Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Country clustering applied to the water and sanitation sector: a new tool with potential applications in research and policy.

PubMed

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2014-03-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were distinct from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. Copyright © 2013 Elsevier GmbH. All rights reserved.

Connecting Different Data Sources to Assess the Interconnections between Biosecurity, Health, Welfare, and Performance in Commercial Pig Farms in Great Britain.

PubMed

Pandolfi, Fanny; Edwards, Sandra A; Maes, Dominiek; Kyriazakis, Ilias

2018-01-01

This study aimed to provide an overview of the interconnections between biosecurity, health, welfare, and performance in commercial pig farms in Great Britain. We collected on-farm data about the level of biosecurity and animal performance in 40 fattening pig farms and 28 breeding pig farms between 2015 and 2016. We identified interconnections between these data, slaughterhouse health indicators, and welfare indicator records in fattening pig farms. After achieving the connections between databases, a secondary data analysis was performed to assess the interconnections between biosecurity, health, welfare, and performance using correlation analysis, principal component analysis, and hierarchical clustering. Although we could connect the different data sources the final sample size was limited, suggesting room for improvement in database connection to conduct secondary data analyses. The farm biosecurity scores ranged from 40 to 90 out of 100, with internal biosecurity scores being lower than external biosecurity scores. Our analysis suggested several interconnections between health, welfare, and performance. The initial correlation analysis showed that the prevalence of lameness and severe tail lesions was associated with the prevalence of enzootic pneumonia-like lesions and pyaemia, and the prevalence of severe body marks was associated with several disease indicators, including peritonitis and milk spots ( r  > 0.3; P  < 0.05). Higher average daily weight gain (ADG) was associated with lower prevalence of pleurisy ( r  > 0.3; P  < 0.05), but no connection was identified between mortality and health indicators. A subsequent cluster analysis enabled identification of patterns which considered concurrently indicators of health, welfare, and performance. Farms from cluster 1 had lower biosecurity scores, lower ADG, and higher prevalence of several disease and welfare indicators. Farms from cluster 2 had higher biosecurity scores than cluster 1, but a higher prevalence of pigs requiring hospitalization and lameness which confirmed the correlation between biosecurity and the prevalence of pigs requiring hospitalization ( r  > 0.3; P  < 0.05). Farms from cluster 3 had higher biosecurity, higher ADG, and lower prevalence for some disease and welfare indicators. The study suggests a smaller impact of biosecurity on issues such as mortality, prevalence of lameness, and pig requiring hospitalization. The correlations and the identified clusters suggested the importance of animal welfare for the pig industry.

Cluster Analysis to Identify Possible Subgroups in Tinnitus Patients.

PubMed

van den Berge, Minke J C; Free, Rolien H; Arnold, Rosemarie; de Kleine, Emile; Hofman, Rutger; van Dijk, J Marc C; van Dijk, Pim

2017-01-01

In tinnitus treatment, there is a tendency to shift from a "one size fits all" to a more individual, patient-tailored approach. Insight in the heterogeneity of the tinnitus spectrum might improve the management of tinnitus patients in terms of choice of treatment and identification of patients with severe mental distress. The goal of this study was to identify subgroups in a large group of tinnitus patients. Data were collected from patients with severe tinnitus complaints visiting our tertiary referral tinnitus care group at the University Medical Center Groningen. Patient-reported and physician-reported variables were collected during their visit to our clinic. Cluster analyses were used to characterize subgroups. For the selection of the right variables to enter in the cluster analysis, two approaches were used: (1) variable reduction with principle component analysis and (2) variable selection based on expert opinion. Various variables of 1,783 tinnitus patients were included in the analyses. Cluster analysis (1) included 976 patients and resulted in a four-cluster solution. The effect of external influences was the most discriminative between the groups, or clusters, of patients. The "silhouette measure" of the cluster outcome was low (0.2), indicating a "no substantial" cluster structure. Cluster analysis (2) included 761 patients and resulted in a three-cluster solution, comparable to the first analysis. Again, a "no substantial" cluster structure was found (0.2). Two cluster analyses on a large database of tinnitus patients revealed that clusters of patients are mostly formed by a different response of external influences on their disease. However, both cluster outcomes based on this dataset showed a poor stability, suggesting that our tinnitus population comprises a continuum rather than a number of clearly defined subgroups.

Is It Feasible to Identify Natural Clusters of TSC-Associated Neuropsychiatric Disorders (TAND)?

PubMed

Leclezio, Loren; Gardner-Lubbe, Sugnet; de Vries, Petrus J

2018-04-01

Tuberous sclerosis complex (TSC) is a genetic disorder with multisystem involvement. The lifetime prevalence of TSC-Associated Neuropsychiatric Disorders (TAND) is in the region of 90% in an apparently unique, individual pattern. This "uniqueness" poses significant challenges for diagnosis, psycho-education, and intervention planning. To date, no studies have explored whether there may be natural clusters of TAND. The purpose of this feasibility study was (1) to investigate the practicability of identifying natural TAND clusters, and (2) to identify appropriate multivariate data analysis techniques for larger-scale studies. TAND Checklist data were collected from 56 individuals with a clinical diagnosis of TSC (n = 20 from South Africa; n = 36 from Australia). Using R, the open-source statistical platform, mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Ward's method rendered six TAND clusters with good face validity and significant convergence with a six-factor exploratory factor analysis solution. The "bottom-up" data-driven strategies identified a "scholastic" cluster of TAND manifestations, an "autism spectrum disorder-like" cluster, a "dysregulated behavior" cluster, a "neuropsychological" cluster, a "hyperactive/impulsive" cluster, and a "mixed/mood" cluster. These feasibility results suggest that a combination of cluster analysis and exploratory factor analysis methods may be able to identify clinically meaningful natural TAND clusters. Findings require replication and expansion in larger dataset, and could include quantification of cluster or factor scores at an individual level. Copyright © 2018 Elsevier Inc. All rights reserved.

Closed-cage tungsten oxide clusters in the gas phase.

PubMed

Singh, D M David Jeba; Pradeep, T; Thirumoorthy, Krishnan; Balasubramanian, Krishnan

2010-05-06

During the course of a study on the clustering of W-Se and W-S mixtures in the gas phase using laser desorption ionization (LDI) mass spectrometry, we observed several anionic W-O clusters. Three distinct species, W(6)O(19)(-), W(13)O(29)(-), and W(14)O(32)(-), stand out as intense peaks in the regular mass spectral pattern of tungsten oxide clusters suggesting unusual stabilities for them. Moreover, these clusters do not fragment in the postsource decay analysis. While trying to understand the precursor material, which produced these clusters, we found the presence of nanoscale forms of tungsten oxide. The structure and thermodynamic parameters of tungsten clusters have been explored using relativistic quantum chemical methods. Our computed results of atomization energy are consistent with the observed LDI mass spectra. The computational results suggest that the clusters observed have closed-cage structure. These distinct W(13) and W(14) clusters were observed for the first time in the gas phase.

Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles.

PubMed

Williams, N J; Nasuto, S J; Saddy, J D

2015-07-30

The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. We propose a complete pipeline for the cluster analysis of ERP data. To increase the signal-to-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA) to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). After validating the pipeline on simulated data, we tested it on data from two experiments - a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership. Our analysis operates on denoised single-trials, the number of clusters are determined in a principled manner and the results are presented through an intuitive visualisation. Given the cluster structure in some experimental conditions, we suggest application of cluster analysis as a preliminary step before ensemble averaging. Copyright © 2015 Elsevier B.V. All rights reserved.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

PubMed

Wardenaar, K J; van Loo, H M; Cai, T; Fava, M; Gruber, M J; Li, J; de Jonge, P; Nierenberg, A A; Petukhova, M V; Rose, S; Sampson, N A; Schoevers, R A; Wilcox, M A; Alonso, J; Bromet, E J; Bunting, B; Florescu, S E; Fukao, A; Gureje, O; Hu, C; Huang, Y Q; Karam, A N; Levinson, D; Medina Mora, M E; Posada-Villa, J; Scott, K M; Taib, N I; Viana, M C; Xavier, M; Zarkov, Z; Kessler, R C

2014-11-01

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study.

PubMed

Barker, Daniel; D'Este, Catherine; Campbell, Michael J; McElduff, Patrick

2017-03-09

Stepped wedge cluster randomised trials frequently involve a relatively small number of clusters. The most common frameworks used to analyse data from these types of trials are generalised estimating equations and generalised linear mixed models. A topic of much research into these methods has been their application to cluster randomised trial data and, in particular, the number of clusters required to make reasonable inferences about the intervention effect. However, for stepped wedge trials, which have been claimed by many researchers to have a statistical power advantage over the parallel cluster randomised trial, the minimum number of clusters required has not been investigated. We conducted a simulation study where we considered the most commonly used methods suggested in the literature to analyse cross-sectional stepped wedge cluster randomised trial data. We compared the per cent bias, the type I error rate and power of these methods in a stepped wedge trial setting with a binary outcome, where there are few clusters available and when the appropriate adjustment for a time trend is made, which by design may be confounding the intervention effect. We found that the generalised linear mixed modelling approach is the most consistent when few clusters are available. We also found that none of the common analysis methods for stepped wedge trials were both unbiased and maintained a 5% type I error rate when there were only three clusters. Of the commonly used analysis approaches, we recommend the generalised linear mixed model for small stepped wedge trials with binary outcomes. We also suggest that in a stepped wedge design with three steps, at least two clusters be randomised at each step, to ensure that the intervention effect estimator maintains the nominal 5% significance level and is also reasonably unbiased.

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

PubMed

Zhang, Xiaohua Douglas; Yang, Xiting Cindy; Chung, Namjin; Gates, Adam; Stec, Erica; Kunapuli, Priya; Holder, Dan J; Ferrer, Marc; Espeseth, Amy S

2006-04-01

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.

Identifying novel phenotypes of acute heart failure using cluster analysis of clinical variables.

PubMed

Horiuchi, Yu; Tanimoto, Shuzou; Latif, A H M Mahbub; Urayama, Kevin Y; Aoki, Jiro; Yahagi, Kazuyuki; Okuno, Taishi; Sato, Yu; Tanaka, Tetsu; Koseki, Keita; Komiyama, Kota; Nakajima, Hiroyoshi; Hara, Kazuhiro; Tanabe, Kengo

2018-07-01

Acute heart failure (AHF) is a heterogeneous disease caused by various cardiovascular (CV) pathophysiology and multiple non-CV comorbidities. We aimed to identify clinically important subgroups to improve our understanding of the pathophysiology of AHF and inform clinical decision-making. We evaluated detailed clinical data of 345 consecutive AHF patients using non-hierarchical cluster analysis of 77 variables, including age, sex, HF etiology, comorbidities, physical findings, laboratory data, electrocardiogram, echocardiogram and treatment during hospitalization. Cox proportional hazards regression analysis was performed to estimate the association between the clusters and clinical outcomes. Three clusters were identified. Cluster 1 (n=108) represented "vascular failure". This cluster had the highest average systolic blood pressure at admission and lung congestion with type 2 respiratory failure. Cluster 2 (n=89) represented "cardiac and renal failure". They had the lowest ejection fraction (EF) and worst renal function. Cluster 3 (n=148) comprised mostly older patients and had the highest prevalence of atrial fibrillation and preserved EF. Death or HF hospitalization within 12-month occurred in 23% of Cluster 1, 36% of Cluster 2 and 36% of Cluster 3 (p=0.034). Compared with Cluster 1, risk of death or HF hospitalization was 1.74 (95% CI, 1.03-2.95, p=0.037) for Cluster 2 and 1.82 (95% CI, 1.13-2.93, p=0.014) for Cluster 3. Cluster analysis may be effective in producing clinically relevant categories of AHF, and may suggest underlying pathophysiology and potential utility in predicting clinical outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

Machine-learned cluster identification in high-dimensional data.

PubMed

Ultsch, Alfred; Lötsch, Jörn

2017-02-01

High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM). Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means. Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data. The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

NASA Astrophysics Data System (ADS)

Grasha, K.; Elmegreen, B. G.; Calzetti, D.; Adamo, A.; Aloisi, A.; Bright, S. N.; Cook, D. O.; Dale, D. A.; Fumagalli, M.; Gallagher, J. S., III; Gouliermis, D. A.; Grebel, E. K.; Kahre, L.; Kim, H.; Krumholz, M. R.; Lee, J. C.; Messa, M.; Ryon, J. E.; Ubeda, L.

2017-06-01

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25-0.6 power, and that the maximum size over which star formation is physically correlated ranges from ˜200 pc to ˜1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are close to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.

Elucidation of the Pattern of the Onset of Male Lower Urinary Tract Symptoms Using Cluster Analysis: Efficacy of Tamsulosin in Each Symptom Group.

PubMed

Aikawa, Ken; Kataoka, Masao; Ogawa, Soichiro; Akaihata, Hidenori; Sato, Yuichi; Yabe, Michihiro; Hata, Junya; Koguchi, Tomoyuki; Kojima, Yoshiyuki; Shiragasawa, Chihaya; Kobayashi, Toshimitsu; Yamaguchi, Osamu

2015-08-01

To present a new grouping of male patients with lower urinary tract symptoms (LUTS) based on symptom patterns and clarify whether the therapeutic effect of α1-blocker differs among the groups. We performed secondary analysis of anonymous data from 4815 patients enrolled in a postmarketing surveillance study of tamsulosin in Japan. Data on 7 International Prostate Symptom Score (IPSS) items at the initial visit were used in the cluster analysis. IPSS and quality of life (QOL) scores before and after tamsulosin treatment for 12 weeks were assessed in each cluster. Partial correlation coefficients were also obtained for IPSS and QOL scores based on changes before and after treatment. Five symptom groups were identified by cluster analysis of IPSS. On their symptom profile, each cluster was labeled as minimal type (cluster 1), multiple severe type (cluster 2), weak stream type (cluster 3), storage type (cluster 4), and voiding type (cluster 5). Prevalence and the mean symptom score were significantly improved in almost all symptoms in all clusters by tamsulosin treatment. Nocturia and weak stream had the strongest effect on QOL in clusters 1, 2, and 4 and clusters 3 and 5, respectively. The study clarified that 5 characteristic symptom patterns exist by cluster analysis of IPSS in male patients with LUTS. Tamsulosin improved various symptoms and QOL in each symptom group. The study reports many male patients with LUTS being satisfied with monotherapy using tamsulosin and suggests the usefulness of α1-blockers as a drug of first choice. Copyright © 2015 Elsevier Inc. All rights reserved.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

PubMed

Nguyen, Hien D; Ullmann, Jeremy F P; McLachlan, Geoffrey J; Voleti, Venkatakaushik; Li, Wenze; Hillman, Elizabeth M C; Reutens, David C; Janke, Andrew L

2018-02-01

Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.

Cloning and Characterization of the Pyrrolomycin Biosynthetic Gene Clusters from Actinosporangium vitaminophilum ATCC 31673 and Streptomyces sp. Strain UC 11065▿

PubMed Central

Zhang, Xiujun; Parry, Ronald J.

2007-01-01

The pyrrolomycins are a family of polyketide antibiotics, some of which contain a nitro group. To gain insight into the nitration mechanism associated with the formation of these antibiotics, the pyrrolomycin biosynthetic gene cluster from Actinosporangium vitaminophilum was cloned. Sequencing of ca. 56 kb of A. vitaminophilum DNA revealed 35 open reading frames (ORFs). Sequence analysis revealed a clear relationship between some of these ORFs and the biosynthetic gene cluster for pyoluteorin, a structurally related antibiotic. Since a gene transfer system could not be devised for A. vitaminophilum, additional proof for the identity of the cloned gene cluster was sought by cloning the pyrrolomycin gene cluster from Streptomyces sp. strain UC 11065, a transformable pyrrolomycin producer. Sequencing of ca. 26 kb of UC 11065 DNA revealed the presence of 17 ORFs, 15 of which exhibit strong similarity to ORFs in the A. vitaminophilum cluster as well as a nearly identical organization. Single-crossover disruption of two genes in the UC 11065 cluster abolished pyrrolomycin production in both cases. These results confirm that the genetic locus cloned from UC 11065 is essential for pyrrolomycin production, and they also confirm that the highly similar locus in A. vitaminophilum encodes pyrrolomycin biosynthetic genes. Sequence analysis revealed that both clusters contain genes encoding the two components of an assimilatory nitrate reductase. This finding suggests that nitrite is required for the formation of the nitrated pyrrolomycins. However, sequence analysis did not provide additional insights into the nitration process, suggesting the operation of a novel nitration mechanism. PMID:17158935

Interplay between Oxygen and Fe–S Cluster Biogenesis: Insights from the Suf Pathway

PubMed Central

2015-01-01

Iron–sulfur (Fe–S) cluster metalloproteins conduct essential functions in nearly all contemporary forms of life. The nearly ubiquitous presence of Fe–S clusters and the fundamental requirement for Fe–S clusters in both aerobic and anaerobic Archaea, Bacteria, and Eukarya suggest that these clusters were likely integrated into central metabolic pathways early in the evolution of life prior to the widespread oxidation of Earth’s atmosphere. Intriguingly, Fe–S cluster-dependent metabolism is sensitive to disruption by oxygen because of the decreased bioavailability of ferric iron as well as direct oxidation of sulfur trafficking intermediates and Fe–S clusters by reactive oxygen species. This fact, coupled with the ubiquity of Fe–S clusters in aerobic organisms, suggests that organisms evolved with mechanisms that facilitate the biogenesis and use of these essential cofactors in the presence of oxygen, which gradually began to accumulate around 2.5 billion years ago as oxygenic photosynthesis proliferated and reduced minerals that buffered against oxidation were depleted. This review highlights the most ancient of the Fe–S cluster biogenesis pathways, the Suf system, which likely was present in early anaerobic forms of life. Herein, we use the evolution of the Suf pathway to assess the relationships between the biochemical functions and physiological roles of Suf proteins, with an emphasis on the selective pressure of oxygen toxicity. Our analysis suggests that diversification into oxygen-containing environments disrupted iron and sulfur metabolism and was a main driving force in the acquisition of accessory Suf proteins (such as SufD, SufE, and SufS) by the core SufB–SufC scaffold complex. This analysis provides a new framework for the study of Fe–S cluster biogenesis pathways and Fe–S cluster-containing metalloenzymes and their complicated patterns of divergence in response to oxygen. PMID:25153801

A Framework for Designing Cluster Randomized Trials with Binary Outcomes

ERIC Educational Resources Information Center

Spybrook, Jessaca; Martinez, Andres

2011-01-01

The purpose of this paper is to provide a frame work for approaching a power analysis for a CRT (cluster randomized trial) with a binary outcome. The authors suggest a framework in the context of a simple CRT and then extend it to a blocked design, or a multi-site cluster randomized trial (MSCRT). The framework is based on proportions, an…

Applying a Resources Framework to Analysis of the Force and Motion Conceptual Evaluation

ERIC Educational Resources Information Center

Smith, Trevor I.; Wittman, Michael C.

2008-01-01

We suggest one redefinition of common clusters of questions used to analyze student responses on the Force and Motion Conceptual Evaluation. Our goal is to propose a methodology that moves beyond an analysis of student learning defined by correct responses, either on the overall test or on clusters of questions defined solely by content. We use…

Clustering of health-related behaviors among early and mid-adolescents in Tuscany: results from a representative cross-sectional study

PubMed Central

Lazzeri, Giacomo; Panatto, Donatella; Domnich, Alexander; Arata, Lucia; Pammolli, Andrea; Simi, Rita; Giacchi, Mariano Vincenzo; Amicizia, Daniela; Gasparini, Roberto

2018-01-01

Abstract Background A huge amount of literature suggests that adolescents’ health-related behaviors tend to occur in clusters, and the understanding of such behavioral clustering may have direct implications for the effective tailoring of health-promotion interventions. Despite the usefulness of analyzing clustering, Italian data on this topic are scant. This study aimed to evaluate the clustering patterns of health-related behaviors. Methods The present study is based on data from the Health Behaviors in School-aged Children (HBSC) study conducted in Tuscany in 2010, which involved 3291 11-, 13- and 15-year olds. To aggregate students’ data on 22 health-related behaviors, factor analysis and subsequent cluster analysis were performed. Results Factor analysis revealed eight factors, which were dubbed in accordance with their main traits: ‘Alcohol drinking’, ‘Smoking’, ‘Physical activity’, ‘Screen time’, ‘Signs & symptoms’, ‘Healthy eating’, ‘Violence’ and ‘Sweet tooth’. These factors explained 67% of variance and underwent cluster analysis. A six-cluster κ-means solution was established with a 93.8% level of classification validity. The between-cluster differences in both mean age and gender distribution were highly statistically significant. Conclusions Health-compromising behaviors are common among Tuscan teens and occur in distinct clusters. These results may be used by schools, health-promotion authorities and other stakeholders to design and implement tailored preventive interventions in Tuscany. PMID:27908972

Clustering of health-related behaviors among early and mid-adolescents in Tuscany: results from a representative cross-sectional study.

PubMed

Lazzeri, Giacomo; Panatto, Donatella; Domnich, Alexander; Arata, Lucia; Pammolli, Andrea; Simi, Rita; Giacchi, Mariano Vincenzo; Amicizia, Daniela; Gasparini, Roberto

2018-03-01

A huge amount of literature suggests that adolescents' health-related behaviors tend to occur in clusters, and the understanding of such behavioral clustering may have direct implications for the effective tailoring of health-promotion interventions. Despite the usefulness of analyzing clustering, Italian data on this topic are scant. This study aimed to evaluate the clustering patterns of health-related behaviors. The present study is based on data from the Health Behaviors in School-aged Children (HBSC) study conducted in Tuscany in 2010, which involved 3291 11-, 13- and 15-year olds. To aggregate students' data on 22 health-related behaviors, factor analysis and subsequent cluster analysis were performed. Factor analysis revealed eight factors, which were dubbed in accordance with their main traits: 'Alcohol drinking', 'Smoking', 'Physical activity', 'Screen time', 'Signs & symptoms', 'Healthy eating', 'Violence' and 'Sweet tooth'. These factors explained 67% of variance and underwent cluster analysis. A six-cluster κ-means solution was established with a 93.8% level of classification validity. The between-cluster differences in both mean age and gender distribution were highly statistically significant. Health-compromising behaviors are common among Tuscan teens and occur in distinct clusters. These results may be used by schools, health-promotion authorities and other stakeholders to design and implement tailored preventive interventions in Tuscany.

A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks.

PubMed

Joshi, Gyanendra Prasad; Kim, Sung Won

2016-09-10

Cognitive radio wireless sensor networks (CR-WSNs) have attracted a great deal of attention recently due to the emerging spectrum scarcity issue. This work attempts to provide a detailed analysis of the role of node clustering in CR-WSNs. We outline the objectives, requirements, and advantages of node clustering in CR-WSNs. We describe how a CR-WSN with node clustering differs from conventional wireless sensor networks, and we discuss its characteristics, architecture, and topologies. We survey the existing clustering algorithms and compare their objectives and features. We suggest how clustering issues and challenges can be handled.

Initial conditions of formation of starburst clusters: constraints from stellar dynamics

NASA Astrophysics Data System (ADS)

Banerjee, Sambaran

2017-03-01

How starburst clusters form out of molecular clouds is still an open question. In this article, I highlight some of the key constraints in this regard, that one can get from the dynamical evolutionary properties of dense stellar systems. I particularly focus on secular expansion of massive star clusters and hierarchical merging of sub-clusters, and discuss their implications vis-á-vis the observed properties of young massive clusters. The analysis suggests that residual gas expulsion is necessary for shaping these clusters as we see them today, irrespective of their monolithic or hierarchical mode of formation.

Isolation of 'Candidatus Nitrosocosmicus franklandus', a novel ureolytic soil archaeal ammonia oxidiser with tolerance to high ammonia concentration.

PubMed

Lehtovirta-Morley, Laura E; Ross, Jenna; Hink, Linda; Weber, Eva B; Gubry-Rangin, Cécile; Thion, Cécile; Prosser, James I; Nicol, Graeme W

2016-05-01

Studies of the distribution of ammonia oxidising archaea (AOA) and bacteria (AOB) suggest distinct ecological niches characterised by ammonia concentration and pH, arising through differences in substrate affinity and ammonia tolerance. AOA form five distinct phylogenetic clades, one of which, the 'Nitrososphaera sister cluster', has no cultivated isolate. A representative of this cluster, named 'Candidatus Nitrosocosmicus franklandus', was isolated from a pH 7.5 arable soil and we propose a new cluster name:'Nitrosocosmicus' While phylogenetic analysis of amoA genes indicates its association with the Nitrososphaera sister cluster, analysis of 16S rRNA genes provided no support for a relative branching that is consistent with a 'sister cluster', indicating placement within a lineage of the order Nitrososphaerales 'Ca.N. franklandus' is capable of ureolytic growth and its tolerances to nitrite and ammonia are higher than in other AOA and similar to those of typical soil AOB. Similarity of other growth characteristics of 'Ca.N. franklandus' with those of typical soil AOB isolates reduces support for niche differentiation between soil AOA and AOB and suggests that AOA have a wider physiological diversity than previously suspected. In particular, the high ammonia tolerance of 'Ca.N. franklandus' suggests potential contributions to nitrification in fertilised soils. © FEMS 2016.

Impact of Sampling Density on the Extent of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2014-01-01

Abstract Identifying and monitoring HIV clusters could be useful in tracking the leading edge of HIV transmission in epidemics. Currently, greater specificity in the definition of HIV clusters is needed to reduce confusion in the interpretation of HIV clustering results. We address sampling density as one of the key aspects of HIV cluster analysis. The proportion of viral sequences in clusters was estimated at sampling densities from 1.0% to 70%. A set of 1,248 HIV-1C env gp120 V1C5 sequences from a single community in Botswana was utilized in simulation studies. Matching numbers of HIV-1C V1C5 sequences from the LANL HIV Database were used as comparators. HIV clusters were identified by phylogenetic inference under bootstrapped maximum likelihood and pairwise distance cut-offs. Sampling density below 10% was associated with stochastic HIV clustering with broad confidence intervals. HIV clustering increased linearly at sampling density >10%, and was accompanied by narrowing confidence intervals. Patterns of HIV clustering were similar at bootstrap thresholds 0.7 to 1.0, but the extent of HIV clustering decreased with higher bootstrap thresholds. The origin of sampling (local concentrated vs. scattered global) had a substantial impact on HIV clustering at sampling densities ≥10%. Pairwise distances at 10% were estimated as a threshold for cluster analysis of HIV-1 V1C5 sequences. The node bootstrap support distribution provided additional evidence for 10% sampling density as the threshold for HIV cluster analysis. The detectability of HIV clusters is substantially affected by sampling density. A minimal genotyping density of 10% and sampling density of 50–70% are suggested for HIV-1 V1C5 cluster analysis. PMID:25275430

Clustering stocks using partial correlation coefficients

NASA Astrophysics Data System (ADS)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Using cluster analysis for medical resource decision making.

PubMed

Dilts, D; Khamalah, J; Plotkin, A

1995-01-01

Escalating costs of health care delivery have in the recent past often made the health care industry investigate, adapt, and apply those management techniques relating to budgeting, resource control, and forecasting that have long been used in the manufacturing sector. A strategy that has contributed much in this direction is the definition and classification of a hospital's output into "products" or groups of patients that impose similar resource or cost demands on the hospital. Existing classification schemes have frequently employed cluster analysis in generating these groupings. Unfortunately, the myriad articles and books on clustering and classification contain few formalized selection methodologies for choosing a technique for solving a particular problem, hence they often leave the novice investigator at a loss. This paper reviews the literature on clustering, particularly as it has been applied in the medical resource-utilization domain, addresses the critical choices facing an investigator in the medical field using cluster analysis, and offers suggestions (using the example of clustering low-vision patients) for how such choices can be made.

New Techniques for Ancient Proteins: Direct Coupling Analysis Applied on Proteins Involved in Iron Sulfur Cluster Biogenesis

PubMed Central

Fantini, Marco; Malinverni, Duccio; De Los Rios, Paolo; Pastore, Annalisa

2017-01-01

Direct coupling analysis (DCA) is a powerful statistical inference tool used to study protein evolution. It was introduced to predict protein folds and protein-protein interactions, and has also been applied to the prediction of entire interactomes. Here, we have used it to analyze three proteins of the iron-sulfur biogenesis machine, an essential metabolic pathway conserved in all organisms. We show that DCA can correctly reproduce structural features of the CyaY/frataxin family (a protein involved in the human disease Friedreich's ataxia) despite being based on the relatively small number of sequences allowed by its genomic distribution. This result gives us confidence in the method. Its application to the iron-sulfur cluster scaffold protein IscU, which has been suggested to function both as an ordered and a disordered form, allows us to distinguish evolutionary traces of the structured species, suggesting that, if present in the cell, the disordered form has not left evolutionary imprinting. We observe instead, for the first time, direct indications of how the protein can dimerize head-to-head and bind 4Fe4S clusters. Analysis of the alternative scaffold protein IscA provides strong support to a coordination of the cluster by a dimeric form rather than a tetramer, as previously suggested. Our analysis also suggests the presence in solution of a mixture of monomeric and dimeric species, and guides us to the prevalent one. Finally, we used DCA to analyze interactions between some of these proteins, and discuss the potentials and limitations of the method. PMID:28664160

Dataset of Fourier transform-infrared coupled with chemometric analysis used to distinguish accessions of Garcinia mangostana L. in Peninsular Malaysia.

PubMed

Samsir, Sri A'jilah; Bunawan, Hamidun; Yen, Choong Chee; Noor, Normah Mohd

2016-09-01

In this dataset, we distinguish 15 accessions of Garcinia mangostana from Peninsular Malaysia using Fourier transform-infrared spectroscopy coupled with chemometric analysis. We found that the position and intensity of characteristic peaks at 3600-3100 cm(-) (1) in IR spectra allowed discrimination of G. mangostana from different locations. Further principal component analysis (PCA) of all the accessions suggests the two main clusters were formed: samples from Johor, Melaka, and Negeri Sembilan (South) were clustered together in one group while samples from Perak, Kedah, Penang, Selangor, Kelantan, and Terengganu (North and East Coast) were in another clustered group.

Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.

PubMed

Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin

2017-01-01

Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grasha, K.; Calzetti, D.; Elmegreen, B. G.

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25–0.6 power, and that the maximum size over which star formation is physically correlated ranges from ∼200 pc to ∼1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are closemore » to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.« less

First evidence of diffuse ultra-steep-spectrum radio emission surrounding the cool core of a cluster

NASA Astrophysics Data System (ADS)

Savini, F.; Bonafede, A.; Brüggen, M.; van Weeren, R.; Brunetti, G.; Intema, H.; Botteon, A.; Shimwell, T.; Wilber, A.; Rafferty, D.; Giacintucci, S.; Cassano, R.; Cuciti, V.; de Gasperin, F.; Röttgering, H.; Hoeft, M.; White, G.

2018-05-01

Diffuse synchrotron radio emission from cosmic-ray electrons is observed at the center of a number of galaxy clusters. These sources can be classified either as giant radio halos, which occur in merging clusters, or as mini halos, which are found only in cool-core clusters. In this paper, we present the first discovery of a cool-core cluster with an associated mini halo that also shows ultra-steep-spectrum emission extending well beyond the core that resembles radio halo emission. The large-scale component is discovered thanks to LOFAR observations at 144 MHz. We also analyse GMRT observations at 610 MHz to characterise the spectrum of the radio emission. An X-ray analysis reveals that the cluster is slightly disturbed, and we suggest that the steep-spectrum radio emission outside the core could be produced by a minor merger that powers electron re-acceleration without disrupting the cool core. This discovery suggests that, under particular circumstances, both a mini and giant halo could co-exist in a single cluster, opening new perspectives for particle acceleration mechanisms in galaxy clusters.

FAST TRACK COMMUNICATION: Poly(methyl methacrylate)-palladium clusters nanocomposite formation by supersonic cluster beam deposition: a method for microstructured metallization of polymer surfaces

NASA Astrophysics Data System (ADS)

Ravagnan, Luca; Divitini, Giorgio; Rebasti, Sara; Marelli, Mattia; Piseri, Paolo; Milani, Paolo

2009-04-01

Nanocomposite films were fabricated by supersonic cluster beam deposition (SCBD) of palladium clusters on poly(methyl methacrylate) (PMMA) surfaces. The evolution of the electrical conductance with cluster coverage and microscopy analysis show that Pd clusters are implanted in the polymer and form a continuous layer extending for several tens of nanometres beneath the polymer surface. This allows the deposition, using stencil masks, of cluster-assembled Pd microstructures on PMMA showing a remarkably high adhesion compared with metallic films obtained by thermal evaporation. These results suggest that SCBD is a promising tool for the fabrication of metallic microstructures on flexible polymeric substrates.

Cluster analysis and subgrouping to investigate inter-individual variability to non-invasive brain stimulation: a systematic review.

PubMed

Pellegrini, Michael; Zoghi, Maryam; Jaberzadeh, Shapour

2018-01-12

Cluster analysis and other subgrouping techniques have risen in popularity in recent years in non-invasive brain stimulation research in the attempt to investigate the issue of inter-individual variability - the issue of why some individuals respond, as traditionally expected, to non-invasive brain stimulation protocols and others do not. Cluster analysis and subgrouping techniques have been used to categorise individuals, based on their response patterns, as responder or non-responders. There is, however, a lack of consensus and consistency on the most appropriate technique to use. This systematic review aimed to provide a systematic summary of the cluster analysis and subgrouping techniques used to date and suggest recommendations moving forward. Twenty studies were included that utilised subgrouping techniques, while seven of these additionally utilised cluster analysis techniques. The results of this systematic review appear to indicate that statistical cluster analysis techniques are effective in identifying subgroups of individuals based on response patterns to non-invasive brain stimulation. This systematic review also reports a lack of consensus amongst researchers on the most effective subgrouping technique and the criteria used to determine whether an individual is categorised as a responder or a non-responder. This systematic review provides a step-by-step guide to carrying out statistical cluster analyses and subgrouping techniques to provide a framework for analysis when developing further insights into the contributing factors of inter-individual variability in response to non-invasive brain stimulation.

Bacillithiol has a role in Fe-S cluster biogenesis in Staphylococcus aureus

PubMed Central

Rosario-Cruz, Zuelay; Chahal, Harsimranjit K.; Mike, Laura A.; Skaar, Eric P.; Boyd, Jeffrey M.

2015-01-01

Summary Staphylococcus aureus does not produce the low-molecular-weight (LMW) thiol glutathione, but it does produce the LMW thiol bacillithiol (BSH). To better understand the roles that BSH plays in staphylococcal metabolism we constructed and examined strains lacking BSH. Phenotypic analysis found that the BSH-deficient strains cultured either aerobically or anaerobically had growth defects that were alleviated by the addition of exogenous iron (Fe) or the amino acids leucine and isoleucine. The activity of the iron-sulfur (Fe-S) cluster-dependent enzymes LeuCD and IlvD, which are required for the biosynthesis of leucine and isoleucine, were decreased in strains lacking BSH. The BSH-deficient cells also had decreased aconitase and glutamate synthase activities suggesting a general defect in Fe-S cluster biogenesis. The phenotypes of the BSH-deficient strains were exacerbated in strains lacking the Fe-S cluster carrier Nfu and partially suppressed by multicopy expression of either sufA or nfu suggesting functional overlap between BSH and Fe-S carrier proteins. Biochemical analysis found that SufA bound and transferred Fe-S clusters to apo-aconitase verifying that it serves as an Fe-S cluster carrier. The results presented are consistent with the hypothesis that BSH has roles in Fe homeostasis and the carriage of Fe-S clusters to apo-proteins in S. aureus. PMID:26135358

Bacillithiol has a role in Fe-S cluster biogenesis in Staphylococcus aureus.

PubMed

Rosario-Cruz, Zuelay; Chahal, Harsimranjit K; Mike, Laura A; Skaar, Eric P; Boyd, Jeffrey M

2015-10-01

Staphylococcus aureus does not produce the low-molecular-weight (LMW) thiol glutathione, but it does produce the LMW thiol bacillithiol (BSH). To better understand the roles that BSH plays in staphylococcal metabolism, we constructed and examined strains lacking BSH. Phenotypic analysis found that the BSH-deficient strains cultured either aerobically or anaerobically had growth defects that were alleviated by the addition of exogenous iron (Fe) or the amino acids leucine and isoleucine. The activities of the iron-sulfur (Fe-S) cluster-dependent enzymes LeuCD and IlvD, which are required for the biosynthesis of leucine and isoleucine, were decreased in strains lacking BSH. The BSH-deficient cells also had decreased aconitase and glutamate synthase activities, suggesting a general defect in Fe-S cluster biogenesis. The phenotypes of the BSH-deficient strains were exacerbated in strains lacking the Fe-S cluster carrier Nfu and partially suppressed by multicopy expression of either sufA or nfu, suggesting functional overlap between BSH and Fe-S carrier proteins. Biochemical analysis found that SufA bound and transferred Fe-S clusters to apo-aconitase, verifying that it serves as an Fe-S cluster carrier. The results presented are consistent with the hypothesis that BSH has roles in Fe homeostasis and the carriage of Fe-S clusters to apo-proteins in S. aureus. © 2015 John Wiley & Sons Ltd.

Clinical Implications of Cluster Analysis-Based Classification of Acute Decompensated Heart Failure and Correlation with Bedside Hemodynamic Profiles.

PubMed

Ahmad, Tariq; Desai, Nihar; Wilson, Francis; Schulte, Phillip; Dunning, Allison; Jacoby, Daniel; Allen, Larry; Fiuzat, Mona; Rogers, Joseph; Felker, G Michael; O'Connor, Christopher; Patel, Chetan B

2016-01-01

Classification of acute decompensated heart failure (ADHF) is based on subjective criteria that crudely capture disease heterogeneity. Improved phenotyping of the syndrome may help improve therapeutic strategies. To derive cluster analysis-based groupings for patients hospitalized with ADHF, and compare their prognostic performance to hemodynamic classifications derived at the bedside. We performed a cluster analysis on baseline clinical variables and PAC measurements of 172 ADHF patients from the ESCAPE trial. Employing regression techniques, we examined associations between clusters and clinically determined hemodynamic profiles (warm/cold/wet/dry). We assessed association with clinical outcomes using Cox proportional hazards models. Likelihood ratio tests were used to compare the prognostic value of cluster data to that of hemodynamic data. We identified four advanced HF clusters: 1) male Caucasians with ischemic cardiomyopathy, multiple comorbidities, lowest B-type natriuretic peptide (BNP) levels; 2) females with non-ischemic cardiomyopathy, few comorbidities, most favorable hemodynamics; 3) young African American males with non-ischemic cardiomyopathy, most adverse hemodynamics, advanced disease; and 4) older Caucasians with ischemic cardiomyopathy, concomitant renal insufficiency, highest BNP levels. There was no association between clusters and bedside-derived hemodynamic profiles (p = 0.70). For all adverse clinical outcomes, Cluster 4 had the highest risk, and Cluster 2, the lowest. Compared to Cluster 4, Clusters 1-3 had 45-70% lower risk of all-cause mortality. Clusters were significantly associated with clinical outcomes, whereas hemodynamic profiles were not. By clustering patients with similar objective variables, we identified four clinically relevant phenotypes of ADHF patients, with no discernable relationship to hemodynamic profiles, but distinct associations with adverse outcomes. Our analysis suggests that ADHF classification using simultaneous considerations of etiology, comorbid conditions, and biomarker levels, may be superior to bedside classifications.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

NASA Astrophysics Data System (ADS)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties.

PubMed

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-25

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi 4 , NLi 5 , CLi 6 , BLI 7 and Al 12 Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability ([Formula: see text]) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review.

