change of cluster 2 presented with the highest area-under-the-curve value (0.96) and the highest sensitivity/specificity/accuracy (96%/100%/97%) with a selected cutoff value. The k-means clustering of the two DCE-MRI pharmacokinetic parameters can characterize the complex microcirculatory changes within a bladder tumor to enable early prediction of the tumor's chemotherapeutic response. © 2014 Wiley Periodicals, Inc.

  1. 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…

  2. Cluster-cluster clustering

    International Nuclear Information System (INIS)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

    1985-01-01

    The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

  3. The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data

    Science.gov (United States)

    Husein, A. M.; Harahap, M.; Aisyah, S.; Purba, W.; Muhazir, A.

    2018-03-01

    Medication planning aim to get types, amount of medicine according to needs, and avoid the emptiness medicine based on patterns of disease. In making the medicine planning is still rely on ability and leadership experience, this is due to take a long time, skill, difficult to obtain a definite disease data, need a good record keeping and reporting, and the dependence of the budget resulted in planning is not going well, and lead to frequent lack and excess of medicines. In this research, we propose Adaptive Neuro Fuzzy Inference System (ANFIS) method to predict medication needs in 2016 and 2017 based on medical data in 2015 and 2016 from two source of hospital. The framework of analysis using two approaches. The first phase is implementing ANFIS to a data source, while the second approach we keep using ANFIS, but after the process of clustering from K-Means algorithm, both approaches are calculated values of Root Mean Square Error (RMSE) for training and testing. From the testing result, the proposed method with better prediction rates based on the evaluation analysis of quantitative and qualitative compared with existing systems, however the implementation of K-Means Algorithm against ANFIS have an effect on the timing of the training process and provide a classification accuracy significantly better without clustering.

  4. 4-Demethylwyosine Synthase from Pyrococcus abyssi Is a Radical-S-adenosyl-l-methionine Enzyme with an Additional [4Fe-4S]+2 Cluster That Interacts with the Pyruvate Co-substrate*

    Science.gov (United States)

    Perche-Letuvée, Phanélie; Kathirvelu, Velavan; Berggren, Gustav; Clemancey, Martin; Latour, Jean-Marc; Maurel, Vincent; Douki, Thierry; Armengaud, Jean; Mulliez, Etienne; Fontecave, Marc; Garcia-Serres, Ricardo; Gambarelli, Serge; Atta, Mohamed

    2012-01-01

    Wybutosine and its derivatives are found in position 37 of tRNA encoding Phe in eukaryotes and archaea. They are believed to play a key role in the decoding function of the ribosome. The second step in the biosynthesis of wybutosine is catalyzed by TYW1 protein, which is a member of the well established class of metalloenzymes called “Radical-SAM.” These enzymes use a [4Fe-4S] cluster, chelated by three cysteines in a CX3CX2C motif, and S-adenosyl-l-methionine (SAM) to generate a 5′-deoxyadenosyl radical that initiates various chemically challenging reactions. Sequence analysis of TYW1 proteins revealed, in the N-terminal half of the enzyme beside the Radical-SAM cysteine triad, an additional highly conserved cysteine motif. In this study we show by combining analytical and spectroscopic methods including UV-visible absorption, Mössbauer, EPR, and HYSCORE spectroscopies that these additional cysteines are involved in the coordination of a second [4Fe-4S] cluster displaying a free coordination site that interacts with pyruvate, the second substrate of the reaction. The presence of two distinct iron-sulfur clusters on TYW1 is reminiscent of MiaB, another tRNA-modifying metalloenzyme whose active form was shown to bind two iron-sulfur clusters. A possible role for the second [4Fe-4S] cluster in the enzyme activity is discussed. PMID:23043105

  5. Predictive coupled-cluster isomer orderings for some Si{sub n}C{sub m} (m, n ≤ 12) clusters: A pragmatic comparison between DFT and complete basis limit coupled-cluster benchmarks

    Energy Technology Data Exchange (ETDEWEB)

    Byrd, Jason N., E-mail: byrd.jason@ensco.com [Quantum Theory Project, University of Florida, Gainesville, Florida 32611 (United States); ENSCO, Inc., 4849 North Wickham Road, Melbourne, Florida 32940 (United States); Lutz, Jesse J., E-mail: jesse.lutz.ctr@afit.edu; Jin, Yifan; Ranasinghe, Duminda S.; Perera, Ajith; Bartlett, Rodney J., E-mail: rodbartl@ufl.edu [Quantum Theory Project, University of Florida, Gainesville, Florida 32611 (United States); Montgomery, John A. [Department of Physics, University of Connecticut, Storrs, Connecticut 06269 (United States); Duan, Xiaofeng F. [Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio 45433 (United States); Air Force Research Laboratory DoD Supercomputing Resource Center, Wright-Patterson Air Force Base, Ohio 45433 (United States); Burggraf, Larry W. [Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio 45433 (United States); Sanders, Beverly A. [Quantum Theory Project, University of Florida, Gainesville, Florida 32611 (United States); Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida 32611 (United States)

    2016-07-14

    The accurate determination of the preferred Si{sub 12}C{sub 12} isomer is important to guide experimental efforts directed towards synthesizing SiC nano-wires and related polymer structures which are anticipated to be highly efficient exciton materials for the opto-electronic devices. In order to definitively identify preferred isomeric structures for silicon carbon nano-clusters, highly accurate geometries, energies, and harmonic zero point energies have been computed using coupled-cluster theory with systematic extrapolation to the complete basis limit for set of silicon carbon clusters ranging in size from SiC{sub 3} to Si{sub 12}C{sub 12}. It is found that post-MBPT(2) correlation energy plays a significant role in obtaining converged relative isomer energies, suggesting that predictions using low rung density functional methods will not have adequate accuracy. Utilizing the best composite coupled-cluster energy that is still computationally feasible, entailing a 3-4 SCF and coupled-cluster theory with singles and doubles extrapolation with triple-ζ (T) correlation, the closo Si{sub 12}C{sub 12} isomer is identified to be the preferred isomer in the support of previous calculations [X. F. Duan and L. W. Burggraf, J. Chem. Phys. 142, 034303 (2015)]. Additionally we have investigated more pragmatic approaches to obtaining accurate silicon carbide isomer energies, including the use of frozen natural orbital coupled-cluster theory and several rungs of standard and double-hybrid density functional theory. Frozen natural orbitals as a way to compute post-MBPT(2) correlation energy are found to be an excellent balance between efficiency and accuracy.

  6. Predictive coupled-cluster isomer orderings for some SinCm (m, n ≤ 12) clusters: A pragmatic comparison between DFT and complete basis limit coupled-cluster benchmarks

    International Nuclear Information System (INIS)

    Byrd, Jason N.; Lutz, Jesse J.; Jin, Yifan; Ranasinghe, Duminda S.; Perera, Ajith; Bartlett, Rodney J.; Montgomery, John A.; Duan, Xiaofeng F.; Burggraf, Larry W.; Sanders, Beverly A.

    2016-01-01

    The accurate determination of the preferred Si 12 C 12 isomer is important to guide experimental efforts directed towards synthesizing SiC nano-wires and related polymer structures which are anticipated to be highly efficient exciton materials for the opto-electronic devices. In order to definitively identify preferred isomeric structures for silicon carbon nano-clusters, highly accurate geometries, energies, and harmonic zero point energies have been computed using coupled-cluster theory with systematic extrapolation to the complete basis limit for set of silicon carbon clusters ranging in size from SiC 3 to Si 12 C 12 . It is found that post-MBPT(2) correlation energy plays a significant role in obtaining converged relative isomer energies, suggesting that predictions using low rung density functional methods will not have adequate accuracy. Utilizing the best composite coupled-cluster energy that is still computationally feasible, entailing a 3-4 SCF and coupled-cluster theory with singles and doubles extrapolation with triple-ζ (T) correlation, the closo Si 12 C 12 isomer is identified to be the preferred isomer in the support of previous calculations [X. F. Duan and L. W. Burggraf, J. Chem. Phys. 142, 034303 (2015)]. Additionally we have investigated more pragmatic approaches to obtaining accurate silicon carbide isomer energies, including the use of frozen natural orbital coupled-cluster theory and several rungs of standard and double-hybrid density functional theory. Frozen natural orbitals as a way to compute post-MBPT(2) correlation energy are found to be an excellent balance between efficiency and accuracy.

  7. Prediction of novel families of enzymes involved in oxidative and other complex modifications of bases in nucleic acids.

    Science.gov (United States)

    Iyer, Lakshminarayan M; Tahiliani, Mamta; Rao, Anjana; Aravind, L

    2009-06-01

    Modified bases in nucleic acids present a layer of information that directs biological function over and beyond the coding capacity of the conventional bases. While a large number of modified bases have been identified, many of the enzymes generating them still remain to be discovered. Recently, members of the 2-oxoglutarate- and iron(II)-dependent dioxygenase super-family, which modify diverse substrates from small molecules to biopolymers, were predicted and subsequently confirmed to catalyze oxidative modification of bases in nucleic acids. Of these, two distinct families, namely the AlkB and the kinetoplastid base J binding proteins (JBP) catalyze in situ hydroxylation of bases in nucleic acids. Using sensitive computational analysis of sequences, structures and contextual information from genomic structure and protein domain architectures, we report five distinct families of 2-oxoglutarate- and iron(II)-dependent dioxygenase that we predict to be involved in nucleic acid modifications. Among the DNA-modifying families, we show that the dioxygenase domains of the kinetoplastid base J-binding proteins belong to a larger family that includes the Tet proteins, prototyped by the human oncogene Tet1, and proteins from basidiomycete fungi, chlorophyte algae, heterolobosean amoeboflagellates and bacteriophages. We present evidence that some of these proteins are likely to be involved in oxidative modification of the 5-methyl group of cytosine leading to the formation of 5-hydroxymethylcytosine. The Tet/JBP homologs from basidiomycete fungi such as Laccaria and Coprinopsis show large lineage-specific expansions and a tight linkage with genes encoding a novel and distinct family of predicted transposases, and a member of the Maelstrom-like HMG family. We propose that these fungal members are part of a mobile transposon. To the best of our knowledge, this is the first report of a eukaryotic transposable element that encodes its own DNA-modification enzyme with a

  8. Genetic polymorphisms in 5-Fluorouracil-related enzymes predict pathologic response after neoadjuvant chemoradiation for rectal cancer.

    Science.gov (United States)

    Nelson, Bailey; Carter, Jane V; Eichenberger, Maurice R; Netz, Uri; Galandiuk, Susan

    2016-11-01

    Many patients with rectal cancer undergo preoperative neoadjuvant chemoradiation, with approximately 70% exhibiting pathologic downstaging in response to treatment. Currently, there is no accurate test to predict patients who are likely to be complete responders to therapy. 5-Fluorouracil is used regularly in the neoadjuvant treatment of rectal cancer. Genetic polymorphisms affect the activity of thymidylate synthase, an enzyme involved in 5-Fluorouracil metabolism, which may account for observed differences in response to neoadjuvant treatment between patients. Detection of genetic polymorphisms might identify patients who are likely to have a complete response to neoadjuvant therapy and perhaps allow them to avoid operation. DNA was isolated from whole blood taken from patients with newly diagnosed rectal cancer who received neoadjuvant therapy (n = 50). Response to therapy was calculated with a tumor regression score based on histology from the time of operation. Polymerase chain reaction was performed targeting the promoter region of thymidylate synthase. Polymerase chain reaction products were separated using electrophoresis to determine whether patients were homozygous for a double-tandem repeat (2R), a triple-tandem repeat (3R), or were heterozygous (2R/3R). A single nucleotide polymorphism, 3G or 3C, also may be present in the second repeat unit of the triple-tandem repeat allele. Restriction fragment length polymorphism assays were performed in patients with at least one 3R allele using HaeIII. Patients with at least 1 thymidylate synthase 3G allele were more likely to have a complete or partial pathologic response to 5-Fluorouracil neoadjuvant therapy (odds ratio 10.4; 95% confidence interval, 1.3-81.6; P = .01) than those without at least one 3G allele. Identification of rectal cancer patients with specific genetic polymorphisms in enzymes involved in 5-Fluorouracil metabolism seems to predict the likelihood of complete or partial pathologic response

  9. Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic

    Energy Technology Data Exchange (ETDEWEB)

    Daisuke Onozuka; Akihito Hagihara [Fukuoka Institute of Health and Environmental Sciences, Fukuoka (Japan). Department of Information Science

    2007-07-01

    Tuberculosis (TB) has reemerged as a global public health epidemic in recent years. Although evaluating local disease clusters leads to effective prevention and control of TB, there are few, if any, spatiotemporal comparisons for epidemic diseases. TB cases among residents in Fukuoka Prefecture between 1999 and 2004 (n = 9,119) were geocoded at the census tract level (n = 109) based on residence at the time of diagnosis. The spatial and space-time scan statistics were then used to identify clusters of census tracts with elevated proportions of TB cases. In the purely spatial analyses, the most likely clusters were in the Chikuho coal mining area (in 1999, 2002, 2003, 2004), the Kita-Kyushu industrial area (in 2000), and the Fukuoka urban area (in 2001). In the space-time analysis, the most likely cluster was the Kita-Kyushu industrial area (in 2000). The north part of Fukuoka Prefecture was the most likely to have a cluster with a significantly high occurrence of TB. The spatial and space-time scan statistics are effective ways of describing circular disease clusters. Since, in reality, infectious diseases might form other cluster types, the effectiveness of the method may be limited under actual practice. The sophistication of the analytical methodology, however, is a topic for future study. 48 refs., 3 figs., 3 tabs.

  10. Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic

    Directory of Open Access Journals (Sweden)

    Onozuka Daisuke

    2007-04-01

    Full Text Available Abstract Background Tuberculosis (TB has reemerged as a global public health epidemic in recent years. Although evaluating local disease clusters leads to effective prevention and control of TB, there are few, if any, spatiotemporal comparisons for epidemic diseases. Methods TB cases among residents in Fukuoka Prefecture between 1999 and 2004 (n = 9,119 were geocoded at the census tract level (n = 109 based on residence at the time of diagnosis. The spatial and space-time scan statistics were then used to identify clusters of census tracts with elevated proportions of TB cases. Results In the purely spatial analyses, the most likely clusters were in the Chikuho coal mining area (in 1999, 2002, 2003, 2004, the Kita-Kyushu industrial area (in 2000, and the Fukuoka urban area (in 2001. In the space-time analysis, the most likely cluster was the Kita-Kyushu industrial area (in 2000. The north part of Fukuoka Prefecture was the most likely to have a cluster with a significantly high occurrence of TB. Conclusion The spatial and space-time scan statistics are effective ways of describing circular disease clusters. Since, in reality, infectious diseases might form other cluster types, the effectiveness of the method may be limited under actual practice. The sophistication of the analytical methodology, however, is a topic for future study.

  11. Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

    Science.gov (United States)

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2014-05-01

    This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Improved pan-specific prediction of MHC class I peptide binding using a novel receptor clustering data partitioning strategy

    DEFF Research Database (Denmark)

    Mattsson, Andreas Holm; Kringelum, Jens Vindahl; Garde, C.

    2016-01-01

    Pan-specific prediction of receptor-ligand interaction is conventionally done using machine-learning methods that integrates information about both receptor and ligand primary sequences. To achieve optimal performance using machine learning, dealing with overfitting and data redundancy is critical....... Most often so-called ligand clustering methods have been used to deal with these issues in the context of pan-specific receptor-ligand predictions, and the MHC system the approach has proven highly effective for extrapolating information from a limited set of receptors with well characterized binding...

  13. The cell wall and cell division gene cluster in the Mra operon of Pseudomonas aeruginosa: cloning, production, and purification of active enzymes.

    Science.gov (United States)

    Azzolina, B A; Yuan, X; Anderson, M S; El-Sherbeini, M

    2001-04-01

    We have cloned the Pseudomonas aeruginosa cell wall biosynthesis and cell division gene cluster that corresponds to the mra operon in the 2-min region of the Escherichia coli chromosome. The organization of the two chromosomal regions in P. aeruginosa and E. coli is remarkably similar with the following gene order: pbp3/pbpB, murE, murF, mraY, murD, ftsW, murG, murC, ddlB, ftsQ, ftsA, ftsZ, and envA/LpxC. All of the above P. aeruginosa genes are transcribed from the same strand of DNA with very small, if any, intragenic regions, indicating that these genes may constitute a single operon. All five amino acid ligases, MurC, MurD, MurE, MurF, and DdlB, in addition to MurG and MraY were cloned in expression vectors. The four recombinant P. aeruginosa Mur ligases, MurC, MurD, MurE, and MurF were overproduced in E. coli and purified as active enzymes. Copyright 2001 Academic Press.

  14. Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

    Science.gov (United States)

    Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

    2015-03-01

    Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new

  15. ClubSub-P: Cluster-based subcellular localization prediction for Gram-negative bacteria and Archaea.

    Directory of Open Access Journals (Sweden)

    Nagarajan eParamasivam

    2011-11-01

    Full Text Available The subcellular localization of proteins provides important clues to their function in a cell. In our efforts to predict useful vaccine targets against Gram-negative bacteria, we noticed that misannotated start codons frequently lead to wrongly assigned subcellular localizations. This and other problems in subcellular localization prediction, such as the relatively high false positive and false negative rates of some tools, can be avoided by applying multiple prediction tools to groups of homologous proteins. Here we present ClubSub-P, an online database that combines existing subcellular localization prediction tools into a consensus pipeline from more than 600 proteomes of fully sequenced microorganisms. On top of the consensus prediction at the level of single sequences, the tool uses clusters of homologous proteins from Gram-negative bacteria and from Archaea to eliminate false positive and false negative predictions. ClubSub-P can assign the subcellular localization of proteins from Gram-negative bacteria and Archaea with high precision. The database is searchable, and can easily be expanded using either new bacterial genomes or new prediction tools as they become available. This will further improve the performance of the subcellular localization prediction, as well as the detection of misannotated start codons and other annotation errors. ClubSub-P is available online at http://toolkit.tuebingen.mpg.de/clubsubp/

  16. ClubSub-P: Cluster-Based Subcellular Localization Prediction for Gram-Negative Bacteria and Archaea

    Science.gov (United States)

    Paramasivam, Nagarajan; Linke, Dirk

    2011-01-01

    The subcellular localization (SCL) of proteins provides important clues to their function in a cell. In our efforts to predict useful vaccine targets against Gram-negative bacteria, we noticed that misannotated start codons frequently lead to wrongly assigned SCLs. This and other problems in SCL prediction, such as the relatively high false-positive and false-negative rates of some tools, can be avoided by applying multiple prediction tools to groups of homologous proteins. Here we present ClubSub-P, an online database that combines existing SCL prediction tools into a consensus pipeline from more than 600 proteomes of fully sequenced microorganisms. On top of the consensus prediction at the level of single sequences, the tool uses clusters of homologous proteins from Gram-negative bacteria and from Archaea to eliminate false-positive and false-negative predictions. ClubSub-P can assign the SCL of proteins from Gram-negative bacteria and Archaea with high precision. The database is searchable, and can easily be expanded using either new bacterial genomes or new prediction tools as they become available. This will further improve the performance of the SCL prediction, as well as the detection of misannotated start codons and other annotation errors. ClubSub-P is available online at http://toolkit.tuebingen.mpg.de/clubsubp/ PMID:22073040

  17. Experimental Determination and Prediction of the Fitness Effects of Random Point Mutations in the Biosynthetic Enzyme HisA

    Science.gov (United States)

    Lundin, Erik; Tang, Po-Cheng; Guy, Lionel; Näsvall, Joakim; Andersson, Dan I

    2018-01-01

    Abstract The distribution of fitness effects of mutations is a factor of fundamental importance in evolutionary biology. We determined the distribution of fitness effects of 510 mutants that each carried between 1 and 10 mutations (synonymous and nonsynonymous) in the hisA gene, encoding an essential enzyme in the l-histidine biosynthesis pathway of Salmonella enterica. For the full set of mutants, the distribution was bimodal with many apparently neutral mutations and many lethal mutations. For a subset of 81 single, nonsynonymous mutants most mutations appeared neutral at high expression levels, whereas at low expression levels only a few mutations were neutral. Furthermore, we examined how the magnitude of the observed fitness effects was correlated to several measures of biophysical properties and phylogenetic conservation.We conclude that for HisA: (i) The effect of mutations can be masked by high expression levels, such that mutations that are deleterious to the function of the protein can still be neutral with regard to organism fitness if the protein is expressed at a sufficiently high level; (ii) the shape of the fitness distribution is dependent on the extent to which the protein is rate-limiting for growth; (iii) negative epistatic interactions, on an average, amplified the combined effect of nonsynonymous mutations; and (iv) no single sequence-based predictor could confidently predict the fitness effects of mutations in HisA, but a combination of multiple predictors could predict the effect with a SD of 0.04 resulting in 80% of the mutations predicted within 12% of their observed selection coefficients. PMID:29294020

  18. Assessment of structures and stabilities of defect clusters and surface energies predicted by nine interatomic potentials for UO{sub 2}

    Energy Technology Data Exchange (ETDEWEB)

    Taller, Stephen A. [School of Nuclear Engineering, Purdue University, West Lafayette, IN 47907 (United States); Bai, Xian-Ming, E-mail: xianming.bai@inl.gov [Fuels Modeling and Simulation Department, Idaho National Laboratory, Idaho Falls, ID 83415 (United States)

    2013-11-15

    The irradiation in nuclear reactors creates many point defects and defect clusters in uranium dioxide (UO{sub 2}) and their evolution severely degrades the thermal and mechanical properties of the nuclear fuels. Previously many empirical interatomic potentials have been developed for modeling defect production and evolution in UO{sub 2}. However, the properties of defect clusters and extended defects are usually not fitted into these potentials. In this work nine interatomic potentials for UO{sub 2} are examined by using molecular statics and molecular dynamics to assess their applicability in predicting the properties of various types of defect clusters in UO{sub 2}. The binding energies and structures for these defect clusters have been evaluated for each potential. In addition, the surface energies of voids of different radii and (1 1 0) flat surfaces predicted by these potentials are also evaluated. It is found that both good agreement and significant discrepancies exist for these potentials in predicting these properties. For oxygen interstitial clusters, these potentials predict significantly different defect cluster structures and stabilities; For defect clusters consisting of both uranium and oxygen defects, the prediction is in better agreement; The surface energies predicted by these potentials have significant discrepancies, and some of them are much higher than the experimentally measured values. The results from this work can provide insight on interpreting the outcome of atomistic modeling of defect production using these potentials and may provide guidelines for choosing appropriate potential models to study problems of interest in UO{sub 2}.

  19. SRMDAP: SimRank and Density-Based Clustering Recommender Model for miRNA-Disease Association Prediction

    Directory of Open Access Journals (Sweden)

    Xiaoying Li

    2018-01-01

    Full Text Available Aberrant expression of microRNAs (miRNAs can be applied for the diagnosis, prognosis, and treatment of human diseases. Identifying the relationship between miRNA and human disease is important to further investigate the pathogenesis of human diseases. However, experimental identification of the associations between diseases and miRNAs is time-consuming and expensive. Computational methods are efficient approaches to determine the potential associations between diseases and miRNAs. This paper presents a new computational method based on the SimRank and density-based clustering recommender model for miRNA-disease associations prediction (SRMDAP. The AUC of 0.8838 based on leave-one-out cross-validation and case studies suggested the excellent performance of the SRMDAP in predicting miRNA-disease associations. SRMDAP could also predict diseases without any related miRNAs and miRNAs without any related diseases.

  20. Cluster evolution

    International Nuclear Information System (INIS)

    Schaeffer, R.

    1987-01-01

    The galaxy and cluster luminosity functions are constructed from a model of the mass distribution based on hierarchical clustering at an epoch where the matter distribution is non-linear. These luminosity functions are seen to reproduce the present distribution of objects as can be inferred from the observations. They can be used to deduce the redshift dependence of the cluster distribution and to extrapolate the observations towards the past. The predicted evolution of the cluster distribution is quite strong, although somewhat less rapid than predicted by the linear theory

  1. The DUB/USP17 deubiquitinating enzymes: A gene family within a tandemly repeated sequence, is also embedded within the copy number variable Beta-defensin cluster

    Directory of Open Access Journals (Sweden)

    Scott Christopher J

    2010-04-01

    Full Text Available Abstract Background The DUB/USP17 subfamily of deubiquitinating enzymes were originally identified as immediate early genes induced in response to cytokine stimulation in mice (DUB-1, DUB-1A, DUB-2, DUB-2A. Subsequently we have identified a number of human family members and shown that one of these (DUB-3 is also cytokine inducible. We originally showed that constitutive expression of DUB-3 can block cell proliferation and more recently we have demonstrated that this is due to its regulation of the ubiquitination and activity of the 'CAAX' box protease RCE1. Results Here we demonstrate that the human DUB/USP17 family members are found on both chromosome 4p16.1, within a block of tandem repeats, and on chromosome 8p23.1, embedded within the copy number variable beta-defensin cluster. In addition, we show that the multiple genes observed in humans and other distantly related mammals have arisen due to the independent expansion of an ancestral sequence within each species. However, it is also apparent when sequences from humans and the more closely related chimpanzee are compared, that duplication events have taken place prior to these species separating. Conclusions The observation that the DUB/USP17 genes, which can influence cell growth and survival, have evolved from an unstable ancestral sequence which has undergone multiple and varied duplications in the species examined marks this as a unique family. In addition, their presence within the beta-defensin repeat raises the question whether they may contribute to the influence of this repeat on immune related conditions.

  2. Using Blue Stragglers to Predict Retained Black Hole Population in Globular Clusters

    Science.gov (United States)

    Hermanek, Keith; Chatterjee, Sourav; Rasio, Frederic

    2018-01-01

    Large numbers of black holes (BHs) are expected to form in massive star clusters typical of the globular clusters (GCs). Sophisticated theoretical models suggest that many of these BHs can be retained in present-day GCs. Observations have also identified several BH candidates in Galactic and extragalactic GCs (e.g., Macarone et al. 2007; Irwin et al. 2010; Strader et al. 2012; Chomiuk et al. 2013; Miller-Jones et al. 2014). It has also been shown that high-mass and high-density clusters such as GCs are efficient factories of merging binary BHs similar to those observed by the LIGO observatories (Abbott et al. 2016a,b,c,d,e; Rodriguez et al. 2016). Understanding the formation rate and properties of binary BHs are dependent on a detailed understanding of how the BHs dynamically evolve within GCs. Nevertheless, directly detecting BHs in GCs is extremely challenging; BHs only in binaries with limited configurations can be directly detected by the detection of gravitational wave, X-ray, or radio emissions. We propose an indirect of inferring the number of undetected retained BHs in a GC by investigating the dynamical effects of a large number of BHs on the production of other tracer populations such as Blue Straggler Stars (BSS). Using a large grid of detailed GC models we show that there is a clear anti-correlation between the number of BSS in a cluster and the number of retained BHs. Being the most massive species, large numbers of retained BHs will dominate the core of the cluster as a result of mass-segregation driving away other low-mass species such as main-sequence stars from central high-density regions. BSS are expected to form from physical collisions between main-sequence (MS) stars mediated by binary encounters (e.g., Chatterjee et al. 2013) in cores of GCs. Production of BSS by collisions or mass transfer channels are suppressed if a large number of retained BHs in a cluster restrict the number of MS stars in the core. Extensive observational data exist on

  3. Clustering predicts memory performance in networks of spiking and non-spiking neurons

    Directory of Open Access Journals (Sweden)

    Weiliang eChen

    2011-03-01

    Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

  4. Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

    Science.gov (United States)

    Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

    2018-02-01

    A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

  5. Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

    Science.gov (United States)

    Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

    2012-07-15

    Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. Characterization and detection of a widely distributed gene cluster that predicts anaerobic choline utilization by human gut bacteria.

    Science.gov (United States)

    Martínez-del Campo, Ana; Bodea, Smaranda; Hamer, Hilary A; Marks, Jonathan A; Haiser, Henry J; Turnbaugh, Peter J; Balskus, Emily P

    2015-04-14

    Elucidation of the molecular mechanisms underlying the human gut microbiota's effects on health and disease has been complicated by difficulties in linking metabolic functions associated with the gut community as a whole to individual microorganisms and activities. Anaerobic microbial choline metabolism, a disease-associated metabolic pathway, exemplifies this challenge, as the specific human gut microorganisms responsible for this transformation have not yet been clearly identified. In this study, we established the link between a bacterial gene cluster, the choline utilization (cut) cluster, and anaerobic choline metabolism in human gut isolates by combining transcriptional, biochemical, bioinformatic, and cultivation-based approaches. Quantitative reverse transcription-PCR analysis and in vitro biochemical characterization of two cut gene products linked the entire cluster to growth on choline and supported a model for this pathway. Analyses of sequenced bacterial genomes revealed that the cut cluster is present in many human gut bacteria, is predictive of choline utilization in sequenced isolates, and is widely but discontinuously distributed across multiple bacterial phyla. Given that bacterial phylogeny is a poor marker for choline utilization, we were prompted to develop a degenerate PCR-based method for detecting the key functional gene choline TMA-lyase (cutC) in genomic and metagenomic DNA. Using this tool, we found that new choline-metabolizing gut isolates universally possessed cutC. We also demonstrated that this gene is widespread in stool metagenomic data sets. Overall, this work represents a crucial step toward understanding anaerobic choline metabolism in the human gut microbiota and underscores the importance of examining this microbial community from a function-oriented perspective. Anaerobic choline utilization is a bacterial metabolic activity that occurs in the human gut and is linked to multiple diseases. While bacterial genes responsible for

  7. Post-traumatic stress symptom clusters in acute whiplash associated disorder and their prediction of chronic pain-related disability.

    Science.gov (United States)

    Maujean, Annick; Gullo, Matthew J; Andersen, Tonny Elmose; Ravn, Sophie Lykkegaard; Sterling, Michele

    2017-11-01

    The presence of post-traumatic stress disorder (PTSD) symptoms has been found to be associated with an increased risk of persisting neck pain and disability in motor vehicle crash (MVC) survivors with whiplash injuries. The findings are mixed as to which PTSD symptom(s) best predicts recovery in this population. The aims were (1) to explore the factor structure of the Post-traumatic Stress Diagnostic Scale (PDS) in a sample of acute whiplash-injured individuals following a MVC and (2) to identify the PTSD-symptom clusters that best predict long-term neck pain-related disability in this population as measured by the Neck Pain Disability Index (NDI). A sample (N = 146) of whiplash-injured individuals completed the NDI and the PDS at baseline (whiplash-injured individuals following a MVC.

  8. Predicting DMS-IV cluster B personality disorder criteria from MMPI-2 and Rorschach data: a test of incremental validity.

    Science.gov (United States)

    Blais, M A; Hilsenroth, M J; Castlebury, F; Fowler, J C; Baity, M R

    2001-02-01

    Despite their frequent conjoint clinical use, the incremental validity of Rorschach (Rorschach, 1921/1942) and MMPI (Hathaway & McKinley, 1943) data has not been adequately established, nor has any study to date explored the incremental validity of these tests for predicting Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) personality disorders (PDs). In a reanalysis of existing data, we used select Rorschach variables and the MMPI PD scales to predict DSM-IV antisocial, borderline, histrionic, and narcissistic PD criteria in a sample of treatment-seeking outpatients. The correlational findings revealed alimited relation between Rorschach and MMPI-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) variables, with only 5 of 30 correlations reaching significance (p psychological characteristics of the DSM-IV Cluster B PDs.

  9. MAPPING THE GAS TURBULENCE IN THE COMA CLUSTER: PREDICTIONS FOR ASTRO-H

    Energy Technology Data Exchange (ETDEWEB)

    ZuHone, J. A. [Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Markevitch, M. [Astrophysics Science Division, X-ray Astrophysics Laboratory, Code 662, NASA/Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Zhuravleva, I. [Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, 452 Lomita Mall, Stanford, California 94305-4085 (United States)

    2016-02-01

    Astro-H will be able for the first time to map gas velocities and detect turbulence in galaxy clusters. One of the best targets for turbulence studies is the Coma cluster, due to its proximity, absence of a cool core, and lack of a central active galactic nucleus. To determine what constraints Astro-H will be able to place on the Coma velocity field, we construct simulated maps of the projected gas velocity and compute the second-order structure function, an analog of the velocity power spectrum. We vary the injection scale, dissipation scale, slope, and normalization of the turbulent power spectrum, and apply measurement errors and finite sampling to the velocity field. We find that even with sparse coverage of the cluster, Astro-H will be able to measure the Mach number and the injection scale of the turbulent power spectrum—the quantities determining the energy flux down the turbulent cascade and the diffusion rate for everything that is advected by the gas (metals, cosmic rays, etc.). Astro-H will not be sensitive to the dissipation scale or the slope of the power spectrum in its inertial range, unless they are outside physically motivated intervals. We give the expected confidence intervals for the injection scale and the normalization of the power spectrum for a number of possible pointing configurations, combining the structure function and velocity dispersion data. Importantly, we also determine that measurement errors on the line shift will bias the velocity structure function upward, and show how to correct this bias.

  10. Mapping the Gas Turbulence in the Coma Cluster: Predictions for Astro-H

    Science.gov (United States)

    ZuHone, J. A.; Markevitch, M.; Zhuravleva, I.

    2016-01-01

    Astro-H will be able for the first time to map gas velocities and detect turbulence in galaxy clusters. One of the best targets for turbulence studies is the Coma cluster, due to its proximity, absence of a cool core, and lack of a central active galactic nucleus. To determine what constraints Astro-H will be able to place on the Coma velocity field, we construct simulated maps of the projected gas velocity and compute the second-order structure function, an analog of the velocity power spectrum. We vary the injection scale, dissipation scale, slope, and normalization of the turbulent power spectrum, and apply measurement errors and finite sampling to the velocity field. We find that even with sparse coverage of the cluster, Astro-H will be able to measure the Mach number and the injection scale of the turbulent power spectrum-the quantities determining the energy flux down the turbulent cascade and the diffusion rate for everything that is advected by the gas (metals, cosmic rays, etc.). Astro-H will not be sensitive to the dissipation scale or the slope of the power spectrum in its inertial range, unless they are outside physically motivated intervals. We give the expected confidence intervals for the injection scale and the normalization of the power spectrum for a number of possible pointing configurations, combining the structure function and velocity dispersion data. Importantly, we also determine that measurement errors on the line shift will bias the velocity structure function upward, and show how to correct this bias.

  11. antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification

    DEFF Research Database (Denmark)

    Blin, Kai; Wolf, Thomas; Chevrette, Marc G.

    2017-01-01

    Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding...... the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features...

  12. Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units

    International Nuclear Information System (INIS)

    Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios, Martha; Baechler, Sébastien

    2015-01-01

    Purpose: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. Method: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). Results: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Conclusion: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables

  13. Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling

    NARCIS (Netherlands)

    Veeger, C.P.L.; Etman, L.F.P.; Herk, van J.; Rooda, J.E.

    2009-01-01

    Predicting the mean cycle time as a function of throughput and product mix is helpful in making the production planning for cluster tools. To predict the mean cycle time, detailed simulation models may be used. However, detailed models require much development time, and it may not be possible to

  14. Motif-independent prediction of a secondary metabolism gene cluster using comparative genomics: application to sequenced genomes of Aspergillus and ten other filamentous fungal species.

    Science.gov (United States)

    Takeda, Itaru; Umemura, Myco; Koike, Hideaki; Asai, Kiyoshi; Machida, Masayuki

    2014-08-01

    Despite their biological importance, a significant number of genes for secondary metabolite biosynthesis (SMB) remain undetected due largely to the fact that they are highly diverse and are not expressed under a variety of cultivation conditions. Several software tools including SMURF and antiSMASH have been developed to predict fungal SMB gene clusters by finding core genes encoding polyketide synthase, nonribosomal peptide synthetase and dimethylallyltryptophan synthase as well as several others typically present in the cluster. In this work, we have devised a novel comparative genomics method to identify SMB gene clusters that is independent of motif information of the known SMB genes. The method detects SMB gene clusters by searching for a similar order of genes and their presence in nonsyntenic blocks. With this method, we were able to identify many known SMB gene clusters with the core genes in the genomic sequences of 10 filamentous fungi. Furthermore, we have also detected SMB gene clusters without core genes, including the kojic acid biosynthesis gene cluster of Aspergillus oryzae. By varying the detection parameters of the method, a significant difference in the sequence characteristics was detected between the genes residing inside the clusters and those outside the clusters. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

  15. A spectral clustering search algorithm for predicting shallow landslide size and location

    Science.gov (United States)

    Dino Bellugi; David G. Milledge; William E. Dietrich; Jim A. McKean; J. Taylor Perron; Erik B. Sudderth; Brian Kazian

    2015-01-01

    The potential hazard and geomorphic significance of shallow landslides depend on their location and size. Commonly applied one-dimensional stability models do not include lateral resistances and cannot predict landslide size. Multi-dimensional models must be applied to specific geometries, which are not known a priori, and testing all possible geometries is...

  16. Clustering Dycom

    KAUST Repository

    Minku, Leandro L.

    2017-10-06

    Background: Software Effort Estimation (SEE) can be formulated as an online learning problem, where new projects are completed over time and may become available for training. In this scenario, a Cross-Company (CC) SEE approach called Dycom can drastically reduce the number of Within-Company (WC) projects needed for training, saving the high cost of collecting such training projects. However, Dycom relies on splitting CC projects into different subsets in order to create its CC models. Such splitting can have a significant impact on Dycom\\'s predictive performance. Aims: This paper investigates whether clustering methods can be used to help finding good CC splits for Dycom. Method: Dycom is extended to use clustering methods for creating the CC subsets. Three different clustering methods are investigated, namely Hierarchical Clustering, K-Means, and Expectation-Maximisation. Clustering Dycom is compared against the original Dycom with CC subsets of different sizes, based on four SEE databases. A baseline WC model is also included in the analysis. Results: Clustering Dycom with K-Means can potentially help to split the CC projects, managing to achieve similar or better predictive performance than Dycom. However, K-Means still requires the number of CC subsets to be pre-defined, and a poor choice can negatively affect predictive performance. EM enables Dycom to automatically set the number of CC subsets while still maintaining or improving predictive performance with respect to the baseline WC model. Clustering Dycom with Hierarchical Clustering did not offer significant advantage in terms of predictive performance. Conclusion: Clustering methods can be an effective way to automatically generate Dycom\\'s CC subsets.

  17. A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting

    International Nuclear Information System (INIS)

    Jin, Cheng Hao; Pok, Gouchol; Lee, Yongmi; Park, Hyun-Woo; Kim, Kwang Deuk; Yun, Unil; Ryu, Keun Ho

    2015-01-01

    Highlights: • A novel pattern sequence-based direct time series forecasting method was proposed. • Due to the use of SOM’s topology preserving property, only SOM can be applied. • SCPSNSP only deals with the cluster patterns not each specific time series value. • SCPSNSP performs better than recently developed forecasting algorithms. - Abstract: In this paper, we propose a new day-ahead direct time series forecasting method for competitive electricity markets based on clustering and next symbol prediction. In the clustering step, pattern sequence and their topology relations are obtained from self organizing map time series clustering. In the next symbol prediction step, with each cluster label in the pattern sequence represented as a pair of its topologically identical coordinates, artificial neural network is used to predict the topological coordinates of next day by training the relationship between previous daily pattern sequence and its next day pattern. According to the obtained topology relations, the nearest nonzero hits pattern is assigned to next day so that the whole time series values can be directly forecasted from the assigned cluster pattern. The proposed method was evaluated on Spanish, Australian and New York electricity markets and compared with PSF and some of the most recently published forecasting methods. Experimental results show that the proposed method outperforms the best forecasting methods at least 3.64%

  18. The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

    Science.gov (United States)

    Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

    2014-05-01

    Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the

  19. Research on time series data prediction based on clustering algorithm - A case study of Yuebao

    Science.gov (United States)

    Lu, Xu; Zhao, Tianzhong

    2017-08-01

    Forecasting is the prerequisite for making scientific decisions, it is based on the past information of the research on the phenomenon, and combined with some of the factors affecting this phenomenon, then using scientific methods to forecast the development trend of the future, it is an important way for people to know the world. This is particularly important in the prediction of financial data, because proper financial data forecasts can provide a great deal of help to financial institutions in their strategic implementation, strategic alignment and risk control. However, the current forecasts of financial data generally use the method of forecast of overall data, which lack of consideration of customer behavior and other factors in the financial data forecasting process, and they are important factors influencing the change of financial data. Based on this situation, this paper analyzed the data of Yuebao, and according to the user's attributes and the operating characteristics, this paper classified 567 users of Yuebao, and made further predicted the data of Yuebao for every class of users, the results showed that the forecasting model in this paper can meet the demand of forecasting.