PubMed

Leech, Rebecca M; McNaughton, Sarah A; Timperio, Anna

2014-01-22

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5-18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥ 9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review

PubMed Central

2014-01-01

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5–18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity. PMID:24450617

The Psychology of Yoga Practitioners: A Cluster Analysis.

PubMed

Genovese, Jeremy E C; Fondran, Kristine M

2017-11-01

Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall -Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.

The Psychology of Yoga Practitioners: A Cluster Analysis.

PubMed

Genovese, Jeremy E C; Fondran, Kristine M

2017-03-30

Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall-Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.

Characterization of the CPAP-treated patient population in Catalonia

PubMed Central

Gavaldá, Ricard; Teixidó, Ivan; Woehrle, Holger; Rué, Montserrat; Solsona, Francesc; Escarrabill, Joan; Colls, Cristina; García-Altés, Anna; de Batlle, Jordi; Sánchez de-la-Torre, Manuel

2017-01-01

There are different phenotypes of obstructive sleep apnoea (OSA), many of which have not been characterised. Identification of these different phenotypes is important in defining prognosis and guiding the therapeutic strategy. The aim of this study was to characterise the entire population of continuous positive airway pressure (CPAP)-treated patients in Catalonia and identify specific patient profiles using cluster analysis. A total of 72,217 CPAP-treated patients who contacted the Catalan Health System (CatSalut) during the years 2012 and 2013 were included. Six clusters were identified, classified as “Neoplastic patients” (Cluster 1, 10.4%), “Metabolic syndrome patients” (Cluster 2, 27.7%), “Asthmatic patients” (Cluster 3, 5.8%), “Musculoskeletal and joint disorder patients” (Cluster 4, 10.3%), “Patients with few comorbidities” (Cluster 5, 35.6%) and “Oldest and cardiac disease patients” (Cluster 6, 10.2%). Healthcare facility use and mortality were highest in patients from Cluster 1 and 6. Conversely, patients in Clusters 2 and 4 had low morbidity, mortality and healthcare resource use. Our findings highlight the heterogeneity of CPAP-treated patients, and suggest that OSA is associated with a different prognosis in the clusters identified. These results suggest the need for a comprehensive and individualised approach to CPAP treatment of OSA. PMID:28934303

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

PubMed

Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra

2016-11-20

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Measuring Systemic and Climate Diversity in Ontario's University Sector

ERIC Educational Resources Information Center

Piché, Pierre Gilles

2015-01-01

This article proposes a methodology for measuring institutional diversity and applies it to Ontario's university sector. This study first used hierarchical cluster analysis, which suggested there has been very little change in diversity between 1994 and 2010 as universities were clustered in three groups for both years. However, by adapting…

Cluster and constraint analysis in tetrahedron packings

NASA Astrophysics Data System (ADS)

Jin, Weiwei; Lu, Peng; Liu, Lufeng; Li, Shuixiang

2015-04-01

The disordered packings of tetrahedra often show no obvious macroscopic orientational or positional order for a wide range of packing densities, and it has been found that the local order in particle clusters is the main order form of tetrahedron packings. Therefore, a cluster analysis is carried out to investigate the local structures and properties of tetrahedron packings in this work. We obtain a cluster distribution of differently sized clusters, and peaks are observed at two special clusters, i.e., dimer and wagon wheel. We then calculate the amounts of dimers and wagon wheels, which are observed to have linear or approximate linear correlations with packing density. Following our previous work, the amount of particles participating in dimers is used as an order metric to evaluate the order degree of the hierarchical packing structure of tetrahedra, and an order map is consequently depicted. Furthermore, a constraint analysis is performed to determine the isostatic or hyperstatic region in the order map. We employ a Monte Carlo algorithm to test jamming and then suggest a new maximally random jammed packing of hard tetrahedra from the order map with a packing density of 0.6337.

X-ray spectral observations of clusters of galaxies undergoing merger events

NASA Astrophysics Data System (ADS)

Henriksen, Mark J.

1993-09-01

We have analyzed the HEAO 1 A2 observations of two clusters whose optical and X-ray isophotes are suggestive of merging subclusters, A119 and A754, and find evidence of nonisothermal X-ray emission from both clusters. The X-ray spectrum of both clusters, when fitted with a single isothermal model, shows residual soft X-ray emission. There is a statistically significant reduction in chi-squared (98 percent probability based on the F-test) when a second temperature component is added. If the asymmetric isophotes seen in the soft X-ray image are indicative of merging subclusters, then our analysis of the Einstein IPC spectra and Solid State Spectrometer observations of A754, which provide some spatial and spectral resolution, suggests that the two temperature components seen in the HEAO 1 A2 spectra are associated with gas trapped in the subcluster potential wells. The implied subcluster isothermal masses suggest that a more massive cluster is accreting a less massive companion in A754. The present observations cannot rule out the alternative possibility that the cooler gas is associated with the outer cluster atmosphere rather than individual subclusters, as appears to be the case for A119. Astro D observations will be necessary to distinguish between these two possibilities for both clusters.

Breaking Self-Similarity in Poor Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Kempner, J. C.; David, L. P.

2005-12-01

The large scatter in the LX--TX relation among poor clusters in the ˜2--4 keV range indicates that the self-similarity seen among hotter clusters does not apply to their cooler siblings. Many forms of non-gravitational heating have been proposed to break this self-similarity, including cluster mergers, AGN heating, and supernova ``pre-heating.'' We present an analysis of a sample of poor clusters from the Chandra and XMM archives that suggests a cycle of heating and cooling in the cores of these clusters is responsible for the departures from self-similarity. That these differences exist only in the core is strongly suggestive of AGN heating as the dominant mechanism. Support for this work was provided by the National Aeronautics and Space Administration through Chandra Award Number G05-5138A issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-39073, and by NASA contract NAG5-12933.

Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding

PubMed Central

Rajan, Aruna; Freddolino, Peter L.; Schulten, Klaus

2010-01-01

Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous. PMID:20419160

Going beyond clustering in MD trajectory analysis: an application to villin headpiece folding.

PubMed

Rajan, Aruna; Freddolino, Peter L; Schulten, Klaus

2010-04-15

Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous.

Topic modeling for cluster analysis of large biological and medical datasets

PubMed Central

2014-01-01

Background The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. Results In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Conclusion Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets. PMID:25350106

Topic modeling for cluster analysis of large biological and medical datasets.

PubMed

Zhao, Weizhong; Zou, Wen; Chen, James J

2014-01-01

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets.

Clustering of worry appraisals among college students.

PubMed

Schwab, Nicholas G; Cullum, Jerry C; Harton, Helen C

2016-01-01

The present study investigated the potential clustering of worry appraisals within college social networks. Participants living in campus residence buildings responded to online surveys across the course of several months. Worry appraisals were measured 10 weeks into the fall semester and again approximately 6 months later. Analysis of sociometric data suggests that the majority of participants' social interactions occurred within their respective residence building floors, indicating that proximity strongly influenced the development of social network ties and sources of social influence. Further, significant clustering of worry appraisals occurred across time, and more importantly, within residence building floors. The present findings compliment previous work suggesting that several physical and psychological states appear to spread and cluster within social networks. Implications for the study of emotional appraisals and future research are discussed.

Revisiting the variation of clustering coefficient of biological networks suggests new modular structure.

PubMed

Hao, Dapeng; Ren, Cong; Li, Chuanxing

2012-05-01

A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling). Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn't show dependence of degree. Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to "deterministic model" of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

Profiling of experiential pleasure, emotional regulation and emotion expression in patients with schizophrenia.

PubMed

Zou, Ying-Min; Ni, Ke; Yang, Zhuo-Ya; Li, Ying; Cai, Xin-Lu; Xie, Dong-Jie; Zhang, Rui-Ting; Zhou, Fu-Chun; Li, Wen-Xiu; Lui, Simon S Y; Shum, David H K; Cheung, Eric F C; Chan, Raymond C K

2018-05-01

Emotion deficits may be the basis of negative symptoms in schizophrenia patients and they are prevalent in these patients. However, inconsistent findings about emotion deficits in schizophrenia suggest that there may be subtypes. The present study aimed to examine and profile experiential pleasure, emotional regulation and expression in patients with schizophrenia. A set of checklists specifically capturing experiential pleasure, emotional regulation, emotion expression, depressive symptoms and anhedonia were administered to 146 in-patients with schizophrenia and 73 demographically-matched healthy controls. Psychiatric symptoms and negative symptoms were also evaluated by a trained psychiatrist for patients with schizophrenia. Two-stage cluster analysis and discriminant function analysis were used to analyze the profile of these measures in patients with schizophrenia. We found a three-cluster solution. Cluster 1 (n=41) was characterized by a deficit in experiential pleasure and emotional regulation, Cluster 2 (n=47) was characterized by a general deficit in experiential pleasure, emotional regulation and emotion expression, and Cluster 3 (n=57) was characterized by a deficit in emotion expression. Results of a discriminant function analysis indicated that the three groups were reasonably discrete. The present findings suggest that schizophrenia patients can be classified into three subtypes based on experiential pleasure, emotional regulation and emotion expression, which are characterized by distinct clinical representations. Copyright © 2017 Elsevier B.V. All rights reserved.

Ultra-small rhenium clusters supported on graphene.

PubMed

Miramontes, Orlando; Bonafé, Franco; Santiago, Ulises; Larios-Rodriguez, Eduardo; Velázquez-Salazar, Jesús J; Mariscal, Marcelo M; Yacaman, Miguel José

2015-03-28

The adsorption of very small rhenium clusters (2-13 atoms) supported on graphene was studied by high-angle annular dark field-scanning transmission electron microscopy (HAADF-STEM). The atomic structure of the clusters was fully resolved with the aid of density functional theory calculations and STEM simulations. It was found that octahedral and tetrahedral structures work as seeds to obtain more complex morphologies. Finally, a detailed analysis of the electronic structure suggested that a higher catalytic effect can be expected in Re clusters when adsorbed on graphene than in isolated ones.

Ultra-small rhenium clusters supported on graphene

PubMed Central

Miramontes, Orlando; Bonafé, Franco; Santiago, Ulises; Larios-Rodriguez, Eduardo; Velázquez-Salazar, Jesús J.; Mariscal, Marcelo M.; Yacaman, Miguel José

2015-01-01

The adsorption of very small rhenium clusters (2 – 13 atoms) supported on graphene was studied with high annular dark field - scanning transmission electron microscopy (HAADF-STEM). The atomic structure of the clusters was fully resolved with the aid of density functional calculations and STEM simulations. It was found that octahedral and tetrahedral structures work as seeds to obtain more complex morphologies. Finally, a detailed analysis of the electronic structure suggested that a higher catalytic effect can be expected in Re clusters when adsorbed on graphene than in isolated ones. PMID:25721176

Delineation of Stenotrophomonas maltophilia isolates from cystic fibrosis patients by fatty acid methyl ester profiles and matrix-assisted laser desorption/ionization time-of-flight mass spectra using hierarchical cluster analysis and principal component analysis.

PubMed

Vidigal, Pedrina Gonçalves; Mosel, Frank; Koehling, Hedda Luise; Mueller, Karl Dieter; Buer, Jan; Rath, Peter Michael; Steinmann, Joerg

2014-12-01

Stenotrophomonas maltophilia is an opportunist multidrug-resistant pathogen that causes a wide range of nosocomial infections. Various cystic fibrosis (CF) centres have reported an increasing prevalence of S. maltophilia colonization/infection among patients with this disease. The purpose of this study was to assess specific fingerprints of S. maltophilia isolates from CF patients (n = 71) by investigating fatty acid methyl esters (FAMEs) through gas chromatography (GC) and highly abundant proteins by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and to compare them with isolates obtained from intensive care unit (ICU) patients (n = 20) and the environment (n = 11). Principal component analysis (PCA) of GC-FAME patterns did not reveal a clustering corresponding to distinct CF, ICU or environmental types. Based on the peak area index, it was observed that S. maltophilia isolates from CF patients produced significantly higher amounts of fatty acids in comparison with ICU patients and the environmental isolates. Hierarchical cluster analysis (HCA) based on the MALDI-TOF MS peak profiles of S. maltophilia revealed the presence of five large clusters, suggesting a high phenotypic diversity. Although HCA of MALDI-TOF mass spectra did not result in distinct clusters predominantly composed of CF isolates, PCA revealed the presence of a distinct cluster composed of S. maltophilia isolates from CF patients. Our data suggest that S. maltophilia colonizing CF patients tend to modify not only their fatty acid patterns but also their protein patterns as a response to adaptation in the unfavourable environment of the CF lung. © 2014 The Authors.

Cluster size selectivity in the product distribution of ethene dehydrogenation on niobium clusters.

PubMed

Parnis, J Mark; Escobar-Cabrera, Eric; Thompson, Matthew G K; Jacula, J Paul; Lafleur, Rick D; Guevara-García, Alfredo; Martínez, Ana; Rayner, David M

2005-08-18

Ethene reactions with niobium atoms and clusters containing up to 25 constituent atoms have been studied in a fast-flow metal cluster reactor. The clusters react with ethene at about the gas-kinetic collision rate, indicating a barrierless association process as the cluster removal step. Exceptions are Nb8 and Nb10, for which a significantly diminished rate is observed, reflecting some cluster size selectivity. Analysis of the experimental primary product masses indicates dehydrogenation of ethene for all clusters save Nb10, yielding either Nb(n)C2H2 or Nb(n)C2. Over the range Nb-Nb6, the extent of dehydrogenation increases with cluster size, then decreases for larger clusters. For many clusters, secondary and tertiary product masses are also observed, showing varying degrees of dehydrogenation corresponding to net addition of C2H4, C2H2, or C2. With Nb atoms and several small clusters, formal addition of at least six ethene molecules is observed, suggesting a polymerization process may be active. Kinetic analysis of the Nb atom and several Nb(n) cluster reactions with ethene shows that the process is consistent with sequential addition of ethene units at rates corresponding approximately to the gas-kinetic collision frequency for several consecutive reacting ethene molecules. Some variation in the rate of ethene pick up is found, which likely reflects small energy barriers or steric constraints associated with individual mechanistic steps. Density functional calculations of structures of Nb clusters up to Nb(6), and the reaction products Nb(n)C2H2 and Nb(n)C2 (n = 1...6) are presented. Investigation of the thermochemistry for the dehydrogenation of ethene to form molecular hydrogen, for the Nb atom and clusters up to Nb6, demonstrates that the exergonicity of the formation of Nb(n)C2 species increases with cluster size over this range, which supports the proposal that the extent of dehydrogenation is determined primarily by thermodynamic constraints. Analysis of the structural variations present in the cluster species studied shows an increase in C-H bond lengths with cluster size that closely correlates with the increased thermodynamic drive to full dehydrogenation. This correlation strongly suggests that all steps in the reaction are barrierless, and that weakening of the C-H bonds is directly reflected in the thermodynamics of the overall dehydrogenation process. It is also demonstrated that reaction exergonicity in the initial partial dehydrogenation step must be carried through as excess internal energy into the second dehydrogenation step.

Constraining AGN triggering mechanisms through the clustering analysis of active black holes

NASA Astrophysics Data System (ADS)

Gatti, M.; Shankar, F.; Bouillot, V.; Menci, N.; Lamastra, A.; Hirschmann, M.; Fiore, F.

2016-02-01

The triggering mechanisms for active galactic nuclei (AGN) are still debated. Some of the most popular ones include galaxy interactions (IT) and disc instabilities (DIs). Using an advanced semi-analytic model (SAM) of galaxy formation, coupled to accurate halo occupation distribution modelling, we investigate the imprint left by each separate triggering process on the clustering strength of AGN at small and large scales. Our main results are as follows: (I) DIs, irrespective of their exact implementation in the SAM, tend to fall short in triggering AGN activity in galaxies at the centre of haloes with Mh > 1013.5 h-1 M⊙. On the contrary, the IT scenario predicts abundance of active central galaxies that generally agrees well with observations at every halo mass. (II) The relative number of satellite AGN in DIs at intermediate-to-low luminosities is always significantly higher than in IT models, especially in groups and clusters. The low AGN satellite fraction predicted for the IT scenario might suggest that different feeding modes could simultaneously contribute to the triggering of satellite AGN. (III) Both scenarios are quite degenerate in matching large-scale clustering measurements, suggesting that the sole average bias might not be an effective observational constraint. (IV) Our analysis suggests the presence of both a mild luminosity and a more consistent redshift dependence in the AGN clustering, with AGN inhabiting progressively less massive dark matter haloes as the redshift increases. We also discuss the impact of different observational selection cuts in measuring AGN clustering, including possible discrepancies between optical and X-ray surveys.

Transcriptional profiles of Arabidopsis stomataless mutants reveal developmental and physiological features of life in the absence of stomata

PubMed Central

de Marcos, Alberto; Triviño, Magdalena; Pérez-Bueno, María Luisa; Ballesteros, Isabel; Barón, Matilde; Mena, Montaña; Fenoll, Carmen

2015-01-01

Loss of function of the positive stomata development regulators SPCH or MUTE in Arabidopsis thaliana renders stomataless plants; spch-3 and mute-3 mutants are extreme dwarfs, but produce cotyledons and tiny leaves, providing a system to interrogate plant life in the absence of stomata. To this end, we compared their cotyledon transcriptomes with that of wild-type plants. K-means clustering of differentially expressed genes generated four clusters: clusters 1 and 2 grouped genes commonly regulated in the mutants, while clusters 3 and 4 contained genes distinctively regulated in mute-3. Classification in functional categories and metabolic pathways of genes in clusters 1 and 2 suggested that both mutants had depressed secondary, nitrogen and sulfur metabolisms, while only a few photosynthesis-related genes were down-regulated. In situ quenching analysis of chlorophyll fluorescence revealed limited inhibition of photosynthesis. This and other fluorescence measurements matched the mutant transcriptomic features. Differential transcriptomes of both mutants were enriched in growth-related genes, including known stomata development regulators, which paralleled their epidermal phenotypes. Analysis of cluster 3 was not informative for developmental aspects of mute-3. Cluster 4 comprised genes differentially up−regulated in mute−3, 35% of which were direct targets for SPCH and may relate to the unique cell types of mute−3. A screen of T-DNA insertion lines in genes differentially expressed in the mutants identified a gene putatively involved in stomata development. A collection of lines for conditional overexpression of transcription factors differentially expressed in the mutants rendered distinct epidermal phenotypes, suggesting that these proteins may be novel stomatal development regulators. Thus, our transcriptome analysis represents a useful source of new genes for the study of stomata development and for characterizing physiology and growth in the absence of stomata. PMID:26157447

Whole Genome Sequence and Phylogenetic Analysis Show Helicobacter pylori Strains from Latin America Have Followed a Unique Evolution Pathway

PubMed Central

Muñoz-Ramírez, Zilia Y.; Mendez-Tenorio, Alfonso; Kato, Ikuko; Bravo, Maria M.; Rizzato, Cosmeri; Thorell, Kaisa; Torres, Roberto; Aviles-Jimenez, Francisco; Camorlinga, Margarita; Canzian, Federico; Torres, Javier

2017-01-01

Helicobacter pylori (HP) genetics may determine its clinical outcomes. Despite high prevalence of HP infection in Latin America (LA), there have been no phylogenetic studies in the region. We aimed to understand the structure of HP populations in LA mestizo individuals, where gastric cancer incidence remains high. The genome of 107 HP strains from Mexico, Nicaragua and Colombia were analyzed with 59 publicly available worldwide genomes. To study bacterial relationship on whole genome level we propose a virtual hybridization technique using thousands of high-entropy 13 bp DNA probes to generate fingerprints. Phylogenetic virtual genome fingerprint (VGF) was compared with Multi Locus Sequence Analysis (MLST) and with phylogenetic analyses of cagPAI virulence island sequences. With MLST some Nicaraguan and Mexican strains clustered close to Africa isolates, whereas European isolates were spread without clustering and intermingled with LA isolates. VGF analysis resulted in increased resolution of populations, separating European from LA strains. Furthermore, clusters with exclusively Colombian, Mexican, or Nicaraguan strains were observed, where the Colombian cluster separated from Europe, Asia, and Africa, while Nicaraguan and Mexican clades grouped close to Africa. In addition, a mixed large LA cluster including Mexican, Colombian, Nicaraguan, Peruvian, and Salvadorian strains was observed; all LA clusters separated from the Amerind clade. With cagPAI sequence analyses LA clades clearly separated from Europe, Asia and Amerind, and Colombian strains formed a single cluster. A NeighborNet analyses suggested frequent and recent recombination events particularly among LA strains. Results suggests that in the new world, H. pylori has evolved to fit mestizo LA populations, already 500 years after the Spanish colonization. This co-adaption may account for regional variability in gastric cancer risk. PMID:28293542

Effects of Dexamethasone and Placebo on Symptom Clusters in Advanced Cancer Patients: A Preliminary Report.

PubMed

Yennurajalingam, Sriram; Williams, Janet L; Chisholm, Gary; Bruera, Eduardo

2016-03-01

Advanced cancer patients frequently experience debilitating symptoms that occur in clusters, but few pharmacological studies have targeted symptom clusters. Our objective was to examine the effects of dexamethasone on symptom clusters in patients with advanced cancer. We reviewed the data from a previous randomized clinical trial to determine the effects of dexamethasone on cancer symptoms. Symptom clusters were identified according to baseline symptoms by using principal component analysis. Correlations and change in the severity of symptom clusters were analyzed after study treatment. A total of 114 participants were included in this study. Three clusters were identified: fatigue/anorexia-cachexia/depression (FAD), sleep/anxiety/drowsiness (SAD), and pain/dyspnea (PD). Changes in severity of FAD and PD significantly correlated over time (at baseline, day 8, and day 15). The FAD cluster was associated with significant improvement in severity at day 8 and day 15, whereas no significant change was observed with the SAD cluster or PD cluster after dexamethasone treatment. The results of this preliminary study suggest significant correlation over time and improvement in the FAD cluster at day 8 and day 15 after treatment with dexamethasone. These findings suggest that fatigue, anorexia-cachexia, and depression may share a common pathophysiologic basis. Further studies are needed to investigate this cluster and target anti-inflammatory therapies. ©AlphaMed Press.

Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis.

PubMed

El Ansari, Walid; Ssewanyana, Derrick; Stock, Christiane

2018-01-01

Limited research has explored clustering of lifestyle behavioral risk factors (BRFs) among university students. This study aimed to explore clustering of BRFs, composition of clusters, and the association of the clusters with self-rated health and perceived academic performance. We assessed (BRFs), namely tobacco smoking, physical inactivity, alcohol consumption, illicit drug use, unhealthy nutrition, and inadequate sleep, using a self-administered general Student Health Survey among 3,706 undergraduates at seven UK universities. A two-step cluster analysis generated: Cluster 1 (the high physically active and health conscious) with very high health awareness/consciousness, good nutrition, and physical activity (PA), and relatively low alcohol, tobacco, and other drug (ATOD) use. Cluster 2 (the abstinent) had very low ATOD use, high health awareness, good nutrition, and medium high PA. Cluster 3 (the moderately health conscious) included the highest regard for healthy eating, second highest fruit/vegetable consumption, and moderately high ATOD use. Cluster 4 (the risk taking) showed the highest ATOD use, were the least health conscious, least fruit consuming, and attached the least importance on eating healthy. Compared to the healthy cluster (Cluster 1), students in other clusters had lower self-rated health, and particularly, students in the risk taking cluster (Cluster 4) reported lower academic performance. These associations were stronger for men than for women. Of the four clusters, Cluster 4 had the youngest students. Our results suggested that prevention among university students should address multiple BRFs simultaneously, with particular focus on the younger students.

Optimal wavelength band clustering for multispectral iris recognition.

PubMed

Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

2012-07-01

This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

Phylogenetic Evidence for Lateral Gene Transfer in the Intestine of Marine Iguanas

PubMed Central

Nelson, David M.; Cann, Isaac K. O.; Altermann, Eric; Mackie, Roderick I.

2010-01-01

Background Lateral gene transfer (LGT) appears to promote genotypic and phenotypic variation in microbial communities in a range of environments, including the mammalian intestine. However, the extent and mechanisms of LGT in intestinal microbial communities of non-mammalian hosts remains poorly understood. Methodology/Principal Findings We sequenced two fosmid inserts obtained from a genomic DNA library derived from an agar-degrading enrichment culture of marine iguana fecal material. The inserts harbored 16S rRNA genes that place the organism from which they originated within Clostridium cluster IV, a well documented group that habitats the mammalian intestinal tract. However, sequence analysis indicates that 52% of the protein-coding genes on the fosmids have top BLASTX hits to bacterial species that are not members of Clostridium cluster IV, and phylogenetic analysis suggests that at least 10 of 44 coding genes on the fosmids may have been transferred from Clostridium cluster XIVa to cluster IV. The fosmids encoded four transposase-encoding genes and an integrase-encoding gene, suggesting their involvement in LGT. In addition, several coding genes likely involved in sugar transport were probably acquired through LGT. Conclusion Our phylogenetic evidence suggests that LGT may be common among phylogenetically distinct members of the phylum Firmicutes inhabiting the intestinal tract of marine iguanas. PMID:20520734

Kinematic gait patterns in healthy runners: A hierarchical cluster analysis.

PubMed

Phinyomark, Angkoon; Osis, Sean; Hettinga, Blayne A; Ferber, Reed

2015-11-05

Previous studies have demonstrated distinct clusters of gait patterns in both healthy and pathological groups, suggesting that different movement strategies may be represented. However, these studies have used discrete time point variables and usually focused on only one specific joint and plane of motion. Therefore, the first purpose of this study was to determine if running gait patterns for healthy subjects could be classified into homogeneous subgroups using three-dimensional kinematic data from the ankle, knee, and hip joints. The second purpose was to identify differences in joint kinematics between these groups. The third purpose was to investigate the practical implications of clustering healthy subjects by comparing these kinematics with runners experiencing patellofemoral pain (PFP). A principal component analysis (PCA) was used to reduce the dimensionality of the entire gait waveform data and then a hierarchical cluster analysis (HCA) determined group sets of similar gait patterns and homogeneous clusters. The results show two distinct running gait patterns were found with the main between-group differences occurring in frontal and sagittal plane knee angles (P<0.001), independent of age, height, weight, and running speed. When these two groups were compared to PFP runners, one cluster exhibited greater while the other exhibited reduced peak knee abduction angles (P<0.05). The variability observed in running patterns across this sample could be the result of different gait strategies. These results suggest care must be taken when selecting samples of subjects in order to investigate the pathomechanics of injured runners. Copyright © 2015 Elsevier Ltd. All rights reserved.

A stellar census in globular clusters with MUSE: The contribution of rotation to cluster dynamics studied with 200 000 stars

NASA Astrophysics Data System (ADS)

Kamann, S.; Husser, T.-O.; Dreizler, S.; Emsellem, E.; Weilbacher, P. M.; Martens, S.; Bacon, R.; den Brok, M.; Giesers, B.; Krajnović, D.; Roth, M. M.; Wendt, M.; Wisotzki, L.

2018-02-01

This is the first of a series of papers presenting the results from our survey of 25 Galactic globular clusters with the MUSE integral-field spectrograph. In combination with our dedicated algorithm for source deblending, MUSE provides unique multiplex capabilities in crowded stellar fields and allows us to acquire samples of up to 20 000 stars within the half-light radius of each cluster. The present paper focuses on the analysis of the internal dynamics of 22 out of the 25 clusters, using about 500 000 spectra of 200 000 individual stars. Thanks to the large stellar samples per cluster, we are able to perform a detailed analysis of the central rotation and dispersion fields using both radial profiles and two-dimensional maps. The velocity dispersion profiles we derive show a good general agreement with existing radial velocity studies but typically reach closer to the cluster centres. By comparison with proper motion data, we derive or update the dynamical distance estimates to 14 clusters. Compared to previous dynamical distance estimates for 47 Tuc, our value is in much better agreement with other methods. We further find significant (>3σ) rotation in the majority (13/22) of our clusters. Our analysis seems to confirm earlier findings of a link between rotation and the ellipticities of globular clusters. In addition, we find a correlation between the strengths of internal rotation and the relaxation times of the clusters, suggesting that the central rotation fields are relics of the cluster formation that are gradually dissipated via two-body relaxation.

Clustering of Health Behaviors and Cardiorespiratory Fitness Among U.S. Adolescents.

PubMed

Hartz, Jacob; Yingling, Leah; Ayers, Colby; Adu-Brimpong, Joel; Rivers, Joshua; Ahuja, Chaarushi; Powell-Wiley, Tiffany M

2018-05-01

Decreased cardiorespiratory fitness (CRF) is associated with an increased risk of cardiovascular disease. However, little is known how the interaction of diet, physical activity (PA), and sedentary time (ST) affects CRF among adolescents. By using a nationally representative sample of U.S. adolescents, we used cluster analysis to investigate the interactions of these behaviors with CRF. We hypothesized that distinct clustering patterns exist and that less healthy clusters are associated with lower CRF. We used 2003-2004 National Health and Nutrition Examination Survey data for persons aged 12-19 years (N = 1,225). PA and ST were measured objectively by an accelerometer, and the American Heart Association Healthy Diet Score quantified diet quality. Maximal oxygen consumption (V˙O 2 ​max) was measured by submaximal treadmill exercise test. We performed cluster analysis to identify sex-specific clustering of diet, PA, and ST. Adjusting for accelerometer wear time, age, body mass index, race/ethnicity, and the poverty-to-income ratio, we performed sex-stratified linear regression analysis to evaluate the association of cluster with V˙O 2 ​max. Three clusters were identified for girls and boys. For girls, there was no difference across clusters for age (p = .1), weight (p = .3), and BMI (p = .5), and no relationship between clusters and V˙O 2 ​max. For boys, the youngest cluster (p < .01) had three healthy behaviors, weighed less, and was associated with a higher V˙O 2 ​max compared with the two older clusters. We observed clustering of diet, PA, and ST in U.S. adolescents. Specific patterns were associated with lower V˙O 2 ​max for boys, suggesting that our clusters may help identify adolescent boys most in need of interventions. Published by Elsevier Inc.

Distinct pathological profiles of inmates showcasing cluster B personality traits, mental disorders and substance use regarding violent behaviors.

PubMed

Dellazizzo, Laura; Dugré, Jules R; Berwald, Marieke; Stafford, Marie-Christine; Côté, Gilles; Potvin, Stéphane; Dumais, Alexandre

2017-12-06

High rates of violence are found amid offenders with severe mental illnesses (SMI), substance use disorders (SUDs) and Cluster B personality disorders. Elevated rates of comorbidity lead to inconsistencies when it comes to this relationship. Furthermore, overlapping Cluster B personality traits have been associated with violence. Using multiple correspondence analysis and cluster analysis, this study was designed to differentiate profiles of 728 male inmates from penitentiary and psychiatric settings marked by personality traits, SMI and SUDs following different violent patterns. Six significantly differing clusters emerged. Cluster 1, "Sensation seekers", presented recklessness with SUDs and low prevalence's of SMI and auto-aggression. Two clusters committed more sexual offenses. While Cluster 2, "Opportunistic-sexual offenders", had more antisocial lifestyles and SUDs, Cluster 6, "Emotional-sexual offenders", displayed more emotional disturbances with SMI and violence. Clusters 3 and 4, representing "Life-course-persistent offenders", shared early signs of persistent antisocial conduct and severe violence. Cluster 3, "Early-onset violent delinquents", emerged as more severely antisocial with SUDs. Cluster 4, "Early-onset unstable-mentally ill delinquents", were more emotionally driven, with SMI and auto-aggression. Cluster 5, "Late-start offenders", was less severely violent, and emotionally driven with antisocial behavior beginning later. This study suggests the presence of specific psychopathological organizations in violent inmates. Copyright © 2017 Elsevier B.V. All rights reserved.

Geographic structure evidenced in the toxic dinoflagellate Alexandrium pacificum Litaker (A. catenella - group IV (Whedon & Kofoid) Balech) along Japanese and Chinese coastal waters.

PubMed

Genovesi, Benjamin; Berrebi, Patrick; Nagai, Satoshi; Reynaud, Nathalie; Wang, Jinhui; Masseret, Estelle

2015-09-15

The intra-specific diversity and genetic structure within the Alexandrium pacificum Litaker (A. catenella - Group IV) populations along the Temperate Asian coasts, were studied among individuals isolated from Japan to China. The UPGMA dendrogram and FCA revealed the existence of 3 clusters. Assignment analysis suggested the occurrence of gene flows between the Japanese Pacific coast (cluster-1) and the Chinese Zhejiang coast (cluster-2). Human transportations are suspected to explain the lack of genetic difference between several pairs of distant Japanese samples, hardly explained by a natural dispersal mechanism. The genetic isolation of the population established in the Sea of Japan (cluster-3) suggested the existence of a strong ecological and geographical barrier. Along the Pacific coasts, the South-North current allows limited exchanges between Chinese and Japanese populations. The relationships between Temperate Asian and Mediterranean individuals suggested different scenario of large-scale dispersal mechanisms. Copyright © 2015. Published by Elsevier Ltd.

Short-term memory and critical clusterization in brain neurons spike series

NASA Astrophysics Data System (ADS)

Bershadskii, A.; Dremencov, E.; Yadid, G.

2003-06-01

A new phenomenon: critical clusterization, is observed in the neuron firing of a genetically defined rat model of depression. The critical clusterization is studied using a multiscaling analysis of the data obtained from the neurons belonging to the Red Nucleus area of the depressive brains. It is suggested that this critical phenomenon can be partially responsible for the observed ill behavior of the depressive brains: loss of short-term motor memory and slow motor reaction.

Analysis of β-Subgroup Proteobacterial Ammonia Oxidizer Populations in Soil by Denaturing Gradient Gel Electrophoresis Analysis and Hierarchical Phylogenetic Probing

PubMed Central

Stephen, John R.; Kowalchuk, George A.; Bruns, Mary-Ann V.; McCaig, Allison E.; Phillips, Carol J.; Embley, T. Martin; Prosser, James I.

1998-01-01

A combination of denaturing gradient gel electrophoresis (DGGE) and oligonucleotide probing was used to investigate the influence of soil pH on the compositions of natural populations of autotrophic β-subgroup proteobacterial ammonia oxidizers. PCR primers specific to this group were used to amplify 16S ribosomal DNA (rDNA) from soils maintained for 36 years at a range of pH values, and PCR products were analyzed by DGGE. Genus- and cluster-specific probes were designed to bind to sequences within the region amplified by these primers. A sequence specific to all β-subgroup ammonia oxidizers could not be identified, but probes specific for Nitrosospira clusters 1 to 4 and Nitrosomonas clusters 6 and 7 (J. R. Stephen, A. E. McCaig, Z. Smith, J. I. Prosser, and T. M. Embley, Appl. Environ. Microbiol. 62:4147–4154, 1996) were designed. Elution profiles of probes against target sequences and closely related nontarget sequences indicated a requirement for high-stringency hybridization conditions to distinguish between different clusters. DGGE banding patterns suggested the presence of Nitrosomonas cluster 6a and Nitrosospira clusters 2, 3, and 4 in all soil plots, but results were ambiguous because of overlapping banding patterns. Unambiguous band identification of the same clusters was achieved by combined DGGE and probing of blots with the cluster-specific radiolabelled probes. The relative intensities of hybridization signals provided information on the apparent selection of different Nitrosospira genotypes in samples of soil of different pHs. The signal from the Nitrosospira cluster 3 probe decreased significantly, relative to an internal control probe, with decreasing soil pH in the range of 6.6 to 3.9, while Nitrosospira cluster 2 hybridization signals increased with increasing soil acidity. Signals from Nitrosospira cluster 4 were greatest at pH 5.5, decreasing at lower and higher values, while Nitrosomonas cluster 6a signals did not vary significantly with pH. These findings are in agreement with a previous molecular study (J. R. Stephen, A. E. McCaig, Z. Smith, J. I. Prosser, and T. M. Embley, Appl. Environ. Microbiol 62:4147–4154, 1996) of the same sites, which demonstrated the presence of the same four clusters of ammonia oxidizers and indicated that selection might be occurring for clusters 2 and 3 at acid and neutral pHs, respectively. The two studies used different sets of PCR primers for amplification of 16S rDNA sequences from soil, and the similar findings suggest that PCR bias was unlikely to be a significant factor. The present study demonstrates the value of DGGE and probing for rapid analysis of natural soil communities of β-subgroup proteobacterial ammonia oxidizers, indicates significant pH-associated differences in Nitrosospira populations, and suggests that Nitrosospira cluster 2 may be of significance for ammonia-oxidizing activity in acid soils. PMID:9687457

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

Phylogenetic analysis of Newcastle disease viruses from Bangladesh suggests continuing evolution of genotype XIII.

PubMed

Barman, Lalita Rani; Nooruzzaman, Mohammed; Sarker, Rahul Deb; Rahman, Md Tazinur; Saife, Md Rajib Bin; Giasuddin, Mohammad; Das, Bidhan Chandra; Das, Priya Mohan; Chowdhury, Emdadul Haque; Islam, Mohammad Rafiqul

2017-10-01

A total of 23 Newcastle disease virus (NDV) isolates from Bangladesh taken between 2010 and 2012 were characterized on the basis of partial F gene sequences. All the isolates belonged to genotype XIII of class II NDV but segregated into three sub-clusters. One sub-cluster with 17 isolates aligned with sub-genotype XIIIc. The other two sub-clusters were phylogenetically distinct from the previously described sub-genotypes XIIIa, XIIIb and XIIIc and could be candidates of new sub-genotypes; however, that needs to be validated through full-length F gene sequence data. The results of the present study suggest that genotype XIII NDVs are under continuing evolution in Bangladesh.

Horizontal transfer of a large and highly toxic secondary metabolic gene cluster between fungi.

PubMed

Slot, Jason C; Rokas, Antonis

2011-01-25

Genes involved in intermediary and secondary metabolism in fungi are frequently physically linked or clustered. For example, in Aspergillus nidulans the entire pathway for the production of sterigmatocystin (ST), a highly toxic secondary metabolite and a precursor to the aflatoxins (AF), is located in a ∼54 kb, 23 gene cluster. We discovered that a complete ST gene cluster in Podospora anserina was horizontally transferred from Aspergillus. Phylogenetic analysis shows that most Podospora cluster genes are adjacent to or nested within Aspergillus cluster genes, although the two genera belong to different taxonomic classes. Furthermore, the Podospora cluster is highly conserved in content, sequence, and microsynteny with the Aspergillus ST/AF clusters and its intergenic regions contain 14 putative binding sites for AflR, the transcription factor required for activation of the ST/AF biosynthetic genes. Examination of ∼52,000 Podospora expressed sequence tags identified transcripts for 14 genes in the cluster, with several expressed at multiple life cycle stages. The presence of putative AflR-binding sites and the expression evidence for several cluster genes, coupled with the recent independent discovery of ST production in Podospora [1], suggest that this HGT event probably resulted in a functional cluster. Given the abundance of metabolic gene clusters in fungi, our finding that one of the largest known metabolic gene clusters moved intact between species suggests that such transfers might have significantly contributed to fungal metabolic diversity. PAPERFLICK: Copyright © 2011 Elsevier Ltd. All rights reserved.

Application of cluster analysis to geochemical compositional data for identifying ore-related geochemical anomalies

NASA Astrophysics Data System (ADS)

Zhou, Shuguang; Zhou, Kefa; Wang, Jinlin; Yang, Genfang; Wang, Shanshan

2017-12-01

Cluster analysis is a well-known technique that is used to analyze various types of data. In this study, cluster analysis is applied to geochemical data that describe 1444 stream sediment samples collected in northwestern Xinjiang with a sample spacing of approximately 2 km. Three algorithms (the hierarchical, k-means, and fuzzy c-means algorithms) and six data transformation methods (the z-score standardization, ZST; the logarithmic transformation, LT; the additive log-ratio transformation, ALT; the centered log-ratio transformation, CLT; the isometric log-ratio transformation, ILT; and no transformation, NT) are compared in terms of their effects on the cluster analysis of the geochemical compositional data. The study shows that, on the one hand, the ZST does not affect the results of column- or variable-based (R-type) cluster analysis, whereas the other methods, including the LT, the ALT, and the CLT, have substantial effects on the results. On the other hand, the results of the row- or observation-based (Q-type) cluster analysis obtained from the geochemical data after applying NT and the ZST are relatively poor. However, we derive some improved results from the geochemical data after applying the CLT, the ILT, the LT, and the ALT. Moreover, the k-means and fuzzy c-means clustering algorithms are more reliable than the hierarchical algorithm when they are used to cluster the geochemical data. We apply cluster analysis to the geochemical data to explore for Au deposits within the study area, and we obtain a good correlation between the results retrieved by combining the CLT or the ILT with the k-means or fuzzy c-means algorithms and the potential zones of Au mineralization. Therefore, we suggest that the combination of the CLT or the ILT with the k-means or fuzzy c-means algorithms is an effective tool to identify potential zones of mineralization from geochemical data.

STAR CLUSTERS IN A NUCLEAR STAR FORMING RING: THE DISAPPEARING STRING OF PEARLS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Väisänen, Petri; Barway, Sudhanshu; Randriamanakoto, Zara, E-mail: petri@saao.ac.za

2014-12-20

An analysis of the star cluster population in a low-luminosity early-type galaxy, NGC 2328, is presented. The clusters are found in a tight star forming nuclear spiral/ring pattern and we also identify a bar from structural two-dimensional decomposition. These massive clusters are forming very efficiently in the circumnuclear environment and they are young, possibly all less than 30 Myr of age. The clusters indicate an azimuthal age gradient, consistent with a ''pearls-on-a-string'' formation scenario, suggesting bar-driven gas inflow. The cluster mass function has a robust down turn at low masses at all age bins. Assuming clusters are born with a power-lawmore » distribution, this indicates extremely rapid disruption at timescales of just several million years. If found to be typical, it means that clusters born in dense circumnuclear rings do not survive to become old globular clusters in non-interacting systems.« less

Heterochromatin influences the secondary metabolite profile in the plant pathogen Fusarium graminearum

PubMed Central

Reyes-Dominguez, Yazmid; Boedi, Stefan; Sulyok, Michael; Wiesenberger, Gerlinde; Stoppacher, Norbert; Krska, Rudolf; Strauss, Joseph

2012-01-01

Chromatin modifications and heterochromatic marks have been shown to be involved in the regulation of secondary metabolism gene clusters in the fungal model system Aspergillus nidulans. We examine here the role of HEP1, the heterochromatin protein homolog of Fusarium graminearum, for the production of secondary metabolites. Deletion of Hep1 in a PH-1 background strongly influences expression of genes required for the production of aurofusarin and the main tricothecene metabolite DON. In the Hep1 deletion strains AUR genes are highly up-regulated and aurofusarin production is greatly enhanced suggesting a repressive role for heterochromatin on gene expression of this cluster. Unexpectedly, gene expression and metabolites are lower for the trichothecene cluster suggesting a positive function of Hep1 for DON biosynthesis. However, analysis of histone modifications in chromatin of AUR and DON gene promoters reveals that in both gene clusters the H3K9me3 heterochromatic mark is strongly reduced in the Hep1 deletion strain. This, and the finding that a DON-cluster flanking gene is up-regulated, suggests that the DON biosynthetic cluster is repressed by HEP1 directly and indirectly. Results from this study point to a conserved mode of secondary metabolite (SM) biosynthesis regulation in fungi by chromatin modifications and the formation of facultative heterochromatin. PMID:22100541

tropical cyclone risk analysis: a decisive role of its track

NASA Astrophysics Data System (ADS)

Chelsea Nam, C.; Park, Doo-Sun R.; Ho, Chang-Hoi

2016-04-01

The tracks of 85 tropical cyclones (TCs) that made landfall to South Korea for the period 1979-2010 are classified into four clusters by using a fuzzy c-means clustering method. The four clusters are characterized by 1) east-short, 2) east-long, 3) west-long, and 4) west-short based on the moving routes around Korean peninsula. We conducted risk comparison analysis for these four clusters regarding their hazards, exposure, and damages. Here, hazard parameters are calculated from two different sources independently, one from the best-track data (BT) and the other from the 60 weather stations over the country (WS). The results show distinct characteristics of the four clusters in terms of the hazard parameters and economic losses (EL), suggesting that there is a clear track-dependency in the overall TC risk. It is appeared that whether there occurred an "effective collision" overweighs the intensity of the TC per se. The EL ranking did not agree with the BT parameters (maximum wind speed, central pressure, or storm radius), but matches to WS parameter (especially, daily accumulated rainfall and TC-influenced period). The west-approaching TCs (i.e. west-long and west-short clusters) generally recorded larger EL than the east-approaching TCs (i.e. east-short and east-long clusters), although the east-long clusters are the strongest in BT point of view. This can be explained through the spatial distribution of the WS parameters and the regional EL maps corresponding to it. West-approaching TCs accompanied heavy rainfall on the southern regions with the helps of the topographic effect on their tracks, and of the extended stay on the Korean Peninsula in their extratropical transition, that were not allowed to the east-approaching TCs. On the other hand, some regions had EL that are not directly proportional to the hazards, and this is partly attributed to spatial disparity in wealth and vulnerability. Correlation analysis also revealed the importance of rainfall; daily accumulated rainfall is the most-correlated with EL among all BT and WS hazard parameters for all clusters except the east-short. The least-correlated hazard parameter is the storm radius which showed significant correlations with EL for only the short clusters. In conclusion, this study suggests that TC track is essential in determining the way it brings damage on South Korea. Thus, it is suggested that the damage warning and adaptation policy need to be different for different TC tracks although South Korea is relatively small compared to average TC size.

Synthesis efficiency of heavy carbon clusters from ETFE ablated by different numbers of laser pulse in vacuum

NASA Astrophysics Data System (ADS)

Shibagaki, K.; Takada, N.; Sasaki, K.; Kadota, K.

2002-09-01

We have carried out mass spectral analysis of positive ions produced by laser ablation of a copolymer of ethylene and tetrafluoroethylene (ETFE: [CH 2CH 2CF 2CF 2] n) in vacuum using time-of-flight mass spectrometry (TOF-MS). The surfaces of the ETFE targets irradiated by different numbers of laser pulse were analyzed by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). Heavy carbon cluster ions C n+ with n≥30 were observed in the mass spectra. The fractional abundance of heavy clusters in the mass spectrum decreased with the number of laser pulse. On the other hand, carbon became rich in the atomic composition of the laser-irradiated surface, and the eroded area on the surface increased with the number of laser pulse. From these results, it is suggested that the carbon-rich material surface results in the less efficient production of heavy carbon clusters. In addition, it is also suggested that clustering reactions in eroded craters do not contribute to the synthesis of heavy clusters.

Cardiovascular reactivity patterns and pathways to hypertension: a multivariate cluster analysis.

PubMed

Brindle, R C; Ginty, A T; Jones, A; Phillips, A C; Roseboom, T J; Carroll, D; Painter, R C; de Rooij, S R

2016-12-01

Substantial evidence links exaggerated mental stress induced blood pressure reactivity to future hypertension, but the results for heart rate reactivity are less clear. For this reason multivariate cluster analysis was carried out to examine the relationship between heart rate and blood pressure reactivity patterns and hypertension in a large prospective cohort (age range 55-60 years). Four clusters emerged with statistically different systolic and diastolic blood pressure and heart rate reactivity patterns. Cluster 1 was characterised by a relatively exaggerated blood pressure and heart rate response while the blood pressure and heart rate responses of cluster 2 were relatively modest and in line with the sample mean. Cluster 3 was characterised by blunted cardiovascular stress reactivity across all variables and cluster 4, by an exaggerated blood pressure response and modest heart rate response. Membership to cluster 4 conferred an increased risk of hypertension at 5-year follow-up (hazard ratio=2.98 (95% CI: 1.50-5.90), P<0.01) that survived adjustment for a host of potential confounding variables. These results suggest that the cardiac reactivity plays a potentially important role in the link between blood pressure reactivity and hypertension and support the use of multivariate approaches to stress psychophysiology.

The Influence of the Host Plant Is the Major Ecological Determinant of the Presence of Nitrogen-Fixing Root Nodule Symbiont Cluster II Frankia Species in Soil

PubMed Central

Battenberg, Kai; Wren, Jannah A.; Hillman, Janell; Edwards, Joseph; Huang, Liujing

2016-01-01

ABSTRACT The actinobacterial genus Frankia establishes nitrogen-fixing root nodule symbioses with specific hosts within the nitrogen-fixing plant clade. Of four genetically distinct subgroups of Frankia, cluster I, II, and III strains are capable of forming effective nitrogen-fixing symbiotic associations, while cluster IV strains generally do not. Cluster II Frankia strains have rarely been detected in soil devoid of host plants, unlike cluster I or III strains, suggesting a stronger association with their host. To investigate the degree of host influence, we characterized the cluster II Frankia strain distribution in rhizosphere soil in three locations in northern California. The presence/absence of cluster II Frankia strains at a given site correlated significantly with the presence/absence of host plants on the site, as determined by glutamine synthetase (glnA) gene sequence analysis, and by microbiome analysis (16S rRNA gene) of a subset of host/nonhost rhizosphere soils. However, the distribution of cluster II Frankia strains was not significantly affected by other potential determinants such as host-plant species, geographical location, climate, soil pH, or soil type. Rhizosphere soil microbiome analysis showed that cluster II Frankia strains occupied only a minute fraction of the microbiome even in the host-plant-present site and further revealed no statistically significant difference in the α-diversity or in the microbiome composition between the host-plant-present or -absent sites. Taken together, these data suggest that host plants provide a factor that is specific for cluster II Frankia strains, not a general growth-promoting factor. Further, the factor accumulates or is transported at the site level, i.e., beyond the host rhizosphere. IMPORTANCE Biological nitrogen fixation is a bacterial process that accounts for a major fraction of net new nitrogen input in terrestrial ecosystems. Transfer of fixed nitrogen to plant biomass is especially efficient via root nodule symbioses, which represent evolutionarily and ecologically specialized mutualistic associations. Frankia spp. (Actinobacteria), especially cluster II Frankia spp., have an extremely broad host range, yet comparatively little is known about the soil ecology of these organisms in relation to the host plants and their rhizosphere microbiomes. This study reveals a strong influence of the host plant on soil distribution of cluster II Frankia spp. PMID:27795313

Species-richness of the Anopheles annulipes Complex (Diptera: Culicidae) Revealed by Tree and Model-Based Allozyme Clustering Analyses

DTIC Science & Technology

2007-01-01

including tree- based methods such as the unweighted pair group method of analysis ( UPGMA ) and Neighbour-joining (NJ) (Saitou & Nei, 1987). By...based Bayesian approach and the tree-based UPGMA and NJ cluster- ing methods. The results obtained suggest that far more species occur in the An...unlikely that groups that differ by more than these levels are conspecific. Genetic distances were clustered using the UPGMA and NJ algorithms in MEGA

Transcriptional analysis of exopolysaccharides biosynthesis gene clusters in Lactobacillus plantarum.

PubMed

Vastano, Valeria; Perrone, Filomena; Marasco, Rosangela; Sacco, Margherita; Muscariello, Lidia

2016-04-01

Exopolysaccharides (EPS) from lactic acid bacteria contribute to specific rheology and texture of fermented milk products and find applications also in non-dairy foods and in therapeutics. Recently, four clusters of genes (cps) associated with surface polysaccharide production have been identified in Lactobacillus plantarum WCFS1, a probiotic and food-associated lactobacillus. These clusters are involved in cell surface architecture and probably in release and/or exposure of immunomodulating bacterial molecules. Here we show a transcriptional analysis of these clusters. Indeed, RT-PCR experiments revealed that the cps loci are organized in five operons. Moreover, by reverse transcription-qPCR analysis performed on L. plantarum WCFS1 (wild type) and WCFS1-2 (ΔccpA), we demonstrated that expression of three cps clusters is under the control of the global regulator CcpA. These results, together with the identification of putative CcpA target sequences (catabolite responsive element CRE) in the regulatory region of four out of five transcriptional units, strongly suggest for the first time a role of the master regulator CcpA in EPS gene transcription among lactobacilli.

A formal concept analysis approach to consensus clustering of multi-experiment expression data

PubMed Central

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological signals. Conclusions The proposed FCA-enhanced consensus clustering technique is a general approach to the combination of clustering algorithms with FCA for deriving clustering solutions from multiple gene expression matrices. The experimental results presented herein demonstrate that it is a robust data integration technique able to produce good quality clustering solution that is representative for the whole set of expression matrices. PMID:24885407

Self-assembly of a tetrahedral 58-nuclear barium vanadium oxide cluster.

PubMed

Kastner, Katharina; Puscher, Bianka; Streb, Carsten

2013-01-07

We report the synthesis and characterization of a molecular barium vanadium oxide cluster featuring high nuclearity and high symmetry. The tetrameric, 2.3 nm cluster H(5)[Ba(10)(NMP)(14)(H(2)O)(8)[V(12)O(33)](4)Br] is based on a bromide-centred, octahedral barium scaffold which is capped by four previously unknown [V(12)O(33)](6-) clusters in a tetrahedral fashion. The compound represents the largest polyoxovanadate-based heterometallic cluster known to date. The cluster is formed in organic solution and it is suggested that the bulky N-methyl-2-pyrrolidone (NMP) solvent ligands allow the isolation of this giant molecule and prevent further condensation to a solid-state metal oxide. The cluster is fully characterized using single-crystal XRD, elemental analysis, ESI mass spectrometry and other spectroscopic techniques.

A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

PubMed

Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

2016-02-01

Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

Chemotaxonomy of heterocystous cyanobacteria using FAME profiling as species markers.

PubMed

Shukla, Ekta; Singh, Satya Shila; Singh, Prashant; Mishra, Arun Kumar

2012-07-01

The fatty acid methyl ester (FAME) analysis of the 12 heterocystous cyanobacterial strains showed different fatty acid profiling based on the presence/absence and the percentage of 13 different types of fatty acids. The major fatty acids viz. palmitic acid (16:0), hexadecadienoic acid (16:2), stearic acid (18:0), oleic acid (18:1), linoleic (18:2), and linolenic acid (18:3) were present among all the strains except Cylindrospermum musicola where oleic acid (18:1) was absent. All the strains showed high levels of polyunsaturated fatty acid (PUFAs; 41-68.35%) followed by saturated fatty acid (SAFAs; 1.82-40.66%) and monounsaturated fatty acid (0.85-24.98%). Highest percentage of PUFAs and essential fatty acid (linolenic acid; 18:3) was reported in Scytonema bohnerii which can be used as fatty acid supplement in medical and biotechnological purpose. The cluster analysis based on FAME profiling suggests the presence of two distinct clusters with Euclidean distance ranging from 0 to 25. S. bohnerii of cluster I was distantly related to the other strains of cluster II. The genotypes of cluster II were further divided into two subclusters, i.e., IIa with C. musicola showing great divergence with the other genotypes of IIb which was further subdivided into two groups. Subsubcluster IIb(1) was represented by a genotype, Anabaena sp. whereas subsubcluster IIb(2) was distinguished by two groups, i.e., one group having significant similarity among their three genotypes showed distant relation with the other group having closely related six genotypes. To test the validity of the fatty acid profiles as a marker, cluster analysis has also been generated on the basis of morphological attributes. Our results suggest that FAME profiling might be used as species markers in the study of polyphasic approach based taxonomy and phylogenetic relationship.

Universal patterns of equilibrium cluster growth in aqueous sugars observed by dynamic light scattering.

PubMed

Sidebottom, D L; Tran, Tri D

2010-11-01

Dynamic light scattering performed on aqueous solutions of three sugars (glucose, maltose and sucrose) reveal a common pattern of sugar cluster formation with a narrow cluster size distribution. In each case, equilibrium clusters form whose size increases with increasing sugar content in an identical power law manner in advance of a common, critical-like, percolation threshold near 83 wt % sugar. The critical exponent of the power law divergence of the cluster size varies with temperature, increasing with decreasing temperature, due to changes in the strength of the intermolecular hydrogen bond and appears to vanish for temperatures in excess of 90 °C. Detailed analysis of the cluster growth process suggests a two-stage process: an initial cluster phase formed at low volume fractions, ϕ, consisting of noninteracting, monodisperse sugar clusters whose size increases ϕ(1/3) followed by an aggregation stage, active at concentrations above about ϕ=40%, where cluster-cluster contact first occurs.

Using Cluster Bootstrapping to Analyze Nested Data With a Few Clusters.

PubMed

Huang, Francis L

2018-04-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials are performed with a low number of clusters (~20 groups). Although multilevel models are often used to analyze nested data, researchers may be concerned of potentially biased results due to having only a few groups under study. Cluster bootstrapping has been suggested as an alternative procedure when analyzing clustered data though it has seen very little use in educational and psychological studies. Using a Monte Carlo simulation that varied the number of clusters, average cluster size, and intraclass correlations, we compared standard errors using cluster bootstrapping with those derived using ordinary least squares regression and multilevel models. Results indicate that cluster bootstrapping, though more computationally demanding, can be used as an alternative procedure for the analysis of clustered data when treatment effects at the group level are of primary interest. Supplementary material showing how to perform cluster bootstrapped regressions using R is also provided.

Identification of the Main Regulator Responsible for Synthesis of the Typical Yellow Pigment Produced by Trichoderma reesei

PubMed Central

Derntl, Christian; Rassinger, Alice; Srebotnik, Ewald; Mach, Robert L.

2016-01-01

ABSTRACT The industrially used ascomycete Trichoderma reesei secretes a typical yellow pigment during cultivation, while other Trichoderma species do not. A comparative genomic analysis suggested that a putative secondary metabolism cluster, containing two polyketide-synthase encoding genes, is responsible for the yellow pigment synthesis. This cluster is conserved in a set of rather distantly related fungi, including Acremonium chrysogenum and Penicillium chrysogenum. In an attempt to silence the cluster in T. reesei, two genes of the cluster encoding transcription factors were individually deleted. For a complete genetic proof-of-function, the genes were reinserted into the genomes of the respective deletion strains. The deletion of the first transcription factor (termed yellow pigment regulator 1 [Ypr1]) resulted in the full abolishment of the yellow pigment formation and the expression of most genes of this cluster. A comparative high-pressure liquid chromatography (HPLC) analysis of supernatants of the ypr1 deletion and its parent strain suggested the presence of several yellow compounds in T. reesei that are all derived from the same cluster. A subsequent gas chromatography/mass spectrometry analysis strongly indicated the presence of sorbicillin in the major HPLC peak. The presence of the second transcription factor, termed yellow pigment regulator 2 (Ypr2), reduces the yellow pigment formation and the expression of most cluster genes, including the gene encoding the activator Ypr1. IMPORTANCE Trichoderma reesei is used for industry-scale production of carbohydrate-active enzymes. During growth, it secretes a typical yellow pigment. This is not favorable for industrial enzyme production because it makes the downstream process more complicated and thus increases operating costs. In this study, we demonstrate which regulators influence the synthesis of the yellow pigment. Based on these data, we also provide indication as to which genes are under the control of these regulators and are finally responsible for the biosynthesis of the yellow pigment. These genes are organized in a cluster that is also found in other industrially relevant fungi, such as the two antibiotic producers Penicillium chrysogenum and Acremonium chrysogenum. The targeted manipulation of a secondary metabolism cluster is an important option for any biotechnologically applied microorganism. PMID:27520818

Cluster analysis differentiates high and low community functioning in schizophrenia: Subgroups differ on working memory but not other neurocognitive domains.

PubMed

Alden, Eva C; Cobia, Derin J; Reilly, James L; Smith, Matthew J

2015-10-01

Schizophrenia is characterized by impairment in multiple aspects of community functioning. Available literature suggests that community functioning may be enhanced through cognitive remediation, however, evidence is limited regarding whether specific neurocognitive domains may be treatment targets. We characterized schizophrenia subjects based on their level of community functioning through cluster analysis in an effort to identify whether specific neurocognitive domains were associated with variation in functioning. Schizophrenia (SCZ, n=60) and control (CON, n=45) subjects completed a functional capacity task, social competence role-play, functional attainment interview, and a neuropsychological battery. Multiple cluster analytic techniques were used on the measures of functioning in the schizophrenia subjects to generate functionally-defined subgroups. MANOVA evaluated between-group differences in neurocognition. The cluster analysis revealed two distinct groups, consisting of 36 SCZ characterized by high levels of community functioning (HF-SCZ) and 24 SCZ with low levels of community functioning (LF-SCZ). There was a main group effect for neurocognitive performance (p<0.001) with CON outperforming both SCZ groups in all neurocognitive domains. Post-hoc tests revealed that HF-SCZ had higher verbal working memory compared to LF-SCZ (p≤0.05, Cohen's d=0.78) but the two groups did not differ in remaining domains. The cluster analysis classified schizophrenia subjects in HF-SCZ and LF-SCZ using a multidimensional assessment of community functioning. Moreover, HF-SCZ demonstrated rather preserved verbal working memory relative to LF-SCZ. The results suggest that verbal working memory may play a critical role in community functioning, and is a potential cognitive treatment target for schizophrenia subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessment of hybridization among wild and cultivated Vigna unguiculata subspecies revealed by arbitrarily primed polymerase chain reaction analysis

PubMed Central

Vijaykumar, Archana; Saini, Ajay; Jawali, Narendra

2012-01-01

Background and aims Intra-species hybridization and incompletely homogenized ribosomal RNA repeat units have earlier been reported in 21 accessions of Vigna unguiculata from six subspecies using internal transcribed spacer (ITS) and 5S intergenic spacer (IGS) analyses. However, the relationships among these accessions were not clear from these analyses. We therefore assessed intra-species hybridization in the same set of accessions. Methodology Arbitrarily primed polymerase chain reaction (AP-PCR) analysis was carried out using 12 primers. The PCR products were resolved on agarose gels and the DNA fragments were scored manually. Genetic relationships were inferred by TREECON software using unweighted paired group method with arithmetic averages (UPGMA) cluster analysis evaluated by bootstrapping and compared with previous analyses based on ITS and 5S IGS. Principal results A total of 202 (86 %) fragments were found to be polymorphic and used for generating a genetic distance matrix. Twenty-one V. unguiculata accessions were grouped into three main clusters. The cultivated subspecies (var. unguiculata) and most of its wild progenitors (var. spontanea) were placed in cluster I along with ssp. pubescens and ssp. stenophylla. Whereas var. spontanea were grouped with ssp. alba and ssp. tenuis accessions in cluster II, ssp. alba and ssp. baoulensis were included in cluster III. Close affinities of ssp. unguiculata, ssp. alba and ssp. tenuis suggested inter-subspecies hybridization. Conclusions Multi-locus AP-PCR analysis reveals that intra-species hybridization is prevalent among V. unguiculata subspecies and suggests that grouping of accessions from two different subspecies is not solely due to the similarity in the ITS and 5S IGS regions but also due to other regions of the genome. PMID:22619698

An application of cluster detection to scene analysis

NASA Technical Reports Server (NTRS)

Rosenfeld, A. H.; Lee, Y. H.

1971-01-01

Certain arrangements of local features in a scene tend to group together and to be seen as units. It is suggested that in some instances, this phenomenon might be interpretable as a process of cluster detection in a graph-structured space derived from the scene. This idea is illustrated using a class of scenes that contain only horizontal and vertical line segments.

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Analysis of basic clustering algorithms for numerical estimation of statistical averages in biomolecules.

PubMed

Anandakrishnan, Ramu; Onufriev, Alexey

2008-03-01

In statistical mechanics, the equilibrium properties of a physical system of particles can be calculated as the statistical average over accessible microstates of the system. In general, these calculations are computationally intractable since they involve summations over an exponentially large number of microstates. Clustering algorithms are one of the methods used to numerically approximate these sums. The most basic clustering algorithms first sub-divide the system into a set of smaller subsets (clusters). Then, interactions between particles within each cluster are treated exactly, while all interactions between different clusters are ignored. These smaller clusters have far fewer microstates, making the summation over these microstates, tractable. These algorithms have been previously used for biomolecular computations, but remain relatively unexplored in this context. Presented here, is a theoretical analysis of the error and computational complexity for the two most basic clustering algorithms that were previously applied in the context of biomolecular electrostatics. We derive a tight, computationally inexpensive, error bound for the equilibrium state of a particle computed via these clustering algorithms. For some practical applications, it is the root mean square error, which can be significantly lower than the error bound, that may be more important. We how that there is a strong empirical relationship between error bound and root mean square error, suggesting that the error bound could be used as a computationally inexpensive metric for predicting the accuracy of clustering algorithms for practical applications. An example of error analysis for such an application-computation of average charge of ionizable amino-acids in proteins-is given, demonstrating that the clustering algorithm can be accurate enough for practical purposes.

Ambiguity and judgments of obese individuals: no news could be bad news.

PubMed

Ross, Kathryn M; Shivy, Victoria A; Mazzeo, Suzanne E

2009-08-01

Stigmatization towards obese individuals has not decreased despite the increasing prevalence of obesity. Nonetheless, stigmatization remains difficult to study, given concerns about social desirability. To address this issue, this study used paired comparisons and cluster analysis to examine how undergraduates (n=189) categorized scenarios describing the health-related behaviors of obese individuals. The cluster analysis found that the scenarios were categorized into two distinct clusters. The first cluster included all scenarios with health behaviors indicating high responsibility for body weight. These individuals were perceived as unattractive, lazy, less likeable, less disciplined, and more deserving of their condition compared to individuals in the second cluster, which included all scenarios with health behaviors indicating low responsibility for body weight. Four scenarios depicted obese individuals with ambiguous information regarding health behaviors; three out of these four individuals were categorized in the high-responsibility cluster. These findings suggested that participants viewed these individuals as negatively as those who were responsible for their condition. These results have practical implications for reducing obesity bias, as the etiology of obesity is typically not known in real-life situations.

CXB surface brightness fluctuations: A new frontier of ICM structure and outskirts studies of (un)resolved galaxy clusters?

NASA Astrophysics Data System (ADS)

Kolodzig, A.; Gilfanov, M.; Hutsi, G.; Sunyaev, R.

2017-10-01

Surface brightness fluctuations of the cosmic X-ray background (CXB) carry unique information about the intracluster-medium (ICM) structure of galaxy clusters and groups up to the virial radius, which is inaccessible by conventional observations of selected nearby resolved clusters. We present results of our CXB fluctuation analysis of the ˜5ks-deep, ˜9deg^2-large Chandra survey XBOOTES. We find that our fluctuation signal of resolved clusters is dominated by nearby, high-luminosity sources. The shape of its power spectrum suggests that for the brightest cluster we are sensitive to the ICM structure up to ˜2× R_{500};(˜2 Mpc/h). The energy spectrum of the fluctuation signal from resolved and unresolved clusters follows a typical ICM spectrum, where redshifts and temperatures are consistent with expectations. It also demonstrates that fluctuations of our unresolved CXB are dominated by unresolved clusters with an average z˜0.4 and T˜1.3keV, suggesting an average L_{0.5-2keV}˜3×10^{42} erg/s and M_{500}˜4×10^{13} M_{Sun}/h. Comparison with modeling suggests, that our fluctuation signal can be described with the one-halo-term of clusters and that it might be sensitive to the presence of substructures. Discrepancies between model and measurement could be utilized to improve our understanding of the ICM structure in a statistical manner. We briefly discuss the potential of larger surveys (e.g. Stripe82, XXL, SRG/eRosita).

Genetic Diversity of Picocyanobacteria in Tibetan Lakes: Assessing the Endemic and Universal Distributions

PubMed Central

Hu, Anyi; Liu, Xiaobo; Chen, Feng; Yao, Tandong; Jiao, Nianzhi

2014-01-01

The phylogenetic diversity of picocyanobacteria in seven alkaline lakes on the Tibetan Plateau was analyzed using the molecular marker 16S-23S rRNA internal transcribed spacer sequence. A total of 1,077 environmental sequences retrieved from the seven lakes were grouped into seven picocyanobacterial clusters, with two clusters newly described here. Each of the lakes was dominated by only one or two clusters, while different lakes could have disparate communities, suggesting low alpha diversity but high beta diversity of picocyanobacteria in these high-altitude freshwater and saline lakes. Several globally distributed clusters were found in these Tibetan lakes, such as subalpine cluster I and the Cyanobium gracile cluster. Although other clusters likely exhibit geographic restriction to the plateau temporally, reflecting endemicity, they can indeed be distributed widely on the plateau. Lakes with similar salinities may have similar genetic populations despite a large geographic distance. Canonical correspondence analysis identified salinity as the only environmental factor that may in part explain the diversity variations among lakes. Mantel tests suggested that the community similarities among lakes are independent of geographic distance. A portion of the picocyanobacterial clusters appear to be restricted to a narrow salinity range, while others are likely adapted to a broad range. A seasonal survey of Lake Namucuo across 3 years did not show season-related variations in diversity, and depth-related population partitioning was observed along a vertical profile of the lake. Our study emphasizes the high dispersive potential of picocyanobacteria and suggests that the regional distribution may result from adaptation to specified environments. PMID:25281375

Activation and comparative analysis of cryptic xiamycin gene cluster from marine-derived Streptomyces sp. FXJ 7.388.

PubMed

Uhong Lü, Yuhong; Liu, Xiaoli; Wang, Miao; Li, Yuanyuan; Liu, Ning; Bao, Yuxin; Liu, Minghao; Li, Xiaoqian; Wang, Yinyin; Qian, Shenyan; Yue, Changwu; Huang, Ying

2016-09-01

In order to obtain the natural products synthesized by the three putative xiamycin biosynthesis gene clusters which were predicted via antiSMASH during the genome mining of marine Streptomyces sp. FXJ 7.388, Streptomyces sp. FXJ 8.012, and Streptomyces olivaceus FXJ 7.023. Sixteen genes involved in xiamycin assembly, modification, and regulation with higher identity than the newest reported xiamycin biosynthetic gene cluster from marine Streptomyces sp. SCSIO 02999, Streptomyces sp. HKI0576, and Streptomyces sp. FXJ 7.388 were discovered via gene cluster comparative analysis. A ribosome engineering strategy was adopted to activate such cryptic gene clusters with different final concentrations antibiotics that act on the ribosome, and two indolosesquiterpenes were isolated from idlethaldose streptomycin-resistant Streptomyces sp. FXJ 7.388 strains. However, no such product was detected in Streptomyces sp. FXJ 8.012 and Streptomyces olivaceus FXJ 7.023 under the same treatment. This result suggested that these genes might hold the least gene content for xiamycin biosynthesis.

MOCCA-SURVEY Database I: Is NGC 6535 a dark star cluster harbouring an IMBH?

NASA Astrophysics Data System (ADS)

Askar, Abbas; Bianchini, Paolo; de Vita, Ruggero; Giersz, Mirek; Hypki, Arkadiusz; Kamann, Sebastian

2017-01-01

We describe the dynamical evolution of a unique type of dark star cluster model in which the majority of the cluster mass at Hubble time is dominated by an intermediate-mass black hole (IMBH). We analysed results from about 2000 star cluster models (Survey Database I) simulated using the Monte Carlo code MOnte Carlo Cluster simulAtor and identified these dark star cluster models. Taking one of these models, we apply the method of simulating realistic `mock observations' by utilizing the Cluster simulatiOn Comparison with ObservAtions (COCOA) and Simulating Stellar Cluster Observation (SISCO) codes to obtain the photometric and kinematic observational properties of the dark star cluster model at 12 Gyr. We find that the perplexing Galactic globular cluster NGC 6535 closely matches the observational photometric and kinematic properties of the dark star cluster model presented in this paper. Based on our analysis and currently observed properties of NGC 6535, we suggest that this globular cluster could potentially harbour an IMBH. If it exists, the presence of this IMBH can be detected robustly with proposed kinematic observations of NGC 6535.

Did factory girls make bad mothers? Women's labor market experience, motherhood, and children's mortality risks in the past.

PubMed

Janssens, Angélique; Pelzer, Ben

2012-01-01

Prior research has suggested that the quality of maternal care given to infants and small children plays an important role in the strong clustering of children's deaths. In this article, we investigate the quality of maternal care provided by those women who most nineteenth-century social commentators declared would never make good housewives or mothers: the young girls and women working in textile mills. We carried out this examination using an analysis of children's mortality risks in two textile cities in The Netherlands between roughly 1900 and 1930. Our analysis suggests that these children's clustered mortality risks cannot have resulted from either their mothers' labor market experience or biological or genetic factors.

Cluster Analysis of Acute Care Use Yields Insights for Tailored Pediatric Asthma Interventions.

PubMed

Abir, Mahshid; Truchil, Aaron; Wiest, Dawn; Nelson, Daniel B; Goldstick, Jason E; Koegel, Paul; Lozon, Marie M; Choi, Hwajung; Brenner, Jeffrey

2017-09-01

We undertake this study to understand patterns of pediatric asthma-related acute care use to inform interventions aimed at reducing potentially avoidable hospitalizations. Hospital claims data from 3 Camden city facilities for 2010 to 2014 were used to perform cluster analysis classifying patients aged 0 to 17 years according to their asthma-related hospital use. Clusters were based on 2 variables: asthma-related ED visits and hospitalizations. Demographics and a number of sociobehavioral and use characteristics were compared across clusters. Children who met the criteria (3,170) were included in the analysis. An examination of a scree plot showing the decline in within-cluster heterogeneity as the number of clusters increased confirmed that clusters of pediatric asthma patients according to hospital use exist in the data. Five clusters of patients with distinct asthma-related acute care use patterns were observed. Cluster 1 (62% of patients) showed the lowest rates of acute care use. These patients were least likely to have a mental health-related diagnosis, were less likely to have visited multiple facilities, and had no hospitalizations for asthma. Cluster 2 (19% of patients) had a low number of asthma ED visits and onetime hospitalization. Cluster 3 (11% of patients) had a high number of ED visits and low hospitalization rates, and the highest rates of multiple facility use. Cluster 4 (7% of patients) had moderate ED use for both asthma and other illnesses, and high rates of asthma hospitalizations; nearly one quarter received care at all facilities, and 1 in 10 had a mental health diagnosis. Cluster 5 (1% of patients) had extreme rates of acute care use. Differences observed between groups across multiple sociobehavioral factors suggest these clusters may represent children who differ along multiple dimensions, in addition to patterns of service use, with implications for tailored interventions. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

An assessment of fatigue in patients with postural orthostatic tachycardia syndrome.

PubMed

Wise, Shelby; Ross, Amanda; Brown, Abigail; Evans, Meredyth; Jason, Leonard

2017-05-01

Individuals with postural orthostatic tachycardia syndrome share many symptoms with those who have chronic fatigue syndrome; one of which is severe fatigue. Previous literature found that those with chronic fatigue syndrome experience many forms of fatigue. The goal of this study was to investigate whether individuals with postural orthostatic tachycardia syndrome also experience multidimensional fatigue and whether these individuals can be clustered into subgroups based on the types of fatigue they endorse. A convenience sample of 138 participants (aged 14-29) with postural orthostatic tachycardia syndrome completed questionnaires that assessed fatigue, brain fog symptom severity, activities that improve brain fog, and brain fog-related disability. An exploratory factor analysis was conducted on the Fatigue Types Questionnaire, and a three-factor solution was produced. Factor scores were then used to cluster the patients into groups using a TwoStep cluster analysis. This resulted in two clusters, a high severity group and a low severity group. The clusters were then compared on a number of items related to symptom expression. Individuals within the more severe cluster had significantly more brain fog at the beginning and end of the survey when compared to cluster two. Those in the more severe cluster also described more activity impairment as well as more frequent, more severe, and more debilitation from postural orthostatic tachycardia syndrome and brain fog. The findings of the factor analysis suggest that patients with postural orthostatic tachycardia syndrome experience fatigue as a multidimensional construct and they also can be subgrouped based on symptom severity.

Clustering cancer gene expression data by projective clustering ensemble

PubMed Central

Yu, Xianxue; Yu, Guoxian

2017-01-01

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

Identification of homogeneous regions for regionalization of watersheds by two-level self-organizing feature maps

NASA Astrophysics Data System (ADS)

Farsadnia, F.; Rostami Kamrood, M.; Moghaddam Nia, A.; Modarres, R.; Bray, M. T.; Han, D.; Sadatinejad, J.

2014-02-01

One of the several methods in estimating flood quantiles in ungauged or data-scarce watersheds is regional frequency analysis. Amongst the approaches to regional frequency analysis, different clustering techniques have been proposed to determine hydrologically homogeneous regions in the literature. Recently, Self-Organization feature Map (SOM), a modern hydroinformatic tool, has been applied in several studies for clustering watersheds. However, further studies are still needed with SOM on the interpretation of SOM output map for identifying hydrologically homogeneous regions. In this study, two-level SOM and three clustering methods (fuzzy c-mean, K-mean, and Ward's Agglomerative hierarchical clustering) are applied in an effort to identify hydrologically homogeneous regions in Mazandaran province watersheds in the north of Iran, and their results are compared with each other. Firstly the SOM is used to form a two-dimensional feature map. Next, the output nodes of the SOM are clustered by using unified distance matrix algorithm and three clustering methods to form regions for flood frequency analysis. The heterogeneity test indicates the four regions achieved by the two-level SOM and Ward approach after adjustments are sufficiently homogeneous. The results suggest that the combination of SOM and Ward is much better than the combination of either SOM and FCM or SOM and K-mean.

Vitamin and mineral supplement users. Do they have healthy or unhealthy dietary behaviours?

PubMed

van der Horst, Klazine; Siegrist, Michael

2011-12-01

It is unknown whether people use vitamin and mineral supplements (VMS) to compensate for unhealthy diets, or people whom already have a healthy diet use VMS. Therefore, this study aimed to examine correlates of VMS use and whether VMS users can be categorised into specific clusters based on dietary lifestyle variables. The data used came from the Swiss Food Panel questionnaire for 2010. The sample consisted of 6189 respondents, mean age was 54 years and 47.6% were males. Data was analysed with logistic regression analysis and hierarchical cluster analysis. The results revealed that for VMS use, gender, age, education, chronic illness, health consciousness, benefits of fortification, convenience food and sugar-sweetened beverage consumption were of importance. Cluster analysis revealed three clusters (1) healthy diet, (2) unhealthy diet and (3) modest diet. Compared to non-users a higher percentage of VMS users was categorised in the healthy cluster and a lower percentage in the unhealthy cluster. More VMS-users were categorised as having an unhealthy diet (31.4%) than having a healthy diet (20.6%). The results suggest that both hypotheses-VMS are used by people with unhealthy diets and by people who least need them-hold true meaning. Copyright © 2011. Published by Elsevier Ltd.

Study on text mining algorithm for ultrasound examination of chronic liver diseases based on spectral clustering

NASA Astrophysics Data System (ADS)

Chang, Bingguo; Chen, Xiaofei

2018-05-01

Ultrasonography is an important examination for the diagnosis of chronic liver disease. The doctor gives the liver indicators and suggests the patient's condition according to the description of ultrasound report. With the rapid increase in the amount of data of ultrasound report, the workload of professional physician to manually distinguish ultrasound results significantly increases. In this paper, we use the spectral clustering method to cluster analysis of the description of the ultrasound report, and automatically generate the ultrasonic diagnostic diagnosis by machine learning. 110 groups ultrasound examination report of chronic liver disease were selected as test samples in this experiment, and the results were validated by spectral clustering and compared with k-means clustering algorithm. The results show that the accuracy of spectral clustering is 92.73%, which is higher than that of k-means clustering algorithm, which provides a powerful ultrasound-assisted diagnosis for patients with chronic liver disease.