  20. Teaching Enzymes to Pre-Service Science Teachers through POE (Predict, Observe, Explain) Method: The Case of Catalase

    Science.gov (United States)

    Güngör, Sema Nur; Özkan, Muhlis

    2016-01-01

    The aim of this study is to teach enzymes, which are one of the biology subjects in understanding which students have a big difficulty, to pre-service teachers through POE method in the case of catalase, which is an oxidoreductase. Descriptive analysis method was employed in this study in which 38 second grade pre-service teachers attending Uludag…

  1. Evaluation of B3LYP, X3LYP, and M06-class density functionals for predicting the binding energies of neutral, protonated, and deprotonated water clusters

    OpenAIRE

    Bryantsev, Vyacheslav S.; Diallo, Mamadou S.; van Duin, Adri C. T.; Goddard, William A., III

    2009-01-01

    In this paper we assess the accuracy of the B3LYP, X3LYP, and newly developed M06-L, M06-2X, and M06 functionals to predict the binding energies of neutral and charged water clusters including (H_2O)_n, n = 2−8, 20), H_3O+(H_2O_)n, n = 1−6, and OH−(H_2O)_n, n = 1−6. We also compare the predicted energies of two ion hydration and neutralization reactions on the basis of the calculated binding energies. In all cases, we use as benchmarks calculated binding energies of water clusters extrapolate...

  2. Prediction of specific depressive symptom clusters in youth with epilepsy: The NDDI-E-Y versus Neuro-QOL SF.

    Science.gov (United States)

    Kellermann, Tanja S; Mueller, Martina; Carter, Emma G; Brooks, Byron; Smith, Gigi; Kopp, Olivia J; Wagner, Janelle L

    2017-08-01

    Proper assessment and early identification of depressive symptoms are essential to initiate treatment and minimize the risk for poor outcomes in youth with epilepsy (YWE). The current study examined the predictive utility of the Neurological Disorders Depression Inventory-Epilepsy for Youth (NDDI-E-Y) and the Neuro-QOL Depression Short Form (Neuro-QOL SF) in explaining variance in overall depressive symptoms and specific symptom clusters on the gold standard Children's Depression Inventory-2 (CDI-2). Cross-sectional study examining 99 YWE (female 68, mean age 14.7 years) during a routine epilepsy visit, who completed self-report measures of depressive symptoms, including the NDDI-E-Y, CDI-2, and the Neuro-QOL SF. Caregivers completed a measure of seizure severity. All sociodemographic and medical information was evaluated through electronic medical record review. After accounting for seizure and demographic variables, the NDDI-E-Y accounted for 45% of the variance in the CDI-2 Total score and the CDI-2 Ineffectiveness subscale. Furthermore, the NDDI-E-Y predicted CDI-2 Total scores and subscales similarly, with the exception of explaining significantly more variance in the CDI-2 Ineffectiveness subscale compared to the Negative Mood subscale. The NDDI-E-Y explained greater variance compared to Neuro-QOL SF across the Total (48% vs. 37%) and all CDI-2 subscale scores; however, the NDDI-E-Y emerged as a stronger predictor of only CDI-2 Ineffectiveness. Both the NDDI-E-Y and Neuro-QOL SF accounted for the lowest amount of variance in CDI-2 Negative Mood. Sensitivity was poor for the Neuro-QOL SF in predicting high versus low CDI-2 scores. The NDDI-E-Y has strong psychometrics and can be easily integrated into routine epilepsy care for quick, brief screening of depressive symptoms in YWE. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

  3. Quantifying the uncertainty of kinetic-theory predictions of clustering. Final Report covering 21 September 2011 - 20 September 2014

    Energy Technology Data Exchange (ETDEWEB)

    Hrenya, Christine [Univ. of Colorado, Boulder, CO (United States). Chemical and Biological Engineering

    2014-09-20

    Previous work has indicated that inelastic grains undergoing homogeneous cooling may be unstable, giving rise to the formation of velocity vortices and particle clusters for sufficiently large systems. Such instabilities are observed in industrial coal and biomass gasifiers and are known to influence gas-solid contact area, mixing dynamics, and heat/mass transfer rates. However, the driving mechanisms that lead to vortices and clusters are not well understood. Discrete-particle simulations provide a well-established method for understanding such mechanisms but are not a feasible technique for predicting the behavior of large-scale systems. Kinetic-theory-based continuum models offer an effective means of describing such flows, and instabilities present a stringent test of such models due to the transient, three-dimensional nature of instabilities and the large range of time and length scales over which these mechanisms occur.This work begins with the study, via a combination of continuum models and discrete- particle simulations, of a relatively simple flow and includes additional complexities in a stepwise manner to assess various driving mechanisms. Comparisons with discrete-particle simulations, which offer detailed, well-established (but computationally limited) descriptions of particle flows, indicate the ability of continuum models to accurately incorporate each mechanism. Specifically, the critical length scale for velocity vortices and/or particle clusters are studied via direct numerical simulation, molecular dynamics simulations, linear stability analyses of the continuum model, and transient simulations of the continuum model in a range of flow complexities, including moderate dissipation and particle concentration, frictional particles collisions, high gradients, and gas-solid flows. Strong agreement between kinetic-theory-based continuum models and discrete-particle simulations is found for a range for conditions. Furthermore, discrete

  4. AR-V7 in circulating tumor cells cluster as a predictive biomarker of abiraterone acetate and enzalutamide treatment in castration-resistant prostate cancer patients.

    Science.gov (United States)

    Okegawa, Takatsugu; Ninomiya, Naoki; Masuda, Kazuki; Nakamura, Yu; Tambo, Mitsuhiro; Nutahara, Kikuo

    2018-06-01

    We examined whether androgen receptor splice variant 7 (AR-V7) in circulating tumor cell(CTC)clusters can be used to predict survival in patients with bone metastatic castration resistant-prostate cancer (mCRPC) treated with abiraterone or enzalutamide. We retrospectively enrolled 98 patients with CRPC on abiraterone or enzalutamide, and investigated the prognostic value of CTC cluster detection (+ v -) and AR-V7 detection (+ v -) using a CTC cluster detection - based AR-V7 mRNA assay. We examined ≤50% prostate-specific antigen (PSA) responses, PSA progression-free survival (PSA-PFS), clinical and radiological progression-free survival (radiologic PSF), and overall survival (OS). We then assessed whether AR-V7 expression in CTC clusters identified after On-chip multi-imaging flow cytometry was related to disease progression and survival after first-line systemic therapy. All abiraterone-treated or enzalutamide-treated patients received prior docetaxel. The median follow-up was 20.7 (range: 3.0-37.0) months in the abiraterone and enzalutamide cohorts, respectively. Forty-nine of the 98 men (50.0%) were CTC cluster (-), 23 of the 98 men (23.5%) were CTC cluster(+)/AR-V7(-), and 26 of the 98 men (26.5%) were CTC cluster(+)/AR-V7(+). CTC cluster(+)/AR-V7(+) patients were more likely to have EOD ≥3 at diagnosis (P = 0.003), pain (P = 0.023), higher alkaline phosphatase levels (P cluster(+), CTC cluster(+)/AR-V7(-), and ALP >UNL were independently associated with a poor PSA-PFS, radiographic PFS, and OS in abiraterone-treated patients and enzalutamide-treated patients. The CTC clusters and AR-V7-positive CTC clusters detected were important for assessing the response to abiraterone or enzalutamide therapy and for predicting disease outcome. © 2018 Wiley Periodicals, Inc.

  5. Prediction of the transition energies of atomic No and Lr by the intermediate Hamiltonian coupled cluster method

    International Nuclear Information System (INIS)

    Borschevsky, A.; Eliav, E.; Kaldor, U.; Vilkas, M.J.; Ishikawa, Y.

    2007-01-01

    Complete text of publication follows: Measurements of the spectroscopic properties of the superheavy elements present a serious challenge to the experimentalist. Their short lifetimes and the low quantities of their production necessitate reliable prediction of transition energies to avoid the need for broad wavelength scans and to assist in identifying the lines. Thus, reliable high-accuracy calculations are necessary prior and parallel to experimental research. Nobelium and Lawrencium are at present the two most likely candidates for spectroscopic measurements, with the first experiments planned at GSI, Darmstadt. The intermediate Hamiltonian (IH) coupled cluster method is applied to the ionization potentials, electron affinities, and excitation energies of atomic nobelium and lawrencium. Large basis sets are used (37s31p26d21f16g11h6i). All levels of a particular atom are obtained simultaneously by diagonalizing the IH matrix. The matrix elements correspond to all excitations from correlated occupied orbitals to virtual orbitals in a large P space, and are 'dressed' by folding in excitations to higher virtual orbitals (Q space) at the coupled cluster singles-and-doubles level. Lamb-shift corrections are included. The same approach was applied to the lighter homologues of Lr and No, lutetium and ytterbium, for which many transition energies are experimentally known, in order to assess the accuracy of the calculation. The average absolute error of 20 excitation energies of Lu is 423 cm -1 , and the error limits for Lr are therefore put at 700 cm -1 . Predicted Lr excitations with large transition moments in the prime range for the planned experiment, 20,000-30,000 cm -1 , are 7p → 8s at 20,100 cm -1 and 7p →p 7d at 28,100 cm -1 . In case of Yb, the calculated ionization potential was within 20 cm -1 of the experiment, and the average error of the 20 lowest calculated excitations was about 300 cm -1 . Hence, the error limits of nobelium are set to 800 cm -1

  6. A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data

    NARCIS (Netherlands)

    Wynants, L.; Bouwmeester, W.; Moons, K. G. M.; Moerbeek, M.; Timmerman, D.; Van Huffel, S.; Van Calster, B.; Vergouwe, Y.

    2015-01-01

    Objectives: This study aims to investigate the influence of the amount of clustering [intraclass correlation (ICC) = 0%, 5%, or 20%], the number of events per variable (EPV) or candidate predictor (EPV = 5, 10, 20, or 50), and backward variable selection on the performance of prediction models.

  7. Pancreatic Enzymes

    Science.gov (United States)

    ... Contact Us DONATE NOW GENERAL DONATION PURPLESTRIDE Pancreatic enzymes Home Facing Pancreatic Cancer Living with Pancreatic Cancer ... and see a registered dietitian. What are pancreatic enzymes? Pancreatic enzymes help break down fats, proteins and ...

  8. A hybrid Genetic Algorithm and Monte Carlo simulation approach to predict hourly energy consumption and generation by a cluster of Net Zero Energy Buildings

    International Nuclear Information System (INIS)

    Garshasbi, Samira; Kurnitski, Jarek; Mohammadi, Yousef

    2016-01-01

    Graphical abstract: The energy consumption and renewable generation in a cluster of NZEBs are modeled by a novel hybrid Genetic Algorithm and Monte Carlo simulation approach and used for the prediction of instantaneous and cumulative net energy balances and hourly amount of energy taken from and supplied to the central energy grid. - Highlights: • Hourly energy consumption and generation by a cluster of NZEBs was simulated. • Genetic Algorithm and Monte Carlo simulation approach were employed. • Dampening effect of energy used by a cluster of buildings was demonstrated. • Hourly amount of energy taken from and supplied to the grid was simulated. • Results showed that NZEB cluster was 63.5% grid dependant on annual bases. - Abstract: Employing a hybrid Genetic Algorithm (GA) and Monte Carlo (MC) simulation approach, energy consumption and renewable energy generation in a cluster of Net Zero Energy Buildings (NZEBs) was thoroughly investigated with hourly simulation. Moreover, the cumulative energy consumption and generation of the whole cluster and each individual building within the simulation space were accurately monitored and reported. The results indicate that the developed simulation algorithm is able to predict the total instantaneous and cumulative amount of energy taken from and supplied to the central energy grid over any time period. During the course of simulation, about 60–100% of total daily generated renewable energy was consumed by NZEBs and up to 40% of that was fed back into the central energy grid as surplus energy. The minimum grid dependency of the cluster was observed in June and July where 11.2% and 9.9% of the required electricity was supplied from the central energy grid, respectively. On the other hand, the NZEB cluster was strongly grid dependant in January and December by importing 70.7% and 76.1% of its required energy demand via the central energy grid, in the order given. Simulation results revealed that the cluster was 63

  9. Asparaginase-associated pancreatitis is not predicted by hypertriglyceridemia or pancreatic enzyme levels in children with acute lymphoblastic leukemia

    DEFF Research Database (Denmark)

    Raja, Raheel Altaf; Schmiegelow, Kjeld; Sørensen, Ditte Nørbo

    2017-01-01

    Background: l-Asparaginase is an important drug for treatment of childhood acute lymphoblastic leukemia (ALL), but is associated with serious toxicities, including pancreatitis and hypertriglyceridemia (HTG). Asparaginase-associated pancreatitis (AAP) is a common reason for stopping asparaginase...... treatment. The aim of this study was to explore if HTG or early elevations in pancreatic enzymes were associated with the subsequent development of AAP. Method: Children (1.0–17.9 years) diagnosed with ALL, treated with asparaginase for 30 weeks, according to the NOPHO ALL2008 protocol at the University...

  10. Acute intermittent porphyria: A single-base deletion and a nonsense mutation in the human hydroxymethylbilane synthase gene, predicting truncations of the enzyme polypeptide

    Energy Technology Data Exchange (ETDEWEB)

    Lee, G.L.; Astrin, K.H.; Desnick, R.J. [Mount Sinai School of Medicine, New York, NY (United States)

    1995-08-28

    Acute intermittent porphyria (AIP) is an autosomal-dominant inborn error of metabolism that results from the half-normal activity of the third enzyme in the heme biosynthetic pathway, hydroxymethylbilane synthase (HMB-synthase). AIP is an ecogenetic condition, since the life-threatening acute attacks are precipitated by various factors, including drugs, alcohol, fasting, and certain hormones. Biochemical diagnosis is problematic, and the identification of mutations in the HMB-synthase gene provides accurate detection of presymptomatic heterozygotes, permitting avoidance of the acute precipitating factors. By direct solid-phase sequencing, two mutations causing AIP were identified, an adenine deletion at position 629 in exon 11(629delA), which alters the reading frame and predicts premature truncation of the enzyme protein after amino acid 255, and a nonsense mutation in exon 12 (R225X). These mutations were confirmed by either restriction enzyme analysis or family studies of symptomatic patients, permitting accurate presymptomatic diagnosis of affected relatives. 29 refs., 2 figs.

  11. Deficits of entropy modulation in schizophrenia are predicted by functional connectivity strength in the theta band and structural clustering.

    Science.gov (United States)

    Gomez-Pilar, Javier; de Luis-García, Rodrigo; Lubeiro, Alba; de Uribe, Nieves; Poza, Jesús; Núñez, Pablo; Ayuso, Marta; Hornero, Roberto; Molina, Vicente

    2018-01-01

    Spectral entropy (SE) allows comparing task-related modulation of electroencephalogram (EEG) between patients and controls, i.e. spectral changes of the EEG associated to task performance. A SE modulation deficit has been replicated in different schizophrenia samples. To investigate the underpinnings of SE modulation deficits in schizophrenia, we applied graph-theory to EEG recordings during a P300 task and fractional anisotropy (FA) data from diffusion tensor imaging in 48 patients (23 first episodes) and 87 healthy controls. Functional connectivity was assessed from phase-locking values among sensors in the theta band, and structural connectivity was based on FA values for the tracts connecting pairs of regions. From those data, averaged clustering coefficient (CLC), characteristic path-length (PL) and connectivity strength (CS, also known as density) were calculated for both functional and structural networks. The corresponding functional modulation values were calculated as the difference in SE and CLC, PL and CS between the pre-stimulus and response windows during the task. The results revealed a higher functional CS in the pre-stimulus window in patients, predictive of smaller modulation of SE in this group. The amount of increase in theta CS from pre-stimulus to response related to SE modulation in patients and controls. Structural CLC was associated with SE modulation in the patients. SE modulation was predictive of negative symptoms, whereas CLC and PL modulation was associated with cognitive performance in the patients. These results support that a hyperactive functional connectivity and/or structural connective deficits in the patients hamper the dynamical modulation of connectivity underlying cognition.

  12. UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

    Science.gov (United States)

    Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

    2016-01-04

    The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. NRSA enzyme decomposition model data

    Data.gov (United States)

    U.S. Environmental Protection Agency — Microbial enzyme activities measured at more than 2000 US streams and rivers. These enzyme data were then used to predict organic matter decomposition and microbial...

  14. Prediction of post translational modifications in avicennia marina Cu-Zn superoxide dismutase: implication of glycation on the enzyme structure

    International Nuclear Information System (INIS)

    Jabeen, U.; Salim, A.; Abbasi, A.

    2012-01-01

    3D homology model of Cu-Zn superoxide dismutase (SOD) from Avicennia marina (AMSOD) was constructed using the structural coordinates of Spinach SOD (SSOD). Prediction of post translational modification was done by PROSITE. The predicted sites were examined in the 3D model. AMSOD model was glycated using modeling software and changes in the structure was analyzed after glycation. The analysis revealed some potential sites and structural changes after glycation. (author)

  15. Predicting stability limits for pure and doped dicationic noble gas clusters undergoing coulomb explosion: A parallel tempering based study.

    Science.gov (United States)

    Ghorai, Sankar; Chaudhury, Pinaki

    2018-05-30

    We have used a replica exchange Monte-Carlo procedure, popularly known as Parallel Tempering, to study the problem of Coulomb explosion in homogeneous Ar and Xe dicationic clusters as well as mixed Ar-Xe dicationic clusters of varying sizes with different degrees of relative composition. All the clusters studied have two units of positive charges. The simulations reveal that in all the cases there is a cutoff size below which the clusters fragment. It is seen that for the case of pure Ar, the value is around 95 while that for Xe it is 55. For the mixed clusters with increasing Xe content, the cutoff limit for suppression of Coulomb explosion gradually decreases from 95 for a pure Ar to 55 for a pure Xe cluster. The hallmark of this study is this smooth progression. All the clusters are simulated using the reliable potential energy surface developed by Gay and Berne (Gay and Berne, Phys. Rev. Lett. 1982, 49, 194). For the hetero clusters, we have also discussed two different ways of charge distribution, that is one in which both positive charges are on two Xe atoms and the other where the two charges are at a Xe atom and at an Ar atom. The fragmentation patterns observed by us are such that single ionic ejections are the favored dissociating pattern. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  16. A 3.55 keV line from DM →a→γ: predictions for cool-core and non-cool-core clusters

    Energy Technology Data Exchange (ETDEWEB)

    Conlon, Joseph P.; Powell, Andrew J. [Rudolf Peierls Centre for Theoretical Physics, University of Oxford, 1 Keble Road, Oxford, OX1 3NP (United Kingdom)

    2015-01-13

    We further study a scenario in which a 3.55 keV X-ray line arises from decay of dark matter to an axion-like particle (ALP), that subsequently converts to a photon in astrophysical magnetic fields. We perform numerical simulations of Gaussian random magnetic fields with radial scaling of the magnetic field magnitude with the electron density, for both cool-core 'Perseus' and non-cool-core 'Coma' electron density profiles. Using these, we quantitatively study the resulting signal strength and morphology for cool-core and non-cool-core clusters. Our study includes the effects of fields of view that cover only the central part of the cluster, the effects of offset pointings on the radial decline of signal strength and the effects of dividing clusters into annuli. We find good agreement with current data and make predictions for future analyses and observations.

  17. Clustering Dycom

    KAUST Repository

    Minku, Leandro L.; Hou, Siqing

    2017-01-01

    baseline WC model is also included in the analysis. Results: Clustering Dycom with K-Means can potentially help to split the CC projects, managing to achieve similar or better predictive performance than Dycom. However, K-Means still requires the number

  18. Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers.

    Science.gov (United States)

    Andersen, Erlend K F; Kristensen, Gunnar B; Lyng, Heidi; Malinen, Eirik

    2011-08-01

    Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K(trans) and ύ(e), were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control.

  19. Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers

    International Nuclear Information System (INIS)

    Andersen, Erlend K. F.; Kristensen, Gunnar B.; Lyng, Heidi; Malinen, Eirik

    2011-01-01

    Introduction. Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Materials and methods. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K trans and u e , were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Results. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Conclusions. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control

  20. Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, Erlend K. F. (Dept. of Medical Physics, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway)), e-mail: eirik.malinen@fys.uio.no; Kristensen, Gunnar B. (Section for Gynaecological Oncology, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway)); Lyng, Heidi (Dept. of Radiation Biology, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway)); Malinen, Eirik (Dept. of Medical Physics, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway); Dept. of Physics, Univ. of Oslo, Oslo (Norway))

    2011-08-15

    Introduction. Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Materials and methods. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, Ktrans and u{sub e}, were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Results. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Conclusions. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control

  1. Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

    Directory of Open Access Journals (Sweden)

    Sharma Animesh

    2007-01-01

    Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

  2. Clustering of near clusters versus cluster compactness

    International Nuclear Information System (INIS)

    Yu Gao; Yipeng Jing

    1989-01-01

    The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

  3. Angiotensin-converting enzyme gene polymorphism in arrhythmogenic right ventricular dysplasia: is DD genotype helpful in predicting syncope risk?

    Science.gov (United States)

    Ozben, Beste; Altun, Ibrahim; Sabri Hancer, Veysel; Bilge, Ahmet Kaya; Tanrikulu, Azra Meryem; Diz-Kucukkaya, Reyhan; Fak, Ali Serdar; Yilmaz, Ercument; Adalet, Kamil

    2008-12-01

    Arrhythmogenic right ventricular dysplasia (ARVD) is a heritable disorder characterised by fibrofatty replacement of right ventricular myocytes and increased risk of ventricular arrhythmias and sudden cardiac death. Angiotensin-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism affects myocardial ACE levels. DD genotype favours myocardial fibrosis and is associated with malignant ventricular tachycardia. The aim of this study was to explore ACE gene polymorphism in ARVD patients. Twenty-nine patients with ARVD and 24 controls were included. All ARVD patients had documented sustained ventricular tachycardia. Thirteen patients had syncopal episodes. Six patients were resuscitated from sudden cardiac death. ACE gene polymorphism was identified by polymerase chain reaction technique. There was no significant difference in DD genotype frequency between ARVD patients and controls (44.8% vs. 45.8%, p=0.94). However, DD genotype frequency was significantly higher in ARVD patients with syncopal episodes compared to those without syncope (69.2% vs. 25.0%, p=0.017, odds ratio:6.750, 95% confidence interval: 1.318-34.565). DD genotype was detected in higher frequency also in patients with a family history of sudden cardiac death (66.7% vs. 39.1%,p=0.36). High prevalence of DD genotype in ARVD patients with syncope suggests that ACE I/D polymorphism might be useful in identifying high-risk patients for syncope.

  4. A computational linguistic measure of clustering behavior on semantic verbal fluency task predicts risk of future dementia in the nun study.

    Science.gov (United States)

    Pakhomov, Serguei V S; Hemmy, Laura S

    2014-06-01

    Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer's disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery, and were followed in 18-month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow-up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher [+1 standard deviation (SD)] MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22-29% memory impairment and 35-40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal

  5. The influence of posttraumatic stress disorder numbing and hyperarousal symptom clusters in the prediction of physical health status in veterans with chronic tobacco dependence and posttraumatic stress disorder.

    Science.gov (United States)

    Harder, Laura H; Chen, Shuo; Baker, Dewleen G; Chow, Bruce; McFall, Miles; Saxon, Andrew; Smith, Mark W

    2011-12-01

    Smoking and PTSD are predictors of poor physical health status. This study examined the unique contribution of PTSD symptoms in the prediction of the SF-36 physical health status subscales accounting for cigarette smoking, chronic medical conditions, alcohol and drug use disorders, and depression. This study examined baseline interview and self-report data from a national tobacco cessation randomized, controlled trial (Veterans Affairs Cooperative Study 519) that enrolled tobacco-dependent veterans with chronic PTSD (N = 943). A series of blockwise multiple regression analyses indicated that PTSD numbing and hyperarousal symptom clusters explained a significant proportion of the variance across all physical health domains except for the Physical Functioning subscale, which measures impairments in specific physical activities. Our findings further explain the impact of PTSD on health status by exploring the way PTSD symptom clusters predict self-perceptions of health, role limitations, pain, and vitality.

  6. Facile Synthesis of Novel Coumarin Derivatives, Antimicrobial Analysis, Enzyme Assay, Docking Study, ADMET Prediction and Toxicity Study

    Directory of Open Access Journals (Sweden)

    Shailee V. Tiwari

    2017-07-01

    Full Text Available The work reports the synthesis under solvent-free condition using the ionic liquid [Et3NH][HSO4] as a catalyst of fifteen novel 3-((dicyclohexylamino(substituted phenyl/heteryl-methyl-4-hydroxy-2H-chromen-2-onederivatives 4a–o as potential antimicrobial agents. The structures of the synthesized compounds were confirmed by IR, 1H-NMR, 13C-NMR, mass spectral studies and elemental analyses. All the synthesized compounds were evaluated for their in vitro antifungal and antibacterial activity. The compound 4k bearing 4-hydroxy-3-ethoxy group on the phenyl ring was found to be the most active antifungal agent. The compound 4e bearing a 2,4-difluoro group on the phenyl ring was found to be the most active antibacterial agent. The mode of action of the most promising antifungal compound 4k was established by an ergosterol extraction and quantitation assay. From the assay it was found that 4k acts by inhibition of ergosterol biosynthesis in C. albicans. Molecular docking studies revealed a highly spontaneous binding ability of the tested compounds to the active site of lanosterol 14α-demethylase, which suggests that the tested compounds inhibit the synthesis of this enzyme. The synthesized compounds were analyzed for in silico ADMET properties to establish oral drug like behavior and showed satisfactory results. To establish the antimicrobial selectivity and safety, the most active compounds 4e and 4k were further tested for cytotoxicity against human cancer cell line HeLa and were found to be non-cytotoxic in nature. An in vivo acute oral toxicity study was also performed for the most active compounds 4e and 4k and results indicated that the compounds are non-toxic.

  7. Elucidation of a carotenoid biosynthesis gene cluster encoding a novel enzyme, 2,2'-beta-hydroxylase, from Brevundimonas sp. strain SD212 and combinatorial biosynthesis of new or rare xanthophylls.

    Science.gov (United States)

    Nishida, Yasuhiro; Adachi, Kyoko; Kasai, Hiroaki; Shizuri, Yoshikazu; Shindo, Kazutoshi; Sawabe, Akiyoshi; Komemushi, Sadao; Miki, Wataru; Misawa, Norihiko

    2005-08-01

    A carotenoid biosynthesis gene cluster mediating the production of 2-hydroxyastaxanthin was isolated from the marine bacterium Brevundimonas sp. strain SD212 by using a common crtI sequence as the probe DNA. A sequence analysis revealed this cluster to contain 12 open reading frames (ORFs), including the 7 known genes, crtW, crtY, crtI, crtB, crtE, idi, and crtZ. The individual ORFs were functionally analyzed by complementation studies using Escherichia coli that accumulated various carotenoid precursors due to the presence of other bacterial crt genes. In addition to functionally identifying the known crt genes, we found that one (ORF11, named crtG) coded for a novel enzyme, carotenoid 2,2'-beta-hydroxylase, which showed intriguingly partial homology with animal sterol-C5-desaturase. When this crtG gene was introduced into E. coli accumulating zeaxanthin and canthaxanthin, the resulting transformants produced their 2-hydroxylated and 2,2'-dihydroxylated products which were structurally novel or rare xanthophylls, as determined by their nuclear magnetic resonance and high-performance liquid chromatography/photodiode array detector/atmospheric pressure chemical ionization mass spectrometry spectral data. The new carotenoid produced was suggested to have a strong inhibitory effect on lipid peroxidation.

  8. Elucidation of a Carotenoid Biosynthesis Gene Cluster Encoding a Novel Enzyme, 2,2′-β-Hydroxylase, from Brevundimonas sp. Strain SD212 and Combinatorial Biosynthesis of New or Rare Xanthophylls

    Science.gov (United States)

    Nishida, Yasuhiro; Adachi, Kyoko; Kasai, Hiroaki; Shizuri, Yoshikazu; Shindo, Kazutoshi; Sawabe, Akiyoshi; Komemushi, Sadao; Miki, Wataru; Misawa, Norihiko

    2005-01-01

    A carotenoid biosynthesis gene cluster mediating the production of 2-hydroxyastaxanthin was isolated from the marine bacterium Brevundimonas sp. strain SD212 by using a common crtI sequence as the probe DNA. A sequence analysis revealed this cluster to contain 12 open reading frames (ORFs), including the 7 known genes, crtW, crtY, crtI, crtB, crtE, idi, and crtZ. The individual ORFs were functionally analyzed by complementation studies using Escherichia coli that accumulated various carotenoid precursors due to the presence of other bacterial crt genes. In addition to functionally identifying the known crt genes, we found that one (ORF11, named crtG) coded for a novel enzyme, carotenoid 2,2′-β-hydroxylase, which showed intriguingly partial homology with animal sterol-C5-desaturase. When this crtG gene was introduced into E. coli accumulating zeaxanthin and canthaxanthin, the resulting transformants produced their 2-hydroxylated and 2,2′-dihydroxylated products which were structurally novel or rare xanthophylls, as determined by their nuclear magnetic resonance and high-performance liquid chromatography/photodiode array detector/atmospheric pressure chemical ionization mass spectrometry spectral data. The new carotenoid produced was suggested to have a strong inhibitory effect on lipid peroxidation. PMID:16085816

  9. The surface science of enzymes

    DEFF Research Database (Denmark)

    Rod, Thomas Holm; Nørskov, Jens Kehlet

    2002-01-01

    One of the largest challenges to science in the coming years is to find the relation between enzyme structure and function. Can we predict which reactions an enzyme catalyzes from knowledge of its structure-or from its amino acid sequence? Can we use that knowledge to modify enzyme function......? To solve these problems we must understand in some detail how enzymes interact with reactants from its surroundings. These interactions take place at the surface of the enzyme and the question of enzyme function can be viewed as the surface science of enzymes. In this article we discuss how to describe...... catalysis by enzymes, and in particular the analogies between enzyme catalyzed reactions and surface catalyzed reactions. We do this by discussing two concrete examples of reactions catalyzed both in nature (by enzymes) and in industrial reactors (by inorganic materials), and show that although analogies...

  10. A method for predicting individual residue contributions to enzyme specificity and binding-site energies, and its application to MTH1.

    Science.gov (United States)

    Stewart, James J P

    2016-11-01

    A new method for predicting the energy contributions to substrate binding and to specificity has been developed. Conventional global optimization methods do not permit the subtle effects responsible for these properties to be modeled with sufficient precision to allow confidence to be placed in the results, but by making simple alterations to the model, the precisions of the various energies involved can be improved from about ±2 kcal mol -1 to ±0.1 kcal mol -1 . This technique was applied to the oxidized nucleotide pyrophosphohydrolase enzyme MTH1. MTH1 is unusual in that the binding and reaction sites are well separated-an advantage from a computational chemistry perspective, as it allows the energetics involved in docking to be modeled without the need to consider any issues relating to reaction mechanisms. In this study, two types of energy terms were investigated: the noncovalent interactions between the binding site and the substrate, and those responsible for discriminating between the oxidized nucleotide 8-oxo-dGTP and the normal dGTP. Both of these were investigated using the semiempirical method PM7 in the program MOPAC. The contributions of the individual residues to both the binding energy and the specificity of MTH1 were calculated by simulating the effect of mutations. Where comparisons were possible, all calculated results were in agreement with experimental observations. This technique provides fresh insight into the binding mechanism that enzymes use for discriminating between possible substrates.

  11. Docking analysis targeted to the whole enzyme: an application to the prediction of inhibition of PTP1B by thiomorpholine and thiazolyl derivatives.

    Science.gov (United States)

    Ganou, C A; Eleftheriou, P Th; Theodosis-Nobelos, P; Fesatidou, M; Geronikaki, A A; Lialiaris, T; Rekka, E A

    2018-02-01

    PTP1b is a protein tyrosine phosphatase involved in the inactivation of insulin receptor. Since inhibition of PTP1b may prolong the action of the receptor, PTP1b has become a drug target for the treatment of type II diabetes. In the present study, prediction of inhibition using docking analysis targeted specifically to the active or allosteric site was performed on 87 compounds structurally belonging to 10 different groups. Two groups, consisting of 15 thiomorpholine and 10 thiazolyl derivatives exhibiting the best prediction results, were selected for in vitro evaluation. All thiomorpholines showed inhibitory action (with IC 50 = 4-45 μΜ, Ki = 2-23 μM), while only three thiazolyl derivatives showed low inhibition (best IC 50 = 18 μΜ, Ki = 9 μΜ). However, free binding energy (E) was in accordance with the IC 50 values only for some compounds. Docking analysis targeted to the whole enzyme revealed that the compounds exhibiting IC 50 values higher than expected could bind to other peripheral sites with lower free energy, E o , than when bound to the active/allosteric site. A prediction factor, E- (Σ Eo × 0.16), which takes into account lower energy binding to peripheral sites, was proposed and was found to correlate well with the IC 50 values following an asymmetrical sigmoidal equation with r 2 = 0.9692.

  12. Prediction of therapeutic response in steroid-treated pulmonary sarcoidosis. Evaluation of clinical parameters, bronchoalveolar lavage, gallium-67 lung scanning, and serum angiotensin-converting enzyme levels

    International Nuclear Information System (INIS)

    Hollinger, W.M.; Staton, G.W. Jr.; Fajman, W.A.; Gilman, M.J.; Pine, J.R.; Check, I.J.

    1985-01-01

    To find a pretreatment predictor of steroid responsiveness in pulmonary sarcoidosis the authors studied 21 patients before and after steroid treatment by clinical evaluation, pulmonary function tests, bronchoalveolar lavage (BAL), gallium-67 lung scan, and serum angiotensin-converting enzyme (SACE) level. Although clinical score, forced vital capacity (FVC), BAL percent lymphocytes (% lymphs), quantitated gallium-67 lung uptake, and SACE levels all improved with therapy, only the pretreatment BAL % lymphs correlated with the improvement in FVC (r = 0.47, p less than 0.05). Pretreatment BAL % lymphs of greater than or equal to 35% predicted improvement in FVC of 10/11 patients, whereas among 10 patients with BAL % lymphs less than 35%, 5 patients improved and 5 deteriorated. Clinical score, pulmonary function parameters, quantitated gallium-67 lung uptake, and SACE level used alone, in combination with BAL % lymphs or in combination with each other, did not improve this predictive value. The authors conclude that steroid therapy improves a number of clinical and laboratory parameters in sarcoidosis, but only the pretreatment BAL % lymphs are useful in predicting therapeutic responsiveness

  13. Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

    Directory of Open Access Journals (Sweden)

    Schrooten Chris

    2009-01-01

    Full Text Available Abstract The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction.

  14. A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control.

    Science.gov (United States)

    Phung, Dung; Talukder, Mohammad Radwanur Rahman; Rutherford, Shannon; Chu, Cordia

    2016-10-01

    To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate-dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1-4 and 5-8 weeks increased the dengue risk 11% (95% CI, 9-13) and 7% (95% CI, 6-8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2-1.4) at lag 1-4 and 0.8% (95% CI, 0.2-1.4) at lag 5-8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05-0.16) at lag 1-4 and 0.11% (95% CI, 0.07-0.16) at lag 5-8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings. © 2016 John Wiley & Sons Ltd.

  15. Evaluation of B3LYP, X3LYP, and M06-Class Density Functionals for Predicting the Binding Energies of Neutral, Protonated, and Deprotonated Water Clusters.

    Science.gov (United States)

    Bryantsev, Vyacheslav S; Diallo, Mamadou S; van Duin, Adri C T; Goddard, William A

    2009-04-14

    In this paper we assess the accuracy of the B3LYP, X3LYP, and newly developed M06-L, M06-2X, and M06 functionals to predict the binding energies of neutral and charged water clusters including (H2O)n, n = 2-8, 20), H3O(+)(H2O)n, n = 1-6, and OH(-)(H2O)n, n = 1-6. We also compare the predicted energies of two ion hydration and neutralization reactions on the basis of the calculated binding energies. In all cases, we use as benchmarks calculated binding energies of water clusters extrapolated to the complete basis set limit of the second-order Møller-Plesset perturbation theory with the effects of higher order correlation estimated at the coupled-cluster theory with single, double, and perturbative triple excitations in the aug-cc-pVDZ basis set. We rank the accuracy of the functionals on the basis of the mean unsigned error (MUE) between calculated benchmark and density functional theory energies. The corresponding MUE (kcal/mol) for each functional is listed in parentheses. We find that M06-L (0.73) and M06 (0.84) give the most accurate binding energies using very extended basis sets such as aug-cc-pV5Z. For more affordable basis sets, the best methods for predicting the binding energies of water clusters are M06-L/aug-cc-pVTZ (1.24), B3LYP/6-311++G(2d,2p) (1.29), and M06/aug-cc-PVTZ (1.33). M06-L/aug-cc-pVTZ also gives more accurate energies for the neutralization reactions (1.38), whereas B3LYP/6-311++G(2d,2p) gives more accurate energies for the ion hydration reactions (1.69).

  16. Effects of Carbonyl Bond and Metal Cluster Dissociation and Evaporation Rates on Predictions of Nanotube Production in HiPco

    Science.gov (United States)

    Scott, Carl D.; Smalley, Richard E.