A clustering method of Chinese medicine prescriptions based on modified firefly algorithm.

PubMed

Yuan, Feng; Liu, Hong; Chen, Shou-Qiang; Xu, Liang

2016-12-01

This paper is aimed to study the clustering method for Chinese medicine (CM) medical cases. The traditional K-means clustering algorithm had shortcomings such as dependence of results on the selection of initial value, trapping in local optimum when processing prescriptions form CM medical cases. Therefore, a new clustering method based on the collaboration of firefly algorithm and simulated annealing algorithm was proposed. This algorithm dynamically determined the iteration of firefly algorithm and simulates sampling of annealing algorithm by fitness changes, and increased the diversity of swarm through expansion of the scope of the sudden jump, thereby effectively avoiding premature problem. The results from confirmatory experiments for CM medical cases suggested that, comparing with traditional K-means clustering algorithms, this method was greatly improved in the individual diversity and the obtained clustering results, the computing results from this method had a certain reference value for cluster analysis on CM prescriptions.

Neuro- and social-cognitive clustering highlights distinct profiles in adults with anorexia nervosa.

PubMed

Renwick, Beth; Musiat, Peter; Lose, Anna; DeJong, Hannah; Broadbent, Hannah; Kenyon, Martha; Loomes, Rachel; Watson, Charlotte; Ghelani, Shreena; Serpell, Lucy; Richards, Lorna; Johnson-Sabine, Eric; Boughton, Nicky; Treasure, Janet; Schmidt, Ulrike

2015-01-01

This study aimed to explore the neuro- and social-cognitive profile of a consecutive series of adult outpatients with anorexia nervosa (AN) when compared with widely available age and gender matched historical control data. The relationship between performance profiles, clinical characteristics, service utilization, and treatment adherence was also investigated. Consecutively recruited outpatients with a broad diagnosis of AN (restricting subtype AN-R: n = 44, binge-purge subtype AN-BP: n = 33 or Eating Disorder Not Otherwise Specified-AN subtype EDNOS-AN: n = 23) completed a comprehensive set of neurocognitive (set-shifting, central coherence) and social-cognitive measures (Emotional Theory of Mind). Data were subjected to hierarchical cluster analysis and a discriminant function analysis. Three separate, meaningful clusters emerged. Cluster 1 (n = 45) showed overall average to high average neuro- and social- cognitive performance, Cluster 2 (n = 38) showed mixed performance characterized by distinct strengths and weaknesses, and Cluster 3 (n = 17) showed poor overall performance (Autism Spectrum disorder (ASD) like cluster). The three clusters did not differ in terms of eating disorder symptoms, comorbid features or service utilization and treatment adherence. A discriminant function analysis confirmed that the clusters were best characterized by performance in perseveration and set-shifting measures. The findings suggest that considerable neuro- and social-cognitive heterogeneity exists in patients with AN, with a subset showing ASD-like features. The value of this method of profiling in predicting longer term patient outcomes and in guiding development of etiologically targeted treatments remains to be seen. © 2014 Wiley Periodicals, Inc.

A Cluster Analysis of Tic Symptoms in Children and Adults with Tourette Syndrome: Clinical Correlates and Treatment Outcome

PubMed Central

McGuire, Joseph F.; Nyirabahizi, Epiphanie; Kircanski, Katharina; Piacentini, John; Peterson, Alan L.; Woods, Douglas W.; Wilhelm, Sabine; Walkup, John T.; Scahill, Lawrence

2013-01-01

Cluster analytic methods have examined the symptom presentation of chronic tic disorders (CTDs), with limited agreement across studies. The present study investigated patterns, clinical correlates, and treatment outcome of tic symptoms. 239 youth and adults with CTDs completed a battery of assessments at baseline to determine diagnoses, tic severity, and clinical characteristics. Participants were randomly assigned to receive either a comprehensive behavioral intervention for tics (CBIT) or psychoeducation and supportive therapy (PST). A cluster analysis was conducted on the baseline Yale Global Tic Severity Scale (YGTSS) symptom checklist to identify the constellations of tic symptoms. Four tic clusters were identified: Impulse Control and Complex Phonic Tics; Complex Motor Tics; Simple Head Motor/Vocal Tics; and Primarily Simple Motor Tics. Frequencies of tic symptoms showed few differences across youth and adults. Tic clusters had small associations with clinical characteristics and showed no associations to the presence of coexisting psychiatric conditions. Cluster membership scores did not predict treatment response to CBIT or tic severity reductions. Tic symptoms distinctly cluster with few difference across youth and adults, or coexisting conditions. This study, which is the first to examine tic clusters in relation to treatment, suggested that tic symptom profiles respond equally well to CBIT. PMID:24144615

MC 2 : galaxy imaging and redshift analysis of the merging cluster Ciza J2242.8+5301

DOE PAGES

Dawson, William A.; Jee, M. James; Stroe, Andra; ...

2015-05-28

X-ray and radio observations of CIZA J2242.8+5301 suggest that it is a major cluster merger. Despite being well studied in the X-ray, and radio, little has been presented on the cluster structure and dynamics inferred from its galaxy population. We carried out a deep (i < 25) broad band imaging survey of the system with Subaru SuprimeCam (g & i bands) and the Canada France Hawaii Telescope (r band) as well as a comprehensive spectroscopic survey of the cluster area (505 redshifts) using Keck DEIMOS. We use this data to perform a comprehensive galaxy/redshift analysis of the system, which ismore » the first step to a proper understanding the geometry and dynamics of the merger, as well as using the merger to constrain self-interacting dark matter.« less

A proteome view of structural, functional, and taxonomic characteristics of major protein domain clusters.

PubMed

Sun, Chia-Tsen; Chiang, Austin W T; Hwang, Ming-Jing

2017-10-27

Proteome-scale bioinformatics research is increasingly conducted as the number of completely sequenced genomes increases, but analysis of protein domains (PDs) usually relies on similarity in their amino acid sequences and/or three-dimensional structures. Here, we present results from a bi-clustering analysis on presence/absence data for 6,580 unique PDs in 2,134 species with a sequenced genome, thus covering a complete set of proteins, for the three superkingdoms of life, Bacteria, Archaea, and Eukarya. Our analysis revealed eight distinctive PD clusters, which, following an analysis of enrichment of Gene Ontology functions and CATH classification of protein structures, were shown to exhibit structural and functional properties that are taxa-characteristic. For examples, the largest cluster is ubiquitous in all three superkingdoms, constituting a set of 1,472 persistent domains created early in evolution and retained in living organisms and characterized by basic cellular functions and ancient structural architectures, while an Archaea and Eukarya bi-superkingdom cluster suggests its PDs may have existed in the ancestor of the two superkingdoms, and others are single superkingdom- or taxa (e.g. Fungi)-specific. These results contribute to increase our appreciation of PD diversity and our knowledge of how PDs are used in species, yielding implications on species evolution.

Complete Genome Sequence and Comparative Analysis of the Fish Pathogen Lactococcus garvieae

PubMed Central

Oshima, Kenshiro; Yoshizaki, Mariko; Kawanishi, Michiko; Nakaya, Kohei; Suzuki, Takehito; Miyauchi, Eiji; Ishii, Yasuo; Tanabe, Soichi; Murakami, Masaru; Hattori, Masahira

2011-01-01

Lactococcus garvieae causes fatal haemorrhagic septicaemia in fish such as yellowtail. The comparative analysis of genomes of a virulent strain Lg2 and a non-virulent strain ATCC 49156 of L. garvieae revealed that the two strains shared a high degree of sequence identity, but Lg2 had a 16.5-kb capsule gene cluster that is absent in ATCC 49156. The capsule gene cluster was composed of 15 genes, of which eight genes are highly conserved with those in exopolysaccharide biosynthesis gene cluster often found in Lactococcus lactis strains. Sequence analysis of the capsule gene cluster in the less virulent strain L. garvieae Lg2-S, Lg2-derived strain, showed that two conserved genes were disrupted by a single base pair deletion, respectively. These results strongly suggest that the capsule is crucial for virulence of Lg2. The capsule gene cluster of Lg2 may be a genomic island from several features such as the presence of insertion sequences flanked on both ends, different GC content from the chromosomal average, integration into the locus syntenic to other lactococcal genome sequences, and distribution in human gut microbiomes. The analysis also predicted other potential virulence factors such as haemolysin. The present study provides new insights into understanding of the virulence mechanisms of L. garvieae in fish. PMID:21829716

Exploring the individual patterns of spiritual well-being in people newly diagnosed with advanced cancer: a cluster analysis.

PubMed

Bai, Mei; Dixon, Jane; Williams, Anna-Leila; Jeon, Sangchoon; Lazenby, Mark; McCorkle, Ruth

2016-11-01

Research shows that spiritual well-being correlates positively with quality of life (QOL) for people with cancer, whereas contradictory findings are frequently reported with respect to the differentiated associations between dimensions of spiritual well-being, namely peace, meaning and faith, and QOL. This study aimed to examine individual patterns of spiritual well-being among patients newly diagnosed with advanced cancer. Cluster analysis was based on the twelve items of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale at Time 1. A combination of hierarchical and k-means (non-hierarchical) clustering methods was employed to jointly determine the number of clusters. Self-rated health, depressive symptoms, peace, meaning and faith, and overall QOL were compared at Time 1 and Time 2. Hierarchical and k-means clustering methods both suggested four clusters. Comparison of the four clusters supported statistically significant and clinically meaningful differences in QOL outcomes among clusters while revealing contrasting relations of faith with QOL. Cluster 1, Cluster 3, and Cluster 4 represented high, medium, and low levels of overall QOL, respectively, with correspondingly high, medium, and low levels of peace, meaning, and faith. Cluster 2 was distinguished from other clusters by its medium levels of overall QOL, peace, and meaning and low level of faith. This study provides empirical support for individual difference in response to a newly diagnosed cancer and brings into focus conceptual and methodological challenges associated with the measure of spiritual well-being, which may partly contribute to the attenuated relation between faith and QOL.

Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

PubMed

Lewandowski, Kathryn E; Baker, Justin T; McCarthy, Julie M; Norris, Lesley A; Öngür, Dost

2018-04-01

Cognitive dysfunction is a core symptom dimension that cuts across the psychoses. Recent findings support classification of patients along the cognitive dimension using cluster analysis; however, data-derived groupings may be highly determined by sampling characteristics and the measures used to derive the clusters, and so their interpretability must be established. We examined cognitive clusters in a cross-diagnostic sample of patients with psychosis and associations with clinical and functional outcomes. We then compared our findings to a previous report of cognitive clusters in a separate sample using a different cognitive battery. Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, and clinical and community functioning assessments. Cluster analyses were performed on cognitive variables, and clusters were compared on demographic, cognitive, and clinical measures. Results were compared to findings from our previous report. A four-cluster solution provided a good fit to the data; profiles included a neuropsychologically normal cluster, a globally impaired cluster, and two clusters of mixed profiles. Cognitive burden was associated with symptom severity and poorer community functioning. The patterns of cognitive performance by cluster were highly consistent with our previous findings. We found evidence of four cognitive subgroups of patients with psychosis, with cognitive profiles that map closely to those produced in our previous work. Clusters were associated with clinical and community variables and a measure of premorbid functioning, suggesting that they reflect meaningful groupings: replicable, and related to clinical presentation and functional outcomes. (JINS, 2018, 24, 382-390).

Financial-Ratio Analysis and Medical School Management.

ERIC Educational Resources Information Center

Eastaugh, Steven R.

1980-01-01

The value of a uniform program of financial assistance to medical education and research is questioned. Medical schools have an uneven ability to compensate for declining federal capitation and research grants. Financial-ratio analysis and cluster analysis are utilized to suggest four adaptive responses to future financial pressures. (Author/MLW)

The JCMT Gould Belt Survey: Dense Core Clusters in Orion B

NASA Astrophysics Data System (ADS)

Kirk, H.; Johnstone, D.; Di Francesco, J.; Lane, J.; Buckle, J.; Berry, D. S.; Broekhoven-Fiene, H.; Currie, M. J.; Fich, M.; Hatchell, J.; Jenness, T.; Mottram, J. C.; Nutter, D.; Pattle, K.; Pineda, J. E.; Quinn, C.; Salji, C.; Tisi, S.; Hogerheijde, M. R.; Ward-Thompson, D.; The JCMT Gould Belt Survey Team

2016-04-01

The James Clerk Maxwell Telescope Gould Belt Legacy Survey obtained SCUBA-2 observations of dense cores within three sub-regions of Orion B: LDN 1622, NGC 2023/2024, and NGC 2068/2071, all of which contain clusters of cores. We present an analysis of the clustering properties of these cores, including the two-point correlation function and Cartwright’s Q parameter. We identify individual clusters of dense cores across all three regions using a minimal spanning tree technique, and find that in each cluster, the most massive cores tend to be centrally located. We also apply the independent M-Σ technique and find a strong correlation between core mass and the local surface density of cores. These two lines of evidence jointly suggest that some amount of mass segregation in clusters has happened already at the dense core stage.

A Deep Chandra Observation of the Distant Galaxy Cluster MS 1137.5+6625

NASA Astrophysics Data System (ADS)

Grego, Laura; Vrtilek, J. M.; Van Speybroeck, Leon; David, Laurence P.; Forman, William; Carlstrom, John E.; Reese, Erik D.; Joy, Marshall K.

2004-06-01

We present results from a deep Chandra observation of MS 1137.5+66, a distant (z=0.783) and massive cluster of galaxies. Only a few similarly massive clusters are currently known at such high redshifts; accordingly, this observation provides much needed information on the dynamical state of these rare systems. The cluster appears both regular and symmetric in the X-ray image. However, our analysis of the spectral and spatial X-ray data in conjunction with interferometric Sunyaev-Zel'dovich effect data and published deep optical imaging suggests that the cluster has a fairly complex structure. The angular diameter distance we calculate from the Chandra and Sunyaev-Zel'dovich effect data assuming an isothermal, spherically symmetric cluster implies a low value for the Hubble constant for which we explore possible explanations.

Rhodium clustering process on defective (8,0) SWCNT: Analysis of chemical and physical properties using density functional theory

NASA Astrophysics Data System (ADS)

Ambrusi, Ruben E.; Luna, C. Romina; Sandoval, Mario G.; Bechthold, Pablo; Pronsato, M. Estela; Juan, Alfredo

2017-12-01

The Spin-polarized density functional theory is used to study the effect of a single vacancy in a (8,0) single-walled carbon nanotube (SWCNT) on the Rh clustering process. The vacancy is considered oxygenated and non-oxygenated and, in each case, different Rhn cluster sizes (n = 1-4) are taken into account. For the analysis of these systems some physical and chemical properties are calculated, such as binding energy (Eb), work function (WF), magnetic moment, charge transfer, bond length, band gap (Eg), and density of state (DOS). From this analysis it can be concluded that: a single Rh atom and Rh2 dimer are adsorbed on vacancy without oxygen, whereas Rh3 and Rh4 clusters prefer to be adsorbed on oxygenated vacancy. In all cases, Rh adsorption induces a magnetic moment. When the Rh atom and Rh2 dimer are bonded to the defective SWCNT, it has been found that they show a semiconductor behavior that could be interesting to use in the spintronic area. In the case of Rh3 and Rh4 clusters our results show a metallic behavior suggesting that these systems are good candidates for nanotube contact.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Molecular comparison of the structural proteins encoding gene clusters of two related Lactobacillus delbrueckii bacteriophages.

PubMed Central

Vasala, A; Dupont, L; Baumann, M; Ritzenthaler, P; Alatossava, T

1993-01-01

Virulent phage LL-H and temperate phage mv4 are two related bacteriophages of Lactobacillus delbrueckii. The gene clusters encoding structural proteins of these two phages have been sequenced and further analyzed. Six open reading frames (ORF-1 to ORF-6) were detected. Protein sequencing and Western immunoblotting experiments confirmed that ORF-3 (g34) encoded the main capsid protein Gp34. The presence of a putative late promoter in front of the phage LL-H g34 gene was suggested by primer extension experiments. Comparative sequence analysis between phage LL-H and phage mv4 revealed striking similarities in the structure and organization of this gene cluster, suggesting that the genes encoding phage structural proteins belong to a highly conservative module. Images PMID:8497043

Compositional variability in Mediterranean archaeofaunas from Upper Paleolithic Southwest Europe

NASA Astrophysics Data System (ADS)

Jones, Emily Lena

2018-03-01

Recent meta-analyses of Upper Paleolithic Southwestern European archaeofaunas (Jones, 2015, 2016) have identified a consistent "Mediterranean" cluster from the Last Glacial Maximum through the early Holocene, suggesting similarities in environment and/or consistency in hunting strategy across this region through time despite radical changes in climate. However, while these archaeofaunas from this cluster all derive from sites located within today's Mediterranean bioclimatic region, many of them are from locations far from the Mediterranean Sea - Atlantic Portugal, the Spanish Meseta - which today differ significantly from each other in biotic composition. In this paper, I explore clustering (through cluster analysis and non-metric multidimensional scaling) within the Mediterranean archaeofaunal group. I test for the influence of sample size as well as the geographic variables of site elevation, latitude, and longitude on variability in the large mammal portions of archaeofaunal assemblages. ANOVA shows no relationship between cluster-defined groups and site elevation or longitude; instead, site latitude appears to be a primary contributor to patterning. However, the overall compositional similarity of the Mediterranean archaeofaunas in this dataset suggests more consistency than variability in Upper Paleolithic hunting strategy in this region.

Characterization of herbaspirillum- and limnobacter-related strains isolated from young volcanic deposits in miyake-jima island, Japan.

PubMed

Lu, Hongsheng; Fujimura, Reiko; Sato, Yoshinori; Nanba, Kenji; Kamijo, Takashi; Ohta, Hiroyuki

2008-01-01

The role of microbes in the early development of ecosystems on new volcanic materials seems to be crucial to primary plant succession but is not well characterized. Here we analyzed the bacterial community colonizing 22-year-old volcanic deposits of the Miyake-jima Island (Japan) using culture-based and 16S rRNA gene clone library methods. The majority of 91 bacterial isolates were placed phylogenetically in two clusters (A and B) of the Betaproteobacteria. Cluster A (82% of isolates) was related to the genus Limnobacter and Cluster B (9%) was affiliated with the Herbaspirillum clade. The clone library analysis supported the predominance of Cluster B rather than Cluster A. Strain KP1-50 of Cluster B was able to grow on a mineral medium under an atmosphere of H(2), O(2), and CO(2) (85:5:10), and characterized by its large-subunit gene of ribulose 1,5-bisphosphate carboxylase/oxygenase (rbcL) and nitrogenase reductase gene (nifH). In contrast, strains of Cluster A did not grow chemolithoautotrophically with H(2), O(2), and CO(2) but increased their cell biomass with the addition of thiosulfate to the succinate medium, suggesting the use of thiosulfate as an energy source. From phenotypic characterization, it was suggested that the Cluster A and B strains were novel species in the genus Limnobacter and Herbaspirillum, respectively.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

PubMed Central

Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

2014-01-01

The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

The young star cluster population of M51 with LEGUS - I. A comprehensive study of cluster formation and evolution

NASA Astrophysics Data System (ADS)

Messa, M.; Adamo, A.; Östlin, G.; Calzetti, D.; Grasha, K.; Grebel, E. K.; Shabani, F.; Chandar, R.; Dale, D. A.; Dobbs, C. L.; Elmegreen, B. G.; Fumagalli, M.; Gouliermis, D. A.; Kim, H.; Smith, L. J.; Thilker, D. A.; Tosi, M.; Ubeda, L.; Walterbos, R.; Whitmore, B. C.; Fedorenko, K.; Mahadevan, S.; Andrews, J. E.; Bright, S. N.; Cook, D. O.; Kahre, L.; Nair, P.; Pellerin, A.; Ryon, J. E.; Ahmad, S. D.; Beale, L. P.; Brown, K.; Clarkson, D. A.; Guidarelli, G. C.; Parziale, R.; Turner, J.; Weber, M.

2018-01-01

Recently acquired WFC3 UV (F275W and F336W) imaging mosaics under the Legacy Extragalactic UV Survey (LEGUS), combined with archival ACS data of M51, are used to study the young star cluster (YSC) population of this interacting system. Our newly extracted source catalogue contains 2834 cluster candidates, morphologically classified to be compact and uniform in colour, for which ages, masses and extinction are derived. In this first work we study the main properties of the YSC population of the whole galaxy, considering a mass-limited sample. Both luminosity and mass functions follow a power-law shape with slope -2, but at high luminosities and masses a dearth of sources is observed. The analysis of the mass function suggests that it is best fitted by a Schechter function with slope -2 and a truncation mass at 1.00 ± 0.12 × 105 M⊙. Through Monte Carlo simulations, we confirm this result and link the shape of the luminosity function to the presence of a truncation in the mass function. A mass limited age function analysis, between 10 and 200 Myr, suggests that the cluster population is undergoing only moderate disruption. We observe little variation in the shape of the mass function at masses above 1 × 104 M⊙ over this age range. The fraction of star formation happening in the form of bound clusters in M51 is ∼ 20 per cent in the age range 10-100 Myr and little variation is observed over the whole range from 1 to 200 Myr.

Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

NASA Astrophysics Data System (ADS)

Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

2018-05-01

Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.

Spatial patterns in vegetation fires in the Indian region.

PubMed

Vadrevu, Krishna Prasad; Badarinath, K V S; Anuradha, Eaturu

2008-12-01

In this study, we used fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to characterize spatial patterns in fire occurrences across highly diverse geographical, vegetation and topographic gradients in the Indian region. For characterizing the spatial patterns of fire occurrences, observed fire point patterns were tested against the hypothesis of a complete spatial random (CSR) pattern using three different techniques, the quadrat analysis, nearest neighbor analysis and Ripley's K function. Hierarchical nearest neighboring technique was used to depict the 'hotspots' of fire incidents. Of the different states, highest fire counts were recorded in Madhya Pradesh (14.77%) followed by Gujarat (10.86%), Maharastra (9.92%), Mizoram (7.66%), Jharkhand (6.41%), etc. With respect to the vegetation categories, highest number of fires were recorded in agricultural regions (40.26%) followed by tropical moist deciduous vegetation (12.72), dry deciduous vegetation (11.40%), abandoned slash and burn secondary forests (9.04%), tropical montane forests (8.07%) followed by others. Analysis of fire counts based on elevation and slope range suggested that maximum number of fires occurred in low and medium elevation types and in very low to low-slope categories. Results from three different spatial techniques for spatial pattern suggested clustered pattern in fire events compared to CSR. Most importantly, results from Ripley's K statistic suggested that fire events are highly clustered at a lag-distance of 125 miles. Hierarchical nearest neighboring clustering technique identified significant clusters of fire 'hotspots' in different states in northeast and central India. The implications of these results in fire management and mitigation were discussed. Also, this study highlights the potential of spatial point pattern statistics in environmental monitoring and assessment studies with special reference to fire events in the Indian region.

Wechsler Adult Intelligence Scale-Third Edition profiles and their relationship to self-reported outcome following traumatic brain injury.

PubMed

Harman-Smith, Yasmin E; Mathias, Jane L; Bowden, Stephen C; Rosenfeld, Jeffrey V; Bigler, Erin D

2013-01-01

Neuropsychological assessments of outcome after traumatic brain injury (TBI) are often unrelated to self-reported problems after TBI. The current study cluster-analyzed the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) subtest scores from mild, moderate, and severe TBI (n=220) and orthopedic injury control (n=95) groups, to determine whether specific cognitive profiles are related to people's perceived outcomes after TBI. A two-stage cluster analysis produced 4- and 6-cluster solutions, with the 6-cluster solution better capturing subtle variations in cognitive functioning. The 6 clusters differed in the levels and profiles of cognitive performance, self-reported recovery, and education and injury severity. The findings suggest that subtle cognitive impairments after TBI should be interpreted in conjunction with patient's self-reported problems.

Defining objective clusters for rabies virus sequences using affinity propagation clustering

PubMed Central

Fischer, Susanne; Freuling, Conrad M.; Pfaff, Florian; Bodenhofer, Ulrich; Höper, Dirk; Fischer, Mareike; Marston, Denise A.; Fooks, Anthony R.; Mettenleiter, Thomas C.; Conraths, Franz J.; Homeier-Bachmann, Timo

2018-01-01

Rabies is caused by lyssaviruses, and is one of the oldest known zoonoses. In recent years, more than 21,000 nucleotide sequences of rabies viruses (RABV), from the prototype species rabies lyssavirus, have been deposited in public databases. Subsequent phylogenetic analyses in combination with metadata suggest geographic distributions of RABV. However, these analyses somewhat experience technical difficulties in defining verifiable criteria for cluster allocations in phylogenetic trees inviting for a more rational approach. Therefore, we applied a relatively new mathematical clustering algorythm named ‘affinity propagation clustering’ (AP) to propose a standardized sub-species classification utilizing full-genome RABV sequences. Because AP has the advantage that it is computationally fast and works for any meaningful measure of similarity between data samples, it has previously been applied successfully in bioinformatics, for analysis of microarray and gene expression data, however, cluster analysis of sequences is still in its infancy. Existing (516) and original (46) full genome RABV sequences were used to demonstrate the application of AP for RABV clustering. On a global scale, AP proposed four clusters, i.e. New World cluster, Arctic/Arctic-like, Cosmopolitan, and Asian as previously assigned by phylogenetic studies. By combining AP with established phylogenetic analyses, it is possible to resolve phylogenetic relationships between verifiably determined clusters and sequences. This workflow will be useful in confirming cluster distributions in a uniform transparent manner, not only for RABV, but also for other comparative sequence analyses. PMID:29357361

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Gas and galaxies in filaments between clusters of galaxies. The study of A399-A401

NASA Astrophysics Data System (ADS)

Bonjean, V.; Aghanim, N.; Salomé, P.; Douspis, M.; Beelen, A.

2018-01-01

We have performed a multi-wavelength analysis of two galaxy cluster systems selected with the thermal Sunyaev-Zel'dovich (tSZ) effect and composed of cluster pairs and an inter-cluster filament. We have focused on one pair of particular interest: A399-A401 at redshift z 0.073 seperated by 3 Mpc. We have also performed the first analysis of one lower-significance newly associated pair: A21-PSZ2 G114.09-34.34 at z 0.094, separated by 4.2 Mpc. We have characterised the intra-cluster gas using the tSZ signal from Planck and, when possible, the galaxy optical and infrared (IR) properties based on two photometric redshift catalogues: 2MPZ and WISExSCOS. From the tSZ data, we measured the gas pressure in the clusters and in the inter-cluster filaments. In the case of A399-A401, the results are in perfect agreement with previous studies and, using the temperature measured from the X-rays, we further estimate the gas density in the filament and find n0 = (4.3 ± 0.7) × 10-4 cm-3. The optical and IR colour-colour and colour-magnitude analyses of the galaxies selected in the cluster system, together with their star formation rate, show no segregation between galaxy populations, both in the clusters and in the filament of A399-A401. Galaxies are all passive, early type, and red and dead. The gas and galaxy properties of this system suggest that the whole system formed at the same time and corresponds to a pre-merger, with a cosmic filament gas heated by the collapse. For the other cluster system, the tSZ analysis was performed and the pressure in the clusters and in the inter-cluster filament was constrained. However, the limited or nonexistent optical and IR data prevent us from concluding on the presence of an actual cosmic filament or from proposing a scenario.

Finding Groups Using Model-based Cluster Analysis: Heterogeneous Emotional Self-regulatory Processes and Heavy Alcohol Use Risk

PubMed Central

Mun, Eun-Young; von Eye, Alexander; Bates, Marsha E.; Vaschillo, Evgeny G.

2010-01-01

Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of non-nested models using the Bayesian Information Criterion (BIC) to compare multiple models and identify the optimum number of clusters. The current study clustered 36 young men and women based on their baseline heart rate (HR) and HR variability (HRV), chronic alcohol use, and reasons for drinking. Two cluster groups were identified and labeled High Alcohol Risk and Normative groups. Compared to the Normative group, individuals in the High Alcohol Risk group had higher levels of alcohol use and more strongly endorsed disinhibition and suppression reasons for use. The High Alcohol Risk group showed significant HRV changes in response to positive and negative emotional and appetitive picture cues, compared to neutral cues. In contrast, the Normative group showed a significant HRV change only to negative cues. Findings suggest that the individuals with autonomic self-regulatory difficulties may be more susceptible to heavy alcohol use and use alcohol for emotional regulation. PMID:18331138

Formation and stability of dense arrays of Au nanoclusters on hexagonal boron nitride/Rh(111)

NASA Astrophysics Data System (ADS)

Patterson, Matthew C.; Habenicht, Bradley F.; Kurtz, Richard L.; Liu, Li; Xu, Ye; Sprunger, Phillip T.

2014-05-01

We have studied the nucleation and growth of Au clusters at submonolayer and greater coverages on the h-BN nanomesh grown on Rh(111) by means of scanning tunneling microscopy (STM), x-ray photoelectron spectroscopy (XPS), and density functional theory (DFT). STM reveals that submonolayer Au deposited at 115 K nucleates within the nanomesh pores and remains confined to the pores even after warming to room temperature. Whereas there is a propensity of monoatomic high islands at low temperature, upon annealing, bi- and multilayer Au clusters emerge. Deposition of higher coverages of Au similarly results in Au clusters primarily confined to the nanomesh pores at room temperature. XPS analysis of core-level electronic states in the deposited Au shows strong final-state effects induced by restricted particle size dominating for low Au coverage, with indications that larger Au clusters are negatively charged by interaction through the h-BN monolayer. DFT calculations suggest that the structure of the Au clusters transitions from monolayer to bilayer at a size between 30 and 37 atoms per cluster, in line with our experiment. Bader charge analysis supports the negative charge state of deposited Au.

A recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure.

PubMed

Liao, Fuyuan; Jan, Yih-Kuen

2012-06-01

This paper presents a recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure. Recurrence is a fundamental property of many dynamical systems, which can be explored in phase spaces constructed from observational time series. A visualization tool of recurrence analysis called recurrence plot (RP) has been proved to be highly effective to detect transitions in the dynamics of the system. However, it was found that delay embedding can produce spurious structures in RPs. Network-based concepts have been applied for the analysis of nonlinear time series recently. We demonstrate that time series with different types of dynamics exhibit distinct global clustering coefficients and distributions of local clustering coefficients and that the global clustering coefficient is robust to the embedding parameters. We applied the approach to study skin blood flow oscillations (BFO) response to loading pressure. The results showed that global clustering coefficients of BFO significantly decreased in response to loading pressure (p<0.01). Moreover, surrogate tests indicated that such a decrease was associated with a loss of nonlinearity of BFO. Our results suggest that the recurrence network approach can practically quantify the nonlinear dynamics of BFO.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan.

PubMed

Park, Rachel; O'Brien, Thomas F; Huang, Susan S; Baker, Meghan A; Yokoe, Deborah S; Kulldorff, Martin; Barrett, Craig; Swift, Jamie; Stelling, John

2016-11-01

While antimicrobial resistance threatens the prevention, treatment, and control of infectious diseases, systematic analysis of routine microbiology laboratory test results worldwide can alert new threats and promote timely response. This study explores statistical algorithms for recognizing geographic clustering of multi-resistant microbes within a healthcare network and monitoring the dissemination of new strains over time. Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. We explored geographic clustering of multi-resistance phenotypes within the network and changes in clustering over time. Geographic clustering identified from both latitude/longitude and non-parametric facility groupings geographic models were similar, while the latter was offers greater flexibility and generalizability. Iterative application of the clustering algorithms suggested the possible recognition of the initial appearance of invasive E. coli ST131 in the clinical database of a single hospital and subsequent dissemination to others. Systematic analysis of routine antimicrobial resistance susceptibility test results supports the recognition of geographic clustering of microbial phenotypic subpopulations with WHONET and SaTScan, and iterative application of these algorithms can detect the initial appearance in and dissemination across a region prompting early investigation, response, and containment measures.

Transcription factor clusters regulate genes in eukaryotic cells

PubMed Central

Hedlund, Erik G; Friemann, Rosmarie; Hohmann, Stefan

2017-01-01

Transcription is regulated through binding factors to gene promoters to activate or repress expression, however, the mechanisms by which factors find targets remain unclear. Using single-molecule fluorescence microscopy, we determined in vivo stoichiometry and spatiotemporal dynamics of a GFP tagged repressor, Mig1, from a paradigm signaling pathway of Saccharomyces cerevisiae. We find the repressor operates in clusters, which upon extracellular signal detection, translocate from the cytoplasm, bind to nuclear targets and turnover. Simulations of Mig1 configuration within a 3D yeast genome model combined with a promoter-specific, fluorescent translation reporter confirmed clusters are the functional unit of gene regulation. In vitro and structural analysis on reconstituted Mig1 suggests that clusters are stabilized by depletion forces between intrinsically disordered sequences. We observed similar clusters of a co-regulatory activator from a different pathway, supporting a generalized cluster model for transcription factors that reduces promoter search times through intersegment transfer while stabilizing gene expression. PMID:28841133

Using cluster ensemble and validation to identify subtypes of pervasive developmental disorders.

PubMed

Shen, Jess J; Lee, Phil-Hyoun; Holden, Jeanette J A; Shatkay, Hagit

2007-10-11

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior. Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.

Using Cluster Ensemble and Validation to Identify Subtypes of Pervasive Developmental Disorders

PubMed Central

Shen, Jess J.; Lee, Phil Hyoun; Holden, Jeanette J.A.; Shatkay, Hagit

2007-01-01

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior.1 Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes19. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.2 PMID:18693920

THE JCMT GOULD BELT SURVEY: DENSE CORE CLUSTERS IN ORION A

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lane, J.; Kirk, H.; Johnstone, D.

The Orion A molecular cloud is one of the most well-studied nearby star-forming regions, and includes regions of both highly clustered and more dispersed star formation across its full extent. Here, we analyze dense, star-forming cores identified in the 850 and 450 μ m SCUBA-2 maps from the JCMT Gould Belt Legacy Survey. We identify dense cores in a uniform manner across the Orion A cloud and analyze their clustering properties. Using two independent lines of analysis, we find evidence that clusters of dense cores tend to be mass segregated, suggesting that stellar clusters may have some amount of primordial mass segregationmore » already imprinted in them at an early stage. We also demonstrate that the dense core clusters have a tendency to be elongated, perhaps indicating a formation mechanism linked to the filamentary structure within molecular clouds.« less

A Holarctic Biogeographical Analysis of the Collembola (Arthropoda, Hexapoda) Unravels Recent Post-Glacial Colonization Patterns

PubMed Central

Ávila-Jiménez, María Luisa; Coulson, Stephen James

2011-01-01

We aimed to describe the main Arctic biogeographical patterns of the Collembola, and analyze historical factors and current climatic regimes determining Arctic collembolan species distribution. Furthermore, we aimed to identify possible dispersal routes, colonization sources and glacial refugia for Arctic collembola. We implemented a Gaussian Mixture Clustering method on species distribution ranges and applied a distance- based parametric bootstrap test on presence-absence collembolan species distribution data. Additionally, multivariate analysis was performed considering species distributions, biodiversity, cluster distribution and environmental factors (temperature and precipitation). No clear relation was found between current climatic regimes and species distribution in the Arctic. Gaussian Mixture Clustering found common elements within Siberian areas, Atlantic areas, the Canadian Arctic, a mid-Siberian cluster and specific Beringian elements, following the same pattern previously described, using a variety of molecular methods, for Arctic plants. Species distribution hence indicate the influence of recent glacial history, as LGM glacial refugia (mid-Siberia, and Beringia) and major dispersal routes to high Arctic island groups can be identified. Endemic species are found in the high Arctic, but no specific biogeographical pattern can be clearly identified as a sign of high Arctic glacial refugia. Ocean currents patterns are suggested as being an important factor shaping the distribution of Arctic Collembola, which is consistent with Antarctic studies in collembolan biogeography. The clear relations between cluster distribution and geographical areas considering their recent glacial history, lack of relationship of species distribution with current climatic regimes, and consistency with previously described Arctic patterns in a series of organisms inferred using a variety of methods, suggest that historical phenomena shaping contemporary collembolan distribution can be inferred through biogeographical analysis. PMID:26467728

Parity among interpretation methods of MLEE patterns and disparity among clustering methods in epidemiological typing of Candida albicans.

PubMed

Boriollo, Marcelo Fabiano Gomes; Rosa, Edvaldo Antonio Ribeiro; Gonçalves, Reginaldo Bruno; Höfling, José Francisco

2006-03-01

The typing of C. albicans by MLEE (multilocus enzyme electrophoresis) is dependent on the interpretation of enzyme electrophoretic patterns, and the study of the epidemiological relationships of these yeasts can be conducted by cluster analysis. Therefore, the aims of the present study were to first determine the discriminatory power of genetic interpretation (deduction of the allelic composition of diploid organisms) and numerical interpretation (mere determination of the presence and absence of bands) of MLEE patterns, and then to determine the concordance (Pearson product-moment correlation coefficient) and similarity (Jaccard similarity coefficient) of the groups of strains generated by three cluster analysis models, and the discriminatory power of such models as well [model A: genetic interpretation, genetic distance matrix of Nei (d(ij)) and UPGMA dendrogram; model B: genetic interpretation, Dice similarity matrix (S(D1)) and UPGMA dendrogram; model C: numerical interpretation, Dice similarity matrix (S(D2)) and UPGMA dendrogram]. MLEE was found to be a powerful and reliable tool for the typing of C. albicans due to its high discriminatory power (>0.9). Discriminatory power indicated that numerical interpretation is a method capable of discriminating a greater number of strains (47 versus 43 subtypes), but also pointed to model B as a method capable of providing a greater number of groups, suggesting its use for the typing of C. albicans by MLEE and cluster analysis. Very good agreement was only observed between the elements of the matrices S(D1) and S(D2), but a large majority of the groups generated in the three UPGMA dendrograms showed similarity S(J) between 4.8% and 75%, suggesting disparities in the conclusions obtained by the cluster assays.

Distribution and Genetic Diversity of Bacteriocin Gene Clusters in Rumen Microbial Genomes.

PubMed

Azevedo, Analice C; Bento, Cláudia B P; Ruiz, Jeronimo C; Queiroz, Marisa V; Mantovani, Hilário C

2015-10-01

Some species of ruminal bacteria are known to produce antimicrobial peptides, but the screening procedures have mostly been based on in vitro assays using standardized methods. Recent sequencing efforts have made available the genome sequences of hundreds of ruminal microorganisms. In this work, we performed genome mining of the complete and partial genome sequences of 224 ruminal bacteria and 5 ruminal archaea to determine the distribution and diversity of bacteriocin gene clusters. A total of 46 bacteriocin gene clusters were identified in 33 strains of ruminal bacteria. Twenty gene clusters were related to lanthipeptide biosynthesis, while 11 gene clusters were associated with sactipeptide production, 7 gene clusters were associated with class II bacteriocin production, and 8 gene clusters were associated with class III bacteriocin production. The frequency of strains whose genomes encode putative antimicrobial peptide precursors was 14.4%. Clusters related to the production of sactipeptides were identified for the first time among ruminal bacteria. BLAST analysis indicated that the majority of the gene clusters (88%) encoding putative lanthipeptides contained all the essential genes required for lanthipeptide biosynthesis. Most strains of Streptococcus (66.6%) harbored complete lanthipeptide gene clusters, in addition to an open reading frame encoding a putative class II bacteriocin. Albusin B-like proteins were found in 100% of the Ruminococcus albus strains screened in this study. The in silico analysis provided evidence of novel biosynthetic gene clusters in bacterial species not previously related to bacteriocin production, suggesting that the rumen microbiota represents an underexplored source of antimicrobial peptides. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Do healthy and unhealthy behaviours cluster in New Zealand?