    2002-01-01

    The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNT) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the co-formation of CO2. It is shown that the production of CO2 is significantly greater for FeCO due to its lower bond energy as compared with that ofNiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

  17. Profiling the orphan enzymes

    Science.gov (United States)

    2014-01-01

    The emergence of Next Generation Sequencing generates an incredible amount of sequence and great potential for new enzyme discovery. Despite this huge amount of data and the profusion of bioinformatic methods for function prediction, a large part of known enzyme activities is still lacking an associated protein sequence. These particular activities are called “orphan enzymes”. The present review proposes an update of previous surveys on orphan enzymes by mining the current content of public databases. While the percentage of orphan enzyme activities has decreased from 38% to 22% in ten years, there are still more than 1,000 orphans among the 5,000 entries of the Enzyme Commission (EC) classification. Taking into account all the reactions present in metabolic databases, this proportion dramatically increases to reach nearly 50% of orphans and many of them are not associated to a known pathway. We extended our survey to “local orphan enzymes” that are activities which have no representative sequence in a given clade, but have at least one in organisms belonging to other clades. We observe an important bias in Archaea and find that in general more than 30% of the EC activities have incomplete sequence information in at least one superkingdom. To estimate if candidate proteins for local orphans could be retrieved by homology search, we applied a simple strategy based on the PRIAM software and noticed that candidates may be proposed for an important fraction of local orphan enzymes. Finally, by studying relation between protein domains and catalyzed activities, it appears that newly discovered enzymes are mostly associated with already known enzyme domains. Thus, the exploration of the promiscuity and the multifunctional aspect of known enzyme families may solve part of the orphan enzyme issue. We conclude this review with a presentation of recent initiatives in finding proteins for orphan enzymes and in extending the enzyme world by the discovery of new

  18. Prediction of difficult mask ventilation using a systematic assessment of risk factors vs. existing practice - a cluster randomised clinical trial in 94,006 patients

    DEFF Research Database (Denmark)

    Nørskov, A K; Wetterslev, J; Rosenstock, C V

    2017-01-01

    We compared implementation of systematic airway assessment with existing practice of airway assessment on prediction of difficult mask ventilation. Twenty-six departments were cluster-randomised to assess eleven risk factors for difficult airway management (intervention) or to continue with their......We compared implementation of systematic airway assessment with existing practice of airway assessment on prediction of difficult mask ventilation. Twenty-six departments were cluster-randomised to assess eleven risk factors for difficult airway management (intervention) or to continue...... with their existing airway assessment (control). In both groups, patients predicted as a difficult mask ventilation and/or difficult intubation were registered in the Danish Anaesthesia Database, with a notational summary of airway management. The trial's primary outcome was the respective incidence of unpredicted...... difficult and easy mask ventilation in the two groups. Among 94,006 patients undergoing mask ventilation, the incidence of unpredicted difficult mask ventilation in the intervention group was 0.91% and 0.88% in the control group; (OR) 0.98 (95% CI 0.66-1.44), p = 0.90. The incidence of patients predicted...

  19. Enzyme Informatics

    Science.gov (United States)

    Alderson, Rosanna G.; Ferrari, Luna De; Mavridis, Lazaros; McDonagh, James L.; Mitchell, John B. O.; Nath, Neetika

    2012-01-01

    Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many cheminformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking. PMID:23116471

  20. A Performance-Prediction Model for PIC Applications on Clusters of Symmetric MultiProcessors: Validation with Hierarchical HPF+OpenMP Implementation

    Directory of Open Access Journals (Sweden)

    Sergio Briguglio

    2003-01-01

    Full Text Available A performance-prediction model is presented, which describes different hierarchical workload decomposition strategies for particle in cell (PIC codes on Clusters of Symmetric MultiProcessors. The devised workload decomposition is hierarchically structured: a higher-level decomposition among the computational nodes, and a lower-level one among the processors of each computational node. Several decomposition strategies are evaluated by means of the prediction model, with respect to the memory occupancy, the parallelization efficiency and the required programming effort. Such strategies have been implemented by integrating the high-level languages High Performance Fortran (at the inter-node stage and OpenMP (at the intra-node one. The details of these implementations are presented, and the experimental values of parallelization efficiency are compared with the predicted results.

  1. Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models.

    Science.gov (United States)

    Najaf, Pooya; Duddu, Venkata R; Pulugurtha, Srinivas S

    2018-03-01

    Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine both ML and statistical methods to develop hybrid link-level crash frequency models with high predictability and interpretability. For this purpose, M5' model trees method (M5') is introduced and applied to classify the crash data and then calibrate a model for each homogenous class. The data for 1134 and 345 randomly selected links on urban arterials in the city of Charlotte, North Carolina was used to develop and validate models, respectively. The outputs from the hybrid approach are compared with the outputs from cluster-based negative binomial regression (NBR) and general NBR models. Findings indicate that M5' has high predictability and is very reliable to interpret the role of different attributes on crash frequency compared to other developed models.

  2. Cardiac metaiodobenzylguanidine activity can predict the long-term efficacy of angiotensin-converting enzyme inhibitors and/or beta-adrenoceptor blockers in patients with heart failure

    Energy Technology Data Exchange (ETDEWEB)

    Nakata, Tomoaki; Wakabayashi, Takeru; Kyuma, Michifumi; Takahashi, Toru; Tsuchihashi, Kazufumi; Shimamoto, Kazuaki [Sapporo Medical University School of Medicine, Second Department of Internal Medicine (Cardiology), Sapporo (Japan)

    2005-02-01

    Although the benefits of treatment with angiotensin-converting enzyme (ACE) inhibitors and beta-blockers are well known, no method has as yet been established to predict the efficacy of drug therapy. This study tested whether cardiac{sup 123}I-metaiodobenzylguanidine (MIBG) activity is of prognostic value and can predict the improvement in heart failure patients resulting from treatment with ACE inhibitors and/or beta-blockers. Following quantification of the heart-to-mediastinum ratio (HMR) of MIBG activity, 88 patients with heart failure who were treated with ACE inhibitors and/or beta-blockers (treated group) and 79 patients with heart failure who were treated conventionally without the aforementioned agents, and who served as controls, were followed up for 43 months with a primary endpoint of cardiac death. The treated group had a significantly lower prevalence of cardiac death and a significantly lower mortality at 5 years compared with the control group (15% vs 37% and 21% vs 42%, p<0.05, respectively). Multivariate analysis revealed that significant predictors were HMR, age, nitrate use and ventricular tachycardia for the treated group, and HMR, nitrate use and NYHA class for the control group. The drug treatment significantly reduced mortality from 36% to 12% when HMR was 1.53 or more and from 53% to 37% when HMR was less than 1.53. The reduction in risk of mortality within 5 years in patients without a severe MIBG defect (67%) was twice that in patients with such a defect (32%) (p<0.05). The reduction in mortality risk achieved by using ACE inhibitors and/or beta-blockers is associated with the severity of impairment of cardiac MIBG uptake. Cardiac MIBG activity can consequently be of long-term prognostic value in predicting the effectiveness of such treatment in patients with heart failure. (orig.)

  3. Cardiac metaiodobenzylguanidine activity can predict the long-term efficacy of angiotensin-converting enzyme inhibitors and/or beta-adrenoceptor blockers in patients with heart failure

    International Nuclear Information System (INIS)

    Nakata, Tomoaki; Wakabayashi, Takeru; Kyuma, Michifumi; Takahashi, Toru; Tsuchihashi, Kazufumi; Shimamoto, Kazuaki

    2005-01-01

    Although the benefits of treatment with angiotensin-converting enzyme (ACE) inhibitors and beta-blockers are well known, no method has as yet been established to predict the efficacy of drug therapy. This study tested whether cardiac 123 I-metaiodobenzylguanidine (MIBG) activity is of prognostic value and can predict the improvement in heart failure patients resulting from treatment with ACE inhibitors and/or beta-blockers. Following quantification of the heart-to-mediastinum ratio (HMR) of MIBG activity, 88 patients with heart failure who were treated with ACE inhibitors and/or beta-blockers (treated group) and 79 patients with heart failure who were treated conventionally without the aforementioned agents, and who served as controls, were followed up for 43 months with a primary endpoint of cardiac death. The treated group had a significantly lower prevalence of cardiac death and a significantly lower mortality at 5 years compared with the control group (15% vs 37% and 21% vs 42%, p<0.05, respectively). Multivariate analysis revealed that significant predictors were HMR, age, nitrate use and ventricular tachycardia for the treated group, and HMR, nitrate use and NYHA class for the control group. The drug treatment significantly reduced mortality from 36% to 12% when HMR was 1.53 or more and from 53% to 37% when HMR was less than 1.53. The reduction in risk of mortality within 5 years in patients without a severe MIBG defect (67%) was twice that in patients with such a defect (32%) (p<0.05). The reduction in mortality risk achieved by using ACE inhibitors and/or beta-blockers is associated with the severity of impairment of cardiac MIBG uptake. Cardiac MIBG activity can consequently be of long-term prognostic value in predicting the effectiveness of such treatment in patients with heart failure. (orig.)

  4. Characterization and prediction of the backscattered form function of an immersed cylindrical shell using hybrid fuzzy clustering and bio-inspired algorithms.

    Science.gov (United States)

    Agounad, Said; Aassif, El Houcein; Khandouch, Younes; Maze, Gérard; Décultot, Dominique

    2018-02-01

    The acoustic scattering of a plane wave by an elastic cylindrical shell is studied. A new approach is developed to predict the form function of an immersed cylindrical shell of the radius ratio b/a ('b' is the inner radius and 'a' is the outer radius). The prediction of the backscattered form function is investigated by a combined approach between fuzzy clustering algorithms and bio-inspired algorithms. Four famous fuzzy clustering algorithms: the fuzzy c-means (FCM), the Gustafson-Kessel algorithm (GK), the fuzzy c-regression model (FCRM) and the Gath-Geva algorithm (GG) are combined with particle swarm optimization and genetic algorithm. The symmetric and antisymmetric circumferential waves A, S 0 , A 1 , S 1 and S 2 are investigated in a reduced frequency (k 1 a) range extends over 0.1predicted and calculated acoustic backscattered form functions. This representation is used as a comparison criterion between the calculated form function by the analytical method and that predicted by the proposed approach on the one hand and is used to extract the predicted cut-off frequencies on the other hand. Moreover, the transverse velocity of the material constituting the cylindrical shell is extracted. The computational results show that the proposed approach is very efficient to predict the form function and consequently, for acoustic characterization purposes. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Predicting symptom clusters of posttraumatic stress disorder (PTSD) in Croatian war veterans: the role of socio-demographics, war experiences and subjective quality of life.

    Science.gov (United States)

    Lončar, Mladen; Plašć, Ivana Dijanić; Bunjevac, Tomislav; Hrabač, Pero; Jakšić, Nenad; Kozina, Slavica; Henigsberg, Neven; Sagud, Marina; Marčinko, Darko

    2014-09-01

    Previous research has documented multiple chains of risk in the development of PTSD among war veterans. However, existing studies were mostly carried out in the West, while they also did not analyze specific symptom clusters of PTSD. The aim of this study was to examine the role of socio-demographic characteristics, war experiences and subjective quality of life in the prediction of three clusters of PTSD symptoms (i.e., avoidance, intrusion, hyperarousal). This study comprised 184 male participants who have survived war imprisonment during the Croatian Homeland War in the period from 1991 to 1995. The data was collected through several self-report measuring instruments: questionnaire on socio-demographic data, war experiences (Questionnaire on Traumatic Combat and War Experiences), subjective quality of life (WHO-Five Well-being Index), and PTSD symptoms (Impact of Events Scale - Revised). The level of three symptom clusters of PTSD was found to be moderate to high, as indicated by the scores on the IES-R. Results of the three hierarchical regression analyses showed the following: traumatic war experiences were significant predictors of avoidance symptoms; traumatic war experiences and subjective quality of life were significant predictors of hyperarousal symptoms; and traumatic war experiences, material status and subjective quality of life were significant predictors of intrusion symptoms. These findings support the widespread belief that the development of war-related PTSD is accounted for by multiple chains of risk, while traumatic war experiences seem to be the only predictor of all three symptom clusters. Future research should put more emphasis on specific PTSD symptom clusters when investigating the etiopathogenesis of this disorder among war-affected populations.

  6. Combining Microbial Enzyme Kinetics Models with Light Use Efficiency Models to Predict CO2 and CH4 Ecosystem Exchange from Flooded and Drained Peatland Systems

    Science.gov (United States)

    Oikawa, P. Y.; Jenerette, D.; Knox, S. H.; Sturtevant, C. S.; Verfaillie, J. G.; Baldocchi, D. D.

    2014-12-01

    Under California's Cap-and-Trade program, companies are looking to invest in land-use practices that will reduce greenhouse gas (GHG) emissions. The Sacramento-San Joaquin River Delta is a drained cultivated peatland system and a large source of CO2. To slow soil subsidence and reduce CO2 emissions, there is growing interest in converting drained peatlands to wetlands. However, wetlands are large sources of CH4 that could offset CO2-based GHG reductions. The goal of our research is to provide accurate measurements and model predictions of the changes in GHG budgets that occur when drained peatlands are restored to wetland conditions. We have installed a network of eddy covariance towers across multiple land use types in the Delta and have been measuring CO2 and CH4 ecosystem exchange for multiple years. In order to upscale these measurements through space and time we are using these data to parameterize and validate a process-based biogeochemical model. To predict gross primary productivity (GPP), we are using a simple light use efficiency (LUE) model which requires estimates of light, leaf area index and air temperature and can explain 90% of the observed variation in GPP in a mature wetland. To predict ecosystem respiration we have adapted the Dual Arrhenius Michaelis-Menten (DAMM) model. The LUE-DAMM model allows accurate simulation of half-hourly net ecosystem exchange (NEE) in a mature wetland (r2=0.85). We are working to expand the model to pasture, rice and alfalfa systems in the Delta. To predict methanogenesis, we again apply a modified DAMM model, using simple enzyme kinetics. However CH4 exchange is complex and we have thus expanded the model to predict not only microbial CH4 production, but also CH4 oxidation, CH4 storage and the physical processes regulating the release of CH4 to the atmosphere. The CH4-DAMM model allows accurate simulation of daily CH4 ecosystem exchange in a mature wetland (r2=0.55) and robust estimates of annual CH4 budgets. The LUE

  7. Comparison of illness representations dimensions and illness representation clusters in predicting outcomes in the first year following diagnosis of type 2 diabetes

    DEFF Research Database (Denmark)

    Skinner, T. C.; Carey, M. E.; Cradock, S.

    2011-01-01

    trial of a self-management education intervention for people with type 2 diabetes, completed measures of illness beliefs (coherence, timeline, impact, seriousness, personal responsibility) and depression along with HbA1c and body mass index (BMI), at baseline 4, 8 and 12 months. The results......This article explores the utility of cluster analysis of illness representations, in comparison to analysing each dimension of the individual's illness representation, to predict an individual's response to diagnosis of type 2 diabetes. Participants in a large multi-centre randomised controlled...

  8. Stabilization of dendritic spine clusters and hyperactive Ras-MAPK signaling predict enhanced motor learning in an autistic savant mouse model

    Directory of Open Access Journals (Sweden)

    Ryan Thomas Ash

    2014-03-01

    Full Text Available That both prominent behavioral inflexibility and exceptional learning abilities are seen occasionally in autistic patients is a mystery. We hypothesize that these altered patterns of learning and memory can arise from a pathological imbalance between the stability and plasticity of internal neural representations. We evaluated this hypothesis in the mouse model of MECP2 duplication syndrome, which demonstrates enhanced motor learning, stereotyped behaviors, and social avoidance. Learning-associated structural plasticity was measured in the motor cortex of MECP2 duplication mice by 2-photon imaging (Fig. 1A. An increased stabilization rate of learning-associated dendritic spines was observed in mutants, and this correlated with rotarod performance. Analysis of the spatial distribution of stabilized spines revealed that the mutant’s increased spine stabilization was due to a specific increase in the stability of spines jointly formed in ~9-micron clusters. Clustered spine stabilization but not isolated spine stabilization predicted enhanced motor performance in MECP2 duplication mice (Fig. 1B. Biochemical assays of Ras-MAPK and mTOR pathway activation demonstrated profound hyperphosphorylation of MAPK in the motor cortex of MECP2 duplication mice with motor training (Fig. 1C. Taken together these data suggest that a pathological bias towards hyperstability of learning-associated dendritic spine clusters driven by hyperactive Ras-MAPK signaling could contribute to neurobehavioral phenotypes in this form of syndromic autism.

  9. Structural prediction and comparative docking studies of psychrophilic β- Galactosidase with lactose, ONPG and PNPG against its counter parts of mesophilic and thermophilic enzymes.

    Science.gov (United States)

    Kumar, Ponnada Suresh; Pulicherla, Kk; Ghosh, Mrinmoy; Kumar, Anmol; Rao, Krs Sambasiva

    2011-01-01

    Enzymes from psychrophiles catalyze the reactions at low temperatures with higher specific activity. Among all the psychrophilic enzymes produced, cold active β-galactosidase from marine psychrophiles revalorizes a new arena in numerous areas at industrial level. The hydrolysis of lactose in to glucose and galactose by cold active β-galactosidase offers a new promising approach in removal of lactose from milk to overcome the problem of lactose intolerance. Herein we propose, a 3D structure of cold active β-galactosidase enzyme sourced from Pseudoalteromonas haloplanktis by using Modeler 9v8 and best model was developed having 88% of favourable region in ramachandran plot. Modelling was followed by docking studies with the help of Auto dock 4.0 against the three substrates lactose, ONPG and PNPG. In addition, comparative docking studies were also performed for the 3D model of psychrophilic β-galactosidase with mesophilic and thermophilic enzymes. Docking studies revealed that binding affinity of enzyme towards the three different substrates is more for psychrophilic enzyme when compared with mesophilic and thermophilic enzymes. It indicates that the enzyme has high specific activity at low temperature when compared with mesophilic and thermophilic enzymes.

  10. SU-D-204-01: A Methodology Based On Machine Learning and Quantum Clustering to Predict Lung SBRT Dosimetric Endpoints From Patient Specific Anatomic Features

    Energy Technology Data Exchange (ETDEWEB)

    Lafata, K; Ren, L; Wu, Q; Kelsey, C; Hong, J; Cai, J; Yin, F [Duke University Medical Center, Durham, NC (United States)

    2016-06-15

    Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space to identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong

  11. Development of a radiation track structure clustering algorithm for the prediction of DNA DSB yields and radiation induced cell death in Eukaryotic cells.

    Science.gov (United States)

    Douglass, Michael; Bezak, Eva; Penfold, Scott

    2015-04-21

    The preliminary framework of a combined radiobiological model is developed and calibrated in the current work. The model simulates the production of individual cells forming a tumour, the spatial distribution of individual ionization events (using Geant4-DNA) and the stochastic biochemical repair of DNA double strand breaks (DSBs) leading to the prediction of survival or death of individual cells. In the current work, we expand upon a previously developed tumour generation and irradiation model to include a stochastic ionization damage clustering and DNA lesion repair model. The Geant4 code enabled the positions of each ionization event in the cells to be simulated and recorded for analysis. An algorithm was developed to cluster the ionization events in each cell into simple and complex double strand breaks. The two lesion kinetic (TLK) model was then adapted to predict DSB repair kinetics and the resultant cell survival curve. The parameters in the cell survival model were then calibrated using experimental cell survival data of V79 cells after low energy proton irradiation. A monolayer of V79 cells was simulated using the tumour generation code developed previously. The cells were then irradiated by protons with mean energies of 0.76 MeV and 1.9 MeV using a customized version of Geant4. By replicating the experimental parameters of a low energy proton irradiation experiment and calibrating the model with two sets of data, the model is now capable of predicting V79 cell survival after low energy (cell survival probability, the cell survival probability is calculated for each cell in the geometric tumour model developed in the current work. This model uses fundamental measurable microscopic quantities such as genome length rather than macroscopic radiobiological quantities such as alpha/beta ratios. This means that the model can be theoretically used under a wide range of conditions with a single set of input parameters once calibrated for a given cell line.

  12. Random-walk enzymes

    Science.gov (United States)

    Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.

    2015-09-01

    Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C →U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.

  13. antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

    Science.gov (United States)

    Weber, Tilmann; Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko; Medema, Marnix H

    2015-07-01

    Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

    Science.gov (United States)

    Shi, Jian-Yu; Yiu, Siu-Ming; Li, Yiming; Leung, Henry C M; Chin, Francis Y L

    2015-07-15

    Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Post-traumatic stress symptom clusters in acute whiplash associated disorder and their prediction of chronic pain-related disability

    OpenAIRE

    Annick Maujean; Matthew J. Gullo; Tonny Elmose Andersen; Sophie Lykkegaard Ravn; Michele Sterling

    2017-01-01

    Abstract. Introduction:. The presence of post-traumatic stress disorder (PTSD) symptoms has been found to be associated with an increased risk of persisting neck pain and disability in motor vehicle crash (MVC) survivors with whiplash injuries. The findings are mixed as to which PTSD symptom(s) best predicts recovery in this population. Objectives:. The aims were (1) to explore the factor structure of the Post-traumatic Stress Diagnostic Scale (PDS) in a sample of acute whiplash-injured in...

  16. The prediction of burnout in non-uniformly heated rod clusters from burnout data for uniformly heated round tubes

    International Nuclear Information System (INIS)

    Barnett, P.G.

    1964-11-01

    The practice of using burnout data for uniformly heated round tubes to predict burnout in non-uniformly heated reactor channels having complex cross sections is examined. At least two hypotheses are involved: (i) a relationship exists between uniform and non-uniform heat flux distributions and (ii) a relationship exists between simple and complex channel cross sections. Use of two such hypotheses each accurate to ± 15% and a correlation of uniformly heated round tube data having an R.M.S. error of 5%, could yield errors of ± 40% in any predicted value; this figure of ± 40% is regarded as a realistic upper limit for design purposes. It is shown that no method can exist for relating different channel cross sections to within ± 15% and existing methods for relating different heat flux distributions incur some errors exceeding 20%. Furthermore, any suggested method for relating different heat flux distributions can be adequately checked only when a sufficiently large number of results are available and then the preferable alternative of correlating the data is possible. It is concluded that no reliable method can exist for predicting burnout in rod bundles from uniformly heated round tube data with sufficient accuracy for design purposes. (author)

  17. Clustering of Emerging Flux

    Science.gov (United States)

    Ruzmaikin, A.

    1997-01-01

    Observations show that newly emerging flux tends to appear on the Solar surface at sites where there is flux already. This results in clustering of solar activity. Standard dynamo theories do not predict this effect.

  18. Trapping of He clusters by inert-gas impurities in tungsten: First-principles predictions and experimental validation

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen-Manh, Duc, E-mail: duc.nguyen@ccfe.ac.uk; Dudarev, S.L.

    2015-06-01

    Properties of point defects resulting from the incorporation of inert-gas atoms in bcc tungsten are investigated systematically using first-principles density functional theory (DFT) calculations. The most stable configuration for the interstitial neon, argon, krypton and xenon atoms is the tetrahedral site, similarly to what was found earlier for helium in W. The calculated formation energies for single inert-gas atoms at interstitial sites as well as at substitutional sites are much larger for Ne, Ar, Kr and Xe than for He. While the variation of the energy of insertion of inert-gas defects into interstitial configurations can be explained by a strong effect of their large atomic size, the trend exhibited by their substitutional energies is more likely related to the covalent interaction between the noble gas impurity atoms and the tungsten atoms. There is a remarkable variation exhibited by the energy of interaction between inert-gas impurities and vacancies, where a pronounced size effect is observed when going from He to Ne, Ar, Kr, Xe. The origin of this trend is explained by electronic structure calculations showing that p-orbitals play an important part in the formation of chemical bonds between a vacancy and an atom of any of the four inert-gas elements in comparison with helium, where the latter contains only 1s{sup 2} electrons in the outer shell. The binding energies of a helium atom trapped by five different defects (He-v, Ne-v, Ar-v, Kr-v, Xe-v, where v denotes a vacancy in bcc-W) are all in excellent agreement with experimental data derived from thermal desorption spectroscopy. Attachment of He clusters to inert gas impurity atom traps in tungsten is analysed as a function of the number of successive trapping helium atoms. Variation of the Young modulus due to inert-gas impurities is analysed on the basis of data derived from DFT calculations.

  19. Cluster headache

    Science.gov (United States)

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

  20. Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study

    Science.gov (United States)

    Marttinen, Pekka; Gillberg, Jussi; Lokki, A. Inkeri; Majander, Kerttu; Ordén, Maija-Riitta; Taipale, Pekka; Pesonen, Anukatriina; Räikkönen, Katri; Hämäläinen, Esa; Kajantie, Eero; Laivuori, Hannele

    2017-01-01

    Objectives Preeclampsia is divided into early-onset (delivery before 34 weeks of gestation) and late-onset (delivery at or after 34 weeks) subtypes, which may rise from different etiopathogenic backgrounds. Early-onset disease is associated with placental dysfunction. Late-onset disease develops predominantly due to metabolic disturbances, obesity, diabetes, lipid dysfunction, and inflammation, which affect endothelial function. Our aim was to use cluster analysis to investigate clinical factors predicting the onset and severity of preeclampsia in a cohort of women with known clinical risk factors. Methods We recruited 903 pregnant women with risk factors for preeclampsia at gestational weeks 12+0–13+6. Each individual outcome diagnosis was independently verified from medical records. We applied a Bayesian clustering algorithm to classify the study participants to clusters based on their particular risk factor combination. For each cluster, we computed the risk ratio of each disease outcome, relative to the risk in the general population. Results The risk of preeclampsia increased exponentially with respect to the number of risk factors. Our analysis revealed 25 number of clusters. Preeclampsia in a previous pregnancy (n = 138) increased the risk of preeclampsia 8.1 fold (95% confidence interval (CI) 5.7–11.2) compared to a general population of pregnant women. Having a small for gestational age infant (n = 57) in a previous pregnancy increased the risk of early-onset preeclampsia 17.5 fold (95%CI 2.1–60.5). Cluster of those two risk factors together (n = 21) increased the risk of severe preeclampsia to 23.8-fold (95%CI 5.1–60.6), intermediate onset (delivery between 34+0–36+6 weeks of gestation) to 25.1-fold (95%CI 3.1–79.9) and preterm preeclampsia (delivery before 37+0 weeks of gestation) to 16.4-fold (95%CI 2.0–52.4). Body mass index over 30 kg/m2 (n = 228) as a sole risk factor increased the risk of preeclampsia to 2.1-fold (95%CI 1.1–3

  1. The Enzyme Function Initiative†

    Science.gov (United States)

    Gerlt, John A.; Allen, Karen N.; Almo, Steven C.; Armstrong, Richard N.; Babbitt, Patricia C.; Cronan, John E.; Dunaway-Mariano, Debra; Imker, Heidi J.; Jacobson, Matthew P.; Minor, Wladek; Poulter, C. Dale; Raushel, Frank M.; Sali, Andrej; Shoichet, Brian K.; Sweedler, Jonathan V.

    2011-01-01

    The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily-specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include: 1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation); 2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia; 3) computational and bioinformatic tools for using the strategy; 4) provision of experimental protocols and/or reagents for enzyme production and characterization; and 5) dissemination of data via the EFI’s website, enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal and pharmaceutical efforts. PMID

  2. The Enzyme Function Initiative.

    Science.gov (United States)

    Gerlt, John A; Allen, Karen N; Almo, Steven C; Armstrong, Richard N; Babbitt, Patricia C; Cronan, John E; Dunaway-Mariano, Debra; Imker, Heidi J; Jacobson, Matthew P; Minor, Wladek; Poulter, C Dale; Raushel, Frank M; Sali, Andrej; Shoichet, Brian K; Sweedler, Jonathan V

    2011-11-22

    The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts.

  3. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  4. Consumer attitudes to enzymes in food production

    DEFF Research Database (Denmark)

    Søndergaard, Helle Alsted; Grunert, Klaus G.; Scholderer, Joachim

    2005-01-01

    The use of enzymes in food production has potential benefits for both food manufacturers and consumers. A central question is how consumers react to new ways of producing foods with enzymes. This study investigates the formation of consumer attitudes to different enzyme production methods in three...... European countries. Results show that consumers are most positive towards non-GM enzyme production methods. The enzyme production method is by far the most important factor for the formation of buying intentions compared to price and benefits. Results also show that environmental concern and attitudes...... to technological progress are the socio-political attitudes that have the highest predictive value regarding attitudes to enzyme production methods....

  5. Cluster management.

    Science.gov (United States)

    Katz, R

    1992-11-01

    Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

  6. Prediction of the fate of Hg and other contaminants in soil around a former chlor-alkali plant using Fuzzy Hierarchical Cross-Clustering approach.

    Science.gov (United States)

    Frenţiu, Tiberiu; Ponta, Michaela; Sârbu, Costel

    2015-11-01

    An associative simultaneous fuzzy divisive hierarchical algorithm was used to predict the fate of Hg and other contaminants in soil around a former chlor-alkali plant. The algorithm was applied on several natural and anthropogenic characteristics of soil including water leachable, mobile, semi-mobile, non-mobile fractions and total Hg, Al, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Sr, Zn, water leachable fraction of Cl(-), NO3(-) and SO4(2)(-), pH and total organic carbon. The cross-classification algorithm provided a divisive fuzzy partition of the soil samples and associated characteristics. Soils outside the perimeter of the former chlor-alkali plant were clustered based on the natural characteristics and total Hg. In contaminated zones Hg speciation becomes relevant and the assessment of species distribution is necessary. The descending order of concentration of Hg species in the test site was semi-mobile>mobile>non-mobile>water-leachable. Physico-chemical features responsible for similarities or differences between uncontaminated soil samples or contaminated with Hg, Cu, Zn, Ba and NO3(-) were also highlighted. Other characteristics of the contaminated soil were found to be Ca, sulfate, Na and chloride, some of which with influence on Hg fate. The presence of Ca and sulfate in soil induced a higher water leachability of Hg, while Cu had an opposite effect by forming amalgam. The used algorithm provided an in-deep understanding of processes involving Hg species and allowed to make prediction of the fate of Hg and contaminants linked to chlor-alkali-industry. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Characteristics of Clusters of Salmonella and Escherichia coli O157 Detected by Pulsed-Field Gel Electrophoresis that Predict Identification of Outbreaks.

    Science.gov (United States)

    Jones, Timothy F; Sashti, Nupur; Ingram, Amanda; Phan, Quyen; Booth, Hillary; Rounds, Joshua; Nicholson, Cyndy S; Cosgrove, Shaun; Crocker, Kia; Gould, L Hannah

    2016-12-01

    Molecular subtyping of pathogens is critical for foodborne disease outbreak detection and investigation. Many clusters initially identified by pulsed-field gel electrophoresis (PFGE) are not confirmed as point-source outbreaks. We evaluated characteristics of clusters that can help prioritize investigations to maximize effective use of limited resources. A multiagency collaboration (FoodNet) collected data on Salmonella and Escherichia coli O157 clusters for 3 years. Cluster size, timing, extent, and nature of epidemiologic investigations were analyzed to determine associations with whether the cluster was identified as a confirmed outbreak. During the 3-year study period, 948 PFGE clusters were identified; 849 (90%) were Salmonella and 99 (10%) were E. coli O157. Of those, 192 (20%) were ultimately identified as outbreaks (154 [18%] of Salmonella and 38 [38%] of E. coli O157 clusters). Successful investigation was significantly associated with larger cluster size, more rapid submission of isolates (e.g., for Salmonella, 6 days for outbreaks vs. 8 days for nonoutbreaks) and PFGE result reporting to investigators (16 days vs. 29 days, respectively), and performance of analytic studies (completed in 33% of Salmonella outbreaks vs. 1% of nonoutbreaks) and environmental investigations (40% and 1%, respectively). Intervals between first and second cases in a cluster did not differ significantly between outbreaks and nonoutbreaks. Molecular subtyping of pathogens is a rapidly advancing technology, and successfully identifying outbreaks will vary by pathogen and methods used. Understanding criteria for successfully investigating outbreaks is critical for efficiently using limited resources.

  8. Isotopic clusters

    International Nuclear Information System (INIS)

    Geraedts, J.M.P.

    1983-01-01

    Spectra of isotopically mixed clusters (dimers of SF 6 ) are calculated as well as transition frequencies. The result leads to speculations about the suitability of the laser-cluster fragmentation process for isotope separation. (Auth.)

  9. Cluster Headache

    Science.gov (United States)

    ... a role. Unlike migraine and tension headache, cluster headache generally isn't associated with triggers, such as foods, hormonal changes or stress. Once a cluster period begins, however, drinking alcohol ...

  10. Ku70, Ku80, and sClusterin: A Cluster of Predicting Factors for Response to Neoadjuvant Chemoradiation Therapy in Patients With Locally Advanced Rectal Cancer

    International Nuclear Information System (INIS)

    Pucci, Sabina; Polidoro, Chiara; Joubert, Alessandro; Mastrangeli, Francesca; Tolu, Barbara; Benassi, Michaela; Fiaschetti, Valeria; Greco, Laura; Miceli, Roberto; Floris, Roberto; Novelli, Giuseppe; Orlandi, Augusto; Santoni, Riccardo

    2017-01-01

    Purpose: The identification of predictive biomarkers for neoadjuvant chemoradiation therapy (CRT) is a current clinical need. The heterodimer Ku70/80 plays a critical role in DNA repair and cell death induction after damage. The aberrant expression and localization of these proteins fail to control DNA repair and apoptosis. sClusterin is the Ku70 partner that sterically inhibits Bax-dependent cell death after damage in some pathologic conditions. This study sought to evaluate the molecular relevance of Ku70-Ku80-Clu as a molecular cluster predicting the response to neoadjuvant CRT in patients with locally advanced rectal cancer (LARC). Methods and Materials: Patients enrolled in this study underwent preoperative CRT followed by surgical excision. A retrospective study based on individual response, evaluated by computed tomography and diffusion-weighted magnetic resonance imaging, identified responder (56%) and no-responder patients (44%). Ku70/80 and Clu expression were observed in biopsy specimens obtained before and after treatment with neoadjuvant CRT from the same LARC patients. In vitro studies before and after irradiation were also performed on radioresistant (SW480) and radiosensitive (SW620) colorectal cancer cell lines, mimicking sensitive or resistant tumor behavior. Results: We found a conventional nuclear localization of Ku70/80 in pretherapeutic tumor biopsies of responder patients, in agreement with their role in DNA repair and regulating apoptosis. By contrast, in the no-responder population we observed an unconventional overexpression of Ku70 in the cytoplasm (P<.001). In this context we also overexpression of sClu in the cytoplasm, which accorded with its role in stabilizing of Bax-Ku70 complex, inhibiting Bax-dependent apoptosis. Strikingly, Ku80 in these tumor tissues was lost (P<.005). In vitro testing of colon cancer cells finally confirmed the results observed in tumor biopsy specimens, proving that Ku70/80-Clu deregulation is extensively

  11. Ku70, Ku80, and sClusterin: A Cluster of Predicting Factors for Response to Neoadjuvant Chemoradiation Therapy in Patients With Locally Advanced Rectal Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Pucci, Sabina, E-mail: sabina.pucci@uniroma2.it; Polidoro, Chiara; Joubert, Alessandro; Mastrangeli, Francesca; Tolu, Barbara; Benassi, Michaela; Fiaschetti, Valeria; Greco, Laura; Miceli, Roberto; Floris, Roberto; Novelli, Giuseppe; Orlandi, Augusto; Santoni, Riccardo

    2017-02-01

    Purpose: The identification of predictive biomarkers for neoadjuvant chemoradiation therapy (CRT) is a current clinical need. The heterodimer Ku70/80 plays a critical role in DNA repair and cell death induction after damage. The aberrant expression and localization of these proteins fail to control DNA repair and apoptosis. sClusterin is the Ku70 partner that sterically inhibits Bax-dependent cell death after damage in some pathologic conditions. This study sought to evaluate the molecular relevance of Ku70-Ku80-Clu as a molecular cluster predicting the response to neoadjuvant CRT in patients with locally advanced rectal cancer (LARC). Methods and Materials: Patients enrolled in this study underwent preoperative CRT followed by surgical excision. A retrospective study based on individual response, evaluated by computed tomography and diffusion-weighted magnetic resonance imaging, identified responder (56%) and no-responder patients (44%). Ku70/80 and Clu expression were observed in biopsy specimens obtained before and after treatment with neoadjuvant CRT from the same LARC patients. In vitro studies before and after irradiation were also performed on radioresistant (SW480) and radiosensitive (SW620) colorectal cancer cell lines, mimicking sensitive or resistant tumor behavior. Results: We found a conventional nuclear localization of Ku70/80 in pretherapeutic tumor biopsies of responder patients, in agreement with their role in DNA repair and regulating apoptosis. By contrast, in the no-responder population we observed an unconventional overexpression of Ku70 in the cytoplasm (P<.001). In this context we also overexpression of sClu in the cytoplasm, which accorded with its role in stabilizing of Bax-Ku70 complex, inhibiting Bax-dependent apoptosis. Strikingly, Ku80 in these tumor tissues was lost (P<.005). In vitro testing of colon cancer cells finally confirmed the results observed in tumor biopsy specimens, proving that Ku70/80-Clu deregulation is extensively

  12. Cluster Headache

    OpenAIRE

    Pearce, Iris

    1985-01-01

    Cluster headache is the most severe primary headache with recurrent pain attacks described as worse than giving birth. The aim of this paper was to make an overview of current knowledge on cluster headache with a focus on pathophysiology and treatment. This paper presents hypotheses of cluster headache pathophysiology, current treatment options and possible future therapy approaches. For years, the hypothalamus was regarded as the key structure in cluster headache, but is now thought to be pa...

  13. Categorias Cluster

    OpenAIRE

    Queiroz, Dayane Andrade

    2015-01-01

    Neste trabalho apresentamos as categorias cluster, que foram introduzidas por Aslak Bakke Buan, Robert Marsh, Markus Reineke, Idun Reiten e Gordana Todorov, com o objetivo de categoriíicar as algebras cluster criadas em 2002 por Sergey Fomin e Andrei Zelevinsky. Os autores acima, em [4], mostraram que existe uma estreita relação entre algebras cluster e categorias cluster para quivers cujo grafo subjacente é um diagrama de Dynkin. Para isto desenvolveram uma teoria tilting na estrutura triang...

  14. Meaningful Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Calapristi, Augustin J.; Crow, Vernon L.; Hetzler, Elizabeth G.; Turner, Alan E.

    2004-05-26

    We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense disambiguation.

  15. Horticultural cluster

    OpenAIRE

    SHERSTIUK S.V.; POSYLAYEVA K.I.

    2013-01-01

    In the article there are the theoretical and methodological approaches to the nature and existence of the cluster. The cluster differences from other kinds of cooperative and integration associations. Was develop by scientific-practical recommendations for forming a competitive horticultur cluster.

  16. Gene polymorphisms as risk factors for predicting the cardiovascular manifestations in Marfan syndrome. Role of folic acid metabolism enzyme gene polymorphisms in Marfan syndrome.

    Science.gov (United States)

    Benke, Kálmán; Ágg, Bence; Mátyás, Gábor; Szokolai, Viola; Harsányi, Gergely; Szilveszter, Bálint; Odler, Balázs; Pólos, Miklós; Maurovich-Horvat, Pál; Radovits, Tamás; Merkely, Béla; Nagy, Zsolt B; Szabolcs, Zoltán

    2015-10-01

    Folic acid metabolism enzyme polymorphisms are believed to be responsible for the elevation of homocysteine (HCY) concentration in the blood plasma, correlating with the pathogenesis of aortic aneurysms and aortic dissection. We studied 71 Marfan patients divided into groups based on the severity of cardiovascular involvement: no intervention required (n=27, Group A); mild involvement requiring intervention (n=17, Group B); severe involvement (n=27, Group C) subdivided into aortic dilatation (n=14, Group C1) and aortic dissection (n=13, Group C2), as well as 117 control subjects. We evaluated HCY, folate, vitamin B12 and the polymorphisms of methylenetetrahydrofolate reductase (MTHFR;c.665C>T and c.1286A>C), methionine synthase (MTR;c.2756A>G) and methionine synthase reductase (MTRR;c.66A>G). Multiple comparisons showed significantly higher levels of HCY in Group C2 compared to Groups A, B, C1 and control group (pMarfan patients, and especially aortic dissection, is associated with higher HCY plasma levels and prevalence of homozygous genotypes of folic acid metabolism enzymes than mild or no cardiovascular involvement. These results suggest that impaired folic acid metabolism has an important role in the development and remodelling of the extracellular matrix of the aorta.

  17. Cluster Matters

    DEFF Research Database (Denmark)

    Gulati, Mukesh; Lund-Thomsen, Peter; Suresh, Sangeetha

    2018-01-01

    sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country...... of this handbook, which focuses on the role of CSR in MSMEs. Hence we contribute to the literature on CSR in industrial clusters and specifically CSR in Indian industrial clusters by investigating the drivers of CSR in India’s industrial clusters....

  18. Multiparticle production through isoscalar clusters

    International Nuclear Information System (INIS)

    Armburst, W.T.; Scott, D.M.

    1975-01-01

    The isoscalar cluster model for multiparticle production was extended to include clusters of A 2 meson pairs in addition to previously studied rho-rho and sigma clusters. The production of each type of cluster is given by an energy dependent Poisson distribution. The Poisson parameters determined from the charged particle multiplicity distributions indicate that the inclusion of A 2 -A 2 clusters does not improve the fit to the data. The predictions of the model for n 0 n/sub -/, f/sup 2//sub -,-/, and f/sup 2//sub 0,0/ compare favorably to the experimental values. (U.S.)

  19. Prediction of settled water turbidity and optimal coagulant dosage in drinking water treatment plant using a hybrid model of k-means clustering and adaptive neuro-fuzzy inference system

    Science.gov (United States)

    Kim, Chan Moon; Parnichkun, Manukid

    2017-11-01

    Coagulation is an important process in drinking water treatment to attain acceptable treated water quality. However, the determination of coagulant dosage is still a challenging task for operators, because coagulation is nonlinear and complicated process. Feedback control to achieve the desired treated water quality is difficult due to lengthy process time. In this research, a hybrid of k-means clustering and adaptive neuro-fuzzy inference system ( k-means-ANFIS) is proposed for the settled water turbidity prediction and the optimal coagulant dosage determination using full-scale historical data. To build a well-adaptive model to different process states from influent water, raw water quality data are classified into four clusters according to its properties by a k-means clustering technique. The sub-models are developed individually on the basis of each clustered data set. Results reveal that the sub-models constructed by a hybrid k-means-ANFIS perform better than not only a single ANFIS model, but also seasonal models by artificial neural network (ANN). The finally completed model consisting of sub-models shows more accurate and consistent prediction ability than a single model of ANFIS and a single model of ANN based on all five evaluation indices. Therefore, the hybrid model of k-means-ANFIS can be employed as a robust tool for managing both treated water quality and production costs simultaneously.

  20. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  1. Enzyme detection by microfluidics

    DEFF Research Database (Denmark)

    2013-01-01

    Microfluidic-implemented methods of detecting an enzyme, in particular a DNA-modifying enzyme, are provided, as well as methods for detecting a cell, or a microorganism expressing said enzyme. The enzyme is detected by providing a nucleic acid substrate, which is specifically targeted...... by that enzyme...

  2. Comparison of gallium-67 scanning, bronchoalveolar lavage, and serum angiotensin-converting enzyme levels in pulmonary sarcoidosis. Predicting response to therapy

    International Nuclear Information System (INIS)

    Baughman, R.P.; Fernandez, M.; Bosken, C.H.; Mantil, J.; Hurtubise, P.

    1984-01-01

    Patients with active pulmonary sarcoidosis underwent bronchoalveolar lavage, gallium scan, and serum angiotensin-converting enzyme (ACE) level determination prior to treatment with corticosteroids. Pulmonary function was tested before and after therapy. Increase in vital capacity after treatment ranged from 40 to 1,030 ml; 12 of the 16 patients studied had an increase of more than 200 ml. There was a close correlation between the percentage uptake of gallium scan and the increase of the vital capacity after therapy (r . 0.95, p less than 0.01). There was no relationship between the percentage of lymphocytes obtained on lavage and the changes in vital capacity with therapy (r . 0.05). There was a positive correlation between the changes in vital capacity and the ratio of T4(+):T8(+)lymphocytes (r . 0.62, p less than 0.05) and number of T4 (+) lymphocytes (r . 0.92, p less than 0.01) in the bronchoalveolar fluid. There was a low correlation between the pretreatment ACE level and the change in vital capacity (r . 0.368, p greater than 0.05)

  3. Discovery of new enzymes and metabolic pathways using structure and genome context

    Science.gov (United States)

    Zhao, Suwen; Kumar, Ritesh; Sakai, Ayano; Vetting, Matthew W.; Wood, B. McKay; Brown, Shoshana; Bonanno, Jeffery B.; Hillerich, Brandan S.; Seidel, Ronald D.; Babbitt, Patricia C.; Almo, Steven C.; Sweedler, Jonathan V.; Gerlt, John A.; Cronan, John E.; Jacobson, Matthew P.

    2014-01-01

    Assigning valid functions to proteins identified in genome projects is challenging, with over-prediction and database annotation errors major concerns1. We, and others2, are developing computation-guided strategies for functional discovery using “metabolite docking” to experimentally derived3 or homology-based4 three-dimensional structures. Bacterial metabolic pathways often are encoded by “genome neighborhoods” (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by “predicting” the intermediates in the glycolytic pathway in E. coli5. Metabolite docking to multiple binding proteins/enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. We report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed i) the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans-4-hydroxy-L-proline betaine (tHyp-B) and cis-4-hydroxy-D-proline betaine (cHyp-B), and ii) the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guide functional predictions to enable the discovery of new metabolic pathways. PMID:24056934

  4. Elevated Liver Enzymes

    Science.gov (United States)

    Symptoms Elevated liver enzymes By Mayo Clinic Staff Elevated liver enzymes may indicate inflammation or damage to cells in the liver. Inflamed or ... than normal amounts of certain chemicals, including liver enzymes, into the bloodstream, which can result in elevated ...

  5. Survival and Predictive Factors of Lethality in Hemodyalisis: D/I Polymorphism of The Angiotensin I-Converting Enzyme and of the Angiotensinogen M235T Genes

    Energy Technology Data Exchange (ETDEWEB)

    Alves, Mauro, E-mail: malves@cardiol.br; Silva, Nelson Albuquerque de Souza e; Salis, Lucia Helena Alvares; Pereira, Basilio de Bragança; Godoy, Paulo Henrique; Nascimento, Emília Matos do [Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ (Brazil); Oliveira, Jose Mario Franco [Universidade Federal Fluminense, Niterói, RJ (Brazil)

    2014-09-15

    End-stage kidney disease patients continue to have markedly increased cardiovascular disease morbidity and mortality. Analysis of genetic factors connected with the renin-angiotensin system that influences the survival of the patients with end-stage kidney disease supports the ongoing search for improved outcomes. To assess survival and its association with the polymorphism of renin-angiotensin system genes: angiotensin I-converting enzyme insertion/deletion and angiotensinogen M235T in patients undergoing hemodialysis. Our study was designed to examine the role of renin-angiotensin system genes. It was an observational study. We analyzed 473 chronic hemodialysis patients in four dialysis units in the state of Rio de Janeiro. Survival rates were calculated by the Kaplan-Meier method and the differences between the curves were evaluated by Tarone-Ware, Peto-Prentice, and log rank tests. We also used logistic regression analysis and the multinomial model. A p value ≤ 0.05 was considered to be statistically significant. The local medical ethics committee gave their approval to this study. The mean age of patients was 45.8 years old. The overall survival rate was 48% at 11 years. The major causes of death were cardiovascular diseases (34%) and infections (15%). Logistic regression analysis found statistical significance for the following variables: age (p = 0.000038), TT angiotensinogen (p = 0.08261), and family income greater than five times the minimum wage (p = 0.03089), the latter being a protective factor. The survival of hemodialysis patients is likely to be influenced by the TT of the angiotensinogen M235T gene.

  6. Survival and Predictive Factors of Lethality in Hemodyalisis: D/I Polymorphism of The Angiotensin I-Converting Enzyme and of the Angiotensinogen M235T Genes

    Directory of Open Access Journals (Sweden)

    Mauro Alves

    2014-09-01

    Full Text Available Background: End-stage kidney disease patients continue to have markedly increased cardiovascular disease morbidity and mortality. Analysis of genetic factors connected with the renin-angiotensin system that influences the survival of the patients with end-stage kidney disease supports the ongoing search for improved outcomes. Objective: To assess survival and its association with the polymorphism of renin-angiotensin system genes: angiotensin I-converting enzyme insertion/deletion and angiotensinogen M235T in patients undergoing hemodialysis. Methods: Our study was designed to examine the role of renin-angiotensin system genes. It was an observational study. We analyzed 473 chronic hemodialysis patients in four dialysis units in the state of Rio de Janeiro. Survival rates were calculated by the Kaplan-Meier method and the differences between the curves were evaluated by Tarone-Ware, Peto-Prentice, and log rank tests. We also used logistic regression analysis and the multinomial model. A p value ≤ 0.05 was considered to be statistically significant. The local medical ethics committee gave their approval to this study. Results: The mean age of patients was 45.8 years old. The overall survival rate was 48% at 11 years. The major causes of death were cardiovascular diseases (34% and infections (15%. Logistic regression analysis found statistical significance for the following variables: age (p = 0.000038, TT angiotensinogen (p = 0.08261, and family income greater than five times the minimum wage (p = 0.03089, the latter being a protective factor. Conclusions: The survival of hemodialysis patients is likely to be influenced by the TT of the angiotensinogen M235T gene.

  7. Survival and Predictive Factors of Lethality in Hemodyalisis: D/I Polymorphism of The Angiotensin I-Converting Enzyme and of the Angiotensinogen M235T Genes

    International Nuclear Information System (INIS)

    Alves, Mauro; Silva, Nelson Albuquerque de Souza e; Salis, Lucia Helena Alvares; Pereira, Basilio de Bragança; Godoy, Paulo Henrique; Nascimento, Emília Matos do; Oliveira, Jose Mario Franco

    2014-01-01

    End-stage kidney disease patients continue to have markedly increased cardiovascular disease morbidity and mortality. Analysis of genetic factors connected with the renin-angiotensin system that influences the survival of the patients with end-stage kidney disease supports the ongoing search for improved outcomes. To assess survival and its association with the polymorphism of renin-angiotensin system genes: angiotensin I-converting enzyme insertion/deletion and angiotensinogen M235T in patients undergoing hemodialysis. Our study was designed to examine the role of renin-angiotensin system genes. It was an observational study. We analyzed 473 chronic hemodialysis patients in four dialysis units in the state of Rio de Janeiro. Survival rates were calculated by the Kaplan-Meier method and the differences between the curves were evaluated by Tarone-Ware, Peto-Prentice, and log rank tests. We also used logistic regression analysis and the multinomial model. A p value ≤ 0.05 was considered to be statistically significant. The local medical ethics committee gave their approval to this study. The mean age of patients was 45.8 years old. The overall survival rate was 48% at 11 years. The major causes of death were cardiovascular diseases (34%) and infections (15%). Logistic regression analysis found statistical significance for the following variables: age (p = 0.000038), TT angiotensinogen (p = 0.08261), and family income greater than five times the minimum wage (p = 0.03089), the latter being a protective factor. The survival of hemodialysis patients is likely to be influenced by the TT of the angiotensinogen M235T gene

  8. Effects of carbonyl bond, metal cluster dissociation, and evaporation rates on predictions of nanotube production in high-pressure carbon monoxide

    Science.gov (United States)

    Scott, Carl D.; Smalley, Richard E.

    2003-01-01

    The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNTs) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the conformation of CO2. It is shown that the production of CO2 is significantly greater for FeCO because of its lower bond energy as compared with that of NiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

  9. Sexual victimization and family violence among urban African American adolescent women: do violence cluster profiles predict partner violence victimization and sex trade exposure?

    Science.gov (United States)

    Kennedy, Angie C; Bybee, Deborah; Kulkarni, Shanti J; Archer, Gretchen

    2012-11-01

    Guided by an intersectional feminist perspective, we examined sexual victimization, witnessing intimate partner violence (IPV) in the family, and familial physical abuse among a sample of 180 urban African American adolescent women. We used cluster analysis to better understand the profiles of cumulative victimization, and the relationships between profiles and IPV victimization and personal exposure to the sex trade. Just under one third of the sample reported sexual victimization, with cooccurrence with both forms of family violence common. The cluster profile with high levels of severe family violence was associated with the highest rate of IPV victimization and sex trade exposure.

  10. Clustering analysis

    International Nuclear Information System (INIS)

    Romli

    1997-01-01

    Cluster analysis is the name of group of multivariate techniques whose principal purpose is to distinguish similar entities from the characteristics they process.To study this analysis, there are several algorithms that can be used. Therefore, this topic focuses to discuss the algorithms, such as, similarity measures, and hierarchical clustering which includes single linkage, complete linkage and average linkage method. also, non-hierarchical clustering method, which is popular name K -mean method ' will be discussed. Finally, this paper will be described the advantages and disadvantages of every methods

  11. Cluster analysis

    CERN Document Server

    Everitt, Brian S; Leese, Morven; Stahl, Daniel

    2011-01-01

    Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.Real life examples are used throughout to demons

  12. Cluster editing

    DEFF Research Database (Denmark)

    Böcker, S.; Baumbach, Jan

    2013-01-01

    . The problem has been the inspiration for numerous algorithms in bioinformatics, aiming at clustering entities such as genes, proteins, phenotypes, or patients. In this paper, we review exact and heuristic methods that have been proposed for the Cluster Editing problem, and also applications......The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side...

  13. Occupational Clusters.

    Science.gov (United States)

    Pottawattamie County School System, Council Bluffs, IA.

    The 15 occupational clusters (transportation, fine arts and humanities, communications and media, personal service occupations, construction, hospitality and recreation, health occupations, marine science occupations, consumer and homemaking-related occupations, agribusiness and natural resources, environment, public service, business and office…

  14. Fuzzy Clustering

    DEFF Research Database (Denmark)

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  15. Cluster generator

    Science.gov (United States)

    Donchev, Todor I [Urbana, IL; Petrov, Ivan G [Champaign, IL

    2011-05-31

    Described herein is an apparatus and a method for producing atom clusters based on a gas discharge within a hollow cathode. The hollow cathode includes one or more walls. The one or more walls define a sputtering chamber within the hollow cathode and include a material to be sputtered. A hollow anode is positioned at an end of the sputtering chamber, and atom clusters are formed when a gas discharge is generated between the hollow anode and the hollow cathode.

  16. Cluster Bulleticity

    OpenAIRE

    Massey, Richard; Kitching, Thomas; Nagai, Daisuke

    2010-01-01

    The unique properties of dark matter are revealed during collisions between clusters of galaxies, such as the bullet cluster (1E 0657−56) and baby bullet (MACS J0025−12). These systems provide evidence for an additional, invisible mass in the separation between the distributions of their total mass, measured via gravitational lensing, and their ordinary ‘baryonic’ matter, measured via its X-ray emission. Unfortunately, the information available from these systems is limited by their rarity. C...

  17. Cluster headache

    OpenAIRE

    Leroux, Elizabeth; Ducros, Anne

    2008-01-01

    Abstract Cluster headache (CH) is a primary headache disease characterized by recurrent short-lasting attacks (15 to 180 minutes) of excruciating unilateral periorbital pain accompanied by ipsilateral autonomic signs (lacrimation, nasal congestion, ptosis, miosis, lid edema, redness of the eye). It affects young adults, predominantly males. Prevalence is estimated at 0.5–1.0/1,000. CH has a circannual and circadian periodicity, attacks being clustered (hence the name) in bouts that can occur ...

  18. Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

    Science.gov (United States)

    Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

    2014-11-01

    Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Pathways to Late-Life Suicidal Behavior: Cluster Analysis and Predictive Validation of Suicidal Behavior in a Sample of Older Adults With Major Depression.

    Science.gov (United States)

    Szanto, Katalin; Galfalvy, Hanga; Vanyukov, Polina M; Keilp, John G; Dombrovski, Alexandre Y

    Clinical heterogeneity is a key challenge to understanding suicidal risk, as different pathways to suicidal behavior are likely to exist. We aimed to identify such pathways by uncovering latent classes of late-life depression cases and relating them to prior and future suicidal behavior. Data were collected from June 2010 to September 2015. In this longitudinal study we examined distinct associations of clinical and cognitive/decision-making factors with suicidal behavior in 194 older (50+ years) nondemented, depressed patients; 57 nonpsychiatric healthy controls provided benchmark data. The DSM-IV was used to establish diagnostic criteria. We identified multivariate patterns of risk factors, defining clusters based on personality traits, perceived social support, cognitive performance, and decision-making in an analysis blinded to participants' history of suicidal behavior. We validated these clusters using past and prospective suicidal ideation and behavior. Of 5 clusters identified, 3 were associated with high risk for suicidal behavior: (1) cognitive deficits, dysfunctional personality, low social support, high willingness to delay future rewards, and overrepresentation of high-lethality attempters; (2) high-personality pathology (ie, low self-esteem), minimal or no cognitive deficits, and overrepresentation of low-lethality attempters and ideators; (3) cognitive deficits, inability to delay future rewards, and similar distribution of high- and low-lethality attempters. There were significant between-cluster differences in number (P suicide attempts and in the likelihood of future suicide attempts (P = .010, 30 attempts by 22 patients, 2 fatal) and emergency psychiatric hospitalizations to prevent suicide (P = .005, 31 participants). Three pathways to suicidal behavior in older patients were found, marked by (1) very high levels of cognitive and dispositional risk factors suggesting a dementia prodrome, (2) dysfunctional personality traits, and (3) impulsive

  20. Several genes encoding enzymes with the same activity are necessary for aerobic fungal degradation of cellulose in nature.

    Directory of Open Access Journals (Sweden)

    Peter K Busk

    Full Text Available The cellulose-degrading fungal enzymes are glycoside hydrolases of the GH families and lytic polysaccharide monooxygenases. The entanglement of glycoside hydrolase families and functions makes it difficult to predict the enzymatic activity of glycoside hydrolases based on their sequence. In the present study we further developed the method Peptide Pattern Recognition to an automatic approach not only to find all genes encoding glycoside hydrolases and lytic polysaccharide monooxygenases in fungal genomes but also to predict the function of the genes. The functional annotation is an important feature as it provides a direct route to predict function from primary sequence. Furthermore, we used Peptide Pattern Recognition to compare the cellulose-degrading enzyme activities encoded by 39 fungal genomes. The results indicated that cellobiohydrolases and AA9 lytic polysaccharide monooxygenases are hallmarks of cellulose-degrading fungi except brown rot fungi. Furthermore, a high number of AA9, endocellulase and β-glucosidase genes were identified, not in what are known to be the strongest, specialized lignocellulose degraders but in saprophytic fungi that can use a wide variety of substrates whereas only few of these genes were found in fungi that have a limited number of natural, lignocellulotic substrates. This correlation suggests that enzymes with different properties are necessary for degradation of cellulose in different complex substrates. Interestingly, clustering of the fungi based on their predicted enzymes indicated that Ascomycota and Basidiomycota use the same enzymatic activities to degrade plant cell walls.

  1. Over-expression of the miRNA cluster at chromosome 14q32 in the alcoholic brain correlates with suppression of predicted target mRNA required for oligodendrocyte proliferation.

    Science.gov (United States)

    Manzardo, A M; Gunewardena, S; Butler, M G

    2013-09-10

    We examined miRNA expression from RNA isolated from the frontal cortex (Broadman area 9) of 9 alcoholics (6 males, 3 females, mean age 48 years) and 9 matched controls using both the Affymetrix GeneChip miRNA 2.0 and Human Exon 1.0 ST Arrays to further characterize genetic influences in alcoholism and the effects of alcohol consumption on predicted target mRNA expression. A total of 12 human miRNAs were significantly up-regulated in alcohol dependent subjects (fold change≥1.5, false discovery rate (FDR)≤0.3; p<0.05) compared with controls including a cluster of 4 miRNAs (e.g., miR-377, miR-379) from the maternally expressed 14q32 chromosome region. The status of the up-regulated miRNAs was supported using the high-throughput method of exon microarrays showing decreased predicted mRNA gene target expression as anticipated from the same RNA aliquot. Predicted mRNA targets were involved in cellular adhesion (e.g., THBS2), tissue differentiation (e.g., CHN2), neuronal migration (e.g., NDE1), myelination (e.g., UGT8, CNP) and oligodendrocyte proliferation (e.g., ENPP2, SEMA4D1). Our data support an association of alcoholism with up-regulation of a cluster of miRNAs located in the genomic imprinted domain on chromosome 14q32 with their predicted gene targets involved with oligodendrocyte growth, differentiation and signaling. Copyright © 2013 Elsevier B.V. All rights reserved.

  2. Enzyme inhibition by iminosugars

    DEFF Research Database (Denmark)

    López, Óscar; Qing, Feng-Ling; Pedersen, Christian Marcus

    2013-01-01

    Imino- and azasugar glycosidase inhibitors display pH dependant inhibition reflecting that both the inhibitor and the enzyme active site have groups that change protonation state with pH. With the enzyme having two acidic groups and the inhibitor one basic group, enzyme-inhibitor complexes...

  3. Method for predicting enzyme-catalyzed reactions

    Science.gov (United States)

    Hlavacek, William S.; Unkefer, Clifford J.; Mu, Fangping; Unkefer, Pat J.

    2013-03-19

    The reactivity of given metabolites is assessed using selected empirical atomic properties in the potential reaction center. Metabolic reactions are represented as biotransformation rules. These rules are generalized from the patterns in reactions. These patterns are not unique to reactants but are widely distributed among metabolites. Using a metabolite database, potential substructures are identified in the metabolites for a given biotransformation. These substructures are divided into reactants or non-reactants, depending on whether they participate in the biotransformation or not. Each potential substructure is then modeled using descriptors of the topological and electronic properties of atoms in the potential reaction center; molecular properties can also be used. A Support Vector Machine (SVM) or classifier is trained to classify a potential reactant as a true or false reactant using these properties.

  4. Combining cluster number counts and galaxy clustering

    Energy Technology Data Exchange (ETDEWEB)

    Lacasa, Fabien; Rosenfeld, Rogerio, E-mail: fabien@ift.unesp.br, E-mail: rosenfel@ift.unesp.br [ICTP South American Institute for Fundamental Research, Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo (Brazil)

    2016-08-01

    The abundance of clusters and the clustering of galaxies are two of the important cosmological probes for current and future large scale surveys of galaxies, such as the Dark Energy Survey. In order to combine them one has to account for the fact that they are not independent quantities, since they probe the same density field. It is important to develop a good understanding of their correlation in order to extract parameter constraints. We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. We employ the framework of the halo model complemented by a Halo Occupation Distribution model (HOD). We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions. Indeed, we show that the non-Gaussian covariance becomes dominant at small scales, low redshifts or high cluster masses. We discuss in particular the case of the super-sample covariance (SSC), including the effects of galaxy shot-noise, halo second order bias and non-local bias. We demonstrate that the SSC obeys mathematical inequalities and positivity. Using the joint covariance matrix and a Fisher matrix methodology, we examine the prospects of combining these two probes to constrain cosmological and HOD parameters. We find that the combination indeed results in noticeably better constraints, with improvements of order 20% on cosmological parameters compared to the best single probe, and even greater improvement on HOD parameters, with reduction of error bars by a factor 1.4-4.8. This happens in particular because the cross-covariance introduces a synergy between the probes on small scales. We conclude that accounting for non-Gaussian effects is required for the joint analysis of these observables in galaxy surveys.

  5. Crisp clustering of airborne geophysical data from the Alto Ligonha pegmatite field, northeastern Mozambique, to predict zones of increased rare earth element potential

    Science.gov (United States)

    Eberle, Detlef G.; Daudi, Elias X. F.; Muiuane, Elônio A.; Nyabeze, Peter; Pontavida, Alfredo M.

    2012-01-01

    The National Geology Directorate of Mozambique (DNG) and Maputo-based Eduardo-Mondlane University (UEM) entered a joint venture with the South African Council for Geoscience (CGS) to conduct a case study over the meso-Proterozoic Alto Ligonha pegmatite field in the Zambézia Province of northeastern Mozambique to support the local exploration and mining sectors. Rare-metal minerals, i.e. tantalum and niobium, as well as rare-earth minerals have been mined in the Alto Ligonha pegmatite field since decades, but due to the civil war (1977-1992) production nearly ceased. The Government now strives to promote mining in the region as contribution to poverty alleviation. This study was undertaken to facilitate the extraction of geological information from the high resolution airborne magnetic and radiometric data sets recently acquired through a World Bank funded survey and mapping project. The aim was to generate a value-added map from the airborne geophysical data that is easier to read and use by the exploration and mining industries than mere airborne geophysical grid data or maps. As a first step towards clustering, thorium (Th) and potassium (K) concentrations were determined from the airborne geophysical data as well as apparent magnetic susceptibility and first vertical magnetic gradient data. These four datasets were projected onto a 100 m spaced regular grid to assemble 850,000 four-element (multivariate) sample vectors over the study area. Classification of the sample vectors using crisp clustering based upon the Euclidian distance between sample and class centre provided a (pseudo-) geology map or value-added map, respectively, displaying the spatial distribution of six different classes in the study area. To learn the quality of sample allocation, the degree of membership of each sample vector was determined using a-posterior discriminant analysis. Geophysical ground truth control was essential to allocate geology/geophysical attributes to the six classes

  6. Enzymes of industrial purpose - review of the market of enzyme preparations and prospects for its development

    Directory of Open Access Journals (Sweden)

    A. A. Tolkacheva

    2017-01-01

    Full Text Available Microbial enzyme preparations are increasingly replacing conventional chemical catalysts in a number of industrial processes. Such drugs, in addition to environmental friendliness and high activity, have a number of advantages over enzyme preparations of vegetable and animal origin, namely: the production of microbial enzymes in bioreactors is easily controlled and predictable; excreted microbiological enzymes are more stable than intracellular animals and plant enzymes; the genetic diversity of microorganisms makes it possible to produce enzyme preparations with a wide range of specificity; microbiological enzymes can be synthesized year-round, in contrast to the production of plant enzymes, which is often seasonal. The leaders of the world market of enzymes are proteases and amylases, which account for 25% and 15%, respectively. Over the past five years, the world market for carbohydrases, including mainly amylases, cellulases and xylanases, has been the fastest growing segment of the enzyme market with an aggregate annual growth rate of more than 7.0%. Another major product of the industrial enzyme market, which has a great potential for growth, is lipases. From the point of view of designation, the main part is represented by food and food enzymes. The Russian market continues to be unsaturated - the current supply is not able to meet the needs of the Russian feed and food industry in enzyme preparations. Enzyme preparations of domestic producers are in demand in forage production, while food industrial enterprises prefer imported products. The most significant enterprises in the enzymatic industry in Russia at the moment are Sibbiofarm, AgroSistema, Agroferment. In the light of the Russian policy of increasing food security, the development of the domestic enzyme industry is an extremely topical task.

  7. Do Physical Activity, Body Mass Index, and Sleep Duration Predict Clustered Cardiovascular Disease Risk in Children?- A Part of the OPUS Study

    DEFF Research Database (Denmark)

    Hjorth, Mads F.; Damsgaard, Camilla T.; Dalskov, Stine-Mathilde

    Objective To investigate the single and combined associations of physical activity (PA), body mass index (BMI), and sleep duration with clustering of cardiovascular disease risk markers in healthy children. Methods We did a cross-sectional pilot-study of 74 Danish school children aged 8-11 years...... BMI was 17.1 (range 13.4-25.4) kg/m2, with 10.8% classified as overweight using isoBMI. Controlled for age and sex, P A was negatively associated with cMET-score (Standardised beta coefficients (sBeta)=-0.32); n=74; P=0.016) and BMI was positively associated with cMETscore (sBeta=0.49; n=74; P...

  8. Exploring functionally related enzymes using radially distributed properties of active sites around the reacting points of bound ligands

    Directory of Open Access Journals (Sweden)

    Ueno Keisuke

    2012-04-01

    Full Text Available Abstract Background Structural genomics approaches, particularly those solving the 3D structures of many proteins with unknown functions, have increased the desire for structure-based function predictions. However, prediction of enzyme function is difficult because one member of a superfamily may catalyze a different reaction than other members, whereas members of different superfamilies can catalyze the same reaction. In addition, conformational changes, mutations or the absence of a particular catalytic residue can prevent inference of the mechanism by which catalytic residues stabilize and promote the elementary reaction. A major hurdle for alignment-based methods for prediction of function is the absence (despite its importance of a measure of similarity of the physicochemical properties of catalytic sites. To solve this problem, the physicochemical features radially distributed around catalytic sites should be considered in addition to structural and sequence similarities. Results We showed that radial distribution functions (RDFs, which are associated with the local structural and physicochemical properties of catalytic active sites, are capable of clustering oxidoreductases and transferases by function. The catalytic sites of these enzymes were also characterized using the RDFs. The RDFs provided a measure of the similarity among the catalytic sites, detecting conformational changes caused by mutation of catalytic residues. Furthermore, the RDFs reinforced the classification of enzyme functions based on conventional sequence and structural alignments. Conclusions Our results demonstrate that the application of RDFs provides advantages in the functional classification of enzymes by providing information about catalytic sites.

  9. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    The cluster theory attributed to Michael Porter has significantly influenced industrial policies in countries across Europe and North America since the beginning of the 1990s. Institutions such as the EU, OECD and the World Bank and governments in countries such as the UK, France, The Netherlands...... or management. Both the Accelerate Wales and the Accelerate Cluster programmes target this issue by trying to establish networks between companies that can be used to supply knowledge from research institutions to manufacturing companies. The paper concludes that public sector interventions can make...... businesses. The universities were not considered by the participating companies to be important parts of the local business environment and inputs from universities did not appear to be an important source to access knowledge about new product development or new techniques in production, distribution...

  10. Diametrical clustering for identifying anti-correlated gene clusters.

    Science.gov (United States)

    Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

    2003-09-01

    Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

  11. Regional Innovation Clusters

    Data.gov (United States)

    Small Business Administration — The Regional Innovation Clusters serve a diverse group of sectors and geographies. Three of the initial pilot clusters, termed Advanced Defense Technology clusters,...

  12. Spectromicroscopy of self-assembled protein clusters

    Energy Technology Data Exchange (ETDEWEB)

    Schonschek, O.; Hormes, J.; Herzog, V. [Univ. of Bonn (Germany)

    1997-04-01

    The aim of this project is to use synchrotron radiation as a tool to study biomedical questions concerned with the thyroid glands. The biological background is outlined in a recent paper. In short, Thyroglobulin (TG), the precursor protein of the hormone thyroxine, forms large (20 - 500 microns in diameter) clusters in the extracellular lumen of thyrocytes. The process of the cluster formation is still not well understood but is thought to be a main storage mechanism of TG and therefore thyroxine inside the thyroid glands. For human thyroids, the interconnections of the proteins inside the clusters are mainly disulfide bondings. Normally, sulfur bridges are catalyzed by an enzyme called Protein Disulfide Bridge Isomerase (PDI). While this enzyme is supposed to be not present in any extracellular space, the cluster formation of TG takes place in the lumen between the thyrocytes. A possible explanation is the autocatalysis of TG.

  13. Cluster analysis

    OpenAIRE

    Mucha, Hans-Joachim; Sofyan, Hizir

    2000-01-01

    As an explorative technique, duster analysis provides a description or a reduction in the dimension of the data. It classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of many variables. Its aim is to construct groups in such a way that the profiles of objects in the same groups are relatively homogenous whereas the profiles of objects in different groups are relatively heterogeneous. Clustering is distinct from classification techniques, ...

  14. Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

    NARCIS (Netherlands)

    Calus, M.P.L.; Meuwissen, T.H.E.; Windig, J.J.; Knol, E.F.; Schrooten, C.; Vereijken, A.L.J.; Veerkamp, R.F.

    2009-01-01

    The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e.

  15. Prediction of soil urea conversion and quantification of the importance degrees of influencing factors through a new combinatorial model based on cluster method and artificial neural network.

    Science.gov (United States)

    Lei, Tao; Guo, Xianghong; Sun, Xihuan; Ma, Juanjuan; Zhang, Shaowen; Zhang, Yong

    2018-05-01

    Quantitative prediction of soil urea conversion is crucial in determining the mechanism of nitrogen transformation and understanding the dynamics of soil nutrients. This study aimed to establish a combinatorial prediction model (MCA-F-ANN) for soil urea conversion and quantify the relative importance degrees (RIDs) of influencing factors with the MCA-F-ANN method. Data samples were obtained from laboratory culture experiments, and soil nitrogen content and physicochemical properties were measured every other day. Results showed that when MCA-F-ANN was used, the mean-absolute-percent error values of NH 4 + -N, NO 3 - -N, and NH 3 contents were 3.180%, 2.756%, and 3.656%, respectively. MCA-F-ANN predicted urea transformation under multi-factor coupling conditions more accurately than traditional models did. The RIDs of reaction time (RT), electrical conductivity (EC), temperature (T), pH, nitrogen application rate (F), and moisture content (W) were 32.2%-36.5%, 24.0%-28.9%, 12.8%-15.2%, 9.8%-12.5%, 7.8%-11.0%, and 3.5%-6.0%, respectively. The RIDs of the influencing factors in a descending order showed the pattern RT > EC > T > pH > F > W. RT and EC were the key factors in the urea conversion process. The prediction accuracy of urea transformation process was improved, and the RIDs of the influencing factors were quantified. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. Enzymes for improved biomass conversion

    Science.gov (United States)

    Brunecky, Roman; Himmel, Michael E.

    2016-02-02

    Disclosed herein are enzymes and combinations of the enzymes useful for the hydrolysis of cellulose and the conversion of biomass. Methods of degrading cellulose and biomass using enzymes and cocktails of enzymes are also disclosed.

  17. Simulations of cm-wavelength Sunyaev-Zel'dovich galaxy cluster and point source blind sky surveys and predictions for the RT32/OCRA-f and the Hevelius 100-m radio telescope

    Energy Technology Data Exchange (ETDEWEB)

    Lew, Bartosz; Kus, Andrzej [Toruń Centre for Astronomy, Nicolaus Copernicus University, ul. Gagarina 11, 87-100 Toruń (Poland); Birkinshaw, Mark [HH Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Wilkinson, Peter, E-mail: blew@astro.uni.torun.pl, E-mail: Mark.Birkinshaw@bristol.ac.uk, E-mail: peter.wilkinson@manchester.ac.uk, E-mail: ajk@astro.uni.torun.pl [Jodrell Bank Centre for Astrophysics, The University of Manchester, Alan Turing Building, Manchester M13 9PL (United Kingdom)

    2015-02-01

    We investigate the effectiveness of blind surveys for radio sources and galaxy cluster thermal Sunyaev-Zel'dovich effects (TSZEs) using the four-pair, beam-switched OCRA-f radiometer on the 32-m radio telescope in Poland. The predictions are based on mock maps that include the cosmic microwave background, TSZEs from hydrodynamical simulations of large scale structure formation, and unresolved radio sources. We validate the mock maps against observational data, and examine the limitations imposed by simplified physics. We estimate the effects of source clustering towards galaxy clusters from NVSS source counts around Planck-selected cluster candidates, and include appropriate correlations in our mock maps. The study allows us to quantify the effects of halo line-of-sight alignments, source confusion, and telescope angular resolution on the detections of TSZEs. We perform a similar analysis for the planned 100-m Hevelius radio telescope (RTH) equipped with a 49-beam radio camera and operating at frequencies up to 22 GHz.We find that RT32/OCRA-f will be suitable for small-field blind radio source surveys, and will detect 33{sup +17}{sub −11} new radio sources brighter than 0.87 mJy at 30 GHz in a 1 deg{sup 2} field at > 5σ CL during a one-year, non-continuous, observing campaign, taking account of Polish weather conditions. It is unlikely that any galaxy cluster will be detected at 3σ CL in such a survey. A 60-deg{sup 2} survey, with field coverage of 2{sup 2} beams per pixel, at 15 GHz with the RTH, would find <1.5 galaxy clusters per year brighter than 60 μJy (at 3σ CL), and would detect about 3.4 × 10{sup 4} point sources brighter than 1 mJy at 5σ CL, with confusion causing flux density errors ∼< 2% (20%) in 68% (95%) of the detected sources.A primary goal of the planned RTH will be a wide-area (π sr) radio source survey at 15 GHz. This survey will detect nearly 3 × 10{sup 5} radio sources at 5σ CL down to 1.3 mJy, and tens of galaxy

  18. Immobilized enzymes and cells

    Energy Technology Data Exchange (ETDEWEB)

    Bucke, C; Wiseman, A

    1981-04-04

    This article reviews the current state of the art of enzyme and cell immobilization and suggests advances which might be made during the 1980's. Current uses of immobilized enzymes include the use of glucoamylase in the production of glucose syrups from starch and glucose isomerase in the production of high fructose corn syrup. Possibilities for future uses of immobilized enzymes and cells include the utilization of whey and the production of ethanol.

  19. Downregulation of miR-99a/let-7c/miR-125b miRNA cluster predicts clinical outcome in patients with unresected malignant pleural mesothelioma.

    Science.gov (United States)

    Truini, Anna; Coco, Simona; Nadal, Ernest; Genova, Carlo; Mora, Marco; Dal Bello, Maria Giovanna; Vanni, Irene; Alama, Angela; Rijavec, Erika; Biello, Federica; Barletta, Giulia; Merlo, Domenico Franco; Valentino, Alessandro; Ferro, Paola; Ravetti, Gian Luigi; Stigliani, Sara; Vigani, Antonella; Fedeli, Franco; Beer, David G; Roncella, Silvio; Grossi, Francesco

    2017-09-15

    Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date no molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed using biopsies on 27 unresected MPM patients with distinct clinical outcome: 15 patients had short survival (OS36 months). Three prognostic miRNAs (mir-99a, let-7c, and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High-risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high-risk score was independently associated with shorter OS (HR=3.14; 95% CI, 1.18-8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM.

  20. Photoabsorption of small sodium and magnesium clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2004-01-01

    We predict the strong enhancement in the photoabsorption of small Mg clusters in the region of 4-5 eV due to the resonant excitation of the plasmon oscillations of cluster electrons. The photoabsorption spectra for neutral Mg clusters consisting of up to N=11 atoms have been calculated using it ab...... initio framework based on the time dependent density functional theory (TDDFT). The nature of predicted resonances has been elucidated by comparison of the results of the it ab initio calculations with the results of the classical Mie theory. The splitting of the plasmon resonances caused by the cluster...

  1. Optical response of small magnesium clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2004-01-01

    We predict strong enhancement in the photoabsorption of small Mg clusters in the region of 4–5 eV due to the resonant excitation of the plasmon oscillations of cluster electrons. Photoabsorption spectra for neutral Mg clusters consisting of up to N = 11 atoms have been calculated using an ab initio...... framework based on the time-dependent density functional theory (TDDFT). The nature of predicted resonances has been elucidated by comparison of the results of the an ab initio calculations with the results of the classical Mie theory. The splitting of the plasmon resonances caused by the cluster...

  2. BrEPS: a flexible and automatic protocol to compute enzyme-specific sequence profiles for functional annotation

    Directory of Open Access Journals (Sweden)

    Schomburg D

    2010-12-01

    Full Text Available Abstract Background Models for the simulation of metabolic networks require the accurate prediction of enzyme function. Based on a genomic sequence, enzymatic functions of gene products are today mainly predicted by sequence database searching and operon analysis. Other methods can support these techniques: We have developed an automatic method "BrEPS" that creates highly specific sequence patterns for the functional annotation of enzymes. Results The enzymes in the UniprotKB are identified and their sequences compared against each other with BLAST. The enzymes are then clustered into a number of trees, where each tree node is associated with a set of EC-numbers. The enzyme sequences in the tree nodes are aligned with ClustalW. The conserved columns of the resulting multiple alignments are used to construct sequence patterns. In the last step, we verify the quality of the patterns by computing their specificity. Patterns with low specificity are omitted and recomputed further down in the tree. The final high-quality patterns can be used for functional annotation. We ran our protocol on a recent Swiss-Prot release and show statistics, as well as a comparison to PRIAM, a probabilistic method that is also specialized on the functional annotation of enzymes. We determine the amount of true positive annotations for five common microorganisms with data from BRENDA and AMENDA serving as standard of truth. BrEPS is almost on par with PRIAM, a fact which we discuss in the context of five manually investigated cases. Conclusions Our protocol computes highly specific sequence patterns that can be used to support the functional annotation of enzymes. The main advantages of our method are that it is automatic and unsupervised, and quite fast once the patterns are evaluated. The results show that BrEPS can be a valuable addition to the reconstruction of metabolic networks.