PubMed

Tobias, Martin; Jackson, Gary; Yeh, Li-Chia; Huang, Ken

2007-04-01

To describe the co-occurrence and clustering of healthy and unhealthy behaviours in New Zealand. Data were sourced from the 2002/03 New Zealand Health Survey. Behaviours selected for analysis were tobacco use, quantity and pattern of alcohol consumption, level of physical activity, and intake of fruit and vegetables. Clustering was defined as co-prevalence of behaviours greater than that expected based on the laws of probability. Co-occurrence was examined using multiple logistic regression modelling, while clustering was examined in a stratified analysis using age and (where appropriate) ethnic standardisation for confounding control. Approximately 29% of adults enjoyed a healthy lifestyle characterised by non-use of tobacco, non- or safe use of alcohol, sufficient physical activity and adequate fruit and vegetable intake. This is only slightly greater than the prevalence expected if all four behaviours were independently distributed through the population i.e. little clustering of healthy behaviours was found. By contrast, 1.5% of adults exhibited all four unhealthy behaviours and 13% exhibited any combination of three of the four unhealthy behaviours. Unhealthy behaviours were more clustered than healthy behaviours, yet Maori exhibited less clustering of unhealthy behaviours than other ethnic groups and no deprivation gradient was seen in clustering. The relative lack of clustering of healthy behaviours supports single issue universal health promotion strategies at the population level. Our results also support targeted interventions at the clinical level for the 15% with 'unhealthy lifestyles'. Our finding of only limited clustering of unhealthy behaviours among Maori and no deprivation gradient suggests that clustering does not contribute to the greater burden of disease experienced by these groups.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

PubMed Central

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; Lim, Jing Quan; Huang, Mi Ni; Padmanabhan, Nisha; Nellore, Vishwa; Kongpetch, Sarinya; Ng, Alvin Wei Tian; Ng, Ley Moy; Choo, Su Pin; Myint, Swe Swe; Thanan, Raynoo; Nagarajan, Sanjanaa; Lim, Weng Khong; Ng, Cedric Chuan Young; Boot, Arnoud; Liu, Mo; Ong, Choon Kiat; Rajasegaran, Vikneswari; Lie, Stefanus; Lim, Alvin Soon Tiong; Lim, Tse Hui; Tan, Jing; Loh, Jia Liang; McPherson, John R.; Khuntikeo, Narong; Bhudhisawasdi, Vajaraphongsa; Yongvanit, Puangrat; Wongkham, Sopit; Totoki, Yasushi; Nakamura, Hiromi; Arai, Yasuhito; Yamasaki, Satoshi; Chow, Pierce Kah-Hoe; Chung, Alexander Yaw Fui; Ooi, London Lucien Peng Jin; Lim, Kiat Hon; Dima, Simona; Duda, Dan G.; Popescu, Irinel; Broet, Philippe; Hsieh, Sen-Yung; Yu, Ming-Chin; Scarpa, Aldo; Lai, Jiaming; Luo, Di-Xian; Carvalho, André Lopes; Vettore, André Luiz; Rhee, Hyungjin; Park, Young Nyun; Alexandrov, Ludmil B.; Gordân, Raluca; Rozen, Steven G.; Shibata, Tatsuhiro; Pairojkul, Chawalit; Teh, Bin Tean; Tan, Patrick

2017-01-01

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters – Fluke-Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3′UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores – mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. PMID:28667006

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less

Characterization of a Large Cluster of Influenza A(H1N1)pdm09 Viruses Cross-Resistant to Oseltamivir and Peramivir during the 2013-2014 Influenza Season in Japan

PubMed Central

Takashita, Emi; Kiso, Maki; Fujisaki, Seiichiro; Yokoyama, Masaru; Nakamura, Kazuya; Shirakura, Masayuki; Sato, Hironori; Odagiri, Takato; Kawaoka, Yoshihiro

2015-01-01

Between September 2013 and July 2014, 2,482 influenza 2009 pandemic A(H1N1) [A(H1N1)pdm09] viruses were screened in Japan for the H275Y substitution in their neuraminidase (NA) protein, which confers cross-resistance to oseltamivir and peramivir. We found that a large cluster of the H275Y mutant virus was present prior to the main influenza season in Sapporo/Hokkaido, with the detection rate for this mutant virus reaching 29% in this area. Phylogenetic analysis suggested the clonal expansion of a single mutant virus in Sapporo/Hokkaido. To understand the reason for this large cluster, we examined the in vitro and in vivo properties of the mutant virus. We found that it grew well in cell culture, with growth comparable to that of the wild-type virus. The cluster virus also replicated well in the upper respiratory tract of ferrets and was transmitted efficiently between ferrets by way of respiratory droplets. Almost all recently circulating A(H1N1)pdm09 viruses, including the cluster virus, possessed two substitutions in NA, V241I and N369K, which are known to increase replication and transmission fitness. A structural analysis of NA predicted that a third substitution (N386K) in the NA of the cluster virus destabilized the mutant NA structure in the presence of the V241I and N369K substitutions. Our results suggest that the cluster virus retained viral fitness to spread among humans and, accordingly, caused the large cluster in Sapporo/Hokkaido. However, the mutant NA structure was less stable than that of the wild-type virus. Therefore, once the wild-type virus began to circulate in the community, the mutant virus could not compete and faded out. PMID:25691635

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

NASA Astrophysics Data System (ADS)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

Remarkable Second-Order Optical Nonlinearity of Nano-Sized Au Cluster: A TDDFT Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Kechen; Li, Jun; Lin, Chensheng

2004-04-21

The dipole polarizability, static first hyperpolarizability, and UV-vis spectrum of the recently identified nano-sized tetrahedral cluster of Au have been investigated by using time-dependent density functional response theory. We have discovered that the Au cluster possesses remarkably large molecular second-order optical nonlinearity with the first hyperpolarizabilty (xyz) calculated to be 14.3 x 10 electrostatic unit (esu). The analysis of the low-energy absorption band suggests that the charge transfer from the edged gold atoms to the vertex ones plays the key role in nonlinear optical (NLO) response of Au.

A cluster analysis of tic symptoms in children and adults with Tourette syndrome: clinical correlates and treatment outcome.

PubMed

McGuire, Joseph F; Nyirabahizi, Epiphanie; Kircanski, Katharina; Piacentini, John; Peterson, Alan L; Woods, Douglas W; Wilhelm, Sabine; Walkup, John T; Scahill, Lawrence

2013-12-30

Cluster analytic methods have examined the symptom presentation of chronic tic disorders (CTDs), with limited agreement across studies. The present study investigated patterns, clinical correlates, and treatment outcome of tic symptoms. 239 youth and adults with CTDs completed a battery of assessments at baseline to determine diagnoses, tic severity, and clinical characteristics. Participants were randomly assigned to receive either a comprehensive behavioral intervention for tics (CBIT) or psychoeducation and supportive therapy (PST). A cluster analysis was conducted on the baseline Yale Global Tic Severity Scale (YGTSS) symptom checklist to identify the constellations of tic symptoms. Four tic clusters were identified: Impulse Control and Complex Phonic Tics; Complex Motor Tics; Simple Head Motor/Vocal Tics; and Primarily Simple Motor Tics. Frequencies of tic symptoms showed few differences across youth and adults. Tic clusters had small associations with clinical characteristics and showed no associations to the presence of coexisting psychiatric conditions. Cluster membership scores did not predict treatment response to CBIT or tic severity reductions. Tic symptoms distinctly cluster with little difference across youth and adults, or coexisting conditions. This study, which is the first to examine tic clusters and response to treatment, suggested that tic symptom profiles respond equally well to CBIT. Clinical trials.gov. identifiers: NCT00218777; NCT00231985. © 2013 Elsevier Ireland Ltd. All rights reserved.

MC2: Subaru and Hubble Space Telescope Weak-lensing Analysis of the Double Radio Relic Galaxy Cluster PLCK G287.0+32.9

NASA Astrophysics Data System (ADS)

Finner, Kyle; Jee, M. James; Golovich, Nathan; Wittman, David; Dawson, William; Gruen, Daniel; Koekemoer, Anton M.; Lemaux, Brian C.; Seitz, Stella

2017-12-01

The second most significant detection of the Planck Sunyaev‑Zel’dovich survey, PLCK G287.0+32.9 (z = 0.385), boasts two similarly bright radio relics and a radio halo. One radio relic is located ∼ 400 {kpc} NW of the X-ray peak and the other ∼ 2.8 Mpc to the SE. This large difference suggests that a complex merging scenario is required. A key missing puzzle for the merging scenario reconstruction is the underlying dark matter distribution in high resolution. We present a joint Subaru Telescope and Hubble Space Telescope weak-lensing analysis of the cluster. Our analysis shows that the mass distribution features four significant substructures. Of the substructures, a primary cluster of mass {M}200{{c}}={1.59}-0.22+0.25× {10}15 {h}70-1 {M}ȯ dominates the weak-lensing signal. This cluster is likely to be undergoing a merger with one (or more) subcluster whose mass is approximately a factor of 10 lower. One candidate is the subcluster of mass {M}200{{c}}={1.16}-0.13+0.15× {10}14 {h}70-1 {M}ȯ located ∼ 400 {kpc} to the SE. The location of this subcluster suggests that its interaction with the primary cluster could be the source of the NW radio relic. Another subcluster is detected ∼ 2 Mpc to the SE of the X-ray peak with mass {M}200{{c}}={1.68}-0.20+0.22× {10}14 {h}70-1 {M}ȯ . This SE subcluster is in the vicinity of the SE radio relic and may have created the SE radio relic during a past merger with the primary cluster. The fourth subcluster, {M}200{{c}}={1.87}-0.22+0.24× {10}14 {h}70-1 {M}ȯ , is NW of the X-ray peak and beyond the NW radio relic.

Examination of Previously Published Data to Identify Patterns in the Social Representation of “Loud Music” in Young Adults Across Countries

PubMed Central

Manchaiah, Vinaya; Zhao, Fei; Oladeji, Susan; Ratinaud, Pierre

2018-01-01

Purpose: The current study was aimed at understanding the patterns in the social representation of loud music reported by young adults in different countries. Materials and Methods: The study included a sample of 534 young adults (18–25 years) from India, Iran, Portugal, United Kingdom, and United States. Participants were recruited using a convince sampling, and data were collected using the free association task. Participants were asked to provide up to five words or phrases that come to mind when thinking about “loud music.” The data were first analyzed using the qualitative content analysis. This was followed by quantitative cluster analysis and chi-square analysis. Results: The content analysis suggested 19 main categories of responses related to loud music. The cluster analysis resulted in for main clusters, namely: (1) emotional oriented perception; (2) problem oriented perception; (3) music and enjoyment oriented perception; and (4) positive emotional and recreation-oriented perception. Country of origin was associated with the likelihood of participants being in each of these clusters. Conclusion: The current study highlights the differences and similarities in young adults’ perception of loud music. These results may have implications to hearing health education to facilitate healthy listening habits. PMID:29457602

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

Cluster Analysis of Vulnerable Groups in Acute Traumatic Brain Injury Rehabilitation.

PubMed

Kucukboyaci, N Erkut; Long, Coralynn; Smith, Michelle; Rath, Joseph F; Bushnik, Tamara

2018-01-06

To analyze the complex relation between various social indicators that contribute to socioeconomic status and health care barriers. Cluster analysis of historical patient data obtained from inpatient visits. Inpatient rehabilitation unit in a large urban university hospital. Adult patients (N=148) receiving acute inpatient care, predominantly for closed head injury. Not applicable. We examined the membership of patients with traumatic brain injury in various "vulnerable group" clusters (eg, homeless, unemployed, racial/ethnic minority) and characterized the rehabilitation outcomes of patients (eg, duration of stay, changes in FIM scores between admission to inpatient stay and discharge). The cluster analysis revealed 4 major clusters (ie, clusters A-D) separated by vulnerable group memberships, with distinct durations of stay and FIM gains during their stay. Cluster B, the largest cluster and also consisting of mostly racial/ethnic minorities, had the shortest duration of hospital stay and one of the lowest FIM improvements among the 4 clusters despite higher FIM scores at admission. In cluster C, also consisting of mostly ethnic minorities with multiple socioeconomic status vulnerabilities, patients were characterized by low cognitive FIM scores at admission and the longest duration of stay, and they showed good improvement in FIM scores. Application of clustering techniques to inpatient data identified distinct clusters of patients who may experience differences in their rehabilitation outcome due to their membership in various "at-risk" groups. The results identified patients (ie, cluster B, with minority patients; and cluster D, with elderly patients) who attain below-average gains in brain injury rehabilitation. The results also suggested that systemic (eg, duration of stay) or clinical service improvements (eg, staff's language skills, ability to offer substance abuse therapy, provide appropriate referrals, liaise with intensive social work services, or plan subacute rehabilitation phase) could be beneficial for acute settings. Stronger recruitment, training, and retention initiatives for bilingual and multiethnic professionals may also be considered to optimize gains from acute inpatient rehabilitation after traumatic brain injury. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Constructing storyboards based on hierarchical clustering analysis

NASA Astrophysics Data System (ADS)

Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

2005-07-01

There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

PubMed

Lee, Hyejoo; Malaspina, Dolores; Ahn, Hongshik; Perrin, Mary; Opler, Mark G; Kleinhaus, Karine; Harlap, Susan; Goetz, Raymond; Antonius, Daniel

2011-05-01

Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia. We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ≥ 35 years) in a series of schizophrenia cases recruited from a research unit. Data were available on demographic variables, symptoms (Positive and Negative Syndrome Scale; PANSS), cognitive tests (Wechsler Adult Intelligence Scale-Revised; WAIS-R) and olfaction (University of Pennsylvania Smell Identification Test; UPSIT). We conducted a series of k-means clustering analyses to identify clusters of cases containing high concentrations of PARS. Two analyses generated clusters with high concentrations of PARS cases. The first analysis (N=136; PARS=34) revealed a cluster containing 83% PARS cases, in which the patients showed a significant discrepancy between verbal and performance intelligence. The mean paternal and maternal ages were 41 and 33, respectively. The second analysis (N=123; PARS=30) revealed a cluster containing 71% PARS cases, of which 93% were females; the mean age of onset of psychosis, at 17.2, was significantly early. These results strengthen the evidence that PARS cases differ from other patients with schizophrenia. Hypothesis-generating findings suggest that features of PARS may include a discrepancy between verbal and performance intelligence, and in females, an early age of onset. These findings provide a rationale for separating these phenotypes from others in future clinical, genetic and pathophysiologic studies of schizophrenia and in considering responses to treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

A clustering approach to segmenting users of internet-based risk calculators.

PubMed

Harle, C A; Downs, J S; Padman, R

2011-01-01

Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

The ergot alkaloid gene cluster in Claviceps purpurea: extension of the cluster sequence and intra species evolution.

PubMed

Haarmann, Thomas; Machado, Caroline; Lübbe, Yvonne; Correia, Telmo; Schardl, Christopher L; Panaccione, Daniel G; Tudzynski, Paul

2005-06-01

The genomic region of Claviceps purpurea strain P1 containing the ergot alkaloid gene cluster [Tudzynski, P., Hölter, K., Correia, T., Arntz, C., Grammel, N., Keller, U., 1999. Evidence for an ergot alkaloid gene cluster in Claviceps purpurea. Mol. Gen. Genet. 261, 133-141] was explored by chromosome walking, and additional genes probably involved in the ergot alkaloid biosynthesis have been identified. The putative cluster sequence (extending over 68.5kb) contains 4 different nonribosomal peptide synthetase (NRPS) genes and several putative oxidases. Northern analysis showed that most of the genes were co-regulated (repressed by high phosphate), and identified probable flanking genes by lack of co-regulation. Comparison of the cluster sequences of strain P1, an ergotamine producer, with that of strain ECC93, an ergocristine producer, showed high conservation of most of the cluster genes, but significant variation in the NRPS modules, strongly suggesting that evolution of these chemical races of C. purpurea is determined by evolution of NRPS module specificity.

The Atacama Cosmology Telescope: Cosmology from Galaxy Clusters Detected Via the Sunyaev-Zel'dovich Effect

NASA Technical Reports Server (NTRS)

Sehgal, Neelima; Trac, Hy; Acquaviva, Viviana; Ade, Peter A. R.; Aguirre, Paula; Amiri, Mandana; Appel, John W.; Barrientos, L. Felipe; Battistelli, Elia S.; Bond, J. Richard;

Legacy ExtraGalactic UV Survey with The Hubble Space Telescope: Stellar Cluster Catalogs and First Insights Into Cluster Formation and Evolution in NGC 628

NASA Astrophysics Data System (ADS)

Adamo, A.; Ryon, J. E.; Messa, M.; Kim, H.; Grasha, K.; Cook, D. O.; Calzetti, D.; Lee, J. C.; Whitmore, B. C.; Elmegreen, B. G.; Ubeda, L.; Smith, L. J.; Bright, S. N.; Runnholm, A.; Andrews, J. E.; Fumagalli, M.; Gouliermis, D. A.; Kahre, L.; Nair, P.; Thilker, D.; Walterbos, R.; Wofford, A.; Aloisi, A.; Ashworth, G.; Brown, T. M.; Chandar, R.; Christian, C.; Cignoni, M.; Clayton, G. C.; Dale, D. A.; de Mink, S. E.; Dobbs, C.; Elmegreen, D. M.; Evans, A. S.; Gallagher, J. S., III; Grebel, E. K.; Herrero, A.; Hunter, D. A.; Johnson, K. E.; Kennicutt, R. C.; Krumholz, M. R.; Lennon, D.; Levay, K.; Martin, C.; Nota, A.; Östlin, G.; Pellerin, A.; Prieto, J.; Regan, M. W.; Sabbi, E.; Sacchi, E.; Schaerer, D.; Schiminovich, D.; Shabani, F.; Tosi, M.; Van Dyk, S. D.; Zackrisson, E.

2017-06-01

We report the large effort that is producing comprehensive high-level young star cluster (YSC) catalogs for a significant fraction of galaxies observed with the Legacy ExtraGalactic UV Survey (LEGUS) Hubble treasury program. We present the methodology developed to extract cluster positions, verify their genuine nature, produce multiband photometry (from NUV to NIR), and derive their physical properties via spectral energy distribution fitting analyses. We use the nearby spiral galaxy NGC 628 as a test case for demonstrating the impact that LEGUS will have on our understanding of the formation and evolution of YSCs and compact stellar associations within their host galaxy. Our analysis of the cluster luminosity function from the UV to the NIR finds a steepening at the bright end and at all wavelengths suggesting a dearth of luminous clusters. The cluster mass function of NGC 628 is consistent with a power-law distribution of slopes ˜ -2 and a truncation of a few times 105 {M}⊙ . After their formation, YSCs and compact associations follow different evolutionary paths. YSCs survive for a longer time frame, confirming their being potentially bound systems. Associations disappear on timescales comparable to hierarchically organized star-forming regions, suggesting that they are expanding systems. We find mass-independent cluster disruption in the inner region of NGC 628, while in the outer part of the galaxy there is little or no disruption. We observe faster disruption rates for low mass (≤104 {M}⊙ ) clusters, suggesting that a mass-dependent component is necessary to fully describe the YSC disruption process in NGC 628. Based on observations obtained with the NASA/ESA Hubble Space Telescope, at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

Architecture of Eph receptor clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Himanen, Juha P.; Yermekbayeva, Laila; Janes, Peter W.

2010-10-04

Eph receptor tyrosine kinases and their ephrin ligands regulate cell navigation during normal and oncogenic development. Signaling of Ephs is initiated in a multistep process leading to the assembly of higher-order signaling clusters that set off bidirectional signaling in interacting cells. However, the structural and mechanistic details of this assembly remained undefined. Here we present high-resolution structures of the complete EphA2 ectodomain and complexes with ephrin-A1 and A5 as the base unit of an Eph cluster. The structures reveal an elongated architecture with novel Eph/Eph interactions, both within and outside of the Eph ligand-binding domain, that suggest the molecular mechanismmore » underlying Eph/ephrin clustering. Structure-function analysis, by using site-directed mutagenesis and cell-based signaling assays, confirms the importance of the identified oligomerization interfaces for Eph clustering.« less

Cluster folding analysis of 20Ne+16O elastic transfer

NASA Astrophysics Data System (ADS)

Hamada, Sh.; Keeley, N.; Kemper, K. W.; Rusek, K.

2018-05-01

The available experimental data for the 20Ne+16O system in the energy range where the effect of α -cluster transfer is well observed are reanalyzed using the cluster folding model. The cluster folding potential, which includes both real and imaginary terms, reproduces the data at forward angles and the inclusion of the 16O(20Ne,16O)20Ne elastic transfer process provides a satisfactory description of the backward angles. The spectroscopic factor for the 20Ne→16O+α overlap was extracted and compared with other values from the literature. The present results suggest that the (20Ne,16O ) reaction might be an alternative means of exploring the α -particle structure of nuclei.

Role and Regulation of the Flp/Tad Pilus in the Virulence of Pectobacterium atrosepticum SCRI1043 and Pectobacterium wasabiae SCC3193

PubMed Central

Nykyri, Johanna; Mattinen, Laura; Niemi, Outi; Adhikari, Satish; Kõiv, Viia; Somervuo, Panu; Fang, Xin; Auvinen, Petri; Mäe, Andres; Palva, E. Tapio; Pirhonen, Minna

2013-01-01

In this study, we characterized a putative Flp/Tad pilus-encoding gene cluster, and we examined its regulation at the transcriptional level and its role in the virulence of potato pathogenic enterobacteria of the genus Pectobacterium. The Flp/Tad pilus-encoding gene clusters in Pectobacterium atrosepticum, Pectobacterium wasabiae and Pectobacterium aroidearum were compared to previously characterized flp/tad gene clusters, including that of the well-studied Flp/Tad pilus model organism Aggregatibacter actinomycetemcomitans, in which this pilus is a major virulence determinant. Comparative analyses revealed substantial protein sequence similarity and open reading frame synteny between the previously characterized flp/tad gene clusters and the cluster in Pectobacterium, suggesting that the predicted flp/tad gene cluster in Pectobacterium encodes a Flp/Tad pilus-like structure. We detected genes for a novel two-component system adjacent to the flp/tad gene cluster in Pectobacterium, and mutant analysis demonstrated that this system has a positive effect on the transcription of selected Flp/Tad pilus biogenesis genes, suggesting that this response regulator regulate the flp/tad gene cluster. Mutagenesis of either the predicted regulator gene or selected Flp/Tad pilus biogenesis genes had a significant impact on the maceration ability of the bacterial strains in potato tubers, indicating that the Flp/Tad pilus-encoding gene cluster represents a novel virulence determinant in Pectobacterium. Soft-rot enterobacteria in the genera Pectobacterium and Dickeya are of great agricultural importance, and an investigation of the virulence of these pathogens could facilitate improvements in agricultural practices, thus benefiting farmers, the potato industry and consumers. PMID:24040039

Role and regulation of the Flp/Tad pilus in the virulence of Pectobacterium atrosepticum SCRI1043 and Pectobacterium wasabiae SCC3193.

PubMed

Nykyri, Johanna; Mattinen, Laura; Niemi, Outi; Adhikari, Satish; Kõiv, Viia; Somervuo, Panu; Fang, Xin; Auvinen, Petri; Mäe, Andres; Palva, E Tapio; Pirhonen, Minna

2013-01-01

In this study, we characterized a putative Flp/Tad pilus-encoding gene cluster, and we examined its regulation at the transcriptional level and its role in the virulence of potato pathogenic enterobacteria of the genus Pectobacterium. The Flp/Tad pilus-encoding gene clusters in Pectobacterium atrosepticum, Pectobacterium wasabiae and Pectobacterium aroidearum were compared to previously characterized flp/tad gene clusters, including that of the well-studied Flp/Tad pilus model organism Aggregatibacter actinomycetemcomitans, in which this pilus is a major virulence determinant. Comparative analyses revealed substantial protein sequence similarity and open reading frame synteny between the previously characterized flp/tad gene clusters and the cluster in Pectobacterium, suggesting that the predicted flp/tad gene cluster in Pectobacterium encodes a Flp/Tad pilus-like structure. We detected genes for a novel two-component system adjacent to the flp/tad gene cluster in Pectobacterium, and mutant analysis demonstrated that this system has a positive effect on the transcription of selected Flp/Tad pilus biogenesis genes, suggesting that this response regulator regulate the flp/tad gene cluster. Mutagenesis of either the predicted regulator gene or selected Flp/Tad pilus biogenesis genes had a significant impact on the maceration ability of the bacterial strains in potato tubers, indicating that the Flp/Tad pilus-encoding gene cluster represents a novel virulence determinant in Pectobacterium. Soft-rot enterobacteria in the genera Pectobacterium and Dickeya are of great agricultural importance, and an investigation of the virulence of these pathogens could facilitate improvements in agricultural practices, thus benefiting farmers, the potato industry and consumers.

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Changing the paradigm: messages for hand hygiene education and audit from cluster analysis.

PubMed

Gould, D J; Navaie, D; Purssell, E; Drey, N S; Creedon, S

2018-04-01

Hand hygiene is considered to be the foremost infection prevention measure. How healthcare workers accept and make sense of the hand hygiene message is likely to contribute to the success and sustainability of initiatives to improve performance, which is often poor. A survey of nurses in critical care units in three National Health Service trusts in England was undertaken to explore opinions about hand hygiene, use of alcohol hand rubs, audit with performance feedback, and other key hand-hygiene-related issues. Data were analysed descriptively and subjected to cluster analysis. Three main clusters of opinion were visualized, each forming a significant group: positive attitudes, pragmatism and scepticism. A smaller cluster suggested possible guilt about ability to perform hand hygiene. Cluster analysis identified previously unsuspected constellations of beliefs about hand hygiene that offer a plausible explanation for behaviour. Healthcare workers might respond to education and audit differently according to these beliefs. Those holding predominantly positive opinions might comply with hand hygiene policy and perform well as infection prevention link nurses and champions. Those holding pragmatic attitudes are likely to respond favourably to the need for professional behaviour and need to protect themselves from infection. Greater persuasion may be needed to encourage those who are sceptical about the importance of hand hygiene to comply with guidelines. Interventions to increase compliance should be sufficiently broad in scope to tackle different beliefs. Alternatively, cluster analysis of hand hygiene beliefs could be used to identify the most effective educational and monitoring strategies for a particular clinical setting. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Evolutionary interpretations of mycobacteriophage biodiversity and host-range through the analysis of codon usage bias.

PubMed

Esposito, Lauren A; Gupta, Swati; Streiter, Fraida; Prasad, Ashley; Dennehy, John J

2016-10-01

In an genomics course sponsored by the Howard Hughes Medical Institute (HHMI), undergraduate students have isolated and sequenced the genomes of more than 1,150 mycobacteriophages, creating the largest database of sequenced bacteriophages able to infect a single host, Mycobacterium smegmatis , a soil bacterium. Genomic analysis indicates that these mycobacteriophages can be grouped into 26 clusters based on genetic similarity. These clusters span a continuum of genetic diversity, with extensive genomic mosaicism among phages in different clusters. However, little is known regarding the primary hosts of these mycobacteriophages in their natural habitats, nor of their broader host ranges. As such, it is possible that the primary host of many newly isolated mycobacteriophages is not M. smegmatis , but instead a range of closely related bacterial species. However, determining mycobacteriophage host range presents difficulties associated with mycobacterial cultivability, pathogenicity and growth. Another way to gain insight into mycobacteriophage host range and ecology is through bioinformatic analysis of their genomic sequences. To this end, we examined the correlations between the codon usage biases of 199 different mycobacteriophages and those of several fully sequenced mycobacterial species in order to gain insight into the natural host range of these mycobacteriophages. We find that UPGMA clustering tends to match, but not consistently, clustering by shared nucleotide sequence identify. In addition, analysis of GC content, tRNA usage and correlations between mycobacteriophage and mycobacterial codon usage bias suggests that the preferred host of many clustered mycobacteriophages is not M. smegmatis but other, as yet unknown, members of the mycobacteria complex or closely allied bacterial species.

Evolutionary interpretations of mycobacteriophage biodiversity and host-range through the analysis of codon usage bias

PubMed Central

Esposito, Lauren A.; Gupta, Swati; Streiter, Fraida; Prasad, Ashley

2016-01-01

In an genomics course sponsored by the Howard Hughes Medical Institute (HHMI), undergraduate students have isolated and sequenced the genomes of more than 1,150 mycobacteriophages, creating the largest database of sequenced bacteriophages able to infect a single host, Mycobacterium smegmatis, a soil bacterium. Genomic analysis indicates that these mycobacteriophages can be grouped into 26 clusters based on genetic similarity. These clusters span a continuum of genetic diversity, with extensive genomic mosaicism among phages in different clusters. However, little is known regarding the primary hosts of these mycobacteriophages in their natural habitats, nor of their broader host ranges. As such, it is possible that the primary host of many newly isolated mycobacteriophages is not M. smegmatis, but instead a range of closely related bacterial species. However, determining mycobacteriophage host range presents difficulties associated with mycobacterial cultivability, pathogenicity and growth. Another way to gain insight into mycobacteriophage host range and ecology is through bioinformatic analysis of their genomic sequences. To this end, we examined the correlations between the codon usage biases of 199 different mycobacteriophages and those of several fully sequenced mycobacterial species in order to gain insight into the natural host range of these mycobacteriophages. We find that UPGMA clustering tends to match, but not consistently, clustering by shared nucleotide sequence identify. In addition, analysis of GC content, tRNA usage and correlations between mycobacteriophage and mycobacterial codon usage bias suggests that the preferred host of many clustered mycobacteriophages is not M. smegmatis but other, as yet unknown, members of the mycobacteria complex or closely allied bacterial species. PMID:28348827

Validity analysis on merged and averaged data using within and between analysis: focus on effect of qualitative social capital on self-rated health.

PubMed

Shin, Sang Soo; Shin, Young-Jeon

2016-01-01

With an increasing number of studies highlighting regional social capital (SC) as a determinant of health, many studies are using multi-level analysis with merged and averaged scores of community residents' survey responses calculated from community SC data. Sufficient examination is required to validate if the merged and averaged data can represent the community. Therefore, this study analyzes the validity of the selected indicators and their applicability in multi-level analysis. Within and between analysis (WABA) was performed after creating community variables using merged and averaged data of community residents' responses from the 2013 Community Health Survey in Korea, using subjective self-rated health assessment as a dependent variable. Further analysis was performed following the model suggested by WABA result. Both E-test results (1) and WABA results (2) revealed that single-level analysis needs to be performed using qualitative SC variable with cluster mean centering. Through single-level multivariate regression analysis, qualitative SC with cluster mean centering showed positive effect on self-rated health (0.054, p<0.001), although there was no substantial difference in comparison to analysis using SC variables without cluster mean centering or multi-level analysis. As modification in qualitative SC was larger within the community than between communities, we validate that relational analysis of individual self-rated health can be performed within the group, using cluster mean centering. Other tests besides the WABA can be performed in the future to confirm the validity of using community variables and their applicability in multi-level analysis.

The full-length microRNA cluster in the intron of large latency transcript is associated with the virulence of pseudorabies virus.

PubMed

Wang, Xin; Zhang, Mei-Mei; Yan, Kai; Tang, Qi; Wu, Yi-Quan; He, Wen-Bo; Chen, Huan-Chun; Liu, Zheng-Fei

2018-07-01

Pseudorabies virus (PRV), the etiological pathogen of Aujeszky's disease, belongs to the Alphaherpesvirus subfamily. Large latency transcript (LLT), the most abundant PRV transcript, harbors a ~ 4.6 kb microRNA (miRNA) cluster-encoding intron. To investigate the function of the LLT miRNA cluster during the life cycle of PRV, we generated a miRNA cluster mutation virus (PRV-∆miR cluster) and revertant virus. Analysis of the growth kinetics of PRV-ΔmiR cluster-infected cells revealed significantly smaller plaques and lower titers than the wild-type and revertant viruses. The mutation virus exhibited increased IE180 and decreased EP0 expression. The clinical symptoms observed in mice infected with PRV-ΔmiR cluster revealed that the miRNA cluster is involved in the pathogenesis of PRV. Physical parameters, virus shedding assays, and the SN 50 titers revealed that the miRNA cluster enhances PRV virulence in pigs. Collectively, our findings suggest that the full-length miRNA cluster is involved in PRV replication and virulence. Copyright © 2018 Elsevier Inc. All rights reserved.

The formation and evolution of M33 as revealed by its star clusters

NASA Astrophysics Data System (ADS)

San Roman, Izaskun

2012-03-01

Numerical simulations based on the Lambda-Cold Dark Matter (Λ-CDM) model predict a scenario consistent with observational evidence in terms of the build-up of Milky Way-like halos. Under this scenario, large disk galaxies derive from the merger and accretion of many smaller subsystems. However, it is less clear how low-mass spiral galaxies fit into this picture. The best way to answer this question is to study the nearest example of a dwarf spiral galaxy, M33. We will use star clusters to understand the structure, kinematics and stellar populations of this galaxy. Star clusters provide a unique and powerful tool for studying the star formation histories of galaxies. In particular, the ages and metallicities of star clusters bear the imprint of the galaxy formation process. We have made use of the star clusters to uncover the formation and evolution of M33. In this dissertation, we have carried out a comprehensive study of the M33 star cluster system, including deep photometry as well as high signal-to-noise spectroscopy. In order to mitigate the significant incompleteness presents in previous catalogs, we have conducted ground-based and space-based photometric surveys of M33 star clusters. Using archival images, we have analyzed 12 fields using the Advanced Camera for Surveys Wide Field Channel onboard the Hubble Space Telescope (ACS/HST) along the major axis of the galaxy. We present integrated photometry and color-magnitude diagrams for 161 star clusters in M33, of which 115 were previously uncataloged. This survey extends the depth of the existing M33 cluster catalogs by ˜ 1 mag. We have expanded our search through a photometric survey in a 1° x 1° area centered on M33 using the MegaCam camera on the 3.6m Canada-France-Hawaii Telescope (CFHT). In this work we discuss the photometric properties of the sample, including color-color diagrams of 599 new candidate stellar clusters, and 204 confirmed clusters. Comparisons with models of simple stellar populations suggest a large range of ages some as old as ˜ 10 Gyr. In addition, we find in the color-color diagrams a significant population of very young clusters (< 10 Myr) possessing nebular emission. Analysis of the radial density distribution suggests that the cluster system of M33 has suffered from significant depletion, possibly due to interactions with M31. To further understand the properties of M33 star clusters, we have carried out a morphological study 161 star clusters in M33 using ACS/HST images. We have obtained, for the first time, ellipticities, position angles, and surface brightness profiles of a statistically significant number of clusters. Ellipticities show that, on average, M33 clusters are more flattened than those of the Milky Way and M31, and more similar to clusters in the Small Magellanic Cloud. The ellipticities do not show any correlation with age or mass, suggesting that rotation is not the main cause of elongation in the M33 clusters. The position angles of the clusters show a bimodality with a strong peak perpendicular to the position angle of the galaxy. These results support the notion that tidal forces are the reason for the cluster flattening. We have fit analytical models to the surface brightness profiles, and derived structural parameters. The overall analysis shows several differences between the structural properties of the M33 cluster system and cluster systems in nearby galaxies. Finally, we have performed a spectroscopic study of star clusters in the above mentioned catalog. We present high-precision velocity measures of 45 star clusters, based on observations from the 10.4m Gran Telescopio Canarias (GTC) using OSIRIS and 4.2m William Herschel Telescope (WHT) using WYFFOS. All the clusters have been previously confirmed using HST imaging, and ages and integrated photometry are known. The velocity of the clusters with respect to local disk motion increases with age for young and intermediate clusters. The mean dispersion velocity for the intermediate age clusters in our sample is significantly larger than in previous studies. Analysis of these velocities along the major axis of the galaxy show no net rotation of the intermediate age subsample. The small number of old clusters in our sample does not allow for any conclusive evidence in that age division.

Comparative genomic analysis of 26 Sphingomonas and Sphingobium strains: Dissemination of bioremediation capabilities, biodegradation potential and horizontal gene transfer.

PubMed

Zhao, Qiang; Yue, Shengjie; Bilal, Muhammad; Hu, Hongbo; Wang, Wei; Zhang, Xuehong

2017-12-31

Bacteria belonging to the genera Sphingomonas and Sphingobium are known for their ability to catabolize aromatic compounds. In this study, we analyzed the whole genome sequences of 26 strains in the genera Sphingomonas and Sphingobium to gain insight into dissemination of bioremediation capabilities, biodegradation potential, central pathways and genome plasticity. Phylogenetic analysis revealed that both Sphingomonas sp. strain BHC-A and Sphingomonas paucimobilis EPA505 should be placed in the genus Sphingobium. The bph and xyl gene cluster was found in 6 polycyclic aromatic hydrocarbons-degrading strains. Transposase and IS coding genes were found in the 6 gene clusters, suggesting the mobility of bph and xyl gene clusters. β-ketoadipate and homogentisate pathways were the main central pathways in Sphingomonas and Sphingobium strains. A large number of oxygenase coding genes were predicted in the 26 genomes, indicating a huge biodegradation potential of the Sphingomonas and Sphingobium strains. Horizontal gene transfer related genes and prophages were predicted in the analyzed strains, suggesting the ongoing evolution and shaping of the genomes. Analysis of the 26 genomes in this work contributes to the understanding of dispersion of bioremediation capabilities, bioremediation potential and genome plasticity in strains belonging to the genera Sphingomonas and Sphingobium. Copyright © 2017 Elsevier B.V. All rights reserved.

Cluster Analysis of Velocity Field Derived from Dense GNSS Network of Japan

NASA Astrophysics Data System (ADS)

Takahashi, A.; Hashimoto, M.

2015-12-01

Dense GNSS networks have been widely used to observe crustal deformation. Simpson et al. (2012) and Savage and Simpson (2013) have conducted cluster analyses of GNSS velocity field in the San Francisco Bay Area and Mojave Desert, respectively. They have successfully found velocity discontinuities. They also showed an advantage of cluster analysis for classifying GNSS velocity field. Since in western United States, strike-slip events are dominant, geometry is simple. However, the Japanese Islands are tectonically complicated due to subduction of oceanic plates. There are many types of crustal deformation such as slow slip event and large postseismic deformation. We propose a modified clustering method of GNSS velocity field in Japan to separate time variant and static crustal deformation. Our modification is performing cluster analysis every several months or years, then qualifying cluster member similarity. If a GNSS station moved differently from its neighboring GNSS stations, the station will not belong to in the cluster which includes its surrounding stations. With this method, time variant phenomena were distinguished. We applied our method to GNSS data of Japan from 1996 to 2015. According to the analyses, following conclusions were derived. The first is the clusters boundaries are consistent with known active faults. For examples, the Arima-Takatsuki-Hanaore fault system and the Shimane-Tottori segment proposed by Nishimura (2015) are recognized, though without using prior information. The second is improving detectability of time variable phenomena, such as a slow slip event in northern part of Hokkaido region detected by Ohzono et al. (2015). The last one is the classification of postseismic deformation caused by large earthquakes. The result suggested velocity discontinuities in postseismic deformation of the Tohoku-oki earthquake. This result implies that postseismic deformation is not continuously decaying proportional to distance from its epicenter.

Measuring consistent masses for 25 Milky Way globular clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kimmig, Brian; Seth, Anil; Ivans, Inese I.