  3. A novel polyketide biosynthesis gene cluster is involved in fruiting body morphogenesis in the filamentous fungi Sordaria macrospora and Neurospora crassa.

    Science.gov (United States)

    Nowrousian, Minou

    2009-04-01

    During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.

  4. Artificial Enzymes, "Chemzymes"

    DEFF Research Database (Denmark)

    Bjerre, Jeannette; Rousseau, Cyril Andre Raphaël; Pedersen, Lavinia Georgeta M

    2008-01-01

    Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models that successf......Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models...... that successfully perform Michaelis-Menten catalysis under enzymatic conditions (i.e., aqueous medium, neutral pH, ambient temperature) and for those that do, very high rate accelerations are seldomly seen. This review will provide a brief summary of the recent developments in artificial enzymes, so called...... "Chemzymes", based on cyclodextrins and other molecules. Only the chemzymes that have shown enzyme-like activity that has been quantified by different methods will be mentioned. This review will summarize the work done in the field of artificial glycosidases, oxidases, epoxidases, and esterases, as well...

  5. Magnetically responsive enzyme powders

    Energy Technology Data Exchange (ETDEWEB)

    Pospiskova, Kristyna, E-mail: kristyna.pospiskova@upol.cz [Regional Centre of Advanced Technologies and Materials, Palacky University, Slechtitelu 11, 783 71 Olomouc (Czech Republic); Safarik, Ivo, E-mail: ivosaf@yahoo.com [Regional Centre of Advanced Technologies and Materials, Palacky University, Slechtitelu 11, 783 71 Olomouc (Czech Republic); Department of Nanobiotechnology, Institute of Nanobiology and Structural Biology of GCRC, Na Sadkach 7, 370 05 Ceske Budejovice (Czech Republic)

    2015-04-15

    Powdered enzymes were transformed into their insoluble magnetic derivatives retaining their catalytic activity. Enzyme powders (e.g., trypsin and lipase) were suspended in various liquid media not allowing their solubilization (e.g., saturated ammonium sulfate and highly concentrated polyethylene glycol solutions, ethanol, methanol, 2-propanol) and subsequently cross-linked with glutaraldehyde. Magnetic modification was successfully performed at low temperature in a freezer (−20 °C) using magnetic iron oxides nano- and microparticles prepared by microwave-assisted synthesis from ferrous sulfate. Magnetized cross-linked enzyme powders were stable at least for two months in water suspension without leakage of fixed magnetic particles. Operational stability of magnetically responsive enzymes during eight repeated reaction cycles was generally without loss of enzyme activity. Separation of magnetically modified cross-linked powdered enzymes from reaction mixtures was significantly simplified due to their magnetic properties. - Highlights: • Cross-linked enzyme powders were prepared in various liquid media. • Insoluble enzymes were magnetized using iron oxides particles. • Magnetic iron oxides particles were prepared by microwave-assisted synthesis. • Magnetic modification was performed under low (freezing) temperature. • Cross-linked powdered trypsin and lipase can be used repeatedly for reaction.

  6. Targeted enzyme prodrug therapies.

    Science.gov (United States)

    Schellmann, N; Deckert, P M; Bachran, D; Fuchs, H; Bachran, C

    2010-09-01

    The cure of cancer is still a formidable challenge in medical science. Long-known modalities including surgery, chemotherapy and radiotherapy are successful in a number of cases; however, invasive, metastasized and inaccessible tumors still pose an unresolved and ongoing problem. Targeted therapies designed to locate, detect and specifically kill tumor cells have been developed in the past three decades as an alternative to treat troublesome cancers. Most of these therapies are either based on antibody-dependent cellular cytotoxicity, targeted delivery of cytotoxic drugs or tumor site-specific activation of prodrugs. The latter is a two-step procedure. In the first step, a selected enzyme is accumulated in the tumor by guiding the enzyme or its gene to the neoplastic cells. In the second step, a harmless prodrug is applied and specifically converted by this enzyme into a cytotoxic drug only at the tumor site. A number of targeting systems, enzymes and prodrugs were investigated and improved since the concept was first envisioned in 1974. This review presents a concise overview on the history and latest developments in targeted therapies for cancer treatment. We cover the relevant technologies such as antibody-directed enzyme prodrug therapy (ADEPT), gene-directed enzyme prodrug therapy (GDEPT) as well as related therapies such as clostridial- (CDEPT) and polymer-directed enzyme prodrug therapy (PDEPT) with emphasis on prodrug-converting enzymes, prodrugs and drugs.

  7. Enzymes in Fermented Fish.

    Science.gov (United States)

    Giyatmi; Irianto, H E

    Fermented fish products are very popular particularly in Southeast Asian countries. These products have unique characteristics, especially in terms of aroma, flavor, and texture developing during fermentation process. Proteolytic enzymes have a main role in hydrolyzing protein into simpler compounds. Fermentation process of fish relies both on naturally occurring enzymes (in the muscle or the intestinal tract) as well as bacteria. Fermented fish products processed using the whole fish show a different characteristic compared to those prepared from headed and gutted fish. Endogenous enzymes like trypsin, chymotrypsin, elastase, and aminopeptidase are the most involved in the fermentation process. Muscle tissue enzymes like cathepsins, peptidases, transaminases, amidases, amino acid decarboxylases, glutamic dehydrogenases, and related enzymes may also play a role in fish fermentation. Due to the decreased bacterial number during fermentation, contribution of microbial enzymes to proteolysis may be expected prior to salting of fish. Commercial enzymes are supplemented during processing for specific purposes, such as quality improvement and process acceleration. In the case of fish sauce, efforts to accelerate fermentation process and to improve product quality have been studied by addition of enzymes such as papain, bromelain, trypsin, pepsin, and chymotrypsin. © 2017 Elsevier Inc. All rights reserved.

  8. A Hierarchical Clustering Methodology for the Estimation of Toxicity

    Science.gov (United States)

    A Quantitative Structure Activity Relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural sim...

  9. CONSTRAINING CLUSTER PHYSICS WITH THE SHAPE OF X-RAY CLUSTERS: COMPARISON OF LOCAL X-RAY CLUSTERS VERSUS ΛCDM CLUSTERS

    International Nuclear Information System (INIS)

    Lau, Erwin T.; Nagai, Daisuke; Kravtsov, Andrey V.; Vikhlinin, Alexey; Zentner, Andrew R.

    2012-01-01

    Recent simulations of cluster formation have demonstrated that condensation of baryons into central galaxies during cluster formation can drive the shape of the gas distribution in galaxy clusters significantly rounder out to their virial radius. These simulations generally predict stellar fractions within cluster virial radii that are ∼2-3 times larger than the stellar masses deduced from observations. In this paper, we compare ellipticity profiles of simulated clusters performed with varying input physics (radiative cooling, star formation, and supernova feedback) to the cluster ellipticity profiles derived from Chandra and ROSAT observations, in an effort to constrain the fraction of gas that cools and condenses into the central galaxies within clusters. We find that local relaxed clusters have an average ellipticity of ε = 0.18 ± 0.05 in the radial range of 0.04 ≤ r/r 500 ≤ 1. At larger radii r > 0.1r 500 , the observed ellipticity profiles agree well with the predictions of non-radiative simulations. In contrast, the ellipticity profiles of simulated clusters that include dissipative gas physics deviate significantly from the observed ellipticity profiles at all radii. The dissipative simulations overpredict (underpredict) ellipticity in the inner (outer) regions of galaxy clusters. By comparing simulations with and without dissipative gas physics, we show that gas cooling causes the gas distribution to be more oblate in the central regions, but makes the outer gas distribution more spherical. We find that late-time gas cooling and star formation are responsible for the significantly oblate gas distributions in cluster cores, but the gas shapes outside of cluster cores are set primarily by baryon dissipation at high redshift (z ≥ 2). Our results indicate that the shapes of X-ray emitting gas in galaxy clusters, especially at large radii, can be used to place constraints on cluster gas physics, making it potential probes of the history of baryonic

  10. Nuclear clustering - a cluster core model study

    International Nuclear Information System (INIS)

    Paul Selvi, G.; Nandhini, N.; Balasubramaniam, M.

    2015-01-01

    Nuclear clustering, similar to other clustering phenomenon in nature is a much warranted study, since it would help us in understanding the nature of binding of the nucleons inside the nucleus, closed shell behaviour when the system is highly deformed, dynamics and structure at extremes. Several models account for the clustering phenomenon of nuclei. We present in this work, a cluster core model study of nuclear clustering in light mass nuclei

  11. Monovalent Cation Activation of the Radical SAM Enzyme Pyruvate Formate-Lyase Activating Enzyme.

    Science.gov (United States)

    Shisler, Krista A; Hutcheson, Rachel U; Horitani, Masaki; Duschene, Kaitlin S; Crain, Adam V; Byer, Amanda S; Shepard, Eric M; Rasmussen, Ashley; Yang, Jian; Broderick, William E; Vey, Jessica L; Drennan, Catherine L; Hoffman, Brian M; Broderick, Joan B

    2017-08-30

    Pyruvate formate-lyase activating enzyme (PFL-AE) is a radical S-adenosyl-l-methionine (SAM) enzyme that installs a catalytically essential glycyl radical on pyruvate formate-lyase. We show that PFL-AE binds a catalytically essential monovalent cation at its active site, yet another parallel with B 12 enzymes, and we characterize this cation site by a combination of structural, biochemical, and spectroscopic approaches. Refinement of the PFL-AE crystal structure reveals Na + as the most likely ion present in the solved structures, and pulsed electron nuclear double resonance (ENDOR) demonstrates that the same cation site is occupied by 23 Na in the solution state of the as-isolated enzyme. A SAM carboxylate-oxygen is an M + ligand, and EPR and circular dichroism spectroscopies reveal that both the site occupancy and the identity of the cation perturb the electronic properties of the SAM-chelated iron-sulfur cluster. ENDOR studies of the PFL-AE/[ 13 C-methyl]-SAM complex show that the target sulfonium positioning varies with the cation, while the observation of an isotropic hyperfine coupling to the cation by ENDOR measurements establishes its intimate, SAM-mediated interaction with the cluster. This monovalent cation site controls enzyme activity: (i) PFL-AE in the absence of any simple monovalent cations has little-no activity; and (ii) among monocations, going down Group 1 of the periodic table from Li + to Cs + , PFL-AE activity sharply maximizes at K + , with NH 4 + closely matching the efficacy of K + . PFL-AE is thus a type I M + -activated enzyme whose M + controls reactivity by interactions with the cosubstrate, SAM, which is bound to the catalytic iron-sulfur cluster.

  12. Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach.

    Science.gov (United States)

    Katiyar, Prateek; Divine, Mathew R; Kohlhofer, Ursula; Quintanilla-Martinez, Leticia; Schölkopf, Bernhard; Pichler, Bernd J; Disselhorst, Jonathan A

    2017-04-01

    In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic 18 F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical 18 F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic 18 F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic 18 F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor

  13. Vacancy-indium clusters in implanted germanium

    KAUST Repository

    Chroneos, Alexander I.

    2010-04-01

    Secondary ion mass spectroscopy measurements of heavily indium doped germanium samples revealed that a significant proportion of the indium dose is immobile. Using electronic structure calculations we address the possibility of indium clustering with point defects by predicting the stability of indium-vacancy clusters, InnVm. We find that the formation of large clusters is energetically favorable, which can explain the immobility of the indium ions. © 2010 Elsevier B.V. All rights reserved.

  14. Vacancy-indium clusters in implanted germanium

    KAUST Repository

    Chroneos, Alexander I.; Kube, R.; Bracht, Hartmut A.; Grimes, Robin W.; Schwingenschlö gl, Udo

    2010-01-01

    Secondary ion mass spectroscopy measurements of heavily indium doped germanium samples revealed that a significant proportion of the indium dose is immobile. Using electronic structure calculations we address the possibility of indium clustering with point defects by predicting the stability of indium-vacancy clusters, InnVm. We find that the formation of large clusters is energetically favorable, which can explain the immobility of the indium ions. © 2010 Elsevier B.V. All rights reserved.

  15. The role of extended Fe4S4 cluster ligands in mediating sulfite reductase hemoprotein activity.

    Science.gov (United States)

    Cepeda, Marisa R; McGarry, Lauren; Pennington, Joseph M; Krzystek, J; Elizabeth Stroupe, M

    2018-05-28

    The siroheme-containing subunit from the multimeric hemoflavoprotein NADPH-dependent sulfite reductase (SiR/SiRHP) catalyzes the six electron-reduction of SO 3 2- to S 2- . Siroheme is an iron-containing isobacteriochlorin that is found in sulfite and homologous siroheme-containing nitrite reductases. Siroheme does not work alone but is covalently coupled to a Fe 4 S 4 cluster through one of the cluster's ligands. One long-standing hypothesis predicted from this observation is that the environment of one iron-containing cofactor influences the properties of the other. We tested this hypothesis by identifying three amino acids (F437, M444, and T477) that interact with the Fe 4 S 4 cluster and probing the effect of altering them to alanine on the function and structure of the resulting enzymes by use of activity assays, X-ray crystallographic analysis, and EPR spectroscopy. We showed that F437 and M444 gate access for electron transfer to the siroheme-cluster assembly and the direct hydrogen bond between T477 and one of the cluster sulfides is important for determining the geometry of the siroheme active site. Copyright © 2018. Published by Elsevier B.V.

  16. Gas phase reactivity of thermal metal clusters

    International Nuclear Information System (INIS)

    Castleman, A.W. Jr.; Harms, A.C.; Leuchtner, R.E.

    1991-01-01

    Reaction kinetics of metal cluster ions under well defined thermal conditions were studied using a flow tube reactor in combination with laser vaporization. Aluminum anions and cations were reacted with oxygen, and several species which are predicted jellium shell closings, were found to have special stability. Metal alloy cluster anions comprised of Al, V and Nb were also seen to react with oxygen. Alloy clusters with an even number of electrons reacted more slowly than odd electron species, and certain clusters appeared to be exceptionally unreactive. Copper cation clusters were observed to associate with carbon monoxide with reactivities that approach bulk behavior at surprisingly small cluster size. These reactions demonstrate how the rate of reaction changes with cluster size. (orig.)

  17. Gas phase reactivity of thermal metal clusters

    Science.gov (United States)

    Castleman, A. W., Jr.; Harms, A. C.; Leuchtner, R. E.

    1991-03-01

    Reaction kinetics of metal cluster ions under well defined thermal conditions were studied using a flow tube reactor in combination with laser vaporization. Aluminum anions and cations were reacted with oxygen, and several species which are predicted jellium shell closings, were found to have special stability. Metal alloy cluster anions comprised of Al, V and Nb were also seen to react with oxygen. Alloy clusters with an even number of electrons reacted more slowly than odd electron species, and certain clusters appeared to be exceptionally unreactive. Copper cation clusters were observed to associate with carbon monoxide with reactivities that approach bulk behavior at surprisingly small cluster size. These reactions demonstrate how the rate of reaction changes with cluster size.

  18. Cluster analysis for portfolio optimization

    OpenAIRE

    Vincenzo Tola; Fabrizio Lillo; Mauro Gallegati; Rosario N. Mantegna

    2005-01-01

    We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio compositi...

  19. Fission approach to cluster radioactivity

    Indian Academy of Sciences (India)

    2015-08-04

    Aug 4, 2015 ... Also, the analytical superasymmetric fission (ASAF) model is successfully employed to make a systematic search and to predict, with other models, cluster ... those of the staff, the journals, various programmes, and Current Science, has changed from 'ias.ernet.in' (or 'academy.ias.ernet.in') to 'ias.ac.in'. Thus ...

  20. PRAMANA Cluster radioactivity in xenon isotopes

    Indian Academy of Sciences (India)

    exotic decay or cluster radioactivity was first predicted by sandulescu et al [1] in. 1980 on the basis of ... separator by 58Ni(58Ni, 2n) reaction and carbon clusters were searched for by means of solid state nuclear ..... Lett. 55, 582 (1985). [22] D N Poenaru, W Greiner, K Depta, M Ivascu, D Mazilu and A Sandulescu, At. Data.

  1. Collective excitations in deformed alkali metal clusters

    International Nuclear Information System (INIS)

    Lipparini, E.; Stringari, S.; Istituto Nazionale di Fisica Nucleare, Povo

    1991-01-01

    A theoretical study of collective excitations in deformed metal clusters is presented. Sum rules are used to study the splittings of the dipole surface plasma resonance originating from the cluster deformation. The vibrating potential model is developed and used to predict the occurrence of a low lying collective mode of orbital magnetic nature. (orig.)

  2. Cluster headache

    Directory of Open Access Journals (Sweden)

    Ducros Anne

    2008-07-01

    Full Text Available Abstract Cluster headache (CH is a primary headache disease characterized by recurrent short-lasting attacks (15 to 180 minutes of excruciating unilateral periorbital pain accompanied by ipsilateral autonomic signs (lacrimation, nasal congestion, ptosis, miosis, lid edema, redness of the eye. It affects young adults, predominantly males. Prevalence is estimated at 0.5–1.0/1,000. CH has a circannual and circadian periodicity, attacks being clustered (hence the name in bouts that can occur during specific months of the year. Alcohol is the only dietary trigger of CH, strong odors (mainly solvents and cigarette smoke and napping may also trigger CH attacks. During bouts, attacks may happen at precise hours, especially during the night. During the attacks, patients tend to be restless. CH may be episodic or chronic, depending on the presence of remission periods. CH is associated with trigeminovascular activation and neuroendocrine and vegetative disturbances, however, the precise cautive mechanisms remain unknown. Involvement of the hypothalamus (a structure regulating endocrine function and sleep-wake rhythms has been confirmed, explaining, at least in part, the cyclic aspects of CH. The disease is familial in about 10% of cases. Genetic factors play a role in CH susceptibility, and a causative role has been suggested for the hypocretin receptor gene. Diagnosis is clinical. Differential diagnoses include other primary headache diseases such as migraine, paroxysmal hemicrania and SUNCT syndrome. At present, there is no curative treatment. There are efficient treatments to shorten the painful attacks (acute treatments and to reduce the number of daily attacks (prophylactic treatments. Acute treatment is based on subcutaneous administration of sumatriptan and high-flow oxygen. Verapamil, lithium, methysergide, prednisone, greater occipital nerve blocks and topiramate may be used for prophylaxis. In refractory cases, deep-brain stimulation of the

  3. Cosmological constraints from the CFHTLenS shear measurements using a new, accurate, and flexible way of predicting non-linear mass clustering

    Science.gov (United States)

    Angulo, Raul E.; Hilbert, Stefan

    2015-03-01

    We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.

  4. Enzymic lactose hydrolysis

    Energy Technology Data Exchange (ETDEWEB)

    Miller, J J; Brand, J C

    1980-01-01

    Acid or enzymic hydrolysis can be used to hydrolyze lactose. Advantages of both are compared and details of enzymic hydrolysis using yeast or fungal enzymes given. The new scheme outlined involves recycling lactase. Because lactose and lactase react to ultrafiltration (UF) membranes differently separation is possible. Milk or milk products are ultrafiltered to separate a concentrate from a lactose-rich permeate which is treated with lactase in a reactor until hydrolysis reaches a required level. The lactase can be removed by UF as it does not permeate the membrane, and it is recycled back to the reactor. Permeate from the second UF stage may or may not be recombined with the concentrate from the first stage to produce a low lactose product (analysis of a typical low-lactose dried whole milk is given). Batch or continuous processes are explained and a batch process without enzyme recovery is discussed. (Refs. 4).

  5. Indicators: Sediment Enzymes

    Science.gov (United States)

    Sediment enzymes are proteins that are produced by microorganisms living in the sediment or soil. They are indicators of key ecosystem processes and can help determine which nutrients are affecting the biological community of a waterbody.

  6. Enzyme Vs. Extremozyme -32 ...

    Indian Academy of Sciences (India)

    Enzymes are biocatalytic protein molecules that enhance the rates of ... to physical forces (hydrogen bonds, hydrophobic 1, electrostatic and Van der ... conformation. In 1995 ... surface against 14.7% in Klenow poll (some of the hydrophobic.

  7. Overproduction of ligninolytic enzymes

    Science.gov (United States)

    Elisashvili, Vladimir; Kachlishvili, Eva; Torok, Tamas

    2014-06-17

    Methods, compositions, and systems for overproducing ligninolytic enzymes from the basidiomycetous fungus are described herein. As described, the method can include incubating a fungal strain of Cerrena unicolor IBB 303 in a fermentation system having growth medium which includes lignocellulosic material and then cultivating the fungal strain in the fermentation system under conditions wherein the fungus expresses the ligninolytic enzymes. In some cases, the lignocellulosic material is mandarin peel, ethanol production residue, walnut pericarp, wheat bran, wheat straw, or banana peel.

  8. Measurement of enzyme activity.

    Science.gov (United States)

    Harris, T K; Keshwani, M M

    2009-01-01

    To study and understand the nature of living cells, scientists have continually employed traditional biochemical techniques aimed to fractionate and characterize a designated network of macromolecular components required to carry out a particular cellular function. At the most rudimentary level, cellular functions ultimately entail rapid chemical transformations that otherwise would not occur in the physiological environment of the cell. The term enzyme is used to singularly designate a macromolecular gene product that specifically and greatly enhances the rate of a chemical transformation. Purification and characterization of individual and collective groups of enzymes has been and will remain essential toward advancement of the molecular biological sciences; and developing and utilizing enzyme reaction assays is central to this mission. First, basic kinetic principles are described for understanding chemical reaction rates and the catalytic effects of enzymes on such rates. Then, a number of methods are described for measuring enzyme-catalyzed reaction rates, which mainly differ with regard to techniques used to detect and quantify concentration changes of given reactants or products. Finally, short commentary is given toward formulation of reaction mixtures used to measure enzyme activity. Whereas a comprehensive treatment of enzymatic reaction assays is not within the scope of this chapter, the very core principles that are presented should enable new researchers to better understand the logic and utility of any given enzymatic assay that becomes of interest.

  9. Fuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision Support

    OpenAIRE

    S. Parkash  Kumar; K. S. Ramaswami

    2011-01-01

    Problem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient valid cluster. With the obtained data clusters, quality assessment is made by predictive mining using...

  10. Brightest Cluster Galaxies in REXCESS Clusters

    Science.gov (United States)

    Haarsma, Deborah B.; Leisman, L.; Bruch, S.; Donahue, M.

    2009-01-01

    Most galaxy clusters contain a Brightest Cluster Galaxy (BCG) which is larger than the other cluster ellipticals and has a more extended profile. In the hierarchical model, the BCG forms through many galaxy mergers in the crowded center of the cluster, and thus its properties give insight into the assembly of the cluster as a whole. In this project, we are working with the Representative XMM-Newton Cluster Structure Survey (REXCESS) team (Boehringer et al 2007) to study BCGs in 33 X-ray luminous galaxy clusters, 0.055 < z < 0.183. We are imaging the BCGs in R band at the Southern Observatory for Astrophysical Research (SOAR) in Chile. In this poster, we discuss our methods and give preliminary measurements of the BCG magnitudes, morphology, and stellar mass. We compare these BCG properties with the properties of their host clusters, particularly of the X-ray emitting gas.

  11. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

    This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

  12. CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

    Science.gov (United States)

    Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

    2017-08-31

    Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

  13. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    Matthew J. Benacquista

    2013-03-01

    Full Text Available Galactic globular clusters are old, dense star systems typically containing 10^4 – 10^6 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution that leads to relativistic binaries, and current and possible future observational evidence for this population. Our discussion of globular cluster evolution will focus on the processes that boost the production of tight binary systems and the subsequent interaction of these binaries that can alter the properties of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker–Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  14. Modified Newtonian dynamics and the Coma cluster

    International Nuclear Information System (INIS)

    The, L.S.; White, S.D.M.

    1988-01-01

    The consistency of Milgrom's theory of modified Newtonian dynamics is checked against optical and X-ray data for the Coma cluster of galaxies. It is found that viable models for the cluster containing no dark matter can be constructed. They require an extensive gaseous atmosphere through which galaxies move on near-radial orbits. The gas temperature is predicted to have a shallow minimum near the cluster center; this structure may conflict with the best X-ray spectra of the cluster. 18 references

  15. Bioethanol from lignocellulose - pretreatment, enzyme immobilization and hydrolysis kinetics

    DEFF Research Database (Denmark)

    Tsai, Chien Tai

    , the cost of enzyme is still the bottle neck, re-using the enzyme is apossible way to reduce the input of enzyme in the process. In the point view of engineering, the prediction of enzymatic hydrolysis kinetics under different substrate loading, enzyme combination is usful for process design. Therefore...... lignocellulose is the required high cellulase enzyme dosages that increase the processing costs. One method to decrease the enzyme dosage is to re-use BG, which hydrolyze the soluble substrate cellobiose. Based on the hypothesis that immobilized BG can be re-used, how many times the enzyme could be recycled...... liquid and pretreatment time can be reduced, the influence of substrate concentration, pretreatment time and temperature were investigated and optimized. Pretreatment of barley straw by [EMIM]Ac, correlative models were constructed using 3 different pretreatment parameters (temperature, time...

  16. Mining the enzymes involved in the detoxification of reactive oxygen species (ROS) in sugarcane.

    Science.gov (United States)

    Kurama, Eiko E; Fenille, Roseli C; Rosa, Vicente E; Rosa, Daniel D; Ulian, Eugenio C

    2002-07-01

    Summary Adopting the sequencing of expressed sequence tags (ESTs) of a sugarcane database derived from libraries induced and not induced by pathogens, we identified EST clusters homologous to genes corresponding to enzymes involved in the detoxification of reactive oxygen species. The predicted amino acids of these enzymes are superoxide dismutases (SODs), glutathione-S-transferase (GST), glutathione peroxidase (GPX), and catalases. Three MnSOD mitochondrial precursors and 10 CuZnSOD were identified in sugarcane: the MnSOD mitochondrial precursor is 96% similar to the maize MnSOD mitochondrial precursor and, of the 10 CuZnSOD identified, seven were 98% identical to maize cytosolic CuZnSOD4 and one was 67% identical to putative peroxisomal CuZnSOD from Arabidopsis. Three homologues to class Phi GST were 87-88% identical to GST III from maize. Five GPX homologues were identified: three were homologous to cytosolic GPX from barley, one was 88% identical to phospholipid hydroperoxide glutathione peroxidase (PHGPX) from rice, and the last was 71% identical to GPX from A. thaliana. Three enzymes similar to maize catalase were identified in sugarcane: two were similar to catalase isozyme 3 and catalase chain 3 from maize, which are mitochondrial, and one was similar to catalase isozyme 1 from maize, whose location is peroxisomal subcellular. All enzymes were induced in all sugarcane libraries (flower, seed, root, callus, leaves) and also in the pathogen-induced libraries, except for CuZnSOD whose cDNA was detected in none of the libraries induced by pathogens (Acetobacter diazotroficans and Herbaspirillum rubrisubalbicans). The expression of the enzymes SOD, GST, GPX, and catalases involved in the detoxification was examined using reverse transcriptase-polymerase chain reaction in cDNA from leaves of sugarcane under biotic stress conditions, inoculated with Puccinia melanocephala, the causal agent of sugarcane rust disease.

  17. Computational Biochemistry-Enzyme Mechanisms Explored.

    Science.gov (United States)

    Culka, Martin; Gisdon, Florian J; Ullmann, G Matthias

    2017-01-01

    Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches. © 2017 Elsevier Inc. All rights reserved.

  18. Diversity among galaxy clusters

    International Nuclear Information System (INIS)

    Struble, M.F.; Rood, H.J.

    1988-01-01

    The classification of galaxy clusters is discussed. Consideration is given to the classification scheme of Abell (1950's), Zwicky (1950's), Morgan, Matthews, and Schmidt (1964), and Morgan-Bautz (1970). Galaxies can be classified based on morphology, chemical composition, spatial distribution, and motion. The correlation between a galaxy's environment and morphology is examined. The classification scheme of Rood-Sastry (1971), which is based on clusters's morphology and galaxy population, is described. The six types of clusters they define include: (1) a cD-cluster dominated by a single large galaxy, (2) a cluster dominated by a binary, (3) a core-halo cluster, (4) a cluster dominated by several bright galaxies, (5) a cluster appearing flattened, and (6) an irregularly shaped cluster. Attention is also given to the evolution of cluster structures, which is related to initial density and cluster motion

  19. BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

    Directory of Open Access Journals (Sweden)

    Valerio Ferrario

    Full Text Available A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space. The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of "pre-organized environment" able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS "roadmap".

  20. Modeling metabolic response to changes of enzyme amount in ...

    African Journals Online (AJOL)

    Based on the work of Hynne et al. (2001), in an in silico model of glycolysis, Saccharomyces cerevisiae is established by introducing an enzyme amount multiple factor (.) into the kinetic equations. The model is aimed to predict the metabolic response to the change of enzyme amount. With the help of .α, the amounts of ...

  1. Non-homologous isofunctional enzymes: a systematic analysis of alternative solutions in enzyme evolution.

    Science.gov (United States)

    Omelchenko, Marina V; Galperin, Michael Y; Wolf, Yuri I; Koonin, Eugene V

    2010-04-30

    Evolutionarily unrelated proteins that catalyze the same biochemical reactions are often referred to as analogous - as opposed to homologous - enzymes. The existence of numerous alternative, non-homologous enzyme isoforms presents an interesting evolutionary problem; it also complicates genome-based reconstruction of the metabolic pathways in a variety of organisms. In 1998, a systematic search for analogous enzymes resulted in the identification of 105 Enzyme Commission (EC) numbers that included two or more proteins without detectable sequence similarity to each other, including 34 EC nodes where proteins were known (or predicted) to have distinct structural folds, indicating independent evolutionary origins. In the past 12 years, many putative non-homologous isofunctional enzymes were identified in newly sequenced genomes. In addition, efforts in structural genomics resulted in a vastly improved structural coverage of proteomes, providing for definitive assessment of (non)homologous relationships between proteins. We report the results of a comprehensive search for non-homologous isofunctional enzymes (NISE) that yielded 185 EC nodes with two or more experimentally characterized - or predicted - structurally unrelated proteins. Of these NISE sets, only 74 were from the original 1998 list. Structural assignments of the NISE show over-representation of proteins with the TIM barrel fold and the nucleotide-binding Rossmann fold. From the functional perspective, the set of NISE is enriched in hydrolases, particularly carbohydrate hydrolases, and in enzymes involved in defense against oxidative stress. These results indicate that at least some of the non-homologous isofunctional enzymes were recruited relatively recently from enzyme families that are active against related substrates and are sufficiently flexible to accommodate changes in substrate specificity.

  2. Matrix Metalloproteinase Enzyme Family

    Directory of Open Access Journals (Sweden)

    Ozlem Goruroglu Ozturk

    2013-04-01

    Full Text Available Matrix metalloproteinases play an important role in many biological processes such as embriogenesis, tissue remodeling, wound healing, and angiogenesis, and in some pathological conditions such as atherosclerosis, arthritis and cancer. Currently, 24 genes have been identified in humans that encode different groups of matrix metalloproteinase enzymes. This review discuss the members of the matrix metalloproteinase family and their substrate specificity, structure, function and the regulation of their enzyme activity by tissue inhibitors. [Archives Medical Review Journal 2013; 22(2.000: 209-220

  3. Effect of deletion polymorphism of angiotensin converting enzyme gene on progression of diabetic nephropathy during inhibition of angiotensin converting enzyme

    DEFF Research Database (Denmark)

    Parving, H H; Jacobsen, P; Tarnow, L

    1996-01-01

    OBJECTIVE: To evaluate the concept that an insertion/deletion polymorphism of the angiotensin converting enzyme gene predicts the therapeutic efficacy of inhibition of angiotensin converting enzyme on progression of diabetic nephropathy. DESIGN: Observational follow up study of patients with insu...

  4. What Makes Clusters Decline?

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    2015-01-01

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark. The longit...... but being quick to withdraw in times of crisis....

  5. Clustering of correlated networks

    OpenAIRE

    Dorogovtsev, S. N.

    2003-01-01

    We obtain the clustering coefficient, the degree-dependent local clustering, and the mean clustering of networks with arbitrary correlations between the degrees of the nearest-neighbor vertices. The resulting formulas allow one to determine the nature of the clustering of a network.

  6. Relevant Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2009-01-01

    Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....

  7. Magnetically responsive enzyme powders

    Czech Academy of Sciences Publication Activity Database

    Pospišková, K.; Šafařík, Ivo

    2015-01-01

    Roč. 380, APR 2015 (2015), s. 197-200 ISSN 0304-8853 R&D Projects: GA MŠk(CZ) LD13021 Institutional support: RVO:67179843 Keywords : enzyme powders * cross-linking * magnetic modification * magnetic separation * magnetic iron oxides particles * microwave-assisted synthesis Subject RIV: CE - Biochemistry Impact factor: 2.357, year: 2015

  8. Enzyme with rhamnogalacturonase activity.

    NARCIS (Netherlands)

    Kofod, L.V.; Andersen, L.N.; Dalboge, H.; Kauppinen, M.S.; Christgau, S.; Heldt-Hansen, H.P.; Christophersen, C.; Nielsen, P.M.; Voragen, A.G.J.; Schols, H.A.

    1998-01-01

    An enzyme exhibiting rhamnogalacturonase activity, capable of cleaving a rhamnogalacturonan backbone in such a manner that galacturonic acids are left as the non-reducing ends, and which exhibits activity on hairy regions from a soy bean material and/or on saponified hairy regions from a sugar beet

  9. Implantable enzyme amperometric biosensors.

    Science.gov (United States)

    Kotanen, Christian N; Moussy, Francis Gabriel; Carrara, Sandro; Guiseppi-Elie, Anthony

    2012-05-15

    The implantable enzyme amperometric biosensor continues as the dominant in vivo format for the detection, monitoring and reporting of biochemical analytes related to a wide range of pathologies. Widely used in animal studies, there is increasing emphasis on their use in diabetes care and management, the management of trauma-associated hemorrhage and in critical care monitoring by intensivists in the ICU. These frontier opportunities demand continuous indwelling performance for up to several years, well in excess of the currently approved seven days. This review outlines the many challenges to successful deployment of chronically implantable amperometric enzyme biosensors and emphasizes the emerging technological approaches in their continued development. The foreign body response plays a prominent role in implantable biotransducer failure. Topics considering the approaches to mitigate the inflammatory response, use of biomimetic chemistries, nanostructured topographies, drug eluting constructs, and tissue-to-device interface modulus matching are reviewed. Similarly, factors that influence biotransducer performance such as enzyme stability, substrate interference, mediator selection and calibration are reviewed. For the biosensor system, the opportunities and challenges of integration, guided by footprint requirements, the limitations of mixed signal electronics, and power requirements, has produced three systems approaches. The potential is great. However, integration along the multiple length scales needed to address fundamental issues and integration across the diverse disciplines needed to achieve success of these highly integrated systems, continues to be a challenge in the development and deployment of implantable amperometric enzyme biosensor systems. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. Advances in enzyme bioelectrochemistry

    Directory of Open Access Journals (Sweden)

    ANDRESSA R. PEREIRA

    Full Text Available ABSTRACT Bioelectrochemistry can be defined as a branch of Chemical Science concerned with electron-proton transfer and transport involving biomolecules, as well as electrode reactions of redox enzymes. The bioelectrochemical reactions and system have direct impact in biotechnological development, in medical devices designing, in the behavior of DNA-protein complexes, in green-energy and bioenergy concepts, and make it possible an understanding of metabolism of all living organisms (e.g. humans where biomolecules are integral to health and proper functioning. In the last years, many researchers have dedicated itself to study different redox enzymes by using electrochemistry, aiming to understand their mechanisms and to develop promising bioanodes and biocathodes for biofuel cells as well as to develop biosensors and implantable bioelectronics devices. Inside this scope, this review try to introduce and contemplate some relevant topics for enzyme bioelectrochemistry, such as the immobilization of the enzymes at electrode surfaces, the electron transfer, the bioelectrocatalysis, and new techniques conjugated with electrochemistry vising understand the kinetics and thermodynamics of redox proteins. Furthermore, examples of recent approaches in designing biosensors and biofuel developed are presented.

  11. Cold-Adapted Enzymes

    Science.gov (United States)

    Georlette, D.; Bentahir, M.; Claverie, P.; Collins, T.; D'amico, S.; Delille, D.; Feller, G.; Gratia, E.; Hoyoux, A.; Lonhienne, T.; Meuwis, M.-a.; Zecchinon, L.; Gerday, Ch.

    In the last few years, increased attention has been focused on enzymes produced by cold-adapted micro-organisms. It has emerged that psychrophilic enzymes represent an extremely powerful tool in both protein folding investigations and for biotechnological purposes. Such enzymes are characterised by an increased thermosensitivity and, most of them, by a higher catalytic efficiency at low and moderate temperatures, when compared to their mesophilic counterparts. The high thermosensitivity probably originates from an increased flexibility of either a selected area of the molecular edifice or the overall protein structure, providing enhanced abilities to undergo conformational changes during catalysis at low temperatures. Structure modelling and recent crystallographic data have allowed to elucidate the structural parameters that could be involved in this higher resilience. It was demonstrated that each psychrophilic enzyme adopts its own adaptive strategy. It appears, moreover, that there is a continuum in the strategy of protein adaptation to temperature, as the previously mentioned structural parameters are implicated in the stability of thermophilic proteins. Additional 3D crystal structures, site-directed and random mutagenesis experiments should now be undertaken to further investigate the stability-flexibility-activity relationship.

  12. Embedded enzymes catalyse capture

    Science.gov (United States)

    Kentish, Sandra

    2018-05-01

    Membrane technologies for carbon capture can offer economic and environmental advantages over conventional amine-based absorption, but can suffer from limited gas flux and selectivity to CO2. Now, a membrane based on enzymes embedded in hydrophilic pores is shown to exhibit combined flux and selectivity that challenges the state of the art.

  13. Photoperiodism and Enzyme Activity

    Science.gov (United States)

    Queiroz, Orlando; Morel, Claudine

    1974-01-01

    Metabolic readjustments after a change from long days to short days appear, in Kalanchoe blossfeldiana, to be achieved through the operation of two main mechanisms: variation in enzyme capacity, and circadian rhythmicity. After a lag time, capacity in phosphoenolpyruvate carboxylase and capacity in aspartate aminotransferase increase exponentially and appear to be allometrically linked during 50 to 60 short days; then a sudden fall takes place in the activity of the former. Malic enzyme and alanine aminotransferase behave differently. Thus, the operation of the two sections of the pathway (before and after the malate step) give rise to a continuously changing functional compartmentation in the pathway. Circadian rhythmicity, on the other hand, produces time compartmentation through phase shifts and variation in amplitude, independently for each enzyme. These characteristics suggest that the operation of a so-called biological clock would be involved. We propose the hypothesis that feedback regulation would be more accurate and efficient when applied to an already oscillating, clock-controlled enzyme system. PMID:16658749

  14. ISFET based enzyme sensors

    NARCIS (Netherlands)

    van der Schoot, Bart H.; Bergveld, Piet

    1987-01-01

    This paper reviews the results that have been reported on ISFET based enzyme sensors. The most important improvement that results from the application of ISFETs instead of glass membrane electrodes is in the method of fabrication. Problems with regard to the pH dependence of the response and the

  15. Cluster ion beam facilities

    International Nuclear Information System (INIS)

    Popok, V.N.; Prasalovich, S.V.; Odzhaev, V.B.; Campbell, E.E.B.

    2001-01-01

    A brief state-of-the-art review in the field of cluster-surface interactions is presented. Ionised cluster beams could become a powerful and versatile tool for the modification and processing of surfaces as an alternative to ion implantation and ion assisted deposition. The main effects of cluster-surface collisions and possible applications of cluster ion beams are discussed. The outlooks of the Cluster Implantation and Deposition Apparatus (CIDA) being developed in Guteborg University are shown

  16. Measurement Error Correction Formula for Cluster-Level Group Differences in Cluster Randomized and Observational Studies

    Science.gov (United States)

    Cho, Sun-Joo; Preacher, Kristopher J.

    2016-01-01

    Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

  17. Halophiles and their enzymes: Negativity put to good use

    Science.gov (United States)

    DasSarma, Shiladitya; DasSarma, Priya

    2015-01-01

    Halophilic microorganisms possess stable enzymes that function in very high salinity, an extreme condition that leads to denaturation, aggregation, and precipitation of most other proteins. Genomic and structural analyses have established that the enzymes of halophilic Archaea and many halophilic Bacteria are negatively charged due to an excess of acidic over basic residues, and altered hydrophobicity, which enhance solubility and promote function in low water activity conditions. Here, we provide an update on recent bioinformatic analysis of predicted halophilic proteomes as well as experimental molecular studies on individual halophilic enzymes. On-going efforts on discovery and utilization of halophiles and their enzymes for biotechnology, including biofuel applications are also considered. PMID:26066288

  18. PREFACE: Nuclear Cluster Conference; Cluster'07

    Science.gov (United States)

    Freer, Martin

    2008-05-01

    The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

  19. Fragmentation of percolation cluster perimeters

    Science.gov (United States)

    Debierre, Jean-Marc; Bradley, R. Mark

    1996-05-01

    We introduce a model for the fragmentation of porous random solids under the action of an external agent. In our model, the solid is represented by a bond percolation cluster on the square lattice and bonds are removed only at the external perimeter (or `hull') of the cluster. This model is shown to be related to the self-avoiding walk on the Manhattan lattice and to the disconnection events at a diffusion front. These correspondences are used to predict the leading and the first correction-to-scaling exponents for several quantities defined for hull fragmentation. Our numerical results support these predictions. In addition, the algorithm used to construct the perimeters reveals itself to be a very efficient tool for detecting subtle correlations in the pseudo-random number generator used. We present a quantitative test of two generators which supports recent results reported in more systematic studies.

  20. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

  1. Management of cluster headache

    DEFF Research Database (Denmark)

    Tfelt-Hansen, Peer C; Jensen, Rigmor H

    2012-01-01

    The prevalence of cluster headache is 0.1% and cluster headache is often not diagnosed or misdiagnosed as migraine or sinusitis. In cluster headache there is often a considerable diagnostic delay - an average of 7 years in a population-based survey. Cluster headache is characterized by very severe...... or severe orbital or periorbital pain with a duration of 15-180 minutes. The cluster headache attacks are accompanied by characteristic associated unilateral symptoms such as tearing, nasal congestion and/or rhinorrhoea, eyelid oedema, miosis and/or ptosis. In addition, there is a sense of restlessness...... and agitation. Patients may have up to eight attacks per day. Episodic cluster headache (ECH) occurs in clusters of weeks to months duration, whereas chronic cluster headache (CCH) attacks occur for more than 1 year without remissions. Management of cluster headache is divided into acute attack treatment...

  2. Symmetries of cluster configurations

    International Nuclear Information System (INIS)

    Kramer, P.

    1975-01-01

    A deeper understanding of clustering phenomena in nuclei must encompass at least two interrelated aspects of the subject: (A) Given a system of A nucleons with two-body interactions, what are the relevant and persistent modes of clustering involved. What is the nature of the correlated nucleon groups which form the clusters, and what is their mutual interaction. (B) Given the cluster modes and their interaction, what systematic patterns of nuclear structure and reactions emerge from it. Are there, for example, families of states which share the same ''cluster parents''. Which cluster modes are compatible or exclude each other. What quantum numbers could characterize cluster configurations. There is no doubt that we can learn a good deal from the experimentalists who have discovered many of the features relevant to aspect (B). Symmetries specific to cluster configurations which can throw some light on both aspects of clustering are discussed

  3. Cluster Decline and Resilience

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark, 1963......-2011. Our longitudinal study reveals that technological lock-in and exit of key firms have contributed to impairment of the cluster’s resilience in adapting to disruptions. Entrepreneurship has a positive effect on cluster resilience, while multinational companies have contradicting effects by bringing...... in new resources to the cluster but being quick to withdraw in times of crisis....

  4. Enzyme based soil stabilization for unpaved road construction

    Directory of Open Access Journals (Sweden)

    Renjith Rintu

    2017-01-01

    Full Text Available Enzymes as soil stabilizers have been successfully used in road construction in several countries for the past 30 years. However, research has shown that the successful application of these enzymes is case specific, emphasizing that enzyme performance is dependent on subgrade soil type, condition and the type of enzyme used as the stabilizer. A universal standard or a tool for road engineers to assess the performance of stabilized unbound pavements using well-established enzymes is not available to date. The research aims to produce a validated assessment tool which can be used to predict strength enhancement within a generalized statistical framework. The objective of the present study is to identify new materials for developing the assessment tool which supports enzyme based stabilization, as well as to identify the correct construction sequence for such new materials. A series of characterization tests were conducted on several soil types obtained from proposed construction sites. Having identified the suitable soil type to mix with the enzyme, a trial road construction has been performed to investigate the efficiency of the enzyme stabilization along with the correct construction sequence. The enzyme stabilization has showed significant improvement of the road performance as was evidenced from the test results which were based on site soil obtained before and after stabilization. The research will substantially benefit the road construction industry by not only replacing traditional construction methods with economical/reliable approaches, but also eliminating site specific tests required in current practice of enzyme based road construction.

  5. Comprehensive cluster analysis with Transitivity Clustering.

    Science.gov (United States)

    Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

    2011-03-01

    Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

  6. Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Blin, Kai; Kim, Hyun Uk; Medema, Marnix H.

    2017-01-01

    Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly...... conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses...... are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats...

  7. Distant Galaxy Clusters Hosting Extreme Central Galaxies

    Science.gov (United States)

    McDonald, Michael

    2014-09-01

    The recently-discovered Phoenix cluster harbors the most star-forming central cluster galaxy of any cluster in the known Universe, by nearly a factor of 10. This extreme system appears to be fulfilling early cooling flow predictions, although the lack of similar systems makes any interpretation difficult. In an attempt to find other "Phoenix-like" clusters, we have cross-correlated archival all-sky surveys (in which Phoenix was detected) and isolated 4 similarly-extreme systems which are also coincident in position and redshift with an overdensity of red galaxies. We propose here to obtain Chandra observations of these extreme, Phoenix-like systems, in order to confirm them as relaxed, rapidly-cooling galaxy clusters.

  8. Cellulase enzyme and biomass utilization

    African Journals Online (AJOL)

    STORAGESEVER

    2009-06-03

    Jun 3, 2009 ... human population grows and economic development. However, the current .... conditions and the production cost of the related enzyme system. Therefore ... Given the importance of this enzyme to these so many industries,.

  9. Discovery and structure determination of the orphan enzyme isoxanthopterin deaminase .

    Science.gov (United States)

    Hall, Richard S; Agarwal, Rakhi; Hitchcock, Daniel; Sauder, J Michael; Burley, Stephen K; Swaminathan, Subramanyam; Raushel, Frank M

    2010-05-25

    Two previously uncharacterized proteins have been identified that efficiently catalyze the deamination of isoxanthopterin and pterin 6-carboxylate. The genes encoding these two enzymes, NYSGXRC-9339a ( gi|44585104 ) and NYSGXRC-9236b ( gi|44611670 ), were first identified from DNA isolated from the Sargasso Sea as part of the Global Ocean Sampling Project. The genes were synthesized, and the proteins were subsequently expressed and purified. The X-ray structure of Sgx9339a was determined at 2.7 A resolution (Protein Data Bank entry 2PAJ ). This protein folds as a distorted (beta/alpha)(8) barrel and contains a single zinc ion in the active site. These enzymes are members of the amidohydrolase superfamily and belong to cog0402 within the clusters of orthologous groups (COG). Enzymes in cog0402 have previously been shown to catalyze the deamination of guanine, cytosine, S-adenosylhomocysteine, and 8-oxoguanine. A small compound library of pteridines, purines, and pyrimidines was used to probe catalytic activity. The only substrates identified in this search were isoxanthopterin and pterin 6-carboxylate. The kinetic constants for the deamination of isoxanthopterin with Sgx9339a were determined to be 1.0 s(-1), 8.0 muM, and 1.3 x 10(5) M(-1) s(-1) (k(cat), K(m), and k(cat)/K(m), respectively). The active site of Sgx9339a most closely resembles the active site for 8-oxoguanine deaminase (Protein Data Bank entry 2UZ9 ). A model for substrate recognition of isoxanthopterin by Sgx9339a was proposed on the basis of the binding of guanine and xanthine in the active site of guanine deaminase. Residues critical for substrate binding appear to be conserved glutamine and tyrosine residues that form hydrogen bonds with the carbonyl oxygen at C4, a conserved threonine residue that forms hydrogen bonds with N5, and another conserved threonine residue that forms hydrogen bonds with the carbonyl group at C7. These conserved active site residues were used to identify 24 other genes

  10. Discovery and Structure Determination of the Orphan Enzyme Isoxanthopterin Deaminase

    Energy Technology Data Exchange (ETDEWEB)

    Hall, R.S.; Swaminathan, S.; Agarwal, R.; Hitchcock, D.; Sauder, J. M.; Burley, S. K.; Raushel, F. M.

    2010-05-25

    Two previously uncharacterized proteins have been identified that efficiently catalyze the deamination of isoxanthopterin and pterin 6-carboxylate. The genes encoding these two enzymes, NYSGXRC-9339a (gi|44585104) and NYSGXRC-9236b (gi|44611670), were first identified from DNA isolated from the Sargasso Sea as part of the Global Ocean Sampling Project. The genes were synthesized, and the proteins were subsequently expressed and purified. The X-ray structure of Sgx9339a was determined at 2.7 {angstrom} resolution (Protein Data Bank entry 2PAJ). This protein folds as a distorted ({beta}/{alpha}){sub 8} barrel and contains a single zinc ion in the active site. These enzymes are members of the amidohydrolase superfamily and belong to cog0402 within the clusters of orthologous groups (COG). Enzymes in cog0402 have previously been shown to catalyze the deamination of guanine, cytosine, S-adenosylhomocysteine, and 8-oxoguanine. A small compound library of pteridines, purines, and pyrimidines was used to probe catalytic activity. The only substrates identified in this search were isoxanthopterin and pterin 6-carboxylate. The kinetic constants for the deamination of isoxanthopterin with Sgx9339a were determined to be 1.0 s{sup -1}, 8.0 {micro}M, and 1.3 x 10{sup 5} M{sup -1} s{sup -1} (k{sub cat}, K{sub m}, and k{sub cat}/K{sub m}, respectively). The active site of Sgx9339a most closely resembles the active site for 8-oxoguanine deaminase (Protein Data Bank entry 2UZ9). A model for substrate recognition of isoxanthopterin by Sgx9339a was proposed on the basis of the binding of guanine and xanthine in the active site of guanine deaminase. Residues critical for substrate binding appear to be conserved glutamine and tyrosine residues that form hydrogen bonds with the carbonyl oxygen at C4, a conserved threonine residue that forms hydrogen bonds with N5, and another conserved threonine residue that forms hydrogen bonds with the carbonyl group at C7. These conserved active site

  11. Redox Behavior of the S-Adenosylmethionine (SAM)-Binding Fe-S Cluster in Methylthiotransferase RimO, toward Understanding Dual SAM Activity.

    Science.gov (United States)

    Molle, Thibaut; Moreau, Yohann; Clemancey, Martin; Forouhar, Farhad; Ravanat, Jean-Luc; Duraffourg, Nicolas; Fourmond, Vincent; Latour, Jean-Marc; Gambarelli, Serge; Mulliez, Etienne; Atta, Mohamed

    2016-10-18

    RimO, a radical-S-adenosylmethionine (SAM) enzyme, catalyzes the specific C 3 methylthiolation of the D89 residue in the ribosomal S 12 protein. Two intact iron-sulfur clusters and two SAM cofactors both are required for catalysis. By using electron paramagnetic resonance, Mössbauer spectroscopies, and site-directed mutagenesis, we show how two SAM molecules sequentially bind to the unique iron site of the radical-SAM cluster for two distinct chemical reactions in RimO. Our data establish that the two SAM molecules bind the radical-SAM cluster to the unique iron site, and spectroscopic evidence obtained under strongly reducing conditions supports a mechanism in which the first molecule of SAM causes the reoxidation of the reduced radical-SAM cluster, impeding reductive cleavage of SAM to occur and allowing SAM to methylate a HS - ligand bound to the additional cluster. Furthermore, by using density functional theory-based methods, we provide a description of the reaction mechanism that predicts the attack of the carbon radical substrate on the methylthio group attached to the additional [4Fe-4S] cluster.

  12. LMC clusters: young

    International Nuclear Information System (INIS)

    Freeman, K.C.

    1980-01-01

    The young globular clusters of the LMC have ages of 10 7 -10 8 y. Their masses and structure are similar to those of the smaller galactic globular clusters. Their stellar mass functions (in the mass range 6 solar masses to 1.2 solar masses) vary greatly from cluster to cluster, although the clusters are similar in total mass, age, structure and chemical composition. It would be very interesting to know why these clusters are forming now in the LMC and not in the Galaxy. The author considers the 'young globular' or 'blue populous' clusters of the LMC. The ages of these objects are 10 7 to 10 8 y, and their masses are 10 4 to 10 5 solar masses, so they are populous enough to be really useful for studying the evolution of massive stars. The author concentrates on the structure and stellar content of these young clusters. (Auth.)

  13. Star clusters and associations

    International Nuclear Information System (INIS)

    Ruprecht, J.; Palous, J.

    1983-01-01

    All 33 papers presented at the symposium were inputted to INIS. They dealt with open clusters, globular clusters, stellar associations and moving groups, and local kinematics and galactic structures. (E.S.)

  14. Cluster beam injection

    International Nuclear Information System (INIS)

    Bottiglioni, F.; Coutant, J.; Fois, M.

    1978-01-01

    Areas of possible applications of cluster injection are discussed. The deposition inside the plasma of molecules, issued from the dissociation of the injected clusters, has been computed. Some empirical scaling laws for the penetration are given

  15. Clustering at high redshifts

    International Nuclear Information System (INIS)

    Shaver, P.A.

    1986-01-01

    Evidence for clustering of and with high-redshift QSOs is discussed. QSOs of different redshifts show no clustering, but QSOs of similar redshifts appear to be clustered on a scale comparable to that of galaxies at the present epoch. In addition, spectroscopic studies of close pairs of QSOs indicate that QSOs are surrounded by a relatively high density of absorbing matter, possibly clusters of galaxies

  16. Network analysis of metabolic enzyme evolution in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Kraulis Per

    2004-02-01

    Full Text Available Abstract Background The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc. Results Sequence comparison between all enzyme pairs was performed and the minimal path length (MPL between all enzyme pairs was determined. We find a strong over-representation of homologous enzymes at MPL 1. We show that the functionally similar and functionally undetermined enzyme pairs are responsible for most of the over-representation of homologous enzyme pairs at MPL 1. Conclusions The retrograde evolution model predicts that homologous enzymes pairs are at short metabolic distances from each other. In general agreement with previous studies we find that homologous enzymes occur close to each other in the network more often than expected by chance, which lends some support to the retrograde evolution model. However, we show that the homologous enzyme pairs which may have evolved through retrograde evolution, namely the pairs that are functionally dissimilar, show a weaker over-representation at MPL 1 than the functionally similar enzyme pairs. Our study indicates that, while the retrograde evolution model may have played a small part, the patchwork evolution model is the predominant process of metabolic enzyme evolution.

  17. Cluster Physics with Merging Galaxy Clusters

    Directory of Open Access Journals (Sweden)

    Sandor M. Molnar

    2016-02-01

    Full Text Available Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ and the matter density by cold dark matter (CDM, structure formation is hierarchical, and clusters grow mostly by merging.Mergers of two massive clusters are the most energetic events in the universe after the Big Bang,hence they provide a unique laboratory to study cluster physics.The two main mass components in clusters behave differently during collisions:the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulenceare developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses.New high spatial and spectral resolution ground and space based telescopeswill come online in the near future. Motivated by these new opportunities,we briefly discuss methods which will be feasible in the near future in studying merging clusters.

  18. Millisecond radio pulsars in globular clusters

    Science.gov (United States)

    Verbunt, Frank; Lewin, Walter H. G.; Van Paradijs, Jan

    1989-01-01

    It is shown that the number of millisecond radio pulsars, in globular clusters, should be larger than 100, applying the standard scenario that all the pulsars descend from low-mass X-ray binaries. Moreover, most of the pulsars are located in a small number of clusters. The prediction that Teran 5 and Liller 1 contain at least about a dozen millisecond radio pulsars each is made. The observations of millisecond radio pulsars in globular clusters to date, in particular the discovery of two millisecond radio pulsars in 47 Tuc, are in agreement with the standard scenario, in which the neutron star is spun up during the mass transfer phase.

  19. Size selected metal clusters

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. The Optical Absorption Spectra of Small Silver Clusters (5-11) ... Soft Landing and Fragmentation of Small Clusters Deposited in Noble-Gas Films. Harbich, W.; Fedrigo, S.; Buttet, J. Phys. Rev. B 1998, 58, 7428. CO combustion on supported gold clusters. Arenz M ...

  20. The Durban Auto Cluster

    DEFF Research Database (Denmark)

    Lorentzen, Jochen; Robbins, Glen; Barnes, Justin

    2004-01-01

    The paper describes the formation of the Durban Auto Cluster in the context of trade liberalization. It argues that the improvement of operational competitiveness of firms in the cluster is prominently due to joint action. It tests this proposition by comparing the gains from cluster activities...

  1. Marketing research cluster analysis

    Directory of Open Access Journals (Sweden)

    Marić Nebojša

    2002-01-01

    Full Text Available One area of applications of cluster analysis in marketing is identification of groups of cities and towns with similar demographic profiles. This paper considers main aspects of cluster analysis by an example of clustering 12 cities with the use of Minitab software.

  2. Marketing research cluster analysis

    OpenAIRE

    Marić Nebojša

    2002-01-01

    One area of applications of cluster analysis in marketing is identification of groups of cities and towns with similar demographic profiles. This paper considers main aspects of cluster analysis by an example of clustering 12 cities with the use of Minitab software.

  3. Minimalist's linux cluster

    International Nuclear Information System (INIS)

    Choi, Chang-Yeong; Kim, Jeong-Hyun; Kim, Seyong

    2004-01-01

    Using barebone PC components and NIC's, we construct a linux cluster which has 2-dimensional mesh structure. This cluster has smaller footprint, is less expensive, and use less power compared to conventional linux cluster. Here, we report our experience in building such a machine and discuss our current lattice project on the machine

  4. Range-clustering queries

    NARCIS (Netherlands)

    Abrahamsen, M.; de Berg, M.T.; Buchin, K.A.; Mehr, M.; Mehrabi, A.D.

    2017-01-01

    In a geometric k -clustering problem the goal is to partition a set of points in R d into k subsets such that a certain cost function of the clustering is minimized. We present data structures for orthogonal range-clustering queries on a point set S : given a query box Q and an integer k>2 , compute

  5. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

    Abstract. Surveys of clusters of galaxies provide us with a powerful probe of the den- sity and nature of the dark energy. The red-shift distribution of detected clusters is highly sensitive to the dark energy equation of state parameter w. Upcoming Sunyaev–. Zel'dovich (SZ) surveys would provide us large yields of clusters to ...

  6. Statistical Issues in Galaxy Cluster Cosmology

    Science.gov (United States)

    Mantz, Adam

    2013-01-01

    The number and growth of massive galaxy clusters are sensitive probes of cosmological structure formation. Surveys at various wavelengths can detect clusters to high redshift, but the fact that cluster mass is not directly observable complicates matters, requiring us to simultaneously constrain scaling relations of observable signals with mass. The problem can be cast as one of regression, in which the data set is truncated, the (cosmology-dependent) underlying population must be modeled, and strong, complex correlations between measurements often exist. Simulations of cosmological structure formation provide a robust prediction for the number of clusters in the Universe as a function of mass and redshift (the mass function), but they cannot reliably predict the observables used to detect clusters in sky surveys (e.g. X-ray luminosity). Consequently, observers must constrain observable-mass scaling relations using additional data, and use the scaling relation model in conjunction with the mass function to predict the number of clusters as a function of redshift and luminosity.

  7. Asteroid clusters similar to asteroid pairs

    Science.gov (United States)

    Pravec, P.; Fatka, P.; Vokrouhlický, D.; Scheeres, D. J.; Kušnirák, P.; Hornoch, K.; Galád, A.; Vraštil, J.; Pray, D. P.; Krugly, Yu. N.; Gaftonyuk, N. M.; Inasaridze, R. Ya.; Ayvazian, V. R.; Kvaratskhelia, O. I.; Zhuzhunadze, V. T.; Husárik, M.; Cooney, W. R.; Gross, J.; Terrell, D.; Világi, J.; Kornoš, L.; Gajdoš, Š.; Burkhonov, O.; Ehgamberdiev, Sh. A.; Donchev, Z.; Borisov, G.; Bonev, T.; Rumyantsev, V. V.; Molotov, I. E.

    2018-04-01

    We studied the membership, size ratio and rotational properties of 13 asteroid clusters consisting of between 3 and 19 known members that are on similar heliocentric orbits. By backward integrations of their orbits, we confirmed their cluster membership and estimated times elapsed since separation of the secondaries (the smaller cluster members) from the primary (i.e., cluster age) that are between 105 and a few 106 years. We ran photometric observations for all the cluster primaries and a sample of secondaries and we derived their accurate absolute magnitudes and rotation periods. We found that 11 of the 13 clusters follow the same trend of primary rotation period vs mass ratio as asteroid pairs that was revealed by Pravec et al. (2010). We generalized the model of the post-fission system for asteroid pairs by Pravec et al. (2010) to a system of N components formed by rotational fission and we found excellent agreement between the data for the 11 asteroid clusters and the prediction from the theory of their formation by rotational fission. The two exceptions are the high-mass ratio (q > 0.7) clusters of (18777) Hobson and (22280) Mandragora for which a different formation mechanism is needed. Two candidate mechanisms for formation of more than one secondary by rotational fission were published: the secondary fission process proposed by Jacobson and Scheeres (2011) and a cratering collision event onto a nearly critically rotating primary proposed by Vokrouhlický et al. (2017). It will have to be revealed from future studies which of the clusters were formed by one or the other process. To that point, we found certain further interesting properties and features of the asteroid clusters that place constraints on the theories of their formation, among them the most intriguing being the possibility of a cascade disruption for some of the clusters.

  8. Galaxy clusters in the cosmic web

    Science.gov (United States)

    Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

    2014-12-01

    Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4DAFT/FADA survey, which combines deep large field multi-band imaging and spectroscopic data, in order to detect filaments and/or structures around these clusters. Based on colour-magnitude diagrams, we have selected the galaxies likely to be in the cluster redshift range and studied their spatial distribution. We detect a number of structures and filaments around several clusters, proving that colour-magnitude diagrams are a reliable method to detect filaments around galaxy clusters. Since this method excludes blue (spiral) galaxies at the cluster redshift, we also apply the LePhare software to compute photometric redshifts from BVRIZ images to select galaxy cluster members and study their spatial distribution. We then find that, if only galaxies classified as early-type by LePhare are considered, we obtain the same distribution than with a red sequence selection, while taking into account late-type galaxies just pollutes the background level and deteriorates our detections. The photometric redshift based method therefore does not provide any additional information.

  9. Investigations of Galaxy Clusters Using Gravitational Lensing

    Energy Technology Data Exchange (ETDEWEB)

    Wiesner, Matthew P. [Northern Illinois Univ., DeKalb, IL (United States)

    2014-08-01

    In this dissertation, we discuss the properties of galaxy clusters that have been determined using strong and weak gravitational lensing. A galaxy cluster is a collection of galaxies that are bound together by the force of gravity, while gravitational lensing is the bending of light by gravity. Strong lensing is the formation of arcs or rings of light surrounding clusters and weak lensing is a change in the apparent shapes of many galaxies. In this work we examine the properties of several samples of galaxy clusters using gravitational lensing. In Chapter 1 we introduce astrophysical theory of galaxy clusters and gravitational lensing. In Chapter 2 we examine evidence from our data that galaxy clusters are more concentrated than cosmology would predict. In Chapter 3 we investigate whether our assumptions about the number of galaxies in our clusters was valid by examining new data. In Chapter 4 we describe a determination of a relationship between mass and number of galaxies in a cluster at higher redshift than has been found before. In Chapter 5 we describe a model of the mass distribution in one of the ten lensing systems discovered by our group at Fermilab. Finally in Chapter 6 we summarize our conclusions.

  10. Cluster analysis for applications

    CERN Document Server

    Anderberg, Michael R

    1973-01-01

    Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis.Comprised of 10 chapters, this book begins with an introduction to the subject o

  11. The growth of Fe clusters over graphene/Cu(111)

    International Nuclear Information System (INIS)

    Takahashi, Keisuke

    2015-01-01

    The growth of Fe clusters up to nine atoms over graphene/Cu(111) is investigated within the density functional theory. Graphene is weakly physisorbed on Cu(111) through van der Waals force. The structures of Fe clusters over graphene/Cu(111) grow differently compared to gas-phase Fe clusters where Fe clusters are predicted to form towards a pyramid-like structure on graphene/Cu(111). The graphene is negatively charged upon the adsorption of Fe clusters as a result of charge transfer from Fe to graphene. Despite the fact that the electronic structure of graphene is affected by Fe clusters, magnetic moment of Fe clusters over graphene/Cu(111) remains relatively high. This suggests that graphene can be a potential substrate for supporting Fe clusters towards applications in magnetism and catalysis. (paper)

  12. Enzyme recycling in lignocellulosic biorefineries

    DEFF Research Database (Denmark)

    Jørgensen, Henning; Pinelo, Manuel

    2017-01-01

    platform. Cellulases are the most important enzymes required in this process, but the complex nature of lignocellulose requires several other enzymes (hemicellulases and auxiliary enzymes) for efficient hydrolysis. Enzyme recycling increases the catalytic productivity of the enzymes by reusing them...... for several batches of hydrolysis, and thereby reduces the overall cost associated with the hydrolysis. Research on this subject has been ongoing for many years and several promising technologies and methods have been developed and demonstrated. But only in a very few cases have these technologies been...... upscaled and tested in industrial settings, mainly because of many difficulties with recycling of enzymes from the complex lignocellulose hydrolyzate at industrially relevant conditions, i.e., high solids loadings. The challenges are associated with the large number of different enzymes required...

  13. Characterising Complex Enzyme Reaction Data.

    Directory of Open Access Journals (Sweden)

    Handan Melike Dönertaş

    Full Text Available The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g., KEGG. Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution.

  14. Clusters in nuclei

    CERN Document Server

    Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This third volume follows the successful Lect. Notes Phys. 818 (Vol. 1) and 848 (Vol. 2), and comprises six extensive lectures covering the following topics:  - Gamma Rays and Molecular Structure - Faddeev Equation Approach for Three Cluster Nuclear Reactions - Tomography of the Cluster Structure of Light Nuclei Via Relativistic Dissociation - Clustering Effects Within the Dinuclear Model : From Light to Hyper-heavy Molecules in Dynamical Mean-field Approach - Clusterization in Ternary Fission - Clusters in Light N...

  15. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...

  16. Clusters and how to make it work : Cluster Strategy Toolkit

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2014-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  17. Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

    Science.gov (United States)

    Murumkar, Prashant Revan; Zambre, Vishal Prakash; Yadav, Mange Ram

    2010-02-01

    A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.

  18. Agricultural Clusters in the Netherlands

    NARCIS (Netherlands)

    Schouten, M.A.; Heijman, W.J.M.

    2012-01-01

    Michael Porter was the first to use the term cluster in an economic context. He introduced the term in The Competitive Advantage of Nations (1990). The term cluster is also known as business cluster, industry cluster, competitive cluster or Porterian cluster. This article aims at determining and

  19. On the Structural Context and Identification of Enzyme Catalytic Residues

    Directory of Open Access Journals (Sweden)

    Yu-Tung Chien

    2013-01-01

    Full Text Available Enzymes play important roles in most of the biological processes. Although only a small fraction of residues are directly involved in catalytic reactions, these catalytic residues are the most crucial parts in enzymes. The study of the fundamental and unique features of catalytic residues benefits the understanding of enzyme functions and catalytic mechanisms. In this work, we analyze the structural context of catalytic residues based on theoretical and experimental structure flexibility. The results show that catalytic residues have distinct structural features and context. Their neighboring residues, whether sequence or structure neighbors within specific range, are usually structurally more rigid than those of noncatalytic residues. The structural context feature is combined with support vector machine to identify catalytic residues from enzyme structure. The prediction results are better or comparable to those of recent structure-based prediction methods.

  20. Ligand Access Channels in Cytochrome P450 Enzymes: A Review

    Directory of Open Access Journals (Sweden)

    Philippe Urban

    2018-05-01

    Full Text Available Quantitative structure-activity relationships may bring invaluable information on structural elements of both enzymes and substrates that, together, govern substrate specificity. Buried active sites in cytochrome P450 enzymes are connected to the solvent by a network of channels exiting at the distal surface of the protein. This review presents different in silico tools that were developed to uncover such channels in P450 crystal structures. It also lists some of the experimental evidence that actually suggest that these predicted channels might indeed play a critical role in modulating P450 functions. Amino acid residues at the entrance of the channels may participate to a first global ligand recognition of ligands by P450 enzymes before they reach the buried active site. Moreover, different P450 enzymes show different networks of predicted channels. The plasticity of P450 structures is also important to take into account when looking at how channels might play their role.

  1. Open source clustering software.

    Science.gov (United States)

    de Hoon, M J L; Imoto, S; Nolan, J; Miyano, S

    2004-06-12

    We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

  2. Measuring the Enzyme Activity of Arabidopsis Deubiquitylating Enzymes.

    Science.gov (United States)

    Kalinowska, Kamila; Nagel, Marie-Kristin; Isono, Erika

    2016-01-01

    Deubiquitylating enzymes, or DUBs, are important regulators of ubiquitin homeostasis and substrate stability, though the molecular mechanisms of most of the DUBs in plants are not yet understood. As different ubiquitin chain types are implicated in different biological pathways, it is important to analyze the enzyme characteristic for studying a DUB. Quantitative analysis of DUB activity is also important to determine enzyme kinetics and the influence of DUB binding proteins on the enzyme activity. Here, we show methods to analyze DUB activity using immunodetection, Coomassie Brilliant Blue staining, and fluorescence measurement that can be useful for understanding the basic characteristic of DUBs.

  3. Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies.

    Directory of Open Access Journals (Sweden)

    Ranyee A Chiang

    2008-08-01

    Full Text Available The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized

  4. Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies.

    Science.gov (United States)

    Chiang, Ranyee A; Sali, Andrej; Babbitt, Patricia C

    2008-08-01

    The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized

  5. Enzyme Molecules in Solitary Confinement

    Directory of Open Access Journals (Sweden)

    Raphaela B. Liebherr

    2014-09-01

    Full Text Available Large arrays of homogeneous microwells each defining a femtoliter volume are a versatile platform for monitoring the substrate turnover of many individual enzyme molecules in parallel. The high degree of parallelization enables the analysis of a statistically representative enzyme population. Enclosing individual enzyme molecules in microwells does not require any surface immobilization step and enables the kinetic investigation of enzymes free in solution. This review describes various microwell array formats and explores their applications for the detection and investigation of single enzyme molecules. The development of new fabrication techniques and sensitive detection methods drives the field of single molecule enzymology. Here, we introduce recent progress in single enzyme molecule analysis in microwell arrays and discuss the challenges and opportunities.

  6. DGAT enzymes and triacylglycerol biosynthesis

    Science.gov (United States)

    Yen, Chi-Liang Eric; Stone, Scot J.; Koliwad, Suneil; Harris, Charles; Farese, Robert V.

    2008-01-01

    Triacylglycerols (triglycerides) (TGs) are the major storage molecules of metabolic energy and FAs in most living organisms. Excessive accumulation of TGs, however, is associated with human diseases, such as obesity, diabetes mellitus, and steatohepatitis. The final and the only committed step in the biosynthesis of TGs is catalyzed by acyl-CoA:diacylglycerol acyltransferase (DGAT) enzymes. The genes encoding two DGAT enzymes, DGAT1 and DGAT2, were identified in the past decade, and the use of molecular tools, including mice deficient in either enzyme, has shed light on their functions. Although DGAT enzymes are involved in TG synthesis, they have distinct protein sequences and differ in their biochemical, cellular, and physiological functions. Both enzymes may be useful as therapeutic targets for diseases. Here we review the current knowledge of DGAT enzymes, focusing on new advances since the cloning of their genes, including possible roles in human health and diseases. PMID:18757836

  7. Enzyme stabilization for pesticide degradation

    Energy Technology Data Exchange (ETDEWEB)

    Rivers, D.B.; Frazer, F.R. III; Mason, D.W.; Tice, T.R.

    1988-01-01

    Enzymes offer inherent advantages and limitations as active components of formulations used to decontaminate soil and equipment contaminated with toxic materials such as pesticides. Because of the catalytic nature of enzymes, each molecule of enzyme has the potential to destroy countless molecules of a contaminating toxic compound. This degradation takes place under mild environmental conditions of pH, temperature, pressure, and solvent. The basic limitation of enzymes is their degree of stability during storage and application conditions. Stabilizing methods such as the use of additives, covalent crosslinking, covalent attachment, gel entrapment, and microencapsulation have been directed developing an enzyme preparation that is stable under extremes of pH, temperature, and exposure to organic solvents. Initial studies were conducted using the model enzymes subtilisin and horseradish peroxidase.

  8. Interplay of drug metabolizing enzymes with cellular transporters.

    Science.gov (United States)

    Böhmdorfer, Michaela; Maier-Salamon, Alexandra; Riha, Juliane; Brenner, Stefan; Höferl, Martina; Jäger, Walter

    2014-11-01

    Many endogenous and xenobiotic substances and their metabolites are substrates for drug metabolizing enzymes and cellular transporters. These proteins may not only contribute to bioavailability of molecules but also to uptake into organs and, consequently, to overall elimination. The coordinated action of uptake transporters, metabolizing enzymes, and efflux pumps, therefore, is a precondition for detoxification and elimination of drugs. As the understanding of the underlying mechanisms is important to predict alterations in drug disposal, adverse drug reactions and, finally, drug-drug interactions, this review illustrates the interplay between selected uptake/efflux transporters and phase I/II metabolizing enzymes.

  9. Electron: Cluster interactions

    International Nuclear Information System (INIS)

    Scheidemann, A.A.; Knight, W.D.

    1994-02-01

    Beam depletion spectroscopy has been used to measure absolute total inelastic electron-sodium cluster collision cross sections in the energy range from E ∼ 0.1 to E ∼ 6 eV. The investigation focused on the closed shell clusters Na 8 , Na 20 , Na 40 . The measured cross sections show an increase for the lowest collision energies where electron attachment is the primary scattering channel. The electron attachment cross section can be understood in terms of Langevin scattering, connecting this measurement with the polarizability of the cluster. For energies above the dissociation energy the measured electron-cluster cross section is energy independent, thus defining an electron-cluster interaction range. This interaction range increases with the cluster size

  10. Clustering high dimensional data

    DEFF Research Database (Denmark)

    Assent, Ira

    2012-01-01

    High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...

  11. Direct comparison of enzyme histochemical and immunohistochemical methods to localize an enzyme

    NARCIS (Netherlands)

    van Noorden, Cornelis J. F.

    2002-01-01

    Immunohistochemical localization of enzymes is compared directly with localization of enzyme activity with (catalytic) enzyme histochemical methods. The two approaches demonstrate principally different aspects of an enzyme. The immunohistochemical method localizes the enzyme protein whether it is

  12. Substructure in clusters of galaxies

    International Nuclear Information System (INIS)

    Fitchett, M.J.

    1988-01-01

    Optical observations suggesting the existence of substructure in clusters of galaxies are examined. Models of cluster formation and methods used to detect substructure in clusters are reviewed. Consideration is given to classification schemes based on a departure of bright cluster galaxies from a spherically symmetric distribution, evidence for statistically significant substructure, and various types of substructure, including velocity, spatial, and spatial-velocity substructure. The substructure observed in the galaxy distribution in clusters is discussed, focusing on observations from general cluster samples, the Virgo cluster, the Hydra cluster, Centaurus, the Coma cluster, and the Cancer cluster. 88 refs

  13. Enzyme Mimics: Advances and Applications.

    Science.gov (United States)

    Kuah, Evelyn; Toh, Seraphina; Yee, Jessica; Ma, Qian; Gao, Zhiqiang

    2016-06-13

    Enzyme mimics or artificial enzymes are a class of catalysts that have been actively pursued for decades and have heralded much interest as potentially viable alternatives to natural enzymes. Aside from having catalytic activities similar to their natural counterparts, enzyme mimics have the desired advantages of tunable structures and catalytic efficiencies, excellent tolerance to experimental conditions, lower cost, and purely synthetic routes to their preparation. Although still in the midst of development, impressive advances have already been made. Enzyme mimics have shown immense potential in the catalysis of a wide range of chemical and biological reactions, the development of chemical and biological sensing and anti-biofouling systems, and the production of pharmaceuticals and clean fuels. This Review concerns the development of various types of enzyme mimics, namely polymeric and dendrimeric, supramolecular, nanoparticulate and proteinic enzyme mimics, with an emphasis on their synthesis, catalytic properties and technical applications. It provides an introduction to enzyme mimics and a comprehensive summary of the advances and current standings of their applications, and seeks to inspire researchers to perfect the design and synthesis of enzyme mimics and to tailor their functionality for a much wider range of applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Phage lytic enzymes: a history.

    Science.gov (United States)

    Trudil, David

    2015-02-01

    There are many recent studies regarding the efficacy of bacteriophage-related lytic enzymes: the enzymes of 'bacteria-eaters' or viruses that infect bacteria. By degrading the cell wall of the targeted bacteria, these lytic enzymes have been shown to efficiently lyse Gram-positive bacteria without affecting normal flora and non-related bacteria. Recent studies have suggested approaches for lysing Gram-negative bacteria as well (Briersa Y, et al., 2014). These enzymes include: phage-lysozyme, endolysin, lysozyme, lysin, phage lysin, phage lytic enzymes, phageassociated enzymes, enzybiotics, muralysin, muramidase, virolysin and designations such as Ply, PAE and others. Bacteriophages are viruses that kill bacteria, do not contribute to antimicrobial resistance, are easy to develop, inexpensive to manufacture and safe for humans, animals and the environment. The current focus on lytic enzymes has been on their use as anti-infectives in humans and more recently in agricultural research models. The initial translational application of lytic enzymes, however, was not associated with treating or preventing a specific disease but rather as an extraction method to be incorporated in a rapid bacterial detection assay (Bernstein D, 1997).The current review traces the translational history of phage lytic enzymes-from their initial discovery in 1986 for the rapid detection of group A streptococcus in clinical specimens to evolving applications in the detection and prevention of disease in humans and in agriculture.