2015-02-01

We present central velocity dispersions, masses, mass-to-light ratios (M/Ls ), and rotation strengths for 25 Galactic globular clusters (GCs). We derive radial velocities of 1951 stars in 12 GCs from single order spectra taken with Hectochelle on the MMT telescope. To this sample we add an analysis of available archival data of individual stars. For the full set of data we fit King models to derive consistent dynamical parameters for the clusters. We find good agreement between single-mass King models and the observed radial dispersion profiles. The large, uniform sample of dynamical masses we derive enables us to examine trendsmore » of M/L with cluster mass and metallicity. The overall values of M/L and the trends with mass and metallicity are consistent with existing measurements from a large sample of M31 clusters. This includes a clear trend of increasing M/L with cluster mass and lower than expected M/Ls for the metal-rich clusters. We find no clear trend of increasing rotation with increasing cluster metallicity suggested in previous work.« less

ANALYSIS AND CHARACTERIZATION OF OZONE-RICH EPISODES IN NORTHEAST PORTUGAL

NASA Astrophysics Data System (ADS)

Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.

2009-12-01

Each summer period extremely high ozone levels are registered at the rural background station of Lamas d’Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes. Synoptic patterns anomalies and back trajectories cluster analysis were performed for a period of 76 days where ozone maximum concentrations were above 200 µg.m-3. This analysis was performed for the period between 2004 and 2007. The obtained anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. In addition, a strong wind flow pattern from NE is visible in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, is responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants may be the main contributor to the ozone levels registered at Lamas d’Olo. This is also highlighted by the correlation of the ozone time series with the meteorological parameters analysed in the frequency domain.

Cerebral and non-cerebral coenurosis: on the genotypic and phenotypic diversity of Taenia multiceps.

PubMed

Christodoulopoulos, Georgios; Dinkel, Anke; Romig, Thomas; Ebi, Dennis; Mackenstedt, Ute; Loos-Frank, Brigitte

2016-12-01

We characterised the causative agents of cerebral and non-cerebral coenurosis in livestock by determining the mitochondrial genotypes and morphological phenotypes of 52 Taenia multiceps isolates from a wide geographical range in Europe, Africa, and western Asia. Three studies were conducted: (1) a morphological comparison of the rostellar hooks of cerebral and non-cerebral cysts of sheep and goats, (2) a morphological comparison of adult worms experimentally produced in dogs, and (3) a molecular analysis of three partial mitochondrial genes (nad1, cox1, and 12S rRNA) of the same isolates. No significant morphological or genetic differences were associated with the species of the intermediate host. Adult parasites originating from cerebral and non-cerebral cysts differed morphologically, e.g. the shape of the small hooks and the distribution of the testes in the mature proglottids. The phylogenetic analysis of the mitochondrial haplotypes produced three distinct clusters: one cluster including both cerebral isolates from Greece and non-cerebral isolates from tropical and subtropical countries, and two clusters including cerebral isolates from Greece. The majority of the non-cerebral specimens clustered together but did not form a monophyletic group. No monophyletic groups were observed based on geography, although specimens from the same region tended to cluster. The clustering indicates high intraspecific diversity. The phylogenetic analysis suggests that all variants of T. multiceps can cause cerebral coenurosis in sheep (which may be the ancestral phenotype), and some variants, predominantly from one genetic cluster, acquired the additional capacity to produce non-cerebral forms in goats and more rarely in sheep.

The observed clustering of damaging extra-tropical cyclones in Europe

NASA Astrophysics Data System (ADS)

Cusack, S.

2015-12-01

The clustering of severe European windstorms on annual timescales has substantial impacts on the re/insurance industry. Management of the risk is impaired by large uncertainties in estimates of clustering from historical storm datasets typically covering the past few decades. The uncertainties are unusually large because clustering depends on the variance of storm counts. Eight storm datasets are gathered for analysis in this study in order to reduce these uncertainties. Six of the datasets contain more than 100~years of severe storm information to reduce sampling errors, and the diversity of information sources and analysis methods between datasets sample observational errors. All storm severity measures used in this study reflect damage, to suit re/insurance applications. It is found that the shortest storm dataset of 42 years in length provides estimates of clustering with very large sampling and observational errors. The dataset does provide some useful information: indications of stronger clustering for more severe storms, particularly for southern countries off the main storm track. However, substantially different results are produced by removal of one stormy season, 1989/1990, which illustrates the large uncertainties from a 42-year dataset. The extended storm records place 1989/1990 into a much longer historical context to produce more robust estimates of clustering. All the extended storm datasets show a greater degree of clustering with increasing storm severity and suggest clustering of severe storms is much more material than weaker storms. Further, they contain signs of stronger clustering in areas off the main storm track, and weaker clustering for smaller-sized areas, though these signals are smaller than uncertainties in actual values. Both the improvement of existing storm records and development of new historical storm datasets would help to improve management of this risk.

Structure function and splice site analysis of the synaptogenic activity of the neurexin-1 beta LNS domain.

PubMed

Graf, Ethan R; Kang, Yunhee; Hauner, Anna M; Craig, Ann Marie

2006-04-19

Recent findings suggest that the neurexin-neuroligin link promotes both GABAergic and glutamatergic synaptogenesis, but the mechanism by which neurexins influence the clustering of appropriate neuroligins and postsynaptic differentiation remains unclear. Previous studies suggested that the presence or absence of alternatively spliced residues at splice site 4 (S4) in the neurexin LNS domain may regulate neurexin function. We demonstrate that addition of the S4 insert selectively reduces the ability of neurexin-1beta to cluster neuroligin-1/3/4 and glutamatergic postsynaptic proteins, although clustering of neuroligin-2 and GABAergic postsynaptic proteins remain strong. Furthermore, addition of the S4 insert decreases the binding affinity of neurexin-1beta to neuroligins-1 and -4 but has little effect on binding to neuroligins-2 and -3. Additional structure-function studies reveal the neurexin binding interface mediating synaptogenic activity to be composed primarily of residues in the beta2beta3, beta6beta7, and beta10beta11 loops on one rim of the LNS domain beta sandwich. Mutation of two predicted Ca(2+)-binding residues disrupts postsynaptic protein clustering and binding to neuroligins, consistent with previous findings that neurexin-neuroligin binding is Ca2+ dependent. Glutamatergic postsynaptic clustering was more readily disrupted by the mutagenesis than GABAergic postsynaptic protein clustering. Perhaps neurexins-neuroligins, or neurexin-1beta at least, is most important for GABA synapse formation or controlling the balance of GABA and glutamate synapses. These results suggest that differential neurexin-neuroligin binding affinities and splice variations may play an instructive role in postsynaptic differentiation.

Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI).

PubMed

Fyffe, Denise; Kalpakjian, Claire Z; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C; Tulsky, David S; Jette, Alan M

2016-09-01

To provide validation of functional ability levels for the Spinal Cord Injury - Functional Index (SCI-FI). Cross-sectional. Inpatient rehabilitation hospital and community settings. A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Not Applicable. Spinal Cord Injury-Functional Index (SCI-FI). Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan

PubMed Central

Park, Rachel; O'Brien, Thomas F.; Huang, Susan S.; Baker, Meghan A.; Yokoe, Deborah S.; Kulldorff, Martin; Barrett, Craig; Swift, Jamie; Stelling, John

2016-01-01

Objectives While antimicrobial resistance threatens the prevention, treatment, and control of infectious diseases, systematic analysis of routine microbiology laboratory test results worldwide can alert new threats and promote timely response. This study explores statistical algorithms for recognizing geographic clustering of multi-resistant microbes within a healthcare network and monitoring the dissemination of new strains over time. Methods Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. We explored geographic clustering of multi-resistance phenotypes within the network and changes in clustering over time. Results Geographic clustering identified from both latitude/longitude and non-parametric facility groupings geographic models were similar, while the latter was offers greater flexibility and generalizability. Iterative application of the clustering algorithms suggested the possible recognition of the initial appearance of invasive E. coli ST131 in the clinical database of a single hospital and subsequent dissemination to others. Conclusion Systematic analysis of routine antimicrobial resistance susceptibility test results supports the recognition of geographic clustering of microbial phenotypic subpopulations with WHONET and SaTScan, and iterative application of these algorithms can detect the initial appearance in and dissemination across a region prompting early investigation, response, and containment measures. PMID:27530311

Typology of schizotypy in non-clinical young adults: Psychopathological and personality disorder traits correlates.

PubMed

Raynal, Patrick; Goutaudier, Nelly; Nidetch, Victoria; Chabrol, Henri

2016-12-30

Few typological studies address schizotypy in young adults. Schizotypal traits were assessed on 466 college students using the Schizotypal Personality Questionnaire-Brief (SPQ-B). Other measures evaluated personality traits previously associated with schizotypy (borderline, obsessionnal, and autistic traits), psychopathological symptoms (suicidal ideations, depressive and obsessive-compulsive symptoms) and psychosocial functioning. A factor analysis was first performed on SPQ-B results, leading to four factors: negative schizotypy, positive schizotypy, social anxiety, and reference ideas. Based on these factors, a cluster analysis was conducted, which yielded four clearly distinct groups characterized by "Low" (non schizotypy), "High schizotypy" (mixed positive and negative), "Positive schizotypy", and "Social impairment". Regarding personality disorder traits and psychopathological symptoms, the "High schizotypy" cluster scored higher than the "Positive" and the "Social impairment" groups, which scored higher than the "Low" cluster. The "Positive" group had higher levels of interpersonal relationships than in the "High" and the "Social impairment" clusters, suggesting that positive schizotypy was associated to benefits such as perceived social relationships. Nevertheless the "Positive" cluster was also linked to high levels of personality disorder traits and psychopathological symptoms, and to low academic achievement, at levels similar those observed in the "Social impairment" cluster, confirming an unhealthy side to positive schizotypy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Phylodynamic and Phylogeographic Patterns of the HIV Type 1 Subtype F1 Parenteral Epidemic in Romania

PubMed Central

Hué, Stéphane; Buckton, Andrew J.; Myers, Richard E.; Duiculescu, Dan; Ene, Luminita; Oprea, Cristiana; Tardei, Gratiela; Rugina, Sorin; Mardarescu, Mariana; Floch, Corinne; Notheis, Gundula; Zöhrer, Bettina; Cane, Patricia A.; Pillay, Deenan

2012-01-01

Abstract In the late 1980s an HIV-1 epidemic emerged in Romania that was dominated by subtype F1. The main route of infection is believed to be parenteral transmission in children. We sequenced partial pol coding regions of 70 subtype F1 samples from children and adolescents from the PENTA-EPPICC network of which 67 were from Romania. Phylogenetic reconstruction using the sequences and other publically available global subtype F sequences showed that 79% of Romanian F1 sequences formed a statistically robust monophyletic cluster. The monophyletic cluster was epidemiologically linked to parenteral transmission in children. Coalescent-based analysis dated the origins of the parenteral epidemic to 1983 [1981–1987; 95% HPD]. The analysis also shows that the epidemic's effective population size has remained fairly constant since the early 1990s suggesting limited onward spread of the virus within the population. Furthermore, phylogeographic analysis suggests that the root location of the parenteral epidemic was Bucharest. PMID:22251065

Probing the History of Galaxy Clusters with Metallicity and Entropy Measurements

NASA Astrophysics Data System (ADS)

Elkholy, Tamer Yohanna

Galaxy clusters are the largest gravitationally bound objects found today in our Universe. The gas they contain, the intra-cluster medium (ICM), is heated to temperatures in the approximate range of 1 to 10 keV, and thus emits X-ray radiation. Studying the ICM through the spatial and spectral analysis of its emission returns the richest information about both the overall cosmological context which governs the formation of clusters, as well as the physical processes occurring within. The aim of this thesis is to learn about the history of the physical processes that drive the evolution of galaxy clusters, through careful, spatially resolved measurements of their metallicity and entropy content. A sample of 45 nearby clusters observed with Chandra is analyzed to produce radial density, temperature, entropy and metallicity profiles. The entropy profiles are computed to larger radial extents than in previous Chandra analyses. The results of this analysis are made available to the scientific community in an electronic database. Comparing metallicity and entropy in the outskirts of clusters, we find no signature on the entropy profiles of the ensemble of supernovae that produced the observed metals. In the centers of clusters, we find that the metallicities of high-mass clusters are much less dispersed than those of low-mass clusters. A comparison of metallicity with the regularity of the X-ray emission morphology suggests that metallicities in low-mass clusters are more susceptible to increase from violent events such as mergers. We also find that the variation in the stellar-to-gas mass ratio as a function of cluster mass can explain the variation of central metallicity with cluster mass, only if we assume that there is a constant level of metallicity for clusters of all masses, above which the observed galaxies add more metals in proportion to their mass. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011.

PubMed

Shields, Timothy; Pinchoff, Jessie; Lubinda, Jailos; Hamapumbu, Harry; Searle, Kelly; Kobayashi, Tamaki; Thuma, Philip E; Moss, William J; Curriero, Frank C

2016-05-31

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Random Walk Quantum Clustering Algorithm Based on Space

NASA Astrophysics Data System (ADS)

Xiao, Shufen; Dong, Yumin; Ma, Hongyang

2018-01-01

In the random quantum walk, which is a quantum simulation of the classical walk, data points interacted when selecting the appropriate walk strategy by taking advantage of quantum-entanglement features; thus, the results obtained when the quantum walk is used are different from those when the classical walk is adopted. A new quantum walk clustering algorithm based on space is proposed by applying the quantum walk to clustering analysis. In this algorithm, data points are viewed as walking participants, and similar data points are clustered using the walk function in the pay-off matrix according to a certain rule. The walk process is simplified by implementing a space-combining rule. The proposed algorithm is validated by a simulation test and is proved superior to existing clustering algorithms, namely, Kmeans, PCA + Kmeans, and LDA-Km. The effects of some of the parameters in the proposed algorithm on its performance are also analyzed and discussed. Specific suggestions are provided.

Sorting Five Human Tumor Types Reveals Specific Biomarkers and Background Classification Genes.

PubMed

Roche, Kimberly E; Weinstein, Marvin; Dunwoodie, Leland J; Poehlman, William L; Feltus, Frank A

2018-05-25

We applied two state-of-the-art, knowledge independent data-mining methods - Dynamic Quantum Clustering (DQC) and t-Distributed Stochastic Neighbor Embedding (t-SNE) - to data from The Cancer Genome Atlas (TCGA). We showed that the RNA expression patterns for a mixture of 2,016 samples from five tumor types can sort the tumors into groups enriched for relevant annotations including tumor type, gender, tumor stage, and ethnicity. DQC feature selection analysis discovered 48 core biomarker transcripts that clustered tumors by tumor type. When these transcripts were removed, the geometry of tumor relationships changed, but it was still possible to classify the tumors using the RNA expression profiles of the remaining transcripts. We continued to remove the top biomarkers for several iterations and performed cluster analysis. Even though the most informative transcripts were removed from the cluster analysis, the sorting ability of remaining transcripts remained strong after each iteration. Further, in some iterations we detected a repeating pattern of biological function that wasn't detectable with the core biomarker transcripts present. This suggests the existence of a "background classification" potential in which the pattern of gene expression after continued removal of "biomarker" transcripts could still classify tumors in agreement with the tumor type.

Systematic Association of Genes to Phenotypes by Genome and Literature Mining

PubMed Central

Jensen, Lars J; Perez-Iratxeta, Carolina; Kaczanowski, Szymon; Hooper, Sean D; Andrade, Miguel A

2005-01-01

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene–phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases. PMID:15799710

Consanguinity and family clustering of male factor infertility in Lebanon.

PubMed

Inhorn, Marcia C; Kobeissi, Loulou; Nassar, Zaher; Lakkis, Da'ad; Fakih, Michael H

2009-04-01

To investigate the influence of consanguineous marriage on male factor infertility in Lebanon, where rates of consanguineous marriage remain high (29.6% among Muslims, 16.5% among Christians). Clinic-based, case-control study, using reproductive history, risk factor interview, and laboratory-based semen analysis. Two IVF clinics in Beirut, Lebanon, during an 8-month period (January-August 2003). One hundred twenty infertile male patients and 100 fertile male controls, distinguished by semen analysis and reproductive history. None. Standard clinical semen analysis. The rates of consanguineous marriage were relatively high among the study sample. Patients (46%) were more likely than controls (37%) to report first-degree (parental) and second-degree (grandparental) consanguinity. The study demonstrated a clear pattern of family clustering of male factor infertility, with patients significantly more likely than controls to report infertility among close male relatives (odds ratio = 2.58). Men with azoospermia and severe oligospermia showed high rates of both consanguinity (50%) and family clustering (41%). Consanguineous marriage is a socially supported institution throughout the Muslim world, yet its relationship to infertility is poorly understood. This study demonstrated a significant association between consanguinity and family clustering of male factor infertility cases, suggesting a strong genetic component.

Comparative Genomic Hybridization Analysis of Two Predominant Nordic Group I (Proteolytic) Clostridium botulinum Type B Clusters▿ †

PubMed Central

Lindström, Miia; Hinderink, Katja; Somervuo, Panu; Kiviniemi, Katri; Nevas, Mari; Chen, Ying; Auvinen, Petri; Carter, Andrew T.; Mason, David R.; Peck, Michael W.; Korkeala, Hannu

2009-01-01

Comparative genomic hybridization analysis of 32 Nordic group I Clostridium botulinum type B strains isolated from various sources revealed two homogeneous clusters, clusters BI and BII. The type B strains differed from reference strain ATCC 3502 by 413 coding sequence (CDS) probes, sharing 88% of all the ATCC 3502 genes represented on the microarray. The two Nordic type B clusters differed from each other by their response to 145 CDS probes related mainly to transport and binding, adaptive mechanisms, fatty acid biosynthesis, the cell membranes, bacteriophages, and transposon-related elements. The most prominent differences between the two clusters were related to resistance to toxic compounds frequently found in the environment, such as arsenic and cadmium, reflecting different adaptive responses in the evolution of the two clusters. Other relatively variable CDS groups were related to surface structures and the gram-positive cell wall, suggesting that the two clusters possess different antigenic properties. All the type B strains carried CDSs putatively related to capsule formation, which may play a role in adaptation to different environmental and clinical niches. Sequencing showed that representative strains of the two type B clusters both carried subtype B2 neurotoxin genes. As many of the type B strains studied have been isolated from foods or associated with botulism, it is expected that the two group I C. botulinum type B clusters present a public health hazard in Nordic countries. Knowing the genetic and physiological markers of these clusters will assist in targeting control measures against these pathogens. PMID:19270141

Microstructure and tuber properties of potato varieties with different genetic profiles.

PubMed

Romano, Annalisa; Masi, Paolo; Aversano, Riccardo; Carucci, Francesca; Palomba, Sara; Carputo, Domenico

2018-01-15

The objectives of this research were to study tuber starch characteristics and chemical - thermal properties of 21 potato varieties, and to determine their genetic diversity through SSR markers. Starch granular size varied among samples, with a wide diameter distribution (5-85μm), while granule shapes were similar. Differential Scanning Calorimeter analysis showed that the transition temperatures (69°C-74°C) and enthalpies of gelatinization (0.9J/g-3.8J/g) of tubers were also variety dependent. SSR analysis allowed the detection of 157 alleles across all varieties, with an average value of 6.8 alleles per locus. Variety-specific alleles were also identified. SSR-based cluster analysis revealed that varieties with interesting quality attributes were distributed among all clusters and sub-clusters, suggesting that the genetic basis of traits analyzed may differ among our varieties. The information obtained in this study may be useful to identify and develop varieties with slowly digestible starch. Copyright © 2017 Elsevier Ltd. All rights reserved.

The use of principal component and cluster analysis to differentiate banana peel flours based on their starch and dietary fibre components.

PubMed

Ramli, Saifullah; Ismail, Noryati; Alkarkhi, Abbas Fadhl Mubarek; Easa, Azhar Mat

2010-08-01

Banana peel flour (BPF) prepared from green or ripe Cavendish and Dream banana fruits were assessed for their total starch (TS), digestible starch (DS), resistant starch (RS), total dietary fibre (TDF), soluble dietary fibre (SDF) and insoluble dietary fibre (IDF). Principal component analysis (PCA) identified that only 1 component was responsible for 93.74% of the total variance in the starch and dietary fibre components that differentiated ripe and green banana flours. Cluster analysis (CA) applied to similar data obtained two statistically significant clusters (green and ripe bananas) to indicate difference in behaviours according to the stages of ripeness based on starch and dietary fibre components. We concluded that the starch and dietary fibre components could be used to discriminate between flours prepared from peels obtained from fruits of different ripeness. The results were also suggestive of the potential of green and ripe BPF as functional ingredients in food.

The Use of Principal Component and Cluster Analysis to Differentiate Banana Peel Flours Based on Their Starch and Dietary Fibre Components

PubMed Central

Ramli, Saifullah; Ismail, Noryati; Alkarkhi, Abbas Fadhl Mubarek; Easa, Azhar Mat

2010-01-01

Banana peel flour (BPF) prepared from green or ripe Cavendish and Dream banana fruits were assessed for their total starch (TS), digestible starch (DS), resistant starch (RS), total dietary fibre (TDF), soluble dietary fibre (SDF) and insoluble dietary fibre (IDF). Principal component analysis (PCA) identified that only 1 component was responsible for 93.74% of the total variance in the starch and dietary fibre components that differentiated ripe and green banana flours. Cluster analysis (CA) applied to similar data obtained two statistically significant clusters (green and ripe bananas) to indicate difference in behaviours according to the stages of ripeness based on starch and dietary fibre components. We concluded that the starch and dietary fibre components could be used to discriminate between flours prepared from peels obtained from fruits of different ripeness. The results were also suggestive of the potential of green and ripe BPF as functional ingredients in food. PMID:24575193

Energy Levels and Co-evolution of Product Innovation in Supply Chain Clusters

NASA Astrophysics Data System (ADS)

Ji, Guojun

In the last decade supply chain clusters phenomenon has emerged as a new approach in product innovation studies. This article makes three contributions to the approach by addressing some open issues. The first contribution is to explicitly incorporate the energy levels in the analysis. Hence, the unit of analysis is widened from sectoral systems of innovation to socio-technical systems. Hence, the unit of analysis is widened from sectoral systems of innovation to socio-technical systems. The second contribution is to suggest an analytical distinction between different evolution method, actors involved in them, and the institutions which guide actor's perceptions and activities. Thirdly, the article opens up the black box of institutions, making them an integral part of supply chain. The article provides a coherent conceptual multi-level perspective, using insights from sociology, institutional theory and innovation studies. The perspective is particularly useful to analyze long-term dynamics supply chain clusters phenomenon, shifts from one energy level to another and the co-evolution of product innovation.

Autonomic specificity of basic emotions: evidence from pattern classification and cluster analysis.

PubMed

Stephens, Chad L; Christie, Israel C; Friedman, Bruce H

2010-07-01

Autonomic nervous system (ANS) specificity of emotion remains controversial in contemporary emotion research, and has received mixed support over decades of investigation. This study was designed to replicate and extend psychophysiological research, which has used multivariate pattern classification analysis (PCA) in support of ANS specificity. Forty-nine undergraduates (27 women) listened to emotion-inducing music and viewed affective films while a montage of ANS variables, including heart rate variability indices, peripheral vascular activity, systolic time intervals, and electrodermal activity, were recorded. Evidence for ANS discrimination of emotion was found via PCA with 44.6% of overall observations correctly classified into the predicted emotion conditions, using ANS variables (z=16.05, p<.001). Cluster analysis of these data indicated a lack of distinct clusters, which suggests that ANS responses to the stimuli were nomothetic and stimulus-specific rather than idiosyncratic and individual-specific. Collectively these results further confirm and extend support for the notion that basic emotions have distinct ANS signatures. Copyright © 2010 Elsevier B.V. All rights reserved.

Clustering of unhealthy behaviors in the aerobics center longitudinal study.

PubMed

Héroux, Mariane; Janssen, Ian; Lee, Duck-chul; Sui, Xuemei; Hebert, James R; Blair, Steven N

2012-04-01

Clustering of unhealthy behaviors has been reported in previous studies; however the link with all-cause mortality and differences between those with and without chronic disease requires further investigation. To observe the clustering effects of unhealthy diet, fitness, smoking, and excessive alcohol consumption in adults with and without chronic disease and to assess all-cause mortality risk according to the clustering of unhealthy behaviors. Participants were 13,621 adults (aged 20-84) from the Aerobics Center Longitudinal Study. Four health behaviors were observed (diet, fitness, smoking, and drinking). Baseline characteristics of the study population and bivariate relations between pairs of the health behaviors were evaluated separately for those with and without chronic disease using cross-tabulation and a chi-square test. The odds of partaking in unhealthy behaviors were also calculated. Latent class analysis (LCA) was used to assess clustering. Cox regression was used to assess the relationship between the behaviors and mortality. The four health behaviors were related to each other. LCA results suggested that two classes existed. Participants in class 1 had a higher probability of partaking in each of the four unhealthy behaviors than participants in class 2. No differences in health behavior clustering were found between participants with and without chronic disease. Mortality risk increased relative to the number of unhealthy behaviors participants engaged in. Unhealthy behaviors cluster together irrespective of chronic disease status. Such findings suggest that multi-behavioral intervention strategies can be similar in those with and without chronic disease.

Strong incidence of Pseudomonas aeruginosa on bacterial rrs and ITS genetic structures of cystic fibrosis sputa

PubMed Central

Pages-Monteiro, Laurence; Marti, Romain; Commun, Carine; Alliot, Nolwenn; Bardel, Claire; Meugnier, Helene; Perouse-de-Montclos, Michele; Reix, Philippe; Durieu, Isabelle; Durupt, Stephane; Vandenesch, Francois; Freney, Jean; Cournoyer, Benoit; Doleans-Jordheim, Anne

2017-01-01

Cystic fibrosis (CF) lungs harbor a complex community of interacting microbes, including pathogens like Pseudomonas aeruginosa. Meta-taxogenomic analysis based on V5-V6 rrs PCR products of 52 P. aeruginosa-positive (Pp) and 52 P. aeruginosa-negative (Pn) pooled DNA extracts from CF sputa suggested positive associations between P. aeruginosa and Stenotrophomonas and Prevotella, but negative ones with Haemophilus, Neisseria and Burkholderia. Internal Transcribed Spacer analyses (RISA) from individual DNA extracts identified three significant genetic structures within the CF cohorts, and indicated an impact of P. aeruginosa. RISA clusters Ip and IIIp contained CF sputa with a P. aeruginosa prevalence above 93%, and of 24.2% in cluster IIp. Clusters Ip and IIIp showed lower RISA genetic diversity and richness than IIp. Highly similar cluster IIp RISA profiles were obtained from two patients harboring isolates of a same P. aeruginosa clone, suggesting convergent evolution in the structure of their microbiota. CF patients of cluster IIp had received significantly less antibiotics than patients of clusters Ip and IIIp but harbored the most resistant P. aeruginosa strains. Patients of cluster IIIp were older than those of Ip. The effects of P. aeruginosa on the RISA structures could not be fully dissociated from the above two confounding factors but several trends in these datasets support the conclusion of a strong incidence of P. aeruginosa on the genetic structure of CF lung microbiota. PMID:28282386

Identifying Two Groups of Entitled Individuals: Cluster Analysis Reveals Emotional Stability and Self-Esteem Distinction.

PubMed

Crowe, Michael L; LoPilato, Alexander C; Campbell, W Keith; Miller, Joshua D

2016-12-01

The present study hypothesized that there exist two distinct groups of entitled individuals: grandiose-entitled, and vulnerable-entitled. Self-report scores of entitlement were collected for 916 individuals using an online platform. Model-based cluster analyses were conducted on the individuals with scores one standard deviation above mean (n = 159) using the five-factor model dimensions as clustering variables. The results support the existence of two groups of entitled individuals categorized as emotionally stable and emotionally vulnerable. The emotionally stable cluster reported emotional stability, high self-esteem, more positive affect, and antisocial behavior. The emotionally vulnerable cluster reported low self-esteem and high levels of neuroticism, disinhibition, conventionality, psychopathy, negative affect, childhood abuse, intrusive parenting, and attachment difficulties. Compared to the control group, both clusters reported being more antagonistic, extraverted, Machiavellian, and narcissistic. These results suggest important differences are missed when simply examining the linear relationships between entitlement and various aspects of its nomological network.

Analysis of genetic association using hierarchical clustering and cluster validation indices.

PubMed

Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

2017-10-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.

Characterization of Oxygen Defect Clusters in UO2+ x Using Neutron Scattering and PDF Analysis.

PubMed

Ma, Yue; Garcia, Philippe; Lechelle, Jacques; Miard, Audrey; Desgranges, Lionel; Baldinozzi, Gianguido; Simeone, David; Fischer, Henry E

2018-06-18

In hyper-stoichiometric uranium oxide, both neutron diffraction work and, more recently, theoretical analyses report the existence of clusters such as the 2:2:2 cluster, comprising two anion vacancies and two types of anion interstitials. However, little is known about whether there exists a region of low deviation-from-stoichiometry in which defects remain isolated, or indeed whether at high deviation-from-stoichiometry defect clusters prevail that contain more excess oxygen atoms than the di-interstitial cluster. In this study, we report pair distribution function (PDF) analyses of UO 2 and UO 2+ x ( x ≈ 0.007 and x ≈ 0.16) samples obtained from high-temperature in situ neutron scattering experiments. PDF refinement for the lower deviation from stoichiometry sample suggests the system is too dilute to differentiate between isolated defects and di-interstitial clusters. For the UO 2.16 sample, several defect structures are tested, and it is found that the data are best represented assuming the presence of center-occupied cuboctahedra.

A Massive Galaxy Cluster At z=1.45 From The XMM Cluster Survey: Discovery, Confirmation And Implications For The L-T Relation And Cosmology

NASA Astrophysics Data System (ADS)

Sabirli, Kivanc; Romer, A. K.; Davidson, M.; Stanford, S. A.; Viana, P. T.; Hilton, M.; Collins, C. A.; Kay, S. T.; Liddle, A. R.; Mann, R. G.; Miller, C. J.; Nichol, R. C.; West, M. J.; Conselice, C. J.; Spinrad, H.; Stern, D.; XCS Collaboration

2006-06-01

We report the discovery of the hottest cluster known at z > 1. It was identified as an extended X-ray source in the XMM Cluster Survey (XCS, Romer et al., 2001) and optical spectroscopy shows that 6 galaxies within a 60 arcsec diameter region lie at z = 1.45 ± 0.01. Hence its redshift is the highest currently known for a spectroscopically-confirmed cluster. Analysis of the X-ray spectra yields kT = 7.9+2.8-1.8 keV (90% confidence) and suggests that it is relatively massive for such a high redshift cluster.We acknowledge financial support from NASA grant NAG-11634 (AKR, RCN, KS, MD, PTPV), The Royal Astronomical Society's Hosie Request (MD, KS), PPARC (ARL, STK, RGM), the NASA XMM program (KS), the Institute of Astronomy at the University of Edinburgh (MD), Liverpool John Moores University (MH), Carnegie Mellon University (KS, AKR), and NSF grant AST-0205960 (MJW).

Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

PubMed

Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

2009-02-01

Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas

DOE PAGES

Lindsey, Cary R.; Neupane, Ghanashym; Spycher, Nicolas; ...

2018-01-03

Although many Known Geothermal Resource Areas in Oregon and Idaho were identified during the 1970s and 1980s, few were subsequently developed commercially. Because of advances in power plant design and energy conversion efficiency since the 1980s, some previously identified KGRAs may now be economically viable prospects. Unfortunately, available characterization data vary widely in accuracy, precision, and granularity, making assessments problematic. In this paper, we suggest a procedure for comparing test areas against proven resources using Principal Component Analysis and cluster identification. The result is a low-cost tool for evaluating potential exploration targets using uncertain or incomplete data.

Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindsey, Cary R.; Neupane, Ghanashym; Spycher, Nicolas

Although many Known Geothermal Resource Areas in Oregon and Idaho were identified during the 1970s and 1980s, few were subsequently developed commercially. Because of advances in power plant design and energy conversion efficiency since the 1980s, some previously identified KGRAs may now be economically viable prospects. Unfortunately, available characterization data vary widely in accuracy, precision, and granularity, making assessments problematic. In this paper, we suggest a procedure for comparing test areas against proven resources using Principal Component Analysis and cluster identification. The result is a low-cost tool for evaluating potential exploration targets using uncertain or incomplete data.

A New Approach to Identify High Burnout Medical Staffs by Kernel K-Means Cluster Analysis in a Regional Teaching Hospital in Taiwan

PubMed Central

Lee, Yii-Ching; Huang, Shian-Chang; Huang, Chih-Hsuan; Wu, Hsin-Hung

2016-01-01

This study uses kernel k-means cluster analysis to identify medical staffs with high burnout. The data collected in October to November 2014 are from the emotional exhaustion dimension of the Chinese version of Safety Attitudes Questionnaire in a regional teaching hospital in Taiwan. The number of effective questionnaires including the entire staffs such as physicians, nurses, technicians, pharmacists, medical administrators, and respiratory therapists is 680. The results show that 8 clusters are generated by kernel k-means method. Employees in clusters 1, 4, and 5 are relatively in good conditions, whereas employees in clusters 2, 3, 6, 7, and 8 need to be closely monitored from time to time because they have relatively higher degree of burnout. When employees with higher degree of burnout are identified, the hospital management can take actions to improve the resilience, reduce the potential medical errors, and, eventually, enhance the patient safety. This study also suggests that the hospital management needs to keep track of medical staffs’ fatigue conditions and provide timely assistance for burnout recovery through employee assistance programs, mindfulness-based stress reduction programs, positivity currency buildup, and forming appreciative inquiry groups. PMID:27895218

Extensions to the instantaneous normal mode analysis of cluster dynamics: Diffusion constants and the role of rotations in clusters

NASA Astrophysics Data System (ADS)

Adams, John E.; Stratt, Richard M.

1990-08-01

For the instantaneous normal mode analysis method to be generally useful in studying the dynamics of clusters of arbitrary size, it ought to yield values of atomic self-diffusion constants which agree with those derived directly from molecular dynamics calculations. The present study proposes that such agreement indeed can be obtained if a sufficiently sophisticated formalism for computing the diffusion constant is adopted, such as the one suggested by Madan, Keyes, and Seeley [J. Chem. Phys. 92, 7565 (1990)]. In order to implement this particular formalism, however, we have found it necessary to pay particular attention to the removal from the computed spectra of spurious rotational contributions. The utility of the formalism is demonstrated via a study of small argon clusters, for which numerous results generated using other approaches are available. We find the same temperature dependence of the Ar13 self-diffusion constant that Beck and Marchioro [J. Chem. Phys. 93, 1347 (1990)] do from their direct calculation of the velocity autocorrelation function: The diffusion constant rises quickly from zero to a liquid-like value as the cluster goes through (the finite-size equivalent of) the melting transition.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

DOE PAGES

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; ...

2017-06-30

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less

Multidimensional analysis of peak pain symptoms and experiences.

PubMed

Kinsman, R; Dirks, J F; Wunder, J; Carbaugh, R; Stieg, R

1989-01-01

Peak pain symptoms and experiences were explored within a group of 243 intractable pain patients seen consecutively at a pain clinic. Using a 5-point scale, patients rated the frequency with which 99 symptom adjectives occurred when their pain was at its worst. Key cluster analysis identified 11 reliable, conceptually clear symptom clusters: Four affective symptom categories, Angry Depression, Diminished Drive, Intropunitive Depression and Anxiety, describing emotional states concomitant with peak pain; two somatic symptom categories, Ecto-Pain and Endo-Pain, describing surface and deep bodily pain, respectively; and five additional symptom categories including Cognitive Dysfunction, Sleep Disturbance, Fatigue, Withdrawal and Disequilibrium. Among the affective symptom clusters, symptoms of Angry Depression were reported to occur frequently by 32% of the patients while only 11% reported the frequent occurrence of Intropunitive Depression. For the somatic symptom clusters, 25 and 52% reported the frequent occurrence of Ecto-Pain and Endo-Pain, respectively. Pain reports measured by Ecto-Pain and Endo-Pain were nearly independent of all other symptom categories. The results suggest that the experiential context of pain differs widely among intractable pain patients. The study derived a Pain Symptom Checklist to measure each symptom cluster as one way to identify coping styles among chronic pain patients.

Network Analysis of Fine Particulate Matter (PM2.5) Emissions in China

NASA Astrophysics Data System (ADS)

Yan, Shaomin; Wu, Guang

2016-09-01

Specification of PM2.5 spatial and temporal characteristics is important for understanding PM2.5 adverse effects and policymaking. We applied network analysis to studying the dataset MIX, which contains PM2.5 emissions recorded from 2168 monitoring stations in China in 2008 and 2010. The results showed that for PM2.5 emissions from industrial sector 8 clusters were found in 2008 but they merged together into a huge cluster in 2010, suggesting that industrial sector underwent an integrating process. For PM2.5 emissions from electricity generation sector, strong locality of clusters was revealed, implying that each region had its own electricity generation system. For PM2.5 emissions from residential sector, the same pattern of 10 clusters was uncovered in both years, implicating the household energy consumption unchanged from 2008 to 2010. For PM2.5 emissions from transportation sector, the same pattern of 5 clusters with many connections in-between was unraveled, indicating the high-speed development of transportation nationalwidely. Except for the known elements, mercury (Hg) surfaced as an element for particle nucleation. To our knowledge, this is the first network study in this field.

Evaluation of data quality, timeliness and acceptability of the tuberculosis surveillance system in Brazil's micro-regions.

PubMed

Silva, Gabriela Drummond Marques da; Bartholomay, Patrícia; Cruz, Oswaldo Gonçalves; Garcia, Leila Posenato

2017-10-01

This study aimed to evaluate quality, acceptability and timeliness of the data in the tuberculosis surveillance system in Brazilian micro-regions. An ecological cross-sectional study was carried out, after a qualitative stage for selecting indicators. All 558 Brazilian micro-regions were used as units of analysis. Data available in the National Notifiable Diseases Information System (SINAN), from 2012 to 2014, were used to calculate 14 indicators relating to four attributes: completeness, consistency, timeliness and acceptability. The study made use of cluster analysis to group micro-regions according to acceptability and timeliness. Three clusters were identified among the 473 micro-regions with optimal or regular completeness (70% to 100%) and with over five notifications. Cluster 1 (n = 109) presented mean timeliness of notification and treatment equal to 62.8% and 24.9%, respectively. Cluster 2 (n = 143) had a mean percentage of cases tested for HIV equal to 55.9%. Cluster 3 (n = 221) had the best performing tuberculosis indicators. Results suggest priority areas for improving surveillance of tuberculosis, predominantly in the central-north part of the country. They also point to the need to increase the timeliness of treatment and the percentage of cases tested for HIV.

A novel unsupervised spike sorting algorithm for intracranial EEG.

PubMed

Yadav, R; Shah, A K; Loeb, J A; Swamy, M N S; Agarwal, R

2011-01-01

This paper presents a novel, unsupervised spike classification algorithm for intracranial EEG. The method combines template matching and principal component analysis (PCA) for building a dynamic patient-specific codebook without a priori knowledge of the spike waveforms. The problem of misclassification due to overlapping classes is resolved by identifying similar classes in the codebook using hierarchical clustering. Cluster quality is visually assessed by projecting inter- and intra-clusters onto a 3D plot. Intracranial EEG from 5 patients was utilized to optimize the algorithm. The resulting codebook retains 82.1% of the detected spikes in non-overlapping and disjoint clusters. Initial results suggest a definite role of this method for both rapid review and quantitation of interictal spikes that could enhance both clinical treatment and research studies on epileptic patients.

Clustering algorithm for determining community structure in large networks

NASA Astrophysics Data System (ADS)

Pujol, Josep M.; Béjar, Javier; Delgado, Jordi

2006-07-01

We propose an algorithm to find the community structure in complex networks based on the combination of spectral analysis and modularity optimization. The clustering produced by our algorithm is as accurate as the best algorithms on the literature of modularity optimization; however, the main asset of the algorithm is its efficiency. The best match for our algorithm is Newman’s fast algorithm, which is the reference algorithm for clustering in large networks due to its efficiency. When both algorithms are compared, our algorithm outperforms the fast algorithm both in efficiency and accuracy of the clustering, in terms of modularity. Thus, the results suggest that the proposed algorithm is a good choice to analyze the community structure of medium and large networks in the range of tens and hundreds of thousand vertices.

Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated k-means clustering and gravity model.

PubMed

Chang, Ni-Bin; Wimberly, Brent; Xuan, Zhemin

2012-03-01

This study presents an integrated k-means clustering and gravity model (IKCGM) for investigating the spatiotemporal patterns of nutrient and associated dissolved oxygen levels in Tampa Bay, Florida. By using a k-means clustering analysis to first partition the nutrient data into a user-specified number of subsets, it is possible to discover the spatiotemporal patterns of nutrient distribution in the bay and capture the inherent linkages of hydrodynamic and biogeochemical features. Such patterns may then be combined with a gravity model to link the nutrient source contribution from each coastal watershed to the generated clusters in the bay to aid in the source proportion analysis for environmental management. The clustering analysis was carried out based on 1 year (2008) water quality data composed of 55 sample stations throughout Tampa Bay collected by the Environmental Protection Commission of Hillsborough County. In addition, hydrological and river water quality data of the same year were acquired from the United States Geological Survey's National Water Information System to support the gravity modeling analysis. The results show that the k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. The datasets indicate that Lower Tampa Bay is an area with limited nutrient input throughout the year. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high values of colored dissolved organic matter are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. With this new integration, improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a critical coastal bay, the Gulf of Mexico. This journal is © The Royal Society of Chemistry 2012

Two Horizontally Transferred Xenobiotic Resistance Gene Clusters Associated with Detoxification of Benzoxazolinones by Fusarium Species

PubMed Central

Glenn, Anthony E.; Davis, C. Britton; Gao, Minglu; Gold, Scott E.; Mitchell, Trevor R.; Proctor, Robert H.; Stewart, Jane E.; Snook, Maurice E.

2016-01-01

Microbes encounter a broad spectrum of antimicrobial compounds in their environments and often possess metabolic strategies to detoxify such xenobiotics. We have previously shown that Fusarium verticillioides, a fungal pathogen of maize known for its production of fumonisin mycotoxins, possesses two unlinked loci, FDB1 and FDB2, necessary for detoxification of antimicrobial compounds produced by maize, including the γ-lactam 2-benzoxazolinone (BOA). In support of these earlier studies, microarray analysis of F. verticillioides exposed to BOA identified the induction of multiple genes at FDB1 and FDB2, indicating the loci consist of gene clusters. One of the FDB1 cluster genes encoded a protein having domain homology to the metallo-β-lactamase (MBL) superfamily. Deletion of this gene (MBL1) rendered F. verticillioides incapable of metabolizing BOA and thus unable to grow on BOA-amended media. Deletion of other FDB1 cluster genes, in particular AMD1 and DLH1, did not affect BOA degradation. Phylogenetic analyses and topology testing of the FDB1 and FDB2 cluster genes suggested two horizontal transfer events among fungi, one being transfer of FDB1 from Fusarium to Colletotrichum, and the second being transfer of the FDB2 cluster from Fusarium to Aspergillus. Together, the results suggest that plant-derived xenobiotics have exerted evolutionary pressure on these fungi, leading to horizontal transfer of genes that enhance fitness or virulence. PMID:26808652

Modeling PTSD Symptom Clusters, Alcohol Misuse, Anger, and Depression as They Relate to Aggression and Suicidality in Returning Veterans

PubMed Central

Hellmuth, Julianne C.; Stappenbeck, Cynthia A.; Hoerster, Katherine D.; Jakupcak, Matthew

2014-01-01

Suicidal ideation (SI) and aggression are common correlates of Posttraumatic Stress Disorder (PTSD) among Iraq and Afghanistan War veterans. The existing literature has established a strong link between these factors, but a more nuanced understanding of how PTSD influences them is needed. The current study examined the direct and indirect relationships between PTSD symptom clusters and SI and general aggression (without a specified target) via depression, alcohol misuse, and trait anger. Participants were 359 (92% male) Iraq/Afghanistan War veterans. Path analysis results suggest that the PTSD numbing cluster was directly (β=.28, p<.01.) and indirectly (β=.17, p=.001) related to SI through depression and the PTSD hyperarousal cluster was indirectly related to SI through depression (β=.13, p<.001). The PTSD re-experiencing cluster was directly related to aggression (β=.17, p<.05), whereas the PTSD numbing and hyperarousal clusters were indirectly related to aggression through trait anger (β=.05, p<.05; β=.20, p<.001). These findings suggest that adjunct treatments aimed at stabilizing anger, depression, and alcohol misuse may help clinicians ameliorate the maladaptive patterns often observed in returning Veterans. These results also point to specific manifestations of PTSD and co-occurring conditions that may inform clinicians in their attempts to identify at-risk veterans and facilitate preventative interventions. PMID:23073972

A large sample of shear-selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S16A Wide field mass maps

NASA Astrophysics Data System (ADS)

Miyazaki, Satoshi; Oguri, Masamune; Hamana, Takashi; Shirasaki, Masato; Koike, Michitaro; Komiyama, Yutaka; Umetsu, Keiichi; Utsumi, Yousuke; Okabe, Nobuhiro; More, Surhud; Medezinski, Elinor; Lin, Yen-Ting; Miyatake, Hironao; Murayama, Hitoshi; Ota, Naomi; Mitsuishi, Ikuyuki

2018-01-01

We present the result of searching for clusters of galaxies based on weak gravitational lensing analysis of the ˜160 deg2 area surveyed by Hyper Suprime-Cam (HSC) as a Subaru Strategic Program. HSC is a new prime focus optical imager with a 1.5°-diameter field of view on the 8.2 m Subaru telescope. The superb median seeing on the HSC i-band images of 0.56" allows the reconstruction of high angular resolution mass maps via weak lensing, which is crucial for the weak lensing cluster search. We identify 65 mass map peaks with a signal-to-noise (S/N) ratio larger than 4.7, and carefully examine their properties by cross-matching the clusters with optical and X-ray cluster catalogs. We find that all the 39 peaks with S/N > 5.1 have counterparts in the optical cluster catalogs, and only 2 out of the 65 peaks are probably false positives. The upper limits of X-ray luminosities from the ROSAT All Sky Survey (RASS) imply the existence of an X-ray underluminous cluster population. We show that the X-rays from the shear-selected clusters can be statistically detected by stacking the RASS images. The inferred average X-ray luminosity is about half that of the X-ray-selected clusters of the same mass. The radial profile of the dark matter distribution derived from the stacking analysis is well modeled by the Navarro-Frenk-White profile with a small concentration parameter value of c500 ˜ 2.5, which suggests that the selection bias on the orientation or the internal structure for our shear-selected cluster sample is not strong.

Comparison of five cluster validity indices performance in brain [18 F]FET-PET image segmentation using k-means.

PubMed

Abualhaj, Bedor; Weng, Guoyang; Ong, Melissa; Attarwala, Ali Asgar; Molina, Flavia; Büsing, Karen; Glatting, Gerhard

2017-01-01

Dynamic [ 18 F]fluoro-ethyl-L-tyrosine positron emission tomography ([ 18 F]FET-PET) is used to identify tumor lesions for radiotherapy treatment planning, to differentiate glioma recurrence from radiation necrosis and to classify gliomas grading. To segment different regions in the brain k-means cluster analysis can be used. The main disadvantage of k-means is that the number of clusters must be pre-defined. In this study, we therefore compared different cluster validity indices for automated and reproducible determination of the optimal number of clusters based on the dynamic PET data. The k-means algorithm was applied to dynamic [ 18 F]FET-PET images of 8 patients. Akaike information criterion (AIC), WB, I, modified Dunn's and Silhouette indices were compared on their ability to determine the optimal number of clusters based on requirements for an adequate cluster validity index. To check the reproducibility of k-means, the coefficients of variation CVs of the objective function values OFVs (sum of squared Euclidean distances within each cluster) were calculated using 100 random centroid initialization replications RCI 100 for 2 to 50 clusters. k-means was performed independently on three neighboring slices containing tumor for each patient to investigate the stability of the optimal number of clusters within them. To check the independence of the validity indices on the number of voxels, cluster analysis was applied after duplication of a slice selected from each patient. CVs of index values were calculated at the optimal number of clusters using RCI 100 to investigate the reproducibility of the validity indices. To check if the indices have a single extremum, visual inspection was performed on the replication with minimum OFV from RCI 100 . The maximum CV of OFVs was 2.7 × 10 -2 from all patients. The optimal number of clusters given by modified Dunn's and Silhouette indices was 2 or 3 leading to a very poor segmentation. WB and I indices suggested in median 5, [range 4-6] and 4, [range 3-6] clusters, respectively. For WB, I, modified Dunn's and Silhouette validity indices the suggested optimal number of clusters was not affected by the number of the voxels. The maximum coefficient of variation of WB, I, modified Dunn's, and Silhouette validity indices were 3 × 10 -2 , 1, 2 × 10 -1 and 3 × 10 -3 , respectively. WB-index showed a single global maximum, whereas the other indices showed also local extrema. From the investigated cluster validity indices, the WB-index is best suited for automated determination of the optimal number of clusters for [ 18 F]FET-PET brain images for the investigated image reconstruction algorithm and the used scanner: it yields meaningful results allowing better differentiation of tissues with higher number of clusters, it is simple, reproducible and has an unique global minimum. © 2016 American Association of Physicists in Medicine.

Analysis of Transcriptional Regulation of the Human miR-17-92 Cluster; Evidence for Involvement of Pim-1

PubMed Central

Thomas, Maren; Lange-Grünweller, Kerstin; Hartmann, Dorothee; Golde, Lara; Schlereth, Julia; Streng, Dennis; Aigner, Achim; Grünweller, Arnold; Hartmann, Roland K.

2013-01-01

The human polycistronic miRNA cluster miR-17-92 is frequently overexpressed in hematopoietic malignancies and cancers. Its transcription is in part controlled by an E2F-regulated host gene promoter. An intronic A/T-rich region directly upstream of the miRNA coding region also contributes to cluster expression. Our deletion analysis of the A/T-rich region revealed a strong dependence on c-Myc binding to the functional E3 site. Yet, constructs lacking the 5′-proximal ~1.3 kb or 3′-distal ~0.1 kb of the 1.5 kb A/T-rich region still retained residual specific promoter activity, suggesting multiple transcription start sites (TSS) in this region. Furthermore, the protooncogenic kinase, Pim-1, its phosphorylation target HP1γ and c-Myc colocalize to the E3 region, as inferred from chromatin immunoprecipitation. Analysis of pri-miR-17-92 expression levels in K562 and HeLa cells revealed that silencing of E2F3, c-Myc or Pim-1 negatively affects cluster expression, with a synergistic effect caused by c-Myc/Pim-1 double knockdown in HeLa cells. Thus, we show, for the first time, that the protooncogene Pim-1 is part of the network that regulates transcription of the human miR-17-92 cluster. PMID:23749113

Social Media Use and Depression and Anxiety Symptoms: A Cluster Analysis.

PubMed

Shensa, Ariel; Sidani, Jaime E; Dew, Mary Amanda; Escobar-Viera, César G; Primack, Brian A

2018-03-01

Individuals use social media with varying quantity, emotional, and behavioral at- tachment that may have differential associations with mental health outcomes. In this study, we sought to identify distinct patterns of social media use (SMU) and to assess associations between those patterns and depression and anxiety symptoms. In October 2014, a nationally-representative sample of 1730 US adults ages 19 to 32 completed an online survey. Cluster analysis was used to identify patterns of SMU. Depression and anxiety were measured using respective 4-item Patient-Reported Outcome Measurement Information System (PROMIS) scales. Multivariable logistic regression models were used to assess associations between clus- ter membership and depression and anxiety. Cluster analysis yielded a 5-cluster solu- tion. Participants were characterized as "Wired," "Connected," "Diffuse Dabblers," "Concentrated Dabblers," and "Unplugged." Membership in 2 clusters - "Wired" and "Connected" - increased the odds of elevated depression and anxiety symptoms (AOR = 2.7, 95% CI = 1.5-4.7; AOR = 3.7, 95% CI = 2.1-6.5, respectively, and AOR = 2.0, 95% CI = 1.3-3.2; AOR = 2.0, 95% CI = 1.3-3.1, respectively). SMU pattern characterization of a large population suggests 2 pat- terns are associated with risk for depression and anxiety. Developing educational interventions that address use patterns rather than single aspects of SMU (eg, quantity) would likely be useful.

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

PubMed Central

Rong, Junkang; Feltus, F. Alex; Waghmare, Vijay N.; Pierce, Gary J.; Chee, Peng W.; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J.; Wilkins, Thea A.; May, O. Lloyd; Smith, C. Wayne; Gannaway, John R.; Wendel, Jonathan F.; Paterson, Andrew H.

2007-01-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. PMID:17565937

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development.

PubMed

Rong, Junkang; Feltus, F Alex; Waghmare, Vijay N; Pierce, Gary J; Chee, Peng W; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J; Wilkins, Thea A; May, O Lloyd; Smith, C Wayne; Gannaway, John R; Wendel, Jonathan F; Paterson, Andrew H

2007-08-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.

Template growth of Au, Ni and Ni–Au nanoclusters on hexagonal boron nitride/Rh(111): a combined STM, TPD and AES study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Fanglue; Huang, Dali; Yue, Yuan

In this study, the template growth of Au, Ni, and Ni–Au bimetallic nanoclusters on hexagonal boron nitride/Rh(111), i.e. h-BN/Rh(111), was investigated via scanning tunneling microscopy (STM), temperature programmed-desorption (TPD), and Auger electron spectroscopy (AES). STM study shows that template growth of Au clusters on h-BN/Rh(111) forms mainly well-dispersed monolayer clusters. In contrast, Ni forms large multilayer clusters showing a relatively high diffusivity on h-BN/Rh(111) substrate. Ni–Au bimetallic clusters are effectively formed first by Au deposition followed by Ni deposition, with the Au clusters functioning as nucleation sites for the subsequently deposited Ni. Further structural analysis was carried out via TPDmore » and AES. The resulting TPD and AES data show the surface composition and charge transfer between Au and Ni of the bimetallic clusters. These results suggest that the h-BN/Rh(111) substrate represents a unique candidate for supporting Ni–Au bimetallic clusters in further catalytic reactions.« less

Template growth of Au, Ni and Ni–Au nanoclusters on hexagonal boron nitride/Rh(111): a combined STM, TPD and AES study

DOE PAGES

Wu, Fanglue; Huang, Dali; Yue, Yuan; ...

2017-09-12

In this study, the template growth of Au, Ni, and Ni–Au bimetallic nanoclusters on hexagonal boron nitride/Rh(111), i.e. h-BN/Rh(111), was investigated via scanning tunneling microscopy (STM), temperature programmed-desorption (TPD), and Auger electron spectroscopy (AES). STM study shows that template growth of Au clusters on h-BN/Rh(111) forms mainly well-dispersed monolayer clusters. In contrast, Ni forms large multilayer clusters showing a relatively high diffusivity on h-BN/Rh(111) substrate. Ni–Au bimetallic clusters are effectively formed first by Au deposition followed by Ni deposition, with the Au clusters functioning as nucleation sites for the subsequently deposited Ni. Further structural analysis was carried out via TPDmore » and AES. The resulting TPD and AES data show the surface composition and charge transfer between Au and Ni of the bimetallic clusters. These results suggest that the h-BN/Rh(111) substrate represents a unique candidate for supporting Ni–Au bimetallic clusters in further catalytic reactions.« less

Eclipsing Binaries in Open Clusters

NASA Astrophysics Data System (ADS)

Southworth, John; Clausen, Jens Viggo

2006-08-01

The study of detached eclipsing binaries in open clusters can provide stringent tests of theoretical stellar evolutionary models, which must simultaneously fit the masses, radii, and luminosities of the eclipsing stars and the radiative properties of every other star in the cluster. We review recent progress in such studies and discuss two unusually interesting objects currently under analysis. GV Carinae is an A0 m + A8 m binary in the Southern open cluster NGC 3532; its eclipse depths have changed by 0.1 mag between 1990 and 2001, suggesting that its orbit is being perturbed by a relatively close third body. DW Carinae is a high-mass unevolved B1 V + B1 V binary in the very young open cluster Collinder 228, and displays double-peaked emission in the centre of the Hα line which is characteristic of Be stars. We conclude by pointing out that the great promise of eclipsing binaries in open clusters can only be satisfied when both the binaries and their parent clusters are well-observed, a situation which is less common than we would like.

Insights into magmatic processes and hydrothermal alteration of in situ superfast spreading ocean crust at ODP/IODP site 1256 from a cluster analysis of rock magnetic properties

NASA Astrophysics Data System (ADS)

Dekkers, Mark J.; Heslop, David; Herrero-Bervera, Emilio; Acton, Gary; Krasa, David

2014-08-01

We analyze magnetic properties from Ocean Drilling Program (ODP)/Integrated ODP (IODP) Hole 1256D (6°44.1' N, 91°56.1' W) on the Cocos Plate in ˜15.2 Ma oceanic crust generated by superfast seafloor spreading, the only drill hole that has sampled all three oceanic crust layers in a tectonically undisturbed setting. Fuzzy c-means cluster analysis and nonlinear mapping are utilized to study down-hole trends in the ratio of the saturation remanent magnetization and the saturation magnetization, the coercive force, the ratio of the remanent coercive force and coercive force, the low-field magnetic susceptibility, and the Curie temperature, to evaluate the effects of magmatic and hydrothermal processes on magnetic properties. A statistically robust five cluster solution separates the data predominantly into three clusters that express increasing hydrothermal alteration of the lavas, which differ from two distinct clusters mainly representing the dikes and gabbros. Extensive alteration can obliterate magnetic property differences between lavas, dikes, and gabbros. The imprint of thermochemical alteration on the iron-titanium oxides is only partially related to the porosity of the rocks. Thus, the analysis complements interpretation based on electrofacies analysis. All clusters display rock magnetic characteristics compatible with an ability to retain a stable natural remanent magnetization suggesting that the entire sampled sequence of ocean crust can contribute to marine magnetic anomalies. Paleointensity determination is difficult because of the propensity of oxyexsolution during laboratory heating and/or the presence of intergrowths. The upper part of the extrusive sequence, the granoblastic dikes, and moderately altered gabbros may contain a comparatively uncontaminated thermoremanent magnetization.

Coordinate based random effect size meta-analysis of neuroimaging studies.

PubMed

Tench, C R; Tanasescu, Radu; Constantinescu, C S; Auer, D P; Cottam, W J

2017-06-01

Low power in neuroimaging studies can make them difficult to interpret, and Coordinate based meta-analysis (CBMA) may go some way to mitigating this issue. CBMA has been used in many analyses to detect where published functional MRI or voxel-based morphometry studies testing similar hypotheses report significant summary results (coordinates) consistently. Only the reported coordinates and possibly t statistics are analysed, and statistical significance of clusters is determined by coordinate density. Here a method of performing coordinate based random effect size meta-analysis and meta-regression is introduced. The algorithm (ClusterZ) analyses both coordinates and reported t statistic or Z score, standardised by the number of subjects. Statistical significance is determined not by coordinate density, but by a random effects meta-analyses of reported effects performed cluster-wise using standard statistical methods and taking account of censoring inherent in the published summary results. Type 1 error control is achieved using the false cluster discovery rate (FCDR), which is based on the false discovery rate. This controls both the family wise error rate under the null hypothesis that coordinates are randomly drawn from a standard stereotaxic space, and the proportion of significant clusters that are expected under the null. Such control is necessary to avoid propagating and even amplifying the very issues motivating the meta-analysis in the first place. ClusterZ is demonstrated on both numerically simulated data and on real data from reports of grey matter loss in multiple sclerosis (MS) and syndromes suggestive of MS, and of painful stimulus in healthy controls. The software implementation is available to download and use freely. Copyright © 2017 Elsevier Inc. All rights reserved.

Millon Clinical Multiaxial Inventory–III Subtypes of Opioid Dependence: Validity and Matching to Behavioral Therapies

PubMed Central

Ball, Samuel A.; Nich, Charla; Rounsaville, Bruce J.; Eagan, Dorothy; Carroll, Kathleen M.

2013-01-01

The concurrent and predictive validity of 2 different methods of Millon Clinical Multiaxial Inventory–III subtyping (protocol sorting, cluster analysis) was evaluated in 125 recently detoxified opioid-dependent outpatients in a 12-week randomized clinical trial. Participants received naltrexone and relapse prevention group counseling and were assigned to 1 of 3 intervention conditions: (a) no-incentive vouchers, (b) incentive vouchers alone, or (c) incentive vouchers plus relationship counseling. Affective disturbance was the most common Axis I protocol-sorted subtype (66%), antisocial–narcissistic was the most common Axis II subtype (46%), and cluster analysis suggested that a 2-cluster solution (high vs. low psychiatric severity) was optimal. Predictive validity analyses indicated less symptom improvement for the higher problem subtypes, and patient treatment matching analyses indicated that some subtypes had better outcomes in the no-incentive voucher conditions. PMID:15301655

Cluster analysis of obsessive-compulsive spectrum disorders in patients with obsessive-compulsive disorder: clinical and genetic correlates.

PubMed

Lochner, Christine; Hemmings, Sian M J; Kinnear, Craig J; Niehaus, Dana J H; Nel, Daniel G; Corfield, Valerie A; Moolman-Smook, Johanna C; Seedat, Soraya; Stein, Dan J

2005-01-01

Comorbidity of certain obsessive-compulsive spectrum disorders (OCSDs; such as Tourette's disorder) in obsessive-compulsive disorder (OCD) may serve to define important OCD subtypes characterized by differing phenomenology and neurobiological mechanisms. Comorbidity of the putative OCSDs in OCD has, however, not often been systematically investigated. The Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition , Axis I Disorders-Patient Version as well as a Structured Clinical Interview for Putative OCSDs (SCID-OCSD) were administered to 210 adult patients with OCD (N = 210, 102 men and 108 women; mean age, 35.7 +/- 13.3). A subset of Caucasian subjects (with OCD, n = 171; control subjects, n = 168), including subjects from the genetically homogeneous Afrikaner population (with OCD, n = 77; control subjects, n = 144), was genotyped for polymorphisms in genes involved in monoamine function. Because the items of the SCID-OCSD are binary (present/absent), a cluster analysis (Ward's method) using the items of SCID-OCSD was conducted. The association of identified clusters with demographic variables (age, gender), clinical variables (age of onset, obsessive-compulsive symptom severity and dimensions, level of insight, temperament/character, treatment response), and monoaminergic genotypes was examined. Cluster analysis of the OCSDs in our sample of patients with OCD identified 3 separate clusters at a 1.1 linkage distance level. The 3 clusters were named as follows: (1) "reward deficiency" (including trichotillomania, Tourette's disorder, pathological gambling, and hypersexual disorder), (2) "impulsivity" (including compulsive shopping, kleptomania, eating disorders, self-injury, and intermittent explosive disorder), and (3) "somatic" (including body dysmorphic disorder and hypochondriasis). Several significant associations were found between cluster scores and other variables; for example, cluster I scores were associated with earlier age of onset of OCD and the presence of tics, cluster II scores were associated with female gender and childhood emotional abuse, and cluster III scores were associated with less insight and with somatic obsessions and compulsions. However, none of these clusters were associated with any particular genetic variant. Analysis of comorbid OCSDs in OCD suggested that these lie on a number of different dimensions. These dimensions are partially consistent with previous theoretical approaches taken toward classifying OCD spectrum disorders. The lack of genetic validation of these clusters in the present study may indicate the involvement of other, as yet untested, genes. Further genetic and cluster analyses of comorbid OCSDs in OCD may ultimately contribute to a better delineation of OCD endophenotypes.

Efficient electronic structure theory via hierarchical scale-adaptive coupled-cluster formalism: I. Theory and computational complexity analysis

NASA Astrophysics Data System (ADS)

Lyakh, Dmitry I.

2018-03-01

A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.

An Objective Classification of Saturn Cloud Features from Cassini ISS Images

NASA Technical Reports Server (NTRS)

Del Genio, Anthony D.; Barbara, John M.

2016-01-01

A k -means clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturn's northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible- infrared images of Earth. It provides a new perspective on giant planet cloud morphology and its relationship to the dynamics and a meteorological context for the analysis of other types of simultaneous Saturn observations. The method identifies 6 clusters that exhibit distinct morphology, vertical structure, and preferred latitudes of occurrence. These correspond to areas dominated by deep convective cells; low contrast areas, some including thinner and thicker clouds possibly associated with baroclinic instability; regions with possible isolated thin cirrus clouds; darker areas due to thinner low level clouds or clearer skies due to downwelling, or due to absorbing particles; and fields of relatively shallow cumulus clouds. The spatial associations among these cloud types suggest that dynamically, there are three distinct types of latitude bands on Saturn: deep convectively disturbed latitudes in cyclonic shear regions poleward of the eastward jets; convectively suppressed regions near and surrounding the westward jets; and baro-clinically unstable latitudes near eastward jet cores and in the anti-cyclonic regions equatorward of them. These are roughly analogous to some of the features of Earth's tropics, subtropics, and midlatitudes, respectively. This classification may be more useful for dynamics purposes than the traditional belt-zone partitioning. Temporal variations of feature contrast and cluster occurrence suggest that the upper tropospheric haze in the northern hemisphere may have thickened by 2014. The results suggest that routine use of clustering may be a worthwhile complement to many different types of planetary atmospheric data analysis.

The complete sequence of Cymbidium mosaic virus from Vanilla fragrans in Hainan, China.

PubMed

He, Zhen; Jiang, Dongmei; Liu, Aiqin; Sang, Liwei; Li, Wenfeng; Li, Shifang

2011-06-01

The complete nucleotide sequence of Cymbidium mosaic virus (CymMV) isolated from vanilla in Hainan province, China was determined for the first time. It comprised 6,224 nucleotides; sequence analysis suggested that the isolate we obtained was a member of the genus Potexvirus, and its sequence shared 86.67-96.61% identities with previously reported sequences. Phylogenetic analysis suggested that CymMV from vanilla fragrans was clustered into subgroup A and the isolates in this subgroup displayed little regional difference.

NGC 346: Looking in the Cradle of a Massive Star Cluster

NASA Astrophysics Data System (ADS)

Gouliermis, Dimitrios A.; Hony, Sacha

2017-03-01

How does a star cluster of more than few 10,000 solar masses form? We present the case of the cluster NGC 346 in the Small Magellanic Cloud, still embedded in its natal star-forming region N66, and we propose a scenario for its formation, based on observations of the rich stellar populations in the region. Young massive clusters host a high fraction of early-type stars, indicating an extremely high star formation efficiency. The Milky Way galaxy hosts several young massive clusters that fill the gap between young low-mass open clusters and old massive globular clusters. Only a handful, though, are young enough to study their formation. Moreover, the investigation of their gaseous natal environments suffers from contamination by the Galactic disk. Young massive clusters are very abundant in distant starburst and interacting galaxies, but the distance of their hosting galaxies do not also allow a detailed analysis of their formation. The Magellanic Clouds, on the other hand, host young massive clusters in a wide range of ages with the youngest being still embedded in their giant HII regions. Hubble Space Telescope imaging of such star-forming complexes provide a stellar sampling with a high dynamic range in stellar masses, allowing the detailed study of star formation at scales typical for molecular clouds. Our cluster analysis on the distribution of newly-born stars in N66 shows that star formation in the region proceeds in a clumpy hierarchical fashion, leading to the formation of both a dominant young massive cluster, hosting about half of the observed pre-main-sequence population, and a self-similar dispersed distribution of the remaining stars. We investigate the correlation between stellar surface density (and star formation rate derived from star-counts) and molecular gas surface density (derived from dust column density) in order to unravel the physical conditions that gave birth to NGC 346. A power law fit to the data yields a steep correlation between these two parameters with a considerable scatter. The fraction of stellar over the total (gas plus young stars) mass is found to be systematically higher within the central 15 pc (where the young massive cluster is located) than outside, which suggests variations in the star formation efficiency within the same star-forming complex. This trend possibly reflects a change of star formation efficiency in N66 between clustered and non-clustered star formation. Our findings suggest that the formation of NGC 346 is the combined result of star formation regulated by turbulence and of early dynamical evolution induced by the gravitational potential of the dense interstellar medium.

The X-ray luminosity functions of Abell clusters from the Einstein Cluster Survey

NASA Technical Reports Server (NTRS)

Burg, R.; Giacconi, R.; Forman, W.; Jones, C.

1994-01-01

We have derived the present epoch X-ray luminosity function of northern Abell clusters using luminosities from the Einstein Cluster Survey. The sample is sufficiently large that we can determine the luminosity function for each richness class separately with sufficient precision to study and compare the different luminosity functions. We find that, within each richness class, the range of X-ray luminosity is quite large and spans nearly a factor of 25. Characterizing the luminosity function for each richness class with a Schechter function, we find that the characteristic X-ray luminosity, L(sub *), scales with richness class as (L(sub *) varies as N(sub*)(exp gamma), where N(sub *) is the corrected, mean number of galaxies in a richness class, and the best-fitting exponent is gamma = 1.3 +/- 0.4. Finally, our analysis suggests that there is a lower limit to the X-ray luminosity of clusters which is determined by the integrated emission of the cluster member galaxies, and this also scales with richness class. The present sample forms a baseline for testing cosmological evolution of Abell-like clusters when an appropriate high-redshift cluster sample becomes available.

Functional analysis of ars gene cluster of Pannonibacter indicus strain HT23(T) (DSM 23407(T)) and identification of a proline residue essential for arsenate reductase activity.

PubMed

Bandyopadhyay, Saumya; Das, Subrata K

2016-04-01

Arsenic is a naturally occurring ubiquitous highly toxic metalloid. In this study, we have identified ars gene cluster in Pannonibacter indicus strain HT23(T) (DSM 23407(T)), responsible for reduction of toxic pentavalent arsenate. The ars gene cluster is comprised of four non-overlapping open reading frames (ORFs) encoding a transcriptional regulator (ArsR), a low molecular weight protein tyrosine phosphatases (LMW-PTPase) with hypothetical function, an arsenite efflux pump (Acr3), and an arsenate reductase (ArsC). Heterologous expression of arsenic inducible ars gene cluster conferred arsenic resistance to Escherichia coli ∆ars mutant strain AW3110. The recombinant ArsC was purified and assayed. Site-directed mutagenesis was employed to ascertain the role of specific amino acids in ArsC catalysis. Pro94X (X = Ala, Arg, Cys, and His) amino acid substitutions led to enzyme inactivation. Circular dichroism spectra analysis suggested Pro94 as an essential amino acid for enzyme catalytic activity as it is indispensable for optimum protein folding in P. indicus Grx-coupled ArsC.

Genome mining of the sordarin biosynthetic gene cluster from Sordaria araneosa Cain ATCC 36386: characterization of cycloaraneosene synthase and GDP-6-deoxyaltrose transferase.

PubMed

Kudo, Fumitaka; Matsuura, Yasunori; Hayashi, Takaaki; Fukushima, Masayuki; Eguchi, Tadashi

2016-07-01

Sordarin is a glycoside antibiotic with a unique tetracyclic diterpene aglycone structure called sordaricin. To understand its intriguing biosynthetic pathway that may include a Diels-Alder-type [4+2]cycloaddition, genome mining of the gene cluster from the draft genome sequence of the producer strain, Sordaria araneosa Cain ATCC 36386, was carried out. A contiguous 67 kb gene cluster consisting of 20 open reading frames encoding a putative diterpene cyclase, a glycosyltransferase, a type I polyketide synthase, and six cytochrome P450 monooxygenases were identified. In vitro enzymatic analysis of the putative diterpene cyclase SdnA showed that it catalyzes the transformation of geranylgeranyl diphosphate to cycloaraneosene, a known biosynthetic intermediate of sordarin. Furthermore, a putative glycosyltransferase SdnJ was found to catalyze the glycosylation of sordaricin in the presence of GDP-6-deoxy-d-altrose to give 4'-O-demethylsordarin. These results suggest that the identified sdn gene cluster is responsible for the biosynthesis of sordarin. Based on the isolated potential biosynthetic intermediates and bioinformatics analysis, a plausible biosynthetic pathway for sordarin is proposed.

The human RHOX gene cluster: target genes and functional analysis of gene variants in infertile men.

PubMed

Borgmann, Jennifer; Tüttelmann, Frank; Dworniczak, Bernd; Röpke, Albrecht; Song, Hye-Won; Kliesch, Sabine; Wilkinson, Miles F; Laurentino, Sandra; Gromoll, Jörg

2016-11-15

The X-linked reproductive homeobox (RHOX) gene cluster encodes transcription factors preferentially expressed in reproductive tissues. This gene cluster has important roles in male fertility based on phenotypic defects of Rhox-mutant mice and the finding that aberrant RHOX promoter methylation is strongly associated with abnormal human sperm parameters. However, little is known about the molecular mechanism of RHOX function in humans. Using gene expression profiling, we identified genes regulated by members of the human RHOX gene cluster. Some genes were uniquely regulated by RHOXF1 or RHOXF2/2B, while others were regulated by both of these transcription factors. Several of these regulated genes encode proteins involved in processes relevant to spermatogenesis; e.g. stress protection and cell survival. One of the target genes of RHOXF2/2B is RHOXF1, suggesting cross-regulation to enhance transcriptional responses. The potential role of RHOX in human infertility was addressed by sequencing all RHOX exons in a group of 250 patients with severe oligozoospermia. This revealed two mutations in RHOXF1 (c.515G > A and c.522C > T) and four in RHOXF2/2B (-73C > G, c.202G > A, c.411C > T and c.679G > A), of which only one (c.202G > A) was found in a control group of men with normal sperm concentration. Functional analysis demonstrated that c.202G > A and c.679G > A significantly impaired the ability of RHOXF2/2B to regulate downstream genes. Molecular modelling suggested that these mutations alter RHOXF2/F2B protein conformation. By combining clinical data with in vitro functional analysis, we demonstrate how the X-linked RHOX gene cluster may function in normal human spermatogenesis and we provide evidence that it is impaired in human male fertility.

Metal mixtures in urban and rural populations in the US: The Multi-Ethnic Study of Atherosclerosis and the Strong Heart Study.

PubMed

Pang, Yuanjie; Peng, Roger D; Jones, Miranda R; Francesconi, Kevin A; Goessler, Walter; Howard, Barbara V; Umans, Jason G; Best, Lyle G; Guallar, Eliseo; Post, Wendy S; Kaufman, Joel D; Vaidya, Dhananjay; Navas-Acien, Ana

2016-05-01

Natural and anthropogenic sources of metal exposure differ for urban and rural residents. We searched to identify patterns of metal mixtures which could suggest common environmental sources and/or metabolic pathways of different urinary metals, and compared metal-mixtures in two population-based studies from urban/sub-urban and rural/town areas in the US: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Strong Heart Study (SHS). We studied a random sample of 308 White, Black, Chinese-American, and Hispanic participants in MESA (2000-2002) and 277 American Indian participants in SHS (1998-2003). We used principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) to evaluate nine urinary metals (antimony [Sb], arsenic [As], cadmium [Cd], lead [Pb], molybdenum [Mo], selenium [Se], tungsten [W], uranium [U] and zinc [Zn]). For arsenic, we used the sum of inorganic and methylated species (∑As). All nine urinary metals were higher in SHS compared to MESA participants. PCA and CA revealed the same patterns in SHS, suggesting 4 distinct principal components (PC) or clusters (∑As-U-W, Pb-Sb, Cd-Zn, Mo-Se). In MESA, CA showed 2 large clusters (∑As-Mo-Sb-U-W, Cd-Pb-Se-Zn), while PCA showed 4 PCs (Sb-U-W, Pb-Se-Zn, Cd-Mo, ∑As). LDA indicated that ∑As, U, W, and Zn were the most discriminant variables distinguishing MESA and SHS participants. In SHS, the ∑As-U-W cluster and PC might reflect groundwater contamination in rural areas, and the Cd-Zn cluster and PC could reflect common sources from meat products or metabolic interactions. Among the metals assayed, ∑As, U, W and Zn differed the most between MESA and SHS, possibly reflecting disproportionate exposure from drinking water and perhaps food in rural Native communities compared to urban communities around the US. Copyright © 2016 Elsevier Inc. All rights reserved.

Microsatellites Reveal a High Population Structure in Triatoma infestans from Chuquisaca, Bolivia

PubMed Central

Pizarro, Juan Carlos; Gilligan, Lauren M.; Stevens, Lori

2008-01-01

Background For Chagas disease, the most serious infectious disease in the Americas, effective disease control depends on elimination of vectors through spraying with insecticides. Molecular genetic research can help vector control programs by identifying and characterizing vector populations and then developing effective intervention strategies. Methods and Findings The population genetic structure of Triatoma infestans (Hemiptera: Reduviidae), the main vector of Chagas disease in Bolivia, was investigated using a hierarchical sampling strategy. A total of 230 adults and nymphs from 23 localities throughout the department of Chuquisaca in Southern Bolivia were analyzed at ten microsatellite loci. Population structure, estimated using analysis of molecular variance (AMOVA) to estimate FST (infinite alleles model) and RST (stepwise mutation model), was significant between western and eastern regions within Chuquisaca and between insects collected in domestic and peri-domestic habitats. Genetic differentiation at three different hierarchical geographic levels was significant, even in the case of adjacent households within a single locality (R ST = 0.14, F ST = 0.07). On the largest geographic scale, among five communities up to 100 km apart, R ST = 0.12 and F ST = 0.06. Cluster analysis combined with assignment tests identified five clusters within the five communities. Conclusions Some houses are colonized by insects from several genetic clusters after spraying, whereas other households are colonized predominately by insects from a single cluster. Significant population structure, measured by both R ST and F ST, supports the hypothesis of poor dispersal ability and/or reduced migration of T. infestans. The high degree of genetic structure at small geographic scales, inferences from cluster analysis and assignment tests, and demographic data suggest reinfesting vectors are coming from nearby and from recrudescence (hatching of eggs that were laid before insecticide spraying). Suggestions for using these results in vector control strategies are made. PMID:18365033

Metabolomic analysis of primary metabolites in citrus leaf during defense responses.