  15. Nonthermal emission from clusters of galaxies

    International Nuclear Information System (INIS)

    Kushnir, Doron; Waxman, Eli

    2009-01-01

    We show that the spectral and radial distribution of the nonthermal emission of massive, M ∼> 10 14.5 M ☉ , galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, β core and η e . β core is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and η e(p) is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that β core ≅ η p /200, nearly independent of cluster mass and with a scatter Δln β core ≅ 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors ≅ 500(η e /η p )(T/10 keV) −1/2 and ≅ 150(η e /η p )(T/10 keV) −1/2 respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (∼> 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for η p ∼ η e ∼ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular, we identify the clusters which are the best candidates for detection in

  16. Nonthermal emission from clusters of galaxies

    Energy Technology Data Exchange (ETDEWEB)

    Kushnir, Doron; Waxman, Eli, E-mail: doron.kushnir@weizmann.ac.il, E-mail: eli.waxman@weizmann.ac.il [Physics Faculty, Weizmann Institute of Science, PO Box 26, Rehovot (Israel)

    2009-08-01

    We show that the spectral and radial distribution of the nonthermal emission of massive, M ∼> 10{sup 14.5}M{sub ☉}, galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, β{sub core} and η{sub e}. β{sub core} is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and η{sub e(p)} is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that β{sub core} ≅ η{sub p}/200, nearly independent of cluster mass and with a scatter Δln β{sub core} ≅ 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors ≅ 500(η{sub e}/η{sub p})(T/10 keV){sup −1/2} and ≅ 150(η{sub e}/η{sub p})(T/10 keV){sup −1/2} respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (∼> 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for η{sub p} ∼ η{sub e} ∼ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular

  17. Nonthermal emission from clusters of galaxies

    Science.gov (United States)

    Kushnir, Doron; Waxman, Eli

    2009-08-01

    We show that the spectral and radial distribution of the nonthermal emission of massive, M gtrsim 1014.5Msun, galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, βcore and ηe. βcore is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and ηe(p) is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that βcore simeq ηp/200, nearly independent of cluster mass and with a scatter Δln βcore simeq 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors simeq 500(ηe/ηp)(T/10 keV)-1/2 and simeq 150(ηe/ηp)(T/10 keV)-1/2 respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (gtrsim 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for ηp ~ ηe ~ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular, we identify the clusters which are the best candidates for detection in γ-rays. Finally, we show

  18. [The rise of enzyme engineering in China].

    Science.gov (United States)

    Li, Gaoxiang

    2015-06-01

    Enzyme engineering is an important part of the modern biotechnology. Industrial biocatalysis is considered the third wave of biotechnology following pharmaceutical and agricultural waves. In 25 years, China has made a mighty advances in enzyme engineering research. This review focuses on enzyme genomics, enzyme proteomics, biosynthesis, microbial conversion and biosensors in the Chinese enzyme engineering symposiums and advances in enzyme preparation industry in China.

  19. Nuclear cluster states

    International Nuclear Information System (INIS)

    Rae, W.D.M.; Merchant, A.C.

    1993-01-01

    We review clustering in light nuclei including molecular resonances in heavy ion reactions. In particular we study the systematics, paying special attention to the relationships between cluster states and superdeformed configurations. We emphasise the selection rules which govern the formation and decay of cluster states. We review some recent experimental results from Daresbury and elsewhere. In particular we report on the evidence for a 7-α chain state in 28 Si in experiments recently performed at the NSF, Daresbury. Finally we begin to address theoretically the important question of the lifetimes of cluster states as deduced from the experimental energy widths of the resonances. (Author)

  20. 15th Cluster workshop

    CERN Document Server

    Laakso, Harri; Escoubet, C. Philippe; The Cluster Active Archive : Studying the Earth’s Space Plasma Environment

    2010-01-01

    Since the year 2000 the ESA Cluster mission has been investigating the small-scale structures and processes of the Earth's plasma environment, such as those involved in the interaction between the solar wind and the magnetospheric plasma, in global magnetotail dynamics, in cross-tail currents, and in the formation and dynamics of the neutral line and of plasmoids. This book contains presentations made at the 15th Cluster workshop held in March 2008. It also presents several articles about the Cluster Active Archive and its datasets, a few overview papers on the Cluster mission, and articles reporting on scientific findings on the solar wind, the magnetosheath, the magnetopause and the magnetotail.

  1. Clusters in simple fluids

    International Nuclear Information System (INIS)

    Sator, N.

    2003-01-01

    This article concerns the correspondence between thermodynamics and the morphology of simple fluids in terms of clusters. Definitions of clusters providing a geometric interpretation of the liquid-gas phase transition are reviewed with an eye to establishing their physical relevance. The author emphasizes their main features and basic hypotheses, and shows how these definitions lead to a recent approach based on self-bound clusters. Although theoretical, this tutorial review is also addressed to readers interested in experimental aspects of clustering in simple fluids

  2. The dyslipidemia-associated SNP on the APOA1/C3/A5 gene cluster predicts post-surgery poor outcome in Taiwanese breast cancer patients: a 10-year follow-up study

    International Nuclear Information System (INIS)

    Hsu, Mei-Chi; Lee, Kuo-Ting; Hsiao, Wei-Chiang; Wu, Chih-Hsing; Sun, Hung-Yu; Lin, I-Ling; Young, Kung-Chia

    2013-01-01

    Post-surgery therapies are given to early-stage breast cancer patients due to the possibility of residual micrometastasis, and optimized by clincopathological parameters such as tumor stage, and hormone receptor/lymph node status. However, current efficacy of post-surgery therapies is unsatisfactory, and may be varied according to unidentified patient genetic factors. Increases of breast cancer occurrence and recurrence have been associated with dyslipidemia, which can attribute to other known risk factors of breast cancer including obesity, diabetes and metabolic syndrome. Thus we reasoned that dyslipidemia-associated nucleotide polymorphisms (SNPs) on the APOA1/C3/A5 gene cluster may predict breast cancer risk and tumor progression. We analyzed the distribution of 5 selected APOA1/C3/A5 SNPs in recruited Taiwanese breast cancer patients (n=223) and healthy controls (n=162). The association of SNP (APOA1 rs670) showing correlation with breast cancer with baseline and follow-up parameters was further examined. APOA1 rs670 A allele carriage was higher in breast cancer patients than controls (59.64% vs. 48.77%, p=0.038). The rs670 A allele carrying patients showed less favorable baseline phenotype with positive lymph nodes (G/A: OR=3.32, 95% CI=1.77-6.20, p<0.001; A/A: OR=2.58, 95% CI=1.05-6.32, p=0.039) and negative hormone receptor expression (A/A: OR=4.85, 95%CI=1.83-12.83, p=0.001) in comparison to G/G carriers. Moreover, rs670 A/A carrying patients had higher risks in both tumor recurrence (HR=3.12, 95% CI=1.29-7.56, p=0.012) and mortality (HR=4.36, 95% CI=1.52-12.47, p=0.006) than patients with no A alleles after adjustments for associated baseline parameters. Furthermore, the prognostic effect of rs670 A/A carriage was most evident in lymph node-negative patients, conferring to the highest risks of recurrence (HR=4.98, 95% CI=1.40-17.70, p=0.013) and mortality (HR=9.87, 95%CI=1.60-60.81, p=0.014) than patients with no A alleles. APOA1 rs670 A/A carriage showed

  3. The dyslipidemia-associated SNP on the APOA1/C3/A5 gene cluster predicts post-surgery poor outcome in Taiwanese breast cancer patients: a 10-year follow-up study

    Energy Technology Data Exchange (ETDEWEB)

    Hsu, Mei-Chi [Research Center for Medical Laboratory Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Department of Medical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Lee, Kuo-Ting [Department of Surgery, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Hsiao, Wei-Chiang [Department of Surgery, Yang Ming Hospital, Chiayi, Taiwan (China); Wu, Chih-Hsing [Department of Family Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Sun, Hung-Yu [Department of Medical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Lin, I-Ling [Department of Medical Laboratory Science and Biotechnology, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan (China); Young, Kung-Chia [Research Center for Medical Laboratory Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Department of Medical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China); Center of Infectious Disease and Signaling Research, College of Medicine, National Cheng Kung University, Tainan, Taiwan (China)

    2013-07-05

    Post-surgery therapies are given to early-stage breast cancer patients due to the possibility of residual micrometastasis, and optimized by clincopathological parameters such as tumor stage, and hormone receptor/lymph node status. However, current efficacy of post-surgery therapies is unsatisfactory, and may be varied according to unidentified patient genetic factors. Increases of breast cancer occurrence and recurrence have been associated with dyslipidemia, which can attribute to other known risk factors of breast cancer including obesity, diabetes and metabolic syndrome. Thus we reasoned that dyslipidemia-associated nucleotide polymorphisms (SNPs) on the APOA1/C3/A5 gene cluster may predict breast cancer risk and tumor progression. We analyzed the distribution of 5 selected APOA1/C3/A5 SNPs in recruited Taiwanese breast cancer patients (n=223) and healthy controls (n=162). The association of SNP (APOA1 rs670) showing correlation with breast cancer with baseline and follow-up parameters was further examined. APOA1 rs670 A allele carriage was higher in breast cancer patients than controls (59.64% vs. 48.77%, p=0.038). The rs670 A allele carrying patients showed less favorable baseline phenotype with positive lymph nodes (G/A: OR=3.32, 95% CI=1.77-6.20, p<0.001; A/A: OR=2.58, 95% CI=1.05-6.32, p=0.039) and negative hormone receptor expression (A/A: OR=4.85, 95%CI=1.83-12.83, p=0.001) in comparison to G/G carriers. Moreover, rs670 A/A carrying patients had higher risks in both tumor recurrence (HR=3.12, 95% CI=1.29-7.56, p=0.012) and mortality (HR=4.36, 95% CI=1.52-12.47, p=0.006) than patients with no A alleles after adjustments for associated baseline parameters. Furthermore, the prognostic effect of rs670 A/A carriage was most evident in lymph node-negative patients, conferring to the highest risks of recurrence (HR=4.98, 95% CI=1.40-17.70, p=0.013) and mortality (HR=9.87, 95%CI=1.60-60.81, p=0.014) than patients with no A alleles. APOA1 rs670 A/A carriage showed

  4. Mechanism of Shiga Toxin Clustering on Membranes

    DEFF Research Database (Denmark)

    Pezeshkian, Weria; Gao, Haifei; Arumugam, Senthil

    2017-01-01

    between them. The precise mechanism by which this clustering occurs remains poorly defined. Here, we used vesicle and cell systems and computer simulations to show that line tension due to curvature, height, or compositional mismatch, and lipid or solvent depletion cannot drive the clustering of Shiga...... toxin molecules. By contrast, in coarse-grained computer simulations, a correlation was found between clustering and toxin nanoparticle-driven suppression of membrane fluctuations, and experimentally we observed that clustering required the toxin molecules to be tightly bound to the membrane surface...... molecules (several nanometers), and persist even beyond. This force is predicted to operate between manufactured nanoparticles providing they are sufficiently rigid and tightly bound to the plasma membrane, thereby suggesting a route for the targeting of nanoparticles to cells for biomedical applications....

  5. Enzyme structure, enzyme function and allozyme diversity in ...

    African Journals Online (AJOL)

    In estimates of population genetic diversity based on allozyme heterozygosity, some enzymes are regularly more variable than others. Evolutionary theory suggests that functionally less important molecules, or parts of molecules, evolve more rapidly than more important ones; the latter enzymes should then theoretically be ...

  6. Computational enzyme design: transitioning from catalytic proteins to enzymes.

    Science.gov (United States)

    Mak, Wai Shun; Siegel, Justin B

    2014-08-01

    The widespread interest in enzymes stem from their ability to catalyze chemical reactions under mild and ecologically friendly conditions with unparalleled catalytic proficiencies. While thousands of naturally occurring enzymes have been identified and characterized, there are still numerous important applications for which there are no biological catalysts capable of performing the desired chemical transformation. In order to engineer enzymes for which there is no natural starting point, efforts using a combination of quantum chemistry and force-field based protein molecular modeling have led to the design of novel proteins capable of catalyzing chemical reactions not catalyzed by naturally occurring enzymes. Here we discuss the current status and potential avenues to pursue as the field of computational enzyme design moves forward. Published by Elsevier Ltd.

  7. Immobilized enzymes: understanding enzyme - surface interactions at the molecular level.

    Science.gov (United States)

    Hoarau, Marie; Badieyan, Somayesadat; Marsh, E Neil G

    2017-11-22

    Enzymes immobilized on solid supports have important and industrial and medical applications. However, their uses are limited by the significant reductions in activity and stability that often accompany the immobilization process. Here we review recent advances in our understanding of the molecular level interactions between proteins and supporting surfaces that contribute to changes in stability and activity. This understanding has been facilitated by the application of various surface-sensitive spectroscopic techniques that allow the structure and orientation of enzymes at the solid/liquid interface to be probed, often with monolayer sensitivity. An appreciation of the molecular interactions between enzyme and surface support has allowed the surface chemistry and method of enzyme attachement to be fine-tuned such that activity and stability can be greatly enhanced. These advances suggest that a much wider variety of enzymes may eventually be amenable to immobilization as green catalysts.

  8. Stability of Enzymes in Granular Enzyme Products for Laundry Detergents

    DEFF Research Database (Denmark)

    Biran, Suzan; Bach, Poul; Simonsen, Ole

    Enzymes have long been of interest to the detergent industry due to their ability to improve the cleaning efficiency of synthetic detergents, contribute to shortening washing times, and reduce energy and water consumption, provision of environmentally friendlier wash water effluents and fabric care....... However, incorporating enzymes in detergent formulations gives rise to numerous practical problems due to their incompatibility with and stability against various detergent components. In powdered detergent formulations, these issues can be partly overcome by physically isolating the enzymes in separate...... particles. However, enzymes may loose a significant part of their activity over a time period of several weeks. Possible causes of inactivation of enzymes in a granule may be related to the release of hydrogen peroxide from the bleaching chemicals in a moisture-containing atmosphere, humidity, autolysis...

  9. Enzymes in Human Milk.

    Science.gov (United States)

    Dallas, David C; German, J Bruce

    2017-01-01

    Milk proteins are a complex and diverse source of biological activities. Beyond their function, intact milk proteins also act as carriers of encrypted functional sequences that, when released as peptides, exert biological functions, including antimicrobial and immunomodulatory activity, which could contribute to the infant's competitive success. Research has now revealed that the release of these functional peptides begins within the mammary gland itself. A complex array of proteases produced in mother's milk has been shown to be active in the milk, releasing these peptides. Moreover, our recent research demonstrates that these milk proteases continue to digest milk proteins within the infant's stomach, possibly even to a larger extent than the infant's own proteases. As the neonate has relatively low digestive capacity, the activity of milk proteases in the infant may provide important assistance to digesting milk proteins. The coordinated release of these encrypted sequences is accomplished by selective proteolytic action provided by an array of native milk proteases and infant-produced enzymes. The task for scientists is now to discover the selective advantages of this protein-protease-based peptide release system. © 2017 Nestec Ltd., Vevey/S. Karger AG, Basel.

  10. clusterMaker: a multi-algorithm clustering plugin for Cytoscape

    Directory of Open Access Journals (Sweden)

    Morris John H

    2011-11-01

    Full Text Available Abstract Background In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view, k-means, k-medoid, SCPS, AutoSOME, and native (Java MCL. Results Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. Conclusions The Cytoscape plugin cluster

  11. Comparative genomics of Cluster O mycobacteriophages.

    Science.gov (United States)

    Cresawn, Steven G; Pope, Welkin H; Jacobs-Sera, Deborah; Bowman, Charles A; Russell, Daniel A; Dedrick, Rebekah M; Adair, Tamarah; Anders, Kirk R; Ball, Sarah; Bollivar, David; Breitenberger, Caroline; Burnett, Sandra H; Butela, Kristen; Byrnes, Deanna; Carzo, Sarah; Cornely, Kathleen A; Cross, Trevor; Daniels, Richard L; Dunbar, David; Findley, Ann M; Gissendanner, Chris R; Golebiewska, Urszula P; Hartzog, Grant A; Hatherill, J Robert; Hughes, Lee E; Jalloh, Chernoh S; De Los Santos, Carla; Ekanem, Kevin; Khambule, Sphindile L; King, Rodney A; King-Smith, Christina; Klyczek, Karen; Krukonis, Greg P; Laing, Christian; Lapin, Jonathan S; Lopez, A Javier; Mkhwanazi, Sipho M; Molloy, Sally D; Moran, Deborah; Munsamy, Vanisha; Pacey, Eddie; Plymale, Ruth; Poxleitner, Marianne; Reyna, Nathan; Schildbach, Joel F; Stukey, Joseph; Taylor, Sarah E; Ware, Vassie C; Wellmann, Amanda L; Westholm, Daniel; Wodarski, Donna; Zajko, Michelle; Zikalala, Thabiso S; Hendrix, Roger W; Hatfull, Graham F

    2015-01-01

    Mycobacteriophages--viruses of mycobacterial hosts--are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages--Corndog, Catdawg, Dylan, Firecracker, and YungJamal--designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange.

  12. Comparative genomics of Cluster O mycobacteriophages.

    Directory of Open Access Journals (Sweden)

    Steven G Cresawn

    Full Text Available Mycobacteriophages--viruses of mycobacterial hosts--are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages--Corndog, Catdawg, Dylan, Firecracker, and YungJamal--designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange.

  13. Probable cluster decays from 298-336126 superheavy nuclei

    International Nuclear Information System (INIS)

    Priyanka, B.; Santhosh, K.P.

    2015-01-01

    The present paper deals with an investigation on the cluster decay of even clusters 4 He, 8,10 Be, 14 C, 18,20,22 O , 22,24,26 Ne, 28,30 Mg and odd clusters 15 N, 23 F, 25 Ne, 29 Mg from both the even-even and even-odd isotopes of Z=126, which has helped in predicting the neutron magicity beyond N=126

  14. MEASURING THE ULTIMATE HALO MASS OF GALAXY CLUSTERS: REDSHIFTS AND MASS PROFILES FROM THE HECTOSPEC CLUSTER SURVEY (HeCS)

    International Nuclear Information System (INIS)

    Rines, Kenneth; Geller, Margaret J.; Kurtz, Michael J.; Diaferio, Antonaldo

    2013-01-01

    The infall regions of galaxy clusters represent the largest gravitationally bound structures in a ΛCDM universe. Measuring cluster mass profiles into the infall regions provides an estimate of the ultimate mass of these halos. We use the caustic technique to measure cluster mass profiles from galaxy redshifts obtained with the Hectospec Cluster Survey (HeCS), an extensive spectroscopic survey of galaxy clusters with MMT/Hectospec. We survey 58 clusters selected by X-ray flux at 0.1 200 , a new observational cosmological test in essential agreement with simulations. Summed profiles binned in M 200 and in L X demonstrate that the predicted Navarro-Frenk-White form of the density profile is a remarkably good representation of the data in agreement with weak lensing results extending to large radius. The concentration of these summed profiles is also consistent with theoretical predictions.

  15. Structure and Mobility of Metal Clusters in MOFs: Au, Pd, and AuPd Clusters in MOF-74

    DEFF Research Database (Denmark)

    Vilhelmsen, Lasse; Walton, Krista S.; Sholl, David S.

    2012-01-01

    is just as important for nanocluster adsorption as open Zn or Mg metal sites. Using the large number of clusters generated by the GA, we developed a systematic method for predicting the mobility of adsorbed clusters. Through the investigation of diffusion paths a relationship between the cluster......Understanding the adsorption and mobility of metal–organic framework (MOF)-supported metal nanoclusters is critical to the development of these catalytic materials. We present the first theoretical investigation of Au-, Pd-, and AuPd-supported clusters in a MOF, namely MOF-74. We combine density...... functional theory (DFT) calculations with a genetic algorithm (GA) to reliably predict the structure of the adsorbed clusters. This approach allows comparison of hundreds of adsorbed configurations for each cluster. From the investigation of Au8, Pd8, and Au4Pd4 we find that the organic part of the MOF...

  16. Lifting to cluster-tilting objects in higher cluster categories

    OpenAIRE

    Liu, Pin

    2008-01-01

    In this note, we consider the $d$-cluster-tilted algebras, the endomorphism algebras of $d$-cluster-tilting objects in $d$-cluster categories. We show that a tilting module over such an algebra lifts to a $d$-cluster-tilting object in this $d$-cluster category.

  17. Improvement in Saccharification Yield of Mixed Rumen Enzymes by Identification of Recalcitrant Cell Wall Constituents Using Enzyme Fingerprinting.

    Science.gov (United States)

    Badhan, Ajay; Wang, Yu-Xi; Gruninger, Robert; Patton, Donald; Powlowski, Justin; Tsang, Adrian; McAllister, Tim A

    2015-01-01

    Identification of recalcitrant factors that limit digestion of forages and the development of enzymatic approaches that improve hydrolysis could play a key role in improving the efficiency of meat and milk production in ruminants. Enzyme fingerprinting of barley silage fed to heifers and total tract indigestible fibre residue (TIFR) collected from feces was used to identify cell wall components resistant to total tract digestion. Enzyme fingerprinting results identified acetyl xylan esterases as key to the enhanced ruminal digestion. FTIR analysis also suggested cross-link cell wall polymers as principal components of indigested fiber residues in feces. Based on structural information from enzymatic fingerprinting and FTIR, enzyme pretreatment to enhance glucose yield from barley straw and alfalfa hay upon exposure to mixed rumen-enzymes was developed. Prehydrolysis effects of recombinant fungal fibrolytic hydrolases were analyzed using microassay in combination with statistical experimental design. Recombinant hemicellulases and auxiliary enzymes initiated degradation of plant structural polysaccharides upon application and improved the in vitro saccharification of alfalfa and barley straw by mixed rumen enzymes. The validation results showed that microassay in combination with statistical experimental design can be successfully used to predict effective enzyme pretreatments that can enhance plant cell wall digestion by mixed rumen enzymes.

  18. Digestive enzymes of some earthworms.

    Science.gov (United States)

    Mishra, P C; Dash, M C

    1980-10-15

    4 species of tropical earthworms differed with regard to enzyme activity. The maximum activity of protease and of cellulase occurred in the posterior region of the gut of the earthworms. On the average Octochaetona surensis shows maximum activity and Drawida calebi shows minimum activity for all the enzymes studied.

  19. Neurostimulation in cluster headache

    DEFF Research Database (Denmark)

    Pedersen, Jeppe L; Barloese, Mads; Jensen, Rigmor H

    2013-01-01

    PURPOSE OF REVIEW: Neurostimulation has emerged as a viable treatment for intractable chronic cluster headache. Several therapeutic strategies are being investigated including stimulation of the hypothalamus, occipital nerves and sphenopalatine ganglion. The aim of this review is to provide...... effective strategy must be preferred as first-line therapy for intractable chronic cluster headache....

  20. Cauchy cluster process

    DEFF Research Database (Denmark)

    Ghorbani, Mohammad

    2013-01-01

    In this paper we introduce an instance of the well-know Neyman–Scott cluster process model with clusters having a long tail behaviour. In our model the offspring points are distributed around the parent points according to a circular Cauchy distribution. Using a modified Cramér-von Misses test...

  1. When Clusters become Networks

    NARCIS (Netherlands)

    S.M.W. Phlippen (Sandra); G.A. van der Knaap (Bert)

    2007-01-01

    textabstractPolicy makers spend large amounts of public resources on the foundation of science parks and other forms of geographically clustered business activities, in order to stimulate regional innovation. Underlying the relation between clusters and innovation is the assumption that co-located

  2. Mixed-Initiative Clustering

    Science.gov (United States)

    Huang, Yifen

    2010-01-01

    Mixed-initiative clustering is a task where a user and a machine work collaboratively to analyze a large set of documents. We hypothesize that a user and a machine can both learn better clustering models through enriched communication and interactive learning from each other. The first contribution or this thesis is providing a framework of…

  3. Coma cluster of galaxies

    Science.gov (United States)

    1999-01-01

    Atlas Image mosaic, covering 34' x 34' on the sky, of the Coma cluster, aka Abell 1656. This is a particularly rich cluster of individual galaxies (over 1000 members), most prominently the two giant ellipticals, NGC 4874 (right) and NGC 4889 (left). The remaining members are mostly smaller ellipticals, but spiral galaxies are also evident in the 2MASS image. The cluster is seen toward the constellation Coma Berenices, but is actually at a distance of about 100 Mpc (330 million light years, or a redshift of 0.023) from us. At this distance, the cluster is in what is known as the 'Hubble flow,' or the overall expansion of the Universe. As such, astronomers can measure the Hubble Constant, or the universal expansion rate, based on the distance to this cluster. Large, rich clusters, such as Coma, allow astronomers to measure the 'missing mass,' i.e., the matter in the cluster that we cannot see, since it gravitationally influences the motions of the member galaxies within the cluster. The near-infrared maps the overall luminous mass content of the member galaxies, since the light at these wavelengths is dominated by the more numerous older stellar populations. Galaxies, as seen by 2MASS, look fairly smooth and homogeneous, as can be seen from the Hubble 'tuning fork' diagram of near-infrared galaxy morphology. Image mosaic by S. Van Dyk (IPAC).

  4. Cluster growth kinetics

    International Nuclear Information System (INIS)

    Dubovik, V.M.; Gal'perin, A.G.; Rikhvitskij, V.S.; Lushnikov, A.A.

    2000-01-01

    Processes of some traffic blocking coming into existence are considered as probabilistic ones. We study analytic solutions for models for the dynamics of both cluster growth and cluster growth with fragmentation in the systems of finite number of objects. Assuming rates constancy of both coalescence and fragmentation, the models under consideration are linear on the probability functions

  5. Alpha clustering in nuclei

    International Nuclear Information System (INIS)

    Hodgson, P.E.

    1990-01-01

    The effects of nucleon clustering in nuclei are described, with reference to both nuclear structure and nuclear reactions, and the advantages of using the cluster formalism to describe a range of phenomena are discussed. It is shown that bound and scattering alpha-particle states can be described in a unified way using an energy-dependent alpha-nucleus potential. (author)

  6. Cluster decay of 218U isotope

    International Nuclear Information System (INIS)

    Shivakumaraswamy, G.; Umesh, T.K.

    2012-01-01

    The phenomenon of spontaneous emission of charged particles heavier than alpha particle and lighter than a fission fragment from radioactive nuclei without accompanied by the emission of neutrons is known as cluster radioactivity or exotic radioactivity. The process of emission of charged particles heavier than alpha particle and lighter than a fission fragment is called exotic decay or cluster decay. The phenomenon of cluster radioactivity was first predicted theoretically by Sandulescu et al in 1980. Rose and Jones made first experimental observations of 14 C emission from 223 Ra in 1984. Several cluster decay modes in trans-lead region have been experimentally observed. The half-life values for different modes of cluster decay from different isotopes of uranium have been calculated using different theoretical models such as the analytical super asymmetric model (ASAFM), Preformed cluster model (PCM) and Coulomb and Proximity potential model (CPPM) etc. Recently some semi-empirical formulae, i.e, single line of universal curve (UNIV), Universal decay law (UDL) for both alpha and cluster radioactivity have also been proposed to explain cluster decay data. The alpha decay half-life of 218-219 U isotopes has been experimentally measured in 2007. The half-life values for different cluster decay modes of 218 U isotopes have been calculated PCM model. Recently in 2011, the half-life values have also been calculated for some cluster decay modes of 222-236 U isotopes using the effective liquid drop description with the varying mass asymmetry (VMAS) shape and effective inertial coefficient. In the light of this, in the present work we have studied the cluster radioactivity of 218 U isotope. The logarithmic half-lives for few cluster decay modes from 218 U isotope have been calculated by using three different approaches, i.e, UNIV proposed by Poenaru et al in 2011, UDL proposed by Qi et al in 2009 and the CPPM model proposed by Santhosh et al in 2002. The CPPM based

  7. Photoreactivating enzyme from Escherichia coli

    International Nuclear Information System (INIS)

    Snapka, R.M.; Fuselier, C.O.

    1977-01-01

    Escherichia coli photoreactivating enzyme (PRE) has been purified in large amounts from an E.coli strain lysogenic for a defective lambda bacteriophage carrying the phr gene. The resulting enzyme had a pH optimum of 7.2 and an ionic strength optimum of 0.18. It consisted of an apoprotein and cofactor, both of which were necessary for catalytic activity. The apoprotein had a monomer molecular weight of 35,200 and showed stable aggregates under denaturing conditions. The amino acid analysis of the E.coli enzyme was very similar to that of the photoreactivating enzyme from orchid seedlings (Cattelya aurantiaca). Both had arginine at the amino terminus. The cofactor, like the holoenzyme, showed absorption, magnetic circular dichroism, and emission properties indicative of an adenine moiety. Although the isolated enzyme had an action spectrum which peaked at about 360 nm, neither the cofactor, apoenzyme nor holoenzyme showed any detectable absorption between 300 and 400 nm. (author)

  8. Positron emitter labeled enzyme inhibitors

    International Nuclear Information System (INIS)

    Fowler, J.S.; MacGregor, R.R.; Wolf, A.P.; Langstrom, B.

    1990-01-01

    This invention involves a new strategy for imagining and mapping enzyme activity in the living human and animal body using positron emitter-labeled suicide enzyme inactivators or inhibitors which become covalently bound to the enzyme as a result of enzymatic catalysis. Two such suicide inactivators for monoamine oxidase have been labeled with carbon-11 and used to map the enzyme subtypes in the living human and animal body using PET. By using positron emission tomography to image the distribution of radioactivity produced by the body penetrating radiation emitted by carbon-11, a map of functionally active monoamine oxidase activity is obtained. Clorgyline and L-deprenyl are suicide enzyme inhibitors and irreversibly inhibit monoamine oxidase. When these inhibitors are labeled with carbon-11 they provide selective probes for monoamine oxidase localization and reactivity in vivo using positron emission tomography

  9. Photoreactivating enzyme from Escherichia coli

    Energy Technology Data Exchange (ETDEWEB)

    Snapka, R M; Fuselier, C O [California Univ., Irvine (USA)

    1977-05-01

    Escherichia coli photoreactivating enzyme (PRE) has been purified in large amounts from an E.coli strain lysogenic for a defective lambda bacteriophage carrying the phr gene. The resulting enzyme had a pH optimum of 7.2 and an ionic strength optimum of 0.18. It consisted of an apoprotein and cofactor, both of which were necessary for catalytic activity. The apoprotein had a monomer molecular weight of 35,200 and showed stable aggregates under denaturing conditions. The amino acid analysis of the E.coli enzyme was very similar to that of the photoreactivating enzyme from orchid seedlings (Cattelya aurantiaca). Both had arginine at the amino terminus. The cofactor, like the holoenzyme, showed absorption, magnetic circular dichroism, and emission properties indicative of an adenine moiety. Although the isolated enzyme had an action spectrum which peaked at about 360 nm, neither the cofactor, apoenzyme nor holoenzyme showed any detectable absorption between 300 and 400 nm.

  10. Warming rays in cluster cool cores

    Science.gov (United States)

    Colafrancesco, S.; Marchegiani, P.

    2008-06-01

    Context: Cosmic rays are confined in the atmospheres of galaxy clusters and, therefore, they can play a crucial role in the heating of their cool cores. Aims: We discuss here the thermal and non-thermal features of a model of cosmic ray heating of cluster cores that can provide a solution to the cooling-flow problems. To this aim, we generalize a model originally proposed by Colafrancesco, Dar & DeRujula (2004) and we show that our model predicts specific correlations between the thermal and non-thermal properties of galaxy clusters and enables various observational tests. Methods: The model reproduces the observed temperature distribution in clusters by using an energy balance condition in which the X-ray energy emitted by clusters is supplied, in a quasi-steady state, by the hadronic cosmic rays, which act as “warming rays” (WRs). The temperature profile of the intracluster (IC) gas is strictly correlated with the pressure distribution of the WRs and, consequently, with the non-thermal emission (radio, hard X-ray and gamma-ray) induced by the interaction of the WRs with the IC gas and the IC magnetic field. Results: The temperature distribution of the IC gas in both cool-core and non cool-core clusters is successfully predicted from the measured IC plasma density distribution. Under this contraint, the WR model is also able to reproduce the thermal and non-thermal pressure distribution in clusters, as well as their radial entropy distribution, as shown by the analysis of three clusters studied in detail: Perseus, A2199 and Hydra. The WR model provides other observable features of galaxy clusters: a correlation of the pressure ratio (WRs to thermal IC gas) with the inner cluster temperature (P_WR/P_th) ˜ (kT_inner)-2/3, a correlation of the gamma-ray luminosity with the inner cluster temperature Lγ ˜ (kT_inner)4/3, a substantial number of cool-core clusters observable with the GLAST-LAT experiment, a surface brightness of radio halos in cool-core clusters

  11. Negotiating Cluster Boundaries

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    2017-01-01

    Palm oil was introduced to Malay(si)a as an alternative to natural rubber, inheriting its cluster organizational structure. In the late 1960s, Malaysia became the world’s largest palm oil exporter. Based on archival material from British colonial institutions and agency houses, this paper focuses...... on the governance dynamics that drove institutional change within this cluster during decolonization. The analysis presents three main findings: (i) cluster boundaries are defined by continuous tug-of-war style negotiations between public and private actors; (ii) this interaction produces institutional change...... within the cluster, in the form of cumulative ‘institutional rounds’ – the correction or disruption of existing institutions or the creation of new ones; and (iii) this process leads to a broader inclusion of local actors in the original cluster configuration. The paper challenges the prevalent argument...

  12. Mathematical classification and clustering

    CERN Document Server

    Mirkin, Boris

    1996-01-01

    I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina­ torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de­ velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par­ titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in­ novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in ...

  13. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  14. Orbital magnetism and dynamics in alkali metal clusters

    International Nuclear Information System (INIS)

    Nesterenko, V.O.; Kleinig, W.; Souza Cruz, FF. de; Marinelli, J.R.

    2000-01-01

    Two remarkable orbital magnetic resonances, M1 scissor mode and M2 twist mode, are predicted in deformed and spherical metal clusters, respectively. We show that these resonances provide a valuable information about many cluster properties (quadrupole deformation, magnetic susceptibility, single-particle spectrum, etc.)

  15. Search for C+ C clustering in Mg ground state

    Indian Academy of Sciences (India)

    2017-01-04

    Jan 4, 2017 ... Finite-range knockout theory predictions were much larger for (12C,212C) reaction, indicating a very small 12C−12C clustering in 24Mg. (g.s.) . Our present results contradict most of the proposed heavy cluster (12C+12C) structure models for the ground state of 24Mg. Keywords. Direct nuclear reactions ...

  16. The Connection between Radio Halos and Cluster Mergers and the ...

    Indian Academy of Sciences (India)

    (2008) suggested that the behavior of clusters in the. P1.4 − LX diagram is connected with their dynamical state. 2.2 The dynamical state of GMRT clusters ..... (e.g., Cassano et al. 2008) and were used to derive expectations for the planned. LOFAR surveys. Accordingly to these predictions the Tier 1 'Large Area Survey' at.

  17. Participant intimacy: A cluster analysis of the intranuclear cascade

    International Nuclear Information System (INIS)

    Cugnon, J.; Knoll, J.; Randrup, J.

    1981-01-01

    The intranuclear cascade for relativistic nuclear collisions is analyzed in terms of clusters consisting of groups of nucleons which are dynamically linked to each other by violent interactions. The formation cross sections for the different cluster types as well as their intrinsic dynamics are studied and compared with the predictions of the linear cascade model ( rows-on-rows ). (orig.)

  18. Gravitational clustering of galaxies in the CfA slice

    International Nuclear Information System (INIS)

    Crane, P.; Saslaw, W.C.

    1988-01-01

    The clustering properties of the Galaxies in the CfA slice have been analyzed by comparing the properties of the neighbor distributions to the predictions of gravitational clustering theory. The agreement is excellent and implies that the observed structures can be explained by gravitational effects alone and do not require exotic explanations

  19. 2008 GRC Iron Sulfur Enzymes-Conference to be held June 8-13, 2008

    Energy Technology Data Exchange (ETDEWEB)

    Cramer, Stephen [Univ. of California, Davis, CA (United States); Gray, Nancy Ryan [Gordon Research Conferences, West Kingston, RI (United States)

    2009-01-01

    Iron-sulfur proteins are among the most common and ancient enzymes and electron-transfer agents in nature. They play key roles in photosynthesis, respiration, and the metabolism of small molecules such as H2, CO, and N2. The Iron Sulfur Enzyme Gordon Research Conference evolved from an earlier GRC on Nitrogen Fixation that began in 1994. The scope of the current meeting has broadened to include all enzymes or metalloproteins in which Fe-S bonds play a key role. This year's meeting will focus on the biosynthesis of Fe-S clusters, as well as the structure and mechanism of key Fe-S enzymes such as hydrogenase, nitrogenase and its homologues, radical SAM enzymes, and aconitase-related enzymes. Recent progress on the role of Fe-S enzymes in health, disease, DNA/RNA-processing, and alternative bio-energy systems will also be highlighted. This conference will assemble a broad, diverse, and international group of biologists and chemists who are investigating fundamental issues related to Fe-S enzymes, on atomic, molecular, organism, and environmental scales. The topics to be addressed will include: Biosynthesis & Genomics of Fe-S Enzymes; Fundamental Fe-S Chemistry; Hydrogen and Fe-S Enzymes; Nitrogenase & Homologous Fe-S Enzymes; Fe-S Enzymes in Health & Disease; Radical SAM and Aconitase-Related Fe-S Enzymes; Fe-S Enzymes and Synthetic Analogues in BioEnergy; and Fe-S Enzymes in Geochemistry and the Origin of Life.

  20. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun; Peng, Chengbin; Li, Yue; Chan, Takming

    2014-01-01

    , this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances

  1. Evolution of Chemical Diversity in a Group of Non-Reduced Polyketide Gene Clusters: Using Phylogenetics to Inform the Search for Novel Fungal Natural Products

    Directory of Open Access Journals (Sweden)

    Kurt Throckmorton

    2015-09-01

    Full Text Available Fungal polyketides are a diverse class of natural products, or secondary metabolites (SMs, with a wide range of bioactivities often associated with toxicity. Here, we focus on a group of non-reducing polyketide synthases (NR-PKSs in the fungal phylum Ascomycota that lack a thioesterase domain for product release, group V. Although widespread in ascomycete taxa, this group of NR-PKSs is notably absent in the mycotoxigenic genus Fusarium and, surprisingly, found in genera not known for their secondary metabolite production (e.g., the mycorrhizal genus Oidiodendron, the powdery mildew genus Blumeria, and the causative agent of white-nose syndrome in bats, Pseudogymnoascus destructans. This group of NR-PKSs, in association with the other enzymes encoded by their gene clusters, produces a variety of different chemical classes including naphthacenediones, anthraquinones, benzophenones, grisandienes, and diphenyl ethers. We discuss the modification of and transitions between these chemical classes, the requisite enzymes, and the evolution of the SM gene clusters that encode them. Integrating this information, we predict the likely products of related but uncharacterized SM clusters, and we speculate upon the utility of these classes of SMs as virulence factors or chemical defenses to various plant, animal, and insect pathogens, as well as mutualistic fungi.

  2. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  3. BAKERY ENZYMES IN CEREAL TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    Václav Koman

    2012-10-01

    Full Text Available Normal 0 21 false false false SK X-NONE X-NONE Bread is the most common and traditional food in the world. For years, enzymes such as malt and fungal alpha-amylase have been used in bread making. Due to the changes in the baking industry and the ever-increasing demand for more natural products, enzymes have gained real importance in bread-making. If an enzyme is added, it is often destroyed by the heat during the baking process. For generations, enzymes have been used for the improvement of texture and appearance, enhancement of nutritional values and generation of appealing flavours and aromas. Enzymes used in bakery industry constitute nearly one third of the market. The bakery products have undergone radical improvements in quality over the past years in terms of flavour, texture and shelf-life. The the biggest contributor for these improvementsis the usage of enzymes. Present work seeks to systematically describe bakery enzymes, their classification, benefits, usage and chemical reactions in the bread making process.doi:10.5219/193

  4. Cluster-cluster correlations and constraints on the correlation hierarchy

    Science.gov (United States)

    Hamilton, A. J. S.; Gott, J. R., III

    1988-01-01

    The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

  5. Formation of stable products from cluster-cluster collisions

    International Nuclear Information System (INIS)

    Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

    2007-01-01

    The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

  6. Tune Your Brown Clustering, Please

    DEFF Research Database (Denmark)

    Derczynski, Leon; Chester, Sean; Bøgh, Kenneth Sejdenfaden

    2015-01-01

    Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly...

  7. [Automated analyzer of enzyme immunoassay].

    Science.gov (United States)

    Osawa, S

    1995-09-01

    Automated analyzers for enzyme immunoassay can be classified by several points of view: the kind of labeled antibodies or enzymes, detection methods, the number of tests per unit time, analytical time and speed per run. In practice, it is important for us consider the several points such as detection limits, the number of tests per unit time, analytical range, and precision. Most of the automated analyzers on the market can randomly access and measure samples. I will describe the recent advance of automated analyzers reviewing their labeling antibodies and enzymes, the detection methods, the number of test per unit time and analytical time and speed per test.

  8. Cluster Management Institutionalization

    DEFF Research Database (Denmark)

    Normann, Leo; Agger Nielsen, Jeppe

    2015-01-01

    of how it was legitimized as a “ready-to-use” management model. Further, our account reveals how cluster management translated into considerably different local variants as it travelled into specific organizations. However, these processes have not occurred sequentially with cluster management first...... legitimized at the field level, then spread, and finally translated into action in the adopting organizations. Instead, we observed entangled field and organizational-level processes. Accordingly, we argue that cluster management institutionalization is most readily understood by simultaneously investigating...

  9. The concept of cluster

    DEFF Research Database (Denmark)

    Laursen, Lea Louise Holst; Møller, Jørgen

    2013-01-01

    villages in order to secure their future. This paper will address the concept of cluster-villages as a possible approach to strengthen the conditions of contemporary Danish villages. Cluster-villages is a concept that gather a number of villages in a network-structure where the villages both work together...... to forskellige positioner ser vi en ny mulighed for landsbyudvikling, som vi kalder Clustervillages. In order to investigate the potentials and possibilities of the cluster-village concept the paper will seek to unfold the concept strategically; looking into the benefits of such concept. Further, the paper seeks...

  10. Raspberry Pi super cluster

    CERN Document Server

    Dennis, Andrew K

    2013-01-01

    This book follows a step-by-step, tutorial-based approach which will teach you how to develop your own super cluster using Raspberry Pi computers quickly and efficiently.Raspberry Pi Super Cluster is an introductory guide for those interested in experimenting with parallel computing at home. Aimed at Raspberry Pi enthusiasts, this book is a primer for getting your first cluster up and running.Basic knowledge of C or Java would be helpful but no prior knowledge of parallel computing is necessary.

  11. Introduction to cluster dynamics

    CERN Document Server

    Reinhard, Paul-Gerhard

    2008-01-01

    Clusters as mesoscopic particles represent an intermediate state of matter between single atoms and solid material. The tendency to miniaturise technical objects requires knowledge about systems which contain a ""small"" number of atoms or molecules only. This is all the more true for dynamical aspects, particularly in relation to the qick development of laser technology and femtosecond spectroscopy. Here, for the first time is a highly qualitative introduction to cluster physics. With its emphasis on cluster dynamics, this will be vital to everyone involved in this interdisciplinary subje

  12. Contextualizing the Cluster

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    This dissertation examines the case of the palm oil cluster in Malaysia and Indonesia, today one of the largest agricultural clusters in the world. My analysis focuses on the evolution of the cluster from the 1880s to the 1970s in order to understand how it helped these two countries to integrate...... into the global economy in both colonial and post-colonial times. The study is based on empirical material drawn from five UK archives and background research using secondary sources, interviews, and archive visits to Malaysia and Singapore. The dissertation comprises three articles, each discussing a major under...

  13. Atomic cluster collisions

    Science.gov (United States)

    Korol, Andrey V.; Solov'yov, Andrey

    2013-01-01

    Atomic cluster collisions are a field of rapidly emerging research interest by both experimentalists and theorists. The international symposium on atomic cluster collisions (ISSAC) is the premier forum to present cutting-edge research in this field. It was established in 2003 and the most recent conference was held in Berlin, Germany in July of 2011. This Topical Issue presents original research results from some of the participants, who attended this conference. This issues specifically focuses on two research areas, namely Clusters and Fullerenes in External Fields and Nanoscale Insights in Radiation Biodamage.

  14. Halophiles and their enzymes: negativity put to good use.

    Science.gov (United States)

    DasSarma, Shiladitya; DasSarma, Priya

    2015-06-01

    Halophilic microorganisms possess stable enzymes that function in very high salinity, an extreme condition that leads to denaturation, aggregation, and precipitation of most other proteins. Genomic and structural analyses have established that the enzymes of halophilic Archaea and many halophilic Bacteria are negatively charged due to an excess of acidic over basic residues, and altered hydrophobicity, which enhance solubility and promote function in low water activity conditions. Here, we provide an update on recent bioinformatic analysis of predicted halophilic proteomes as well as experimental molecular studies on individual halophilic enzymes. Recent efforts on discovery and utilization of halophiles and their enzymes for biotechnology, including biofuel applications are also considered. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. An indigoidine biosynthetic gene cluster from Streptomyces chromofuscus ATCC 49982 contains an unusual IndB homologue.

    Science.gov (United States)

    Yu, Dayu; Xu, Fuchao; Valiente, Jonathan; Wang, Siyuan; Zhan, Jixun

    2013-01-01

    A putative indigoidine biosynthetic gene cluster was located in the genome of Streptomyces chromofuscus ATCC 49982. The silent 9.4-kb gene cluster consists of five open reading frames, named orf1, Sc-indC, Sc-indA, Sc-indB, and orf2, respectively. Sc-IndC was functionally characterized as an indigoidine synthase through heterologous expression of the enzyme in both Streptomyces coelicolor CH999 and Escherichia coli BAP1. The yield of indigoidine in E. coli BAP1 reached 2.78 g/l under the optimized conditions. The predicted protein product of Sc-indB is unusual and much larger than any other reported IndB-like protein. The N-terminal portion of this enzyme resembles IdgB and the C-terminal portion is a hypothetical protein. Sc-IndA and/or Sc-IndB were co-expressed with Sc-IndC in E. coli BAP1, which demonstrated the involvement of Sc-IndB, but not Sc-IndA, in the biosynthetic pathway of indigoidine. The yield of indigoidine was dramatically increased by 41.4 % (3.93 g/l) when Sc-IndB was co-expressed with Sc-IndC in E. coli BAP1. Indigoidine is more stable at low temperatures.

  16. 2D Dust Clusters in Theory and Experiments

    International Nuclear Information System (INIS)

    Tsytovich, V.N.; Gousein-zade, N.G.; Morfill, G.E.

    2005-01-01

    The theory is applied for more detail analysis of existing experiments of 2D dust clusters with parabolic confinement. It is shown that the equilibrium condition and the frequency of one of the modes of the cluster determines all dimensionless parameters of the cluster allowing to predict the value of other modes and compare them with existing experimental data. This comparison depends on the shielding model, the calculations starting with N = 4 cluster breathing mode predict for Debye shielding model without attraction the frequency of the antisymmetric mode in disagreement with the observed value about 6 standard deviations, while the same calculations for the non-linear screening model gives disagreement about 1 standard deviation. Including the attraction provides an agrement with observations only for non-linear screening model showing the sensitivity of cluster structure to dust attraction. The value of the obtained attractions coefficient is in reasonable agreement with the theoretically expected value. It is shown theoretically that in absence of external parabolic confinement a weak shadow attraction can provide an existence of equilibria for 2D clusters. The equilibrium radius is rapidly decreasing with an increase of the attraction coefficient and with number of grains N in a cluster. The energies of one shell clusters with different N and the energies of N - 1 grain clusters with additional grain in the center of the shell are calculated as functions of attraction coefficient. It is demonstrated that a dissociation of cluster in several smaller clusters needs less energy than a removal of one grain from the cluster. The calculations were performed for Yukawa screening and for non-linear screening and demonstrate the sensitivity of cluster structures to the screening. Frequencies of all modes are calculated up to N = 7 for one shell structure. Stable and unstable modes as well as universal magic numbers are found

  17. Two Gene Clusters Coordinate Galactose and Lactose Metabolism in Streptococcus gordonii

    Science.gov (United States)

    Zeng, Lin; Martino, Nicole C.

    2012-01-01

    Streptococcus gordonii is an early colonizer of the human oral cavity and an abundant constituent of oral biofilms. Two tandemly arranged gene clusters, designated lac and gal, were identified in the S. gordonii DL1 genome, which encode genes of the tagatose pathway (lacABCD) and sugar phosphotransferase system (PTS) enzyme II permeases. Genes encoding a predicted phospho-β-galactosidase (LacG), a DeoR family transcriptional regulator (LacR), and a transcriptional antiterminator (LacT) were also present in the clusters. Growth and PTS assays supported that the permease designated EIILac transports lactose and galactose, whereas EIIGal transports galactose. The expression of the gene for EIIGal was markedly upregulated in cells growing on galactose. Using promoter-cat fusions, a role for LacR in the regulation of the expressions of both gene clusters was demonstrated, and the gal cluster was also shown to be sensitive to repression by CcpA. The deletion of lacT caused an inability to grow on lactose, apparently because of its role in the regulation of the expression of the genes for EIILac, but had little effect on galactose utilization. S. gordonii maintained a selective advantage over Streptococcus mutans in a mixed-species competition assay, associated with its possession of a high-affinity galactose PTS, although S. mutans could persist better at low pHs. Collectively, these results support the concept that the galactose and lactose systems of S. gordonii are subject to complex regulation and that a high-affinity galactose PTS may be advantageous when S. gordonii is competing against the caries pathogen S. mutans in oral biofilms. PMID:22660715

  18. A theoretical study of cluster radioactivity in platinum isotopes

    Energy Technology Data Exchange (ETDEWEB)

    Joseph, Deepthy Maria; Ashok, Nithu; Joseph, Antony [University of Calicut, Department of Physics, Malappuram, Kerala (India)

    2018-01-15

    The probable cluster decay modes in platinum isotopes are predicted with the help of effective liquid drop model. The calculated half-lives are compared with those of universal decay law model and with the experimental data. The investigation affirms the decisive role of neutron magicity in the phenomenon of cluster radioactivity. It is found that the probability of cluster emission decreases with the increase in the neutron number of parent nucleus. Geiger-Nuttall plots of the probable decay modes show linear behaviour, which in turn leads to the equation for logarithmic half-life for the clusters emitted from Pt isotopes. (orig.)

  19. Time-resolved explosion of intense-laser-heated clusters.

    Science.gov (United States)

    Kim, K Y; Alexeev, I; Parra, E; Milchberg, H M

    2003-01-17

    We investigate the femtosecond explosive dynamics of intense laser-heated argon clusters by measuring the cluster complex transient polarizability. The time evolution of the polarizability is characteristic of competition in the optical response between supercritical and subcritical density regions of the expanding cluster. The results are consistent with time-resolved Rayleigh scattering measurements, and bear out the predictions of a recent laser-cluster interaction model [H. M. Milchberg, S. J. McNaught, and E. Parra, Phys. Rev. E 64, 056402 (2001)

  20. Time-resolved explosion of intense-laser-heated clusters

    International Nuclear Information System (INIS)

    Kim, K.Y.; Alexeev, I.; Parra, E.; Milchberg, H.M.

    2003-01-01

    We investigate the femtosecond explosive dynamics of intense laser-heated argon clusters by measuring the cluster complex transient polarizability. The time evolution of the polarizability is characteristic of competition in the optical response between supercritical and subcritical density regions of the expanding cluster. The results are consistent with time-resolved Rayleigh scattering measurements, and bear out the predictions of a recent laser-cluster interaction model [H. M. Milchberg, S. J. McNaught, and E. Parra, Phys. Rev. E 64, 056402 (2001)

  1. Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

    International Nuclear Information System (INIS)

    Walther, B.

    1988-01-01

    This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

  2. Intergalactic stellar populations in intermediate redshift clusters

    Science.gov (United States)

    Melnick, J.; Giraud, E.; Toledo, I.; Selman, F.; Quintana, H.

    2012-11-01

    A substantial fraction of the total stellar mass in rich clusters of galaxies resides in a diffuse intergalactic component usually referred to as the intracluster light (ICL). Theoretical models indicate that these intergalactic stars originate mostly from the tidal interaction of the cluster galaxies during the assembly history of the cluster, and that a significant fraction of these stars could have formed in situ from the late infall of cold metal-poor gas clouds on to the cluster. However, these models also overpredict the fraction of stellar mass in the ICL by a substantial margin, something that is still not well understood. The models also make predictions about the age distribution of the ICL stars, which may provide additional observational constraints. Here we present population synthesis models for the ICL of an intermediate redshift (z = 0.29) X-ray cluster that we have extensively studied in previous papers. The advantage of observing intermediate redshift clusters rather than nearby ones is that the former fit the field of view of multi-object spectrographs in 8-m telescopes and therefore permit us to encompass most of the ICL with only a few well-placed slits. In this paper we show that by stacking spectra at different locations within the ICL it is possible to reach sufficiently high signal-to-noise ratios to fit population synthesis models and derive meaningful results. The models provide ages and metallicities for the dominant populations at several different locations within the ICL and the brightest cluster galaxies (BCG) halo, as well as measures of the kinematics of the stars as a function of distance from the BCG. We thus find that the ICL in our cluster is dominated by old metal-rich stars, at odds with what has been found in nearby clusters where the stars that dominate the ICL are old and metal poor. While we see weak evidence of a young, metal-poor component, if real, these young stars would amount to less than 1 per cent of the total ICL

  3. Multi-enzyme Process Modeling

    DEFF Research Database (Denmark)

    Andrade Santacoloma, Paloma de Gracia

    are affected (in a positive or negative way) by the presence of the other enzymes and compounds in the media. In this thesis the concept of multi-enzyme in-pot term is adopted for processes that are carried out by the combination of enzymes in a single reactor and implemented at pilot or industrial scale...... features of the process and provides the information required to structure the process model by using a step-by-step procedure with the required tools and methods. In this way, this framework increases efficiency of the model development process with respect to time and resources needed (fast and effective....... In this way the model parameters that drives the main dynamic behavior can be identified and thus a better understanding of this type of processes. In order to develop, test and verify the methodology, three case studies were selected, specifically the bi-enzyme process for the production of lactobionic acid...

  4. PIXE analysis of Zn enzymes

    International Nuclear Information System (INIS)

    Solis, C.; Oliver, A.; Andrade, E.; Ruvalcaba-Sil, J.L.; Romero, I.; Celis, H.

    1999-01-01

    Zinc is a necessary component in the action and structural stability of many enzymes. Some of them are well characterized, but in others, Zn stoichiometry and its association is not known. PIXE has been proven to be a suitable technique for analyzing metallic proteins embedded in electrophoresis gels. In this study, PIXE has been used to investigate the Zn content of enzymes that are known to carry Zn atoms. These include the carbonic anhydrase, an enzyme well characterized by other methods and the cytoplasmic pyrophosphatase of Rhodospirillum rubrum that is known to require Zn to be stable but not how many metal ions are involved or how they are bound to the enzyme. Native proteins have been purified by polyacrylamide gel electrophoresis and direct identification and quantification of Zn in the gel bands was performed with an external proton beam of 3.7 MeV energy

  5. GRE Enzymes for Vector Analysis

    Data.gov (United States)

    U.S. Environmental Protection Agency — Microbial enzyme data that were collected during the 2004-2006 EMAP-GRE program. These data were then used by Moorhead et al (2016) in their ecoenzyme vector...

  6. Watching Individual Enzymes at Work

    Science.gov (United States)

    Blank, Kerstin; Rocha, Susana; De Cremer, Gert; Roeffaers, Maarten B. J.; Uji-i, Hiroshi; Hofkens, Johan

    Single-molecule fluorescence experiments are a powerful tool to analyze reaction mechanisms of enzymes. Because of their unique potential to detect heterogeneities in space and time, they have provided unprecedented insights into the nature and mechanisms of conformational changes related to the catalytic reaction. The most important finding from experiments with single enzymes is the generally observed phenomenon that the catalytic rate constants fluctuate over time (dynamic disorder). These fluctuations originate from conformational changes occurring on time scales, which are similar to or slower than that of the catalytic reaction. Here, we summarize experiments with enzymes that show dynamic disorder and introduce new experimental strategies showing how single-molecule fluorescence experiments can be applied to address other open questions in medical and industrial enzymology, such as enzyme inactivation processes, reactant transfer in cascade reactions, and the mechanisms of interfacial catalysis.

  7. Photosynthetic fuel for heterologous enzymes

    DEFF Research Database (Denmark)

    Mellor, Silas Busck; Vavitsas, Konstantinos; Nielsen, Agnieszka Janina Zygadlo

    2017-01-01

    of reducing power. Recent work on the metabolic engineering of photosynthetic organisms has shown that the electron carriers such as ferredoxin and flavodoxin can be used to couple heterologous enzymes to photosynthetic reducing power. Because these proteins have a plethora of interaction partners and rely...... on electrostatically steered complex formation, they form productive electron transfer complexes with non-native enzymes. A handful of examples demonstrate channeling of photosynthetic electrons to drive the activity of heterologous enzymes, and these focus mainly on hydrogenases and cytochrome P450s. However......, competition from native pathways and inefficient electron transfer rates present major obstacles, which limit the productivity of heterologous reactions coupled to photosynthesis. We discuss specific approaches to address these bottlenecks and ensure high productivity of such enzymes in a photosynthetic...

  8. Disentangling Porterian Clusters

    DEFF Research Database (Denmark)

    Jagtfelt, Tue

    , contested theory become so widely disseminated and applied as a normative and prescriptive strategy for economic development? The dissertation traces the introduction of the cluster notion into the EU’s Lisbon Strategy and demonstrates how its inclusion originates from Porter’s colleagues: Professor Örjan...... to his membership on the Commission on Industrial Competitiveness, and that the cluster notion found in his influential book, Nations, represents a significant shift in his conception of cluster compared with his early conceptions. This shift, it is argued, is a deliberate attempt by Porter to create...... a paradigmatic textbook that follows Kuhn’s blueprint for scientific revolutions by instilling Nations with circular references and thus creating a local linguistic holism conceptualized through an encompassing notion of cluster. The dissertation concludes that the two research questions are philosophically...

  9. Remarks on stellar clusters

    International Nuclear Information System (INIS)

    Teller, E.

    1985-01-01

    In the following, a few simple remarks on the evolution and properties of stellar clusters will be collected. In particular, globular clusters will be considered. Though details of such clusters are often not known, a few questions can be clarified with the help of primitive arguments. These are:- why are spherical clusters spherical, why do they have high densities, why do they consist of approximately a million stars, how may a black hole of great mass form within them, may they be the origin of gamma-ray bursts, may their invisible remnants account for the missing mass of our galaxy. The available data do not warrant a detailed evaluation. However, it is remarkable that exceedingly simple models can shed some light on the questions enumerated above. (author)

  10. From collisions to clusters

    DEFF Research Database (Denmark)

    Loukonen, Ville; Bork, Nicolai; Vehkamaki, Hanna

    2014-01-01

    -principles molecular dynamics collision simulations of (sulphuric acid)1(water)0, 1 + (dimethylamine) → (sulphuric acid)1(dimethylamine)1(water)0, 1 cluster formation processes. The simulations indicate that the sticking factor in the collisions is unity: the interaction between the molecules is strong enough...... control. As a consequence, the clusters show very dynamic ion pair structure, which differs from both the static structure optimisation calculations and the equilibrium first-principles molecular dynamics simulations. In some of the simulation runs, water mediates the proton transfer by acting as a proton...... to overcome the possible initial non-optimal collision orientations. No post-collisional cluster break up is observed. The reasons for the efficient clustering are (i) the proton transfer reaction which takes place in each of the collision simulations and (ii) the subsequent competition over the proton...

  11. How Clusters Work

    Science.gov (United States)

    Technology innovation clusters are geographic concentrations of interconnected companies, universities, and other organizations with a focus on environmental technology. They play a key role in addressing the nation’s pressing environmental problems.

  12. Evolution of clustered storage

    CERN Multimedia

    CERN. Geneva; Van de Vyvre, Pierre

    2007-01-01

    The session actually featured two presentations: * Evolution of clustered storage by Lance Hukill, Quantum Corporation * ALICE DAQ - Usage of a Cluster-File System: Quantum StorNext by Pierre Vande Vyvre, CERN-PH the second one prepared at short notice by Pierre (thanks!) to present how the Quantum technologies are being used in the ALICE experiment. The abstract to Mr Hukill's follows. Clustered Storage is a technology that is driven by business and mission applications. The evolution of Clustered Storage solutions starts first at the alignment between End-users needs and Industry trends: * Push-and-Pull between managing for today versus planning for tomorrow * Breaking down the real business problems to the core applications * Commoditization of clients, servers, and target devices * Interchangeability, Interoperability, Remote Access, Centralized control * Oh, and yes, there is a budget and the "real world" to deal with This presentation will talk through these needs and trends, and then ask the question, ...

  13. Galaxy clusters and cosmology

    CERN Document Server

    White, S

    1994-01-01

    Galaxy clusters are the largest coherent objects in Universe. It has been known since 1933 that their dynamical properties require either a modification of the theory of gravity, or the presence of a dominant component of unseen material of unknown nature. Clusters still provide the best laboratories for studying the amount and distribution of this dark matter relative to the material which can be observed directly -- the galaxies themselves and the hot,X-ray-emitting gas which lies between them.Imaging and spectroscopy of clusters by satellite-borne X -ray telescopes has greatly improved our knowledge of the structure and composition of this intergalactic medium. The results permit a number of new approaches to some fundamental cosmological questions,but current indications from the data are contradictory. The observed irregularity of real clusters seems to imply recent formation epochs which would require a universe with approximately the critical density. On the other hand, the large baryon fraction observ...

  14. Applications of Clustering

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Applications of Clustering. Biology – medical imaging, bioinformatics, ecology, phylogenies problems etc. Market research. Data Mining. Social Networks. Any problem measuring similarity/correlation. (dimensions represent different parameters)

  15. Clustering Game Behavior Data

    DEFF Research Database (Denmark)

    Bauckhage, C.; Drachen, Anders; Sifa, Rafet

    2015-01-01

    of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...... scientists and present a review and tutorial focusing on the application of clustering techniques to mine behavioral game data. Several algorithms are reviewed and examples of their application shown. Key topics such as feature normalization are discussed and open problems in the context of game analytics...

  16. Clustering on Membranes

    DEFF Research Database (Denmark)

    Johannes, Ludger; Pezeshkian, Weria; Ipsen, John H

    2018-01-01

    Clustering of extracellular ligands and proteins on the plasma membrane is required to perform specific cellular functions, such as signaling and endocytosis. Attractive forces that originate in perturbations of the membrane's physical properties contribute to this clustering, in addition to direct...... protein-protein interactions. However, these membrane-mediated forces have not all been equally considered, despite their importance. In this review, we describe how line tension, lipid depletion, and membrane curvature contribute to membrane-mediated clustering. Additional attractive forces that arise...... from protein-induced perturbation of a membrane's fluctuations are also described. This review aims to provide a survey of the current understanding of membrane-mediated clustering and how this supports precise biological functions....

  17. Air void clustering.

    Science.gov (United States)

    2015-06-01

    Air void clustering around coarse aggregate in concrete has been identified as a potential source of : low strengths in concrete mixes by several Departments of Transportation around the country. Research was : carried out to (1) develop a quantitati...

  18. Subaru Weak Lensing Measurements of Four Strong Lensing Clusters: Are Lensing Clusters Over-Concentrated?

    Energy Technology Data Exchange (ETDEWEB)

    Oguri, Masamune; Hennawi, Joseph F.; Gladders, Michael D.; Dahle, Haakon; Natarajan, Priyamvada; Dalal, Neal; Koester, Benjamin P.; Sharon, Keren; Bayliss, Matthew

    2009-01-29

    We derive radial mass profiles of four strong lensing selected clusters which show prominent giant arcs (Abell 1703, SDSS J1446+3032, SDSS J1531+3414, and SDSS J2111-0115), by combining detailed strong lens modeling with weak lensing shear measured from deep Subaru Suprime-cam images. Weak lensing signals are detected at high significance for all four clusters, whose redshifts range from z = 0.28 to 0.64. We demonstrate that adding strong lensing information with known arc redshifts significantly improves constraints on the mass density profile, compared to those obtained from weak lensing alone. While the mass profiles are well fitted by the universal form predicted in N-body simulations of the {Lambda}-dominated cold dark matter model, all four clusters appear to be slightly more centrally concentrated (the concentration parameters c{sub vir} {approx} 8) than theoretical predictions, even after accounting for the bias toward higher concentrations inherent in lensing selected samples. Our results are consistent with previous studies which similarly detected a concentration excess, and increases the total number of clusters studied with the combined strong and weak lensing technique to ten. Combining our sample with previous work, we find that clusters with larger Einstein radii are more anomalously concentrated. We also present a detailed model of the lensing cluster Abell 1703 with constraints from multiple image families, and find the dark matter inner density profile to be cuspy with the slope consistent with -1, in agreement with expectations.

  19. DGAT enzymes and triacylglycerol biosynthesis

    OpenAIRE

    Yen, Chi-Liang Eric; Stone, Scot J.; Koliwad, Suneil; Harris, Charles; Farese, Robert V.

    2008-01-01

    Triacylglycerols (triglycerides) (TGs) are the major storage molecules of metabolic energy and FAs in most living organisms. Excessive accumulation of TGs, however, is associated with human diseases, such as obesity, diabetes mellitus, and steatohepatitis. The final and the only committed step in the biosynthesis of TGs is catalyzed by acyl-CoA:diacylglycerol acyltransferase (DGAT) enzymes. The genes encoding two DGAT enzymes, DGAT1 and DGAT2, were identified in the past decade, ...

  20. Enzymes: principles and biotechnological applications

    Science.gov (United States)

    Robinson, Peter K.

    2015-01-01

    Enzymes are biological catalysts (also known as biocatalysts) that speed up biochemical reactions in living organisms, and which can be extracted from cells and then used to catalyse a wide range of commercially important processes. This chapter covers the basic principles of enzymology, such as classification, structure, kinetics and inhibition, and also provides an overview of industrial applications. In addition, techniques for the purification of enzymes are discussed. PMID:26504249

  1. Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome.

    Science.gov (United States)

    Mallory, Emily K; Acharya, Ambika; Rensi, Stefano E; Turnbaugh, Peter J; Bright, Roselie A; Altman, Russ B

    2018-01-01

    Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.

  2. Empirical Flutter Prediction Method.

    Science.gov (United States)

    1988-03-05

    been used in this way to discover species or subspecies of animals, and to discover different types of voter or comsumer requiring different persuasions...respect to behavior or performance or response variables. Once this were done, corresponding clusters might be sought among descriptive or predictive or...jump in a response. The first sort of usage does not apply to the flutter prediction problem. Here the types of behavior are the different kinds of

  3. Speaker segmentation and clustering

    OpenAIRE

    Kotti, M; Moschou, V; Kotropoulos, C

    2008-01-01

    07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...

  4. Fermion cluster algorithms

    International Nuclear Information System (INIS)

    Chandrasekharan, Shailesh

    2000-01-01

    Cluster algorithms have been recently used to eliminate sign problems that plague Monte-Carlo methods in a variety of systems. In particular such algorithms can also be used to solve sign problems associated with the permutation of fermion world lines. This solution leads to the possibility of designing fermion cluster algorithms in certain cases. Using the example of free non-relativistic fermions we discuss the ideas underlying the algorithm

  5. BUILDING e-CLUSTERS

    OpenAIRE

    Milan Davidovic

    2013-01-01

    E-clusters are strategic alliance in TIMES technology sector (Telecommunication, Information technology, Multimedia, Entertainment, Security) where products and processes are digitalized. They enable horizontal and vertical integration of small and medium companies and establish new added value e-chains. E-clusters also build supply chains based on cooperation relationship, innovation, organizational knowledge and compliance of intellectual properties. As an innovative approach for economic p...

  6. Clusters and exotic processes

    International Nuclear Information System (INIS)

    Schiffer, J.P.

    1975-01-01

    An attempt is made to present some data which may be construed as indicating that perhaps clusters play a role in high energy and exotic pion or kaon interactions with complex (A much greater than 16) nuclei. Also an attempt is made to summarize some very recent experimental work on pion interactions with nuclei which may or may not in the end support a picture in which clusters play an important role. (U.S.)

  7. Study on distributed re-clustering algorithm for moblie wireless sensor networks

    Directory of Open Access Journals (Sweden)

    XU Chaojie

    2016-04-01

    Full Text Available In mobile wireless sensor networks,node mobility influences the topology of the hierarchically clustered network,thus affects packet delivery ratio and energy consumption of communications in clusters.To reduce the influence of node mobility,a distributed re-clustering algorithm is proposed in this paper.In this algorithm,basing on the clustered network,nodes estimate their current locations with particle algorithm and predict the most possible locations of next time basing on the mobility model.Each boundary node of a cluster periodically estimates the need for re-clustering and re-cluster itself to the optimal cluster through communicating with the cluster headers when needed.The simulation results indicate that,with small re-clustering periods,the proposed algorithm can be effective to keep appropriate communication distance and outperforms existing schemes on packet delivery ratio and energy consumption.

  8. Salmonella enterica pulsed-field gel electrophoresis clusters, Minnesota, USA, 2001-2007.

    Science.gov (United States)

    Rounds, Joshua M; Hedberg, Craig W; Meyer, Stephanie; Boxrud, David J; Smith, Kirk E

    2010-11-01

    We determined characteristics of Salmonella enterica pulsed-field gel electrophoresis clusters that predict their being solved (i.e., that result in identification of a confirmed outbreak). Clusters were investigated by the Minnesota Department of Health by using a dynamic iterative model. During 2001-2007, a total of 43 (12.5%) of 344 clusters were solved. Clusters of ≥4 isolates were more likely to be solved than clusters of 2 isolates. Clusters in which the first 3 case isolates were received at the Minnesota Department of Health within 7 days were more likely to be solved than were clusters in which the first 3 case isolates were received over a period >14 days. If resources do not permit investigation of all S. enterica pulsed-field gel electrophoresis clusters, investigation of clusters of ≥4 cases and clusters in which the first 3 case isolates were received at a public health laboratory within 7 days may improve outbreak investigations.

  9. Clustering and visualizing similarity networks of membrane proteins.

    Science.gov (United States)

    Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

    2015-08-01

    We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

  10. de novo computational enzyme design.

    Science.gov (United States)

    Zanghellini, Alexandre

    2014-10-01

    Recent advances in systems and synthetic biology as well as metabolic engineering are poised to transform industrial biotechnology by allowing us to design cell factories for the sustainable production of valuable fuels and chemicals. To deliver on their promises, such cell factories, as much as their brick-and-mortar counterparts, will require appropriate catalysts, especially for classes of reactions that are not known to be catalyzed by enzymes in natural organisms. A recently developed methodology, de novo computational enzyme design can be used to create enzymes catalyzing novel reactions. Here we review the different classes of chemical reactions for which active protein catalysts have been designed as well as the results of detailed biochemical and structural characterization studies. We also discuss how combining de novo computational enzyme design with more traditional protein engineering techniques can alleviate the shortcomings of state-of-the-art computational design techniques and create novel enzymes with catalytic proficiencies on par with natural enzymes. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Robust continuous clustering.

    Science.gov (United States)

    Shah, Sohil Atul; Koltun, Vladlen

    2017-09-12

    Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.

  12. Cluster bomb ocular injuries.

    Science.gov (United States)

    Mansour, Ahmad M; Hamade, Haya; Ghaddar, Ayman; Mokadem, Ahmad Samih; El Hajj Ali, Mohamad; Awwad, Shady

    2012-01-01

    To present the visual outcomes and ocular sequelae of victims of cluster bombs. This retrospective, multicenter case series of ocular injury due to cluster bombs was conducted for 3 years after the war in South Lebanon (July 2006). Data were gathered from the reports to the Information Management System for Mine Action. There were 308 victims of clusters bombs; 36 individuals were killed, of which 2 received ocular lacerations and; 272 individuals were injured with 18 receiving ocular injury. These 18 surviving individuals were assessed by the authors. Ocular injury occurred in 6.5% (20/308) of cluster bomb victims. Trauma to multiple organs occurred in 12 of 18 cases (67%) with ocular injury. Ocular findings included corneal or scleral lacerations (16 eyes), corneal foreign bodies (9 eyes), corneal decompensation (2 eyes), ruptured cataract (6 eyes), and intravitreal foreign bodies (10 eyes). The corneas of one patient had extreme attenuation of the endothelium. Ocular injury occurred in 6.5% of cluster bomb victims and 67% of the patients with ocular injury sustained trauma to multiple organs. Visual morbidity in civilians is an additional reason for a global ban on the use of cluster bombs.

  13. Determination of atomic cluster structure with cluster fusion algorithm

    DEFF Research Database (Denmark)

    Obolensky, Oleg I.; Solov'yov, Ilia; Solov'yov, Andrey V.

    2005-01-01

    We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters.......We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters....

  14. Engineering Cellulase Enzymes for Bioenergy

    Science.gov (United States)

    Atreya, Meera Elizabeth

    Sustainable energy sources, such as biofuels, offer increasingly important alternatives to fossil fuels that contribute less to global climate change. The energy contained within cellulosic biofuels derives from sunlight energy stored in the form of carbon-carbon bonds comprising sugars such as glucose. Second-generation biofuels are produced from lignocellulosic biomass feedstocks, including agricultural waste products and non-food crops like Miscanthus, that contain lignin and the polysaccharides hemicellulose and cellulose. Cellulose is the most abundant biological material on Earth; it is a polymer of glucose and a structural component of plant cell walls. Accessing the sugar is challenging, as the crystalline structure of cellulose resists degradation; biochemical and thermochemical means can be used to depolymerize cellulose. Cellulase enzymes catalyze the biochemical depolymerization of cellulose into glucose. Glucose can be used as a carbon source for growth of a biofuel-producing microorganism. When it converts glucose to a hydrocarbon fuel, this microbe completes the biofuels process of transforming sunlight energy into accessible, chemical energy capable of replacing non-renewable transportation fuels. Due to strong intermolecular interactions between polymer chains, cellulose is significantly more challenging to depolymerize than starch, a more accessible polymer of glucose utilized in first-generation biofuels processes (often derived from corn). While most mammals cannot digest cellulose (dietary fiber), certain fungi and bacteria produce cellulase enzymes capable of hydrolyzing it. These organisms secrete a wide variety of glycoside hydrolase and other classes of enzymes that work in concert. Because cellulase enzymes are slow-acting and expensive to produce, my aim has been to improve the properties of these enzymes as a means to make a cellulosic biofuels process possible that is more efficient and, consequently, more economical than current

  15. Activity of an enzyme immobilized on superparamagnetic particles in a rotational magnetic field

    Energy Technology Data Exchange (ETDEWEB)

    Mizuki, Toru; Watanabe, Noriyuki; Nagaoka, Yutaka [Bio-Nano Electronics Research Centre, Toyo University, Saitama 350-8585 (Japan); Fukushima, Tadamasa [Shimadzu GLC Ltd., Phenomenex Support Centre, Tokyo 110-0016 (Japan); Morimoto, Hisao; Usami, Ron [Bio-Nano Electronics Research Centre, Toyo University, Saitama 350-8585 (Japan); Maekawa, Toru, E-mail: maekawa@toyonet.toyo.ac.jp [Bio-Nano Electronics Research Centre, Toyo University, Saitama 350-8585 (Japan)

    2010-03-19

    We immobilize {alpha}-amylase extracted from Bacillus Iicheniformis on the surfaces of superparamagnetic particles and investigate the effect of a rotational magnetic field on the enzyme's activity. We find that the activity of the enzyme molecules immobilized on superparamagnetic particles increases in the rotational magnetic field and reaches maximum at a certain frequency. We clarify the effect of the cluster structures formed by the superparamagnetic particles on the activity. Enzyme reactions are enhanced even in a tiny volume of solution using the present method, which is very important for the development of efficient micro reactors and micro total analysis systems ({mu}-TAS).

  16. Mechanism of electron attachment to van der Waals clusters: Application to carbon dioxide clusters

    International Nuclear Information System (INIS)

    Tsukada, M.; Shima, N.; Tsuneyuki, S.; Kageshima, H.; Kondow, T.

    1987-01-01

    A theory on the attachment of very slow electrons to van der Waals clusters was developed on the basis of the electronic structure theory, and was applied to clarify the mechanism of the collisional electron transfer from a high-Rydberg atom to a CO 2 cluster. The strong coupled electron--phonon model is found to afford a reasonable mechanism of the attachment. The equilibrium geometry of (CO 2 )/sub N/ (2≤N≤13) clusters are determined and their vertical affinity levels are obtained by the DV-X α-transition state method. Using this information, as well as some plausible assumptions on the values of the coupling constants, the attachment cross section σ is evaluated as a function of the energy of the incident electron. The theory predicts the existence of the threshold cluster size for the attachment and a sharp decrease of σ with the energy, which are consistent with the experimental results

  17. Clustering impact regime with shocks in freely evolving granular gas

    Science.gov (United States)

    Isobe, Masaharu

    2017-06-01

    A freely cooling granular gas without any external force evolves from the initial homogeneous state to the inhomogeneous clustering state, at which the energy decay deviates from the Haff's law. The asymptotic behavior of energy in the inelastic hard sphere model have been predicted by several theories, which are based on the mode coupling theory or extension of inelastic hard rods gas. In this study, we revisited the clustering regime of freely evolving granular gas via large-scale molecular dynamics simulation with up to 16.7 million inelastic hard disks. We found novel regime regarding on collisions between "clusters" spontaneously appearing after clustering regime, which can only be identified more than a few million particles system. The volumetric dilatation pattern of semicircular shape originated from density shock propagation are well characterized on the appearing of "cluster impact" during the aggregation process of clusters.

  18. Cluster dynamics at different cluster size and incident laser wavelengths

    International Nuclear Information System (INIS)

    Desai, Tara; Bernardinello, Andrea

    2002-01-01

    X-ray emission spectra from aluminum clusters of diameter -0.4 μm and gold clusters of dia. ∼1.25 μm are experimentally studied by irradiating the cluster foil targets with 1.06 μm laser, 10 ns (FWHM) at an intensity ∼10 12 W/cm 2 . Aluminum clusters show a different spectra compared to bulk material whereas gold cluster evolve towards bulk gold. Experimental data are analyzed on the basis of cluster dimension, laser wavelength and pulse duration. PIC simulations are performed to study the behavior of clusters at higher intensity I≥10 17 W/cm 2 for different size of the clusters irradiated at different laser wavelengths. Results indicate the dependence of cluster dynamics on cluster size and incident laser wavelength

  19. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2006-01-01

    paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

  20. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2008-01-01

    paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...