PubMed

Asai, Tomonori; Matsukawa, Tetsuya; Kajiyama, Shin'ichiro

2017-03-01

Mechanical damage is one of the unavoidable environmental stresses to plant growth and development. Plants induce a variety of reactions which defend against natural enemies and/or heal the wounded sites. Jasmonic acid (JA) and salicylic acid (SA), defense-related plant hormones, are well known to be involved in induction of defense reactions and play important roles as signal molecules. However, defense related metabolites are so numerous and diverse that roles of individual compounds are still to be elucidated. In this report, we carried out a comprehensive analysis of metabolic changes during wound response in citrus plants which are one of the most commercially important fruit tree families. Changes in amino acid, sugar, and organic acid profiles in leaves were surveyed after wounding, JA and SA treatments using gas chromatography-mass spectrometry (GC/MS) in seven citrus species, Citrus sinensis, Citrus limon, Citrus paradisi, Citrus unshiu, Citrus kinokuni, Citrus grandis, and Citrus hassaku. GC/MS data were applied to multivariate analyses including hierarchical cluster analysis (HCA), primary component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) to extract stress-related compounds. HCA showed the amino acid cluster including phenylalanine and tryptophan, suggesting that amino acids in this cluster are concertedly regulated during responses against treatments. OPLS-DA exhibited that tryptophan was accumulated after wounding and JA treatments in all species tested, while serine was down regulated. Our results suggest that tryptophan and serine are common biomarker candidates in citrus plants for wound stress. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

MC 2: Subaru and Hubble Space Telescope Weak-lensing Analysis of the Double Radio Relic Galaxy Cluster PLCK G287.0+32.9

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finner, Kyle; Jee, M. James; Golovich, Nathan

The second most significant detection of the Planck Sunyaev-Zel'dovich survey, PLCK G287.0+32.9 (z = 0.385), boasts two similarly bright radio relics and a radio halo. One radio relic is locatedmore » $$\\sim 400\\,\\mathrm{kpc}$$ NW of the X-ray peak and the other $$\\sim 2.8$$ Mpc to the SE. This large difference suggests that a complex merging scenario is required. A key missing puzzle for the merging scenario reconstruction is the underlying dark matter distribution in high resolution. Here, we present a joint Subaru Telescope and Hubble Space Telescope weak-lensing analysis of the cluster. Our analysis shows that the mass distribution features four significant substructures. Of the substructures, a primary cluster of mass $${M}_{200{\\rm{c}}}={1.59}_{-0.22}^{+0.25}\\times {10}^{15}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$ dominates the weak-lensing signal. This cluster is likely to be undergoing a merger with one (or more) subcluster whose mass is approximately a factor of 10 lower. One candidate is the subcluster of mass $${M}_{200{\\rm{c}}}={1.16}_{-0.13}^{+0.15}\\times {10}^{14}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$ located $$\\sim 400\\,\\mathrm{kpc}$$ to the SE. The location of this subcluster suggests that its interaction with the primary cluster could be the source of the NW radio relic. Another subcluster is detected $$\\sim 2$$ Mpc to the SE of the X-ray peak with mass $${M}_{200{\\rm{c}}}={1.68}_{-0.20}^{+0.22}\\times {10}^{14}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$. This SE subcluster is in the vicinity of the SE radio relic and may have created the SE radio relic during a past merger with the primary cluster. The fourth subcluster, $${M}_{200{\\rm{c}}}={1.87}_{-0.22}^{+0.24}\\times {10}^{14}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$, is NW of the X-ray peak and beyond the NW radio relic.« less

MC 2: Subaru and Hubble Space Telescope Weak-lensing Analysis of the Double Radio Relic Galaxy Cluster PLCK G287.0+32.9

DOE PAGES

Finner, Kyle; Jee, M. James; Golovich, Nathan; ...

2017-12-11

The second most significant detection of the Planck Sunyaev-Zel'dovich survey, PLCK G287.0+32.9 (z = 0.385), boasts two similarly bright radio relics and a radio halo. One radio relic is locatedmore » $$\\sim 400\\,\\mathrm{kpc}$$ NW of the X-ray peak and the other $$\\sim 2.8$$ Mpc to the SE. This large difference suggests that a complex merging scenario is required. A key missing puzzle for the merging scenario reconstruction is the underlying dark matter distribution in high resolution. Here, we present a joint Subaru Telescope and Hubble Space Telescope weak-lensing analysis of the cluster. Our analysis shows that the mass distribution features four significant substructures. Of the substructures, a primary cluster of mass $${M}_{200{\\rm{c}}}={1.59}_{-0.22}^{+0.25}\\times {10}^{15}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$ dominates the weak-lensing signal. This cluster is likely to be undergoing a merger with one (or more) subcluster whose mass is approximately a factor of 10 lower. One candidate is the subcluster of mass $${M}_{200{\\rm{c}}}={1.16}_{-0.13}^{+0.15}\\times {10}^{14}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$ located $$\\sim 400\\,\\mathrm{kpc}$$ to the SE. The location of this subcluster suggests that its interaction with the primary cluster could be the source of the NW radio relic. Another subcluster is detected $$\\sim 2$$ Mpc to the SE of the X-ray peak with mass $${M}_{200{\\rm{c}}}={1.68}_{-0.20}^{+0.22}\\times {10}^{14}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$. This SE subcluster is in the vicinity of the SE radio relic and may have created the SE radio relic during a past merger with the primary cluster. The fourth subcluster, $${M}_{200{\\rm{c}}}={1.87}_{-0.22}^{+0.24}\\times {10}^{14}\\ {h}_{70}^{-1}\\ {M}_{\\odot }$$, is NW of the X-ray peak and beyond the NW radio relic.« less

Effluent concentration and removal efficiency of nine heavy metals in secondary treatment plants in Shanghai, China.

PubMed

Feng, Jingjing; Chen, Xiaolin; Jia, Lei; Liu, Qizhen; Chen, Xiaojia; Han, Deming; Cheng, Jinping

2018-04-10

Wastewater treatment plants (WWTPs) are the most common form of industrial and municipal wastewater control. To evaluate the performance of wastewater treatment and the potential risk of treated wastewater to aquatic life and human health, the influent and effluent concentrations of nine toxic metals were determined in 12 full-scale WWTPs in Shanghai, China. The performance was evaluated based on national standards for reclamation and aquatic criteria published by US EPA, and by comparison with other full-scale WWTPs in different countries. Potential sources of heavy metals were recognized using partial correlation analysis, hierarchical clustering, and principal component analysis (PCA). Results indicated significant treatment effect on As, Cd, Cr, Cu, Hg, Mn, Pb, and Zn. The removal efficiencies ranged from 92% (Cr) to 16.7% (Hg). The results indicated potential acute and/or chronic effect of Cu, Ni, Pb, and Zn on aquatic life and potential harmful effect of As and Mn on human health for the consumption of water and/or organism. The results of partial correlation analysis, hierarchical clustering based on cosine distance, and PCA, which were consistent with each other, suggested common source of Cd, Cr, Cu, and Pb and common source of As, Hg, Mn, Ni, and Zn. Hierarchical clustering based on Jaccard similarity suggested common source of Cd, Hg, and Ni, which was statistically proved by Fisher's exact test.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal FWERs. Those rejected clusters were outlying values in the distribution of cluster size but cannot be distinguished from true positive findings without further analyses, including assessing whether fMRI signal in those regions correlates with other clinical, behavioral, or cognitive measures. Rejecting the large clusters, however, significantly reduced the statistical power of nonparametric methods in detecting true findings compared with parametric methods, which would have detected most true findings that are essential for making valid biological inferences in MRI data. Parametric analyses, in contrast, detected most true findings while generating relatively few false positives: on average, less than one of those very large clusters would be deemed a true finding in each brain-wide analysis. We therefore recommend the continued use of parametric methods that model nonstationary smoothness for cluster-level, familywise control of false positives, particularly when using a Cluster Defining Threshold of 2.5 or higher, and subsequently assessing rigorously the biological plausibility of the findings, even for large clusters. Finally, because nonparametric methods yielded a large reduction in statistical power to detect true positive findings, we conclude that the modest reduction in false positive findings that nonparametric analyses afford does not warrant a re-analysis of previously published fMRI studies using nonparametric techniques. Copyright © 2018 Elsevier Inc. All rights reserved.

Evolution of the degree of substructures in simulated galaxy clusters

NASA Astrophysics Data System (ADS)

De Boni, Cristiano; Böhringer, Hans; Chon, Gayoung; Dolag, Klaus

2018-05-01

We study the evolution of substructure in the mass distribution with mass, redshift and radius in a sample of simulated galaxy clusters. The sample, containing 1226 objects, spans the mass range M200 = 1014 - 1.74 × 1015 M⊙ h-1 in six redshift bins from z = 0 to z = 1.179. We consider three different diagnostics: 1) subhalos identified with SUBFIND; 2) overdense regions localized by dividing the cluster into octants; 3) offset between the potential minimum and the center of mass. The octant analysis is a new method that we introduce in this work. We find that none of the diagnostics indicate a correlation between the mass of the cluster and the fraction of substructures. On the other hand, all the diagnostics suggest an evolution of substructures with redshift. For SUBFIND halos, the mass fraction is constant with redshift at Rvir, but shows a mild evolution at R200 and R500. Also, the fraction of clusters with at least a subhalo more massive than one thirtieth of the total mass is less than 20%. Our new method based on the octants returns a mass fraction in substructures which has a strong evolution with redshift at all radii. The offsets also evolve strongly with redshift. We also find a strong correlation for individual clusters between the offset and the fraction of substructures identified with the octant analysis. Our work puts strong constraints on the amount of substructures we expect to find in galaxy clusters and on their evolution with redshift.

Multilocus sequence analysis of Anaplasma phagocytophilum reveals three distinct lineages with different host ranges in clinically ill French cattle.

PubMed

Chastagner, Amélie; Dugat, Thibaud; Vourc'h, Gwenaël; Verheyden, Hélène; Legrand, Loïc; Bachy, Véronique; Chabanne, Luc; Joncour, Guy; Maillard, Renaud; Boulouis, Henri-Jean; Haddad, Nadia; Bailly, Xavier; Leblond, Agnès

2014-12-09

Molecular epidemiology represents a powerful approach to elucidate the complex epidemiological cycles of multi-host pathogens, such as Anaplasma phagocytophilum. A. phagocytophilum is a tick-borne bacterium that affects a wide range of wild and domesticated animals. Here, we characterized its genetic diversity in populations of French cattle; we then compared the observed genotypes with those found in horses, dogs, and roe deer to determine whether genotypes of A. phagocytophilum are shared among different hosts. We sampled 120 domesticated animals (104 cattle, 13 horses, and 3 dogs) and 40 wild animals (roe deer) and used multilocus sequence analysis on nine loci (ankA, msp4, groESL, typA, pled, gyrA, recG, polA, and an intergenic region) to characterize the genotypes of A. phagocytophilum present. Phylogenic analysis revealed three genetic clusters of bacterial variants in domesticated animals. The two principal clusters included 98% of the bacterial genotypes found in cattle, which were only distantly related to those in roe deer. One cluster comprised only cattle genotypes, while the second contained genotypes from cattle, horses, and dogs. The third contained all roe deer genotypes and three cattle genotypes. Geographical factors could not explain this clustering pattern. These results suggest that roe deer do not contribute to the spread of A. phagocytophilum in cattle in France. Further studies should explore if these different clusters are associated with differing disease severity in domesticated hosts. Additionally, it remains to be seen if the three clusters of A. phagocytophilum genotypes in cattle correspond to distinct epidemiological cycles, potentially involving different reservoir hosts.

AFLP-based genetic diversity assessment of commercially important tea germplasm in India.

PubMed

Sharma, R K; Negi, M S; Sharma, S; Bhardwaj, P; Kumar, R; Bhattachrya, E; Tripathi, S B; Vijayan, D; Baruah, A R; Das, S C; Bera, B; Rajkumar, R; Thomas, J; Sud, R K; Muraleedharan, N; Hazarika, M; Lakshmikumaran, M; Raina, S N; Ahuja, P S

2010-08-01

India has a large repository of important tea accessions and, therefore, plays a major role in improving production and quality of tea across the world. Using seven AFLP primer combinations, we analyzed 123 commercially important tea accessions representing major populations in India. The overall genetic similarity recorded was 51%. No significant differences were recorded in average genetic similarity among tea populations cultivated in various geographic regions (northwest 0.60, northeast and south both 0.59). UPGMA cluster analysis grouped the tea accessions according to geographic locations, with a bias toward China or Assam/Cambod types. Cluster analysis results were congruent with principal component analysis. Further, analysis of molecular variance detected a high level of genetic variation (85%) within and limited genetic variation (15%) among the populations, suggesting their origin from a similar genetic pool.

Using Self-Organizing Neural Network Map Combined with Ward's Clustering Algorithm for Visualization of Students' Cognitive Structural Models about Aliveness Concept

PubMed Central

Ugulu, Ilker; Aydin, Halil

2016-01-01

We propose an approach to clustering and visualization of students' cognitive structural models. We use the self-organizing map (SOM) combined with Ward's clustering to conduct cluster analysis. In the study carried out on 100 subjects, a conceptual understanding test consisting of open-ended questions was used as a data collection tool. The results of analyses indicated that students constructed the aliveness concept by associating it predominantly with human. Motion appeared as the most frequently associated term with the aliveness concept. The results suggest that the aliveness concept has been constructed using anthropocentric and animistic cognitive structures. In the next step, we used the data obtained from the conceptual understanding test for training the SOM. Consequently, we propose a visualization method about cognitive structure of the aliveness concept. PMID:26819579

STAR FORMATION ACROSS THE W3 COMPLEX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Román-Zúñiga, Carlos G.; Ybarra, Jason E.; Tapia, Mauricio

We present a multi-wavelength analysis of the history of star formation in the W3 complex. Using deep, near-infrared ground-based images combined with images obtained with Spitzer and Chandra observatories, we identified and classified young embedded sources. We identified the principal clusters in the complex and determined their structure and extension. We constructed extinction-limited samples for five principal clusters and constructed K-band luminosity functions that we compare with those of artificial clusters with varying ages. This analysis provided mean ages and possible age spreads for the clusters. We found that IC 1795, the centermost cluster of the complex, still hosts amore » large fraction of young sources with circumstellar disks. This indicates that star formation was active in IC 1795 as recently as 2 Myr ago, simultaneous to the star-forming activity in the flanking embedded clusters, W3-Main and W3(OH). A comparison with carbon monoxide emission maps indicates strong velocity gradients in the gas clumps hosting W3-Main and W3(OH) and shows small receding clumps of gas at IC 1795, suggestive of rapid gas removal (faster than the T Tauri timescale) in the cluster-forming regions. We discuss one possible scenario for the progression of cluster formation in the W3 complex. We propose that early processes of gas collapse in the main structure of the complex could have defined the progression of cluster formation across the complex with relatively small age differences from one group to another. However, triggering effects could act as catalysts for enhanced efficiency of formation at a local level, in agreement with previous studies.« less

Phylogeny of Bacteroides, Prevotella, and Porphyromonas spp. and related bacteria.

PubMed Central

Paster, B J; Dewhirst, F E; Olsen, I; Fraser, G J

1994-01-01

The phylogenetic structure of the bacteroides subgroup of the cytophaga-flavobacter-bacteroides (CFB) phylum was examined by 16S rRNA sequence comparative analysis. Approximately 95% of the 16S rRNA sequence was determined for 36 representative strains of species of Prevotella, Bacteroides, and Porphyromonas and related species by a modified Sanger sequencing method. A phylogenetic tree was constructed from a corrected distance matrix by the neighbor-joining method, and the reliability of tree branching was established by bootstrap analysis. The bacteroides subgroup was divided primarily into three major phylogenetic clusters which contained most of the species examined. The first cluster, termed the prevotella cluster, was composed of 16 species of Prevotella, including P. melaninogenica, P. intermedia, P. nigrescens, and the ruminal species P. ruminicola. Two oral species, P. zoogleoformans and P. heparinolytica, which had been recently placed in the genus Prevotella, did not fall within the prevotella cluster. These two species and six species of Bacteroides, including the type species B. fragilis, formed the second cluster, termed the bacteroides cluster. The third cluster, termed the porphyromonas cluster, was divided into two subclusters. The first contained Porphyromonas gingivalis, P. endodontalis, P. asaccharolytica, P. circumdentaria, P. salivosa, [Bacteroides] levii (the brackets around genus are used to indicate that the species does not belong to the genus by the sensu stricto definition), and [Bacteroides] macacae, and the second subcluster contained [Bacteroides] forsythus and [Bacteroides] distasonis. [Bacteroides] splanchnicus fell just outside the three major clusters but still belonged within the bacteroides subgroup. With few exceptions, the 16 S rRNA data were in overall agreement with previously proposed reclassifications of species of Bacteroides, Prevotella, and Porphyromonas. Suggestions are made to accommodate those species which do not fit previous reclassification schemes. PMID:8300528

The metallicity of M4: Accurate spectroscopic fundamental parameters for four giants

NASA Technical Reports Server (NTRS)

Drake, J. J.; Smith, V. V.; Suntzeff, N. B.

1994-01-01

High-quality spectra, covering the wavelength range 5480 to 7080 A, have been obtained for four giant stars in the intermediate-metallicity CN-bimodal globular cluster M4 (NGC 6121). We have employed a model atmosphere analysis that is entirely independent from cluster parameters, such as distance, age, and reddening, in order to derive accurate values for the stellar parameters effective temperature, surface gravity, and microturbulence, and for the abundance of iron relative to the Sun, (Fe/H), and of calcium, Ca/H, for each of the four stars. Detailed radiative transfer and statistical equilibrium calculations carried out for iron and calcium suggest that departures from local thermodynamic equilibrium are not significant for the purposes of our analysis. The spectroscopically derived effective temperatures for our program stars are hotter by about 200 K than existing photometric calibrations suggest. We conclude that this is due partly to the uncertain reddening of M4 and to the existing photometric temperature calibration for red giants being too cool by about 100 K. Comparison of our spectroscopic and existing photometric temperatures supports the prognosis of a significant east-west gradient in the reddening across M4. Our derived iron abundances are slightly higher than previous high-resolution studies suggested; the differences are most probably due to the different temperature scale and choice of microturbulent velocities adopted by earlier workers. The resulting value for the metallicity of M4 is (Fe/H )(sub M4) = -1.05 + or - 0.15. Based on this result, we suggest that metallicities derived in previous high-dispersion globular cluster abundance analyses could be too low by 0.2 to 0.3 dex. Our calcium abundances suggest an enhancement of calcium, an alpha element, over iron, relative to the Sun, in M4 of (Ca/H) = 0.23.

Phenotypes of sleeplessness: stressing the need for psychodiagnostics in the assessment of insomnia.

PubMed

van de Laar, Merijn; Leufkens, Tim; Bakker, Bart; Pevernagie, Dirk; Overeem, Sebastiaan

2017-09-01

Insomnia is a too general term for various subtypes that might have different etiologies and therefore require different types of treatment. In this explorative study we used cluster analysis to distinguish different phenotypes in 218 patients with insomnia, taking into account several factors including sleep variables and characteristics related to personality and psychiatric comorbidity. Three clusters emerged from the analysis. The 'moderate insomnia with low psychopathology'-cluster was characterized by relatively normal personality traits, as well as normal levels of anxiety and depressive symptoms in the presence of moderate insomnia severity. The 'severe insomnia with moderate psychopathology'-cluster showed relatively high scores on the Insomnia Severity Index and scores on the sleep log that were indicative for severe insomnia. Anxiety and depressive symptoms were slightly above the cut-off and they were characterized by below average self-sufficiency and less goal-directed behavior. The 'early onset insomnia with high psychopathology'-cluster showed a much younger age and earlier insomnia onset than the other two groups. Anxiety and depressive symptoms were well above the cut-off score and the group consisted of a higher percentage of subjects with comorbid psychiatric disorders. This cluster showed a 'typical psychiatric' personality profile. Our findings stress the need for psychodiagnostic procedures next to a sleep-related diagnostic approach, especially in the younger insomnia patients. Specific treatment suggestions are given based on the three phenotypes.

Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland.

PubMed

Sasidharan, Lekshmi; Wu, Kun-Feng; Menendez, Monica

2015-12-01

One of the major challenges in traffic safety analyses is the heterogeneous nature of safety data, due to the sundry factors involved in it. This heterogeneity often leads to difficulties in interpreting results and conclusions due to unrevealed relationships. Understanding the underlying relationship between injury severities and influential factors is critical for the selection of appropriate safety countermeasures. A method commonly employed to address systematic heterogeneity is to focus on any subgroup of data based on the research purpose. However, this need not ensure homogeneity in the data. In this paper, latent class cluster analysis is applied to identify homogenous subgroups for a specific crash type-pedestrian crashes. The manuscript employs data from police reported pedestrian (2009-2012) crashes in Switzerland. The analyses demonstrate that dividing pedestrian severity data into seven clusters helps in reducing the systematic heterogeneity of the data and to understand the hidden relationships between crash severity levels and socio-demographic, environmental, vehicle, temporal, traffic factors, and main reason for the crash. The pedestrian crash injury severity models were developed for the whole data and individual clusters, and were compared using receiver operating characteristics curve, for which results favored clustering. Overall, the study suggests that latent class clustered regression approach is suitable for reducing heterogeneity and revealing important hidden relationships in traffic safety analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Proteomic analysis of protein-protein interactions within the Cysteine Sulfinate Desulfinase Fe-S cluster biogenesis system.

PubMed

Bolstad, Heather M; Botelho, Danielle J; Wood, Matthew J

2010-10-01

Fe-S cluster biogenesis is of interest to many fields, including bioenergetics and gene regulation. The CSD system is one of three Fe-S cluster biogenesis systems in E. coli and is comprised of the cysteine desulfurase CsdA, the sulfur acceptor protein CsdE, and the E1-like protein CsdL. The biological role, biochemical mechanism, and protein targets of the system remain uncharacterized. Here we present that the active site CsdE C61 has a lowered pK(a) value of 6.5, which is nearly identical to that of C51 in the homologous SufE protein and which is likely critical for its function. We observed that CsdE forms disulfide bonds with multiple proteins and identified the proteins that copurify with CsdE. The identification of Fe-S proteins and both putative and established Fe-S cluster assembly (ErpA, glutaredoxin-3, glutaredoxin-4) and sulfur trafficking (CsdL, YchN) proteins supports the two-pathway model, in which the CSD system is hypothesized to synthesize both Fe-S clusters and other sulfur-containing cofactors. We suggest that the identified Fe-S cluster assembly proteins may be the scaffold and/or shuttle proteins for the CSD system. By comparison with previous analysis of SufE, we demonstrate that there is some overlap in the CsdE and SufE interactomes.

Deriving spatial patterns from a novel database of volcanic rock geochemistry in the Virunga Volcanic Province, East African Rift

NASA Astrophysics Data System (ADS)

Poppe, Sam; Barette, Florian; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu

2016-04-01

The Virunga Volcanic Province (VVP) is situated within the western branch of the East-African Rift. The geochemistry and petrology of its' volcanic products has been studied extensively in a fragmented manner. They represent a unique collection of silica-undersaturated, ultra-alkaline and ultra-potassic compositions, displaying marked geochemical variations over the area occupied by the VVP. We present a novel spatially-explicit database of existing whole-rock geochemical analyses of the VVP volcanics, compiled from international publications, (post-)colonial scientific reports and PhD theses. In the database, a total of 703 geochemical analyses of whole-rock samples collected from the 1950s until recently have been characterised with a geographical location, eruption source location, analytical results and uncertainty estimates for each of these categories. Comparative box plots and Kruskal-Wallis H tests on subsets of analyses with contrasting ages or analytical methods suggest that the overall database accuracy is consistent. We demonstrate how statistical techniques such as Principal Component Analysis (PCA) and subsequent cluster analysis allow the identification of clusters of samples with similar major-element compositions. The spatial patterns represented by the contrasting clusters show that both the historically active volcanoes represent compositional clusters which can be identified based on their contrasted silica and alkali contents. Furthermore, two sample clusters are interpreted to represent the most primitive, deep magma source within the VVP, different from the shallow magma reservoirs that feed the eight dominant large volcanoes. The samples from these two clusters systematically originate from locations which 1. are distal compared to the eight large volcanoes and 2. mostly coincide with the surface expressions of rift faults or NE-SW-oriented inherited Precambrian structures which were reactivated during rifting. The lava from the Mugogo eruption of 1957 belongs to these primitive clusters and is the only known to have erupted outside the current rift valley in historical times. We thus infer there is a distributed hazard of vent opening susceptibility additional to the susceptibility associated with the main Virunga edifices. This study suggests that the statistical analysis of such geochemical database may help to understand complex volcanic plumbing systems and the spatial distribution of volcanic hazards in active and poorly known volcanic areas such as the Virunga Volcanic Province.

Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL.

PubMed

Wang, Lili; Palmer, Andrew J; Cocker, Fiona; Sanderson, Kristy

2017-01-09

No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population. Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods. The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: -0.18, SE: -0.01, p < 0.001), MM3+ (β: -0.23, SE: -0.02, p < 0.001), cluster-1 (β: -0.10, SE: 0.01, p < 0.001) and cluster-2 (β: -0.36, SE: 0.01, p < 0.001). Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.

The properties of small Ag clusters bound to DNA bases.

PubMed

Soto-Verdugo, Víctor; Metiu, Horia; Gwinn, Elisabeth

2010-05-21

We study the binding of neutral silver clusters, Ag(n) (n=1-6), to the DNA bases adenine (A), cytosine (C), guanine (G), and thymine (T) and the absorption spectra of the silver cluster-base complexes. Using density functional theory (DFT), we find that the clusters prefer to bind to the doubly bonded ring nitrogens and that binding to T is generally much weaker than to C, G, and A. Ag(3) and Ag(4) make the stronger bonds. Bader charge analysis indicates a mild electron transfer from the base to the clusters for all bases, except T. The donor bases (C, G, and A) bind to the sites on the cluster where the lowest unoccupied molecular orbital has a pronounced protrusion. The site where cluster binds to the base is controlled by the shape of the higher occupied states of the base. Time-dependent DFT calculations show that different base-cluster isomers may have very different absorption spectra. In particular, we find new excitations in base-cluster molecules, at energies well below those of the isolated components, and with strengths that depend strongly on the orientations of planar clusters with respect to the base planes. Our results suggest that geometric constraints on binding, imposed by designed DNA structures, may be a feasible route to engineering the selection of specific cluster-base assemblies.

Genome-Wide Analysis of Secondary Metabolite Gene Clusters in Ophiostoma ulmi and Ophiostoma novo-ulmi Reveals a Fujikurin-Like Gene Cluster with a Putative Role in Infection.

PubMed

Sbaraini, Nicolau; Andreis, Fábio C; Thompson, Claudia E; Guedes, Rafael L M; Junges, Ângela; Campos, Thais; Staats, Charley C; Vainstein, Marilene H; Ribeiro de Vasconcelos, Ana T; Schrank, Augusto

2017-01-01

The emergence of new microbial pathogens can result in destructive outbreaks, since their hosts have limited resistance and pathogens may be excessively aggressive. Described as the major ecological incident of the twentieth century, Dutch elm disease, caused by ascomycete fungi from the Ophiostoma genus, has caused a significant decline in elm tree populations ( Ulmus sp.) in North America and Europe. Genome sequencing of the two main causative agents of Dutch elm disease ( Ophiostoma ulmi and Ophiostoma novo-ulmi ), along with closely related species with different lifestyles, allows for unique comparisons to be made to identify how pathogens and virulence determinants have emerged. Among several established virulence determinants, secondary metabolites (SMs) have been suggested to play significant roles during phytopathogen infection. Interestingly, the secondary metabolism of Dutch elm pathogens remains almost unexplored, and little is known about how SM biosynthetic genes are organized in these species. To better understand the metabolic potential of O. ulmi and O. novo-ulmi , we performed a deep survey and description of SM biosynthetic gene clusters (BGCs) in these species and assessed their conservation among eight species from the Ophiostomataceae family. Among 19 identified BGCs, a fujikurin-like gene cluster (OpPKS8) was unique to Dutch elm pathogens. Phylogenetic analysis revealed that orthologs for this gene cluster are widespread among phytopathogens and plant-associated fungi, suggesting that OpPKS8 may have been horizontally acquired by the Ophiostoma genus. Moreover, the detailed identification of several BGCs paves the way for future in-depth research and supports the potential impact of secondary metabolism on Ophiostoma genus' lifestyle.

Clustering the lexicon in the brain: a meta-analysis of the neurofunctional evidence on noun and verb processing

PubMed Central

Crepaldi, Davide; Berlingeri, Manuela; Cattinelli, Isabella; Borghese, Nunzio A.; Luzzatti, Claudio; Paulesu, Eraldo

2013-01-01

Although it is widely accepted that nouns and verbs are functionally independent linguistic entities, it is less clear whether their processing recruits different brain areas. This issue is particularly relevant for those theories of lexical semantics (and, more in general, of cognition) that suggest the embodiment of abstract concepts, i.e., based strongly on perceptual and motoric representations. This paper presents a formal meta-analysis of the neuroimaging evidence on noun and verb processing in order to address this dichotomy more effectively at the anatomical level. We used a hierarchical clustering algorithm that grouped fMRI/PET activation peaks solely on the basis of spatial proximity. Cluster specificity for grammatical class was then tested on the basis of the noun-verb distribution of the activation peaks included in each cluster. Thirty-two clusters were identified: three were associated with nouns across different tasks (in the right inferior temporal gyrus, the left angular gyrus, and the left inferior parietal gyrus); one with verbs across different tasks (in the posterior part of the right middle temporal gyrus); and three showed verb specificity in some tasks and noun specificity in others (in the left and right inferior frontal gyrus and the left insula). These results do not support the popular tenets that verb processing is predominantly based in the left frontal cortex and noun processing relies specifically on temporal regions; nor do they support the idea that verb lexical-semantic representations are heavily based on embodied motoric information. Our findings suggest instead that the cerebral circuits deputed to noun and verb processing lie in close spatial proximity in a wide network including frontal, parietal, and temporal regions. The data also indicate a predominant—but not exclusive—left lateralization of the network. PMID:23825451

OGLE II Eclipsing Binaries In The LMC: Analysis With Class

NASA Astrophysics Data System (ADS)

Devinney, Edward J.; Prsa, A.; Guinan, E. F.; DeGeorge, M.

2011-01-01

The Eclipsing Binaries (EBs) via Artificial Intelligence (EBAI) Project is applying machine learning techniques to elucidate the nature of EBs. Previously, Prsa, et al. applied artificial neural networks (ANNs) trained on physically-realistic Wilson-Devinney models to solve the light curves of the 1882 detached EBs in the LMC discovered by the OGLE II Project (Wyrzykowski, et al.) fully automatically, bypassing the need for manually-derived starting solutions. A curious result is the non-monotonic distribution of the temperature ratio parameter T2/T1, featuring a subsidiary peak noted previously by Mazeh, et al. in an independent analysis using the EBOP EB solution code (Tamuz, et al.). To explore this and to gain a fuller understanding of the multivariate EBAI LMC observational plus solutions data, we have employed automatic clustering and advanced visualization (CAV) techniques. Clustering the OGLE II data aggregates objects that are similar with respect to many parameter dimensions. Measures of similarity for example, could include the multidimensional Euclidean Distance between data objects, although other measures may be appropriate. Applying clustering, we find good evidence that the T2/T1 subsidiary peak is due to evolved binaries, in support of Mazeh et al.'s speculation. Further, clustering suggests that the LMC detached EBs occupying the main sequence region belong to two distinct classes. Also identified as a separate cluster in the multivariate data are stars having a Period-I band relation. Derekas et al. had previously found a Period-K band relation for LMC EBs discovered by the MACHO Project (Alcock, et al.). We suggest such CAV techniques will prove increasingly useful for understanding the large, multivariate datasets increasingly being produced in astronomy. We are grateful for the support of this research from NSF/RUI Grant AST-05-75042 f.

Association of Interleukin-1 gene clusters polymorphisms with primary open-angle glaucoma: a meta-analysis.

PubMed

Li, Junhua; Feng, Yifan; Sung, Mi Sun; Lee, Tae Hee; Park, Sang Woo

2017-11-28

Previous studies have associated the Interleukin-1 (IL-1) gene clusters polymorphisms with the risk of primary open-angle glaucoma (POAG). However, the results were not consistent. Here, we performed a meta-analysis to evaluate the role of IL-1 gene clusters polymorphisms in POAG susceptibility. PubMed, EMBASE and Cochrane Library (up to July 15, 2017) were searched by two independent investigators. All case-control studies investigating the association between single-nucleotide polymorphisms (SNPs) of IL-1 gene clusters and POAG risk were included. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for quantifying the strength of association that has been involved in at least two studies. Five studies on IL-1β rs16944 (c. -511C > T) (1053 cases and 986 controls), 4 studies on IL-1α rs1800587 (c. -889C > T) (822 cases and 714 controls), and 4 studies on IL-1β rs1143634 (c. +3953C > T) (798 cases and 730 controls) were included. The results suggest that all three SNPs were not associated with POAG risk. Stratification analyses indicated that the rs1143634 has a suggestive associated with high tension glaucoma (HTG) under dominant (P = 0.03), heterozygote (P = 0.04) and allelic models (P = 0.02), however, the weak association was nullified after Bonferroni adjustments for multiple tests. Based on current meta-analysis, we indicated that there is lack of association between the three SNPs of IL-1 and POAG. However, this conclusion should be interpreted with caution and further well designed studies with large sample-size are required to validate the conclusion as low statistical powers.

HTLV-1aA introduction into Brazil and its association with the trans-Atlantic slave trade.

PubMed

Amoussa, Adjile Edjide Roukiyath; Wilkinson, Eduan; Giovanetti, Marta; de Almeida Rego, Filipe Ferreira; Araujo, Thessika Hialla A; de Souza Gonçalves, Marilda; de Oliveira, Tulio; Alcantara, Luiz Carlos Junior

2017-03-01

Human T-lymphotropic virus (HTLV) is an endemic virus in some parts of the world, with Africa being home to most of the viral genetic diversity. In Brazil, HTLV-1 is endemic amongst Japanese and African immigrant populations. Multiple introductions of the virus in Brazil from other epidemic foci were hypothesized. The long terminal repeat (LTR) region of HTLV-1 was used to infer the origin of the virus in Brazil, using phylogenetic analysis. LTR sequences were obtained from the HTLV-1 database (http://htlv1db.bahia.fiocruz.br). Sequences were aligned and maximum-likelihood and Bayesian tree topologies were inferred. Brazilian specific clusters were identified and molecular-clock and coalescent models were used to estimate each cluster's time to the most recent common ancestor (tMRCA). Three Brazilian clusters were identified with a posterior probability ranged from 0.61 to 0.99. Molecular clock analysis of these three clusters dated back their respective tMRCAs between the year 1499 and the year 1668. Additional analysis also identified a close association between Brazilian sequences and new sequences from South Africa. Our results support the hypothesis of a multiple introductions of HTLV-1 into Brazil, with the majority of introductions occurring in the post-Colombian period. Our results further suggest that HTLV-1 introduction into Brazil was facilitated by the trans-Atlantic slave trade from endemic areas of Africa. The close association between southern African and Brazilian sequences also suggested that greater numbers of the southern African Bantu population might also have been part of the slave trade than previously thought. Copyright © 2016. Published by Elsevier B.V.

High ozone levels in the northeast of Portugal: Analysis and characterization

NASA Astrophysics Data System (ADS)

Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A. I.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.

2010-03-01

Each summer period extremely high ozone levels are registered at the rural background station of Lamas d'Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes at this site. Synoptic patterns anomalies and back trajectories cluster analysis were performed, for the period between 2004 and 2007, considering 76 days when ozone maximum hourly concentrations were above 200 μg m -3. The obtained atmospheric anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. A strong wind flow pattern from NE is observable in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal during summer. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, are responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants is the main contributor to the ozone levels registered at Lamas d'Olo. This is also highlighted by the correlation of the ozone time-series with the meteorological parameters analysed in the frequency domain.

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

Partner-Drug Resistance and Population Substructuring of Artemisinin-Resistant Plasmodium falciparum in Cambodia

PubMed Central

Parobek, Christian M.; Parr, Jonathan B.; Brazeau, Nicholas F.; Lon, Chanthap; Chaorattanakawee, Suwanna; Gosi, Panita; Barnett, Eric J.; Norris, Lauren D.; Meshnick, Steven R.; Spring, Michele D.; Lanteri, Charlotte A.; Bailey, Jeffrey A.; Saunders, David L.; Lin, Jessica T.

2017-01-01

Abstract Plasmodium falciparum in western Cambodia has developed resistance to artemisinin and its partner drugs, causing frequent treatment failure. Understanding this evolution can inform the deployment of new therapies. We investigated the genetic architecture of 78 falciparum isolates using whole-genome sequencing, correlating results to in vivo and ex vivo drug resistance and exploring the relationship between population structure, demographic history, and partner drug resistance. Principle component analysis, network analysis and demographic inference identified a diverse central population with three clusters of clonally expanding parasite populations, each associated with specific K13 artemisinin resistance alleles and partner drug resistance profiles which were consistent with the sequential deployment of artemisinin combination therapies in the region. One cluster displayed ex vivo piperaquine resistance and mefloquine sensitivity with a high rate of in vivo failure of dihydroartemisinin-piperaquine. Another cluster displayed ex vivo mefloquine resistance and piperaquine sensitivity with high in vivo efficacy of dihydroartemisinin-piperaquine. The final cluster was clonal and displayed intermediate sensitivity to both drugs. Variations in recently described piperaquine resistance markers did not explain the difference in mean IC90 or clinical failures between the high and intermediate piperaquine resistance groups, suggesting additional loci may be involved in resistance. The results highlight an important role for partner drug resistance in shaping the P. falciparum genetic landscape in Southeast Asia and suggest that further work is needed to evaluate for other mutations that drive piperaquine resistance. PMID:28854635

Optimization of self-interstitial clusters in 3C-SiC with genetic algorithm

NASA Astrophysics Data System (ADS)

Ko, Hyunseok; Kaczmarowski, Amy; Szlufarska, Izabela; Morgan, Dane

2017-08-01

Under irradiation, SiC develops damage commonly referred to as black spot defects, which are speculated to be self-interstitial atom clusters. To understand the evolution of these defect clusters and their impacts (e.g., through radiation induced swelling) on the performance of SiC in nuclear applications, it is important to identify the cluster composition, structure, and shape. In this work the genetic algorithm code StructOpt was utilized to identify groundstate cluster structures in 3C-SiC. The genetic algorithm was used to explore clusters of up to ∼30 interstitials of C-only, Si-only, and Si-C mixtures embedded in the SiC lattice. We performed the structure search using Hamiltonians from both density functional theory and empirical potentials. The thermodynamic stability of clusters was investigated in terms of their composition (with a focus on Si-only, C-only, and stoichiometric) and shape (spherical vs. planar), as a function of the cluster size (n). Our results suggest that large Si-only clusters are likely unstable, and clusters are predominantly C-only for n ≤ 10 and stoichiometric for n > 10. The results imply that there is an evolution of the shape of the most stable clusters, where small clusters are stable in more spherical geometries while larger clusters are stable in more planar configurations. We also provide an estimated energy vs. size relationship, E(n), for use in future analysis.

Investigation of spacial clustering of rare diseases: childhood malignancies in North Humberside.

PubMed

Alexander, F; Cartwright, R; McKinney, P A; Ricketts, T J

1990-03-01

The aims of the study were (1) to test for uniformity of distribution of childhood leukaemias and other malignancies; and (2) to consider the aetiological implications of unusual distributions. A test for spacial clustering was applied using a method which allows for unequal distribution of the population at risk and avoids using census data to provide population denominators. When clustering was identified, four possible aetiological links which had already been suggested to the Leukaemia Research Fund Centre were examined in a local area. The study was carried out in the Yorkshire Health Region in the north of England. 144 children under 15 years of age with a diagnosis of malignant disease known to the Yorkshire Regional Childhood Tumour Registry between 1974 and 1986 were included in the analysis. Of these 53 had leukaemias and nine had lymphomas. Significant localised clustering was found in North Humberside, though not in the whole of the Yorkshire Health Region. A number of clustered cases were identified, some of whom were in a post code sector, Hull 10, to the west of Kingston-upon-Hull, about which concern had been expressed since 1985. There was however no evidence that disease clustering was confined to this area. Four previously suggested hypotheses about causation in this particular area were examined but the results were negative or inconclusive. The identification of spacial clustering must be seen as only the first step in a series of investigations; it can only rarely lead to aetiological conclusions by itself, but it can motivate and target other investigations.

Differential regulation of ParaHox genes by retinoic acid in the invertebrate chordate amphioxus (Branchiostoma floridae).

PubMed

Osborne, Peter W; Benoit, Gérard; Laudet, Vincent; Schubert, Michael; Ferrier, David E K

2009-03-01

The ParaHox cluster is the evolutionary sister to the Hox cluster. Like the Hox cluster, the ParaHox cluster displays spatial and temporal regulation of the component genes along the anterior/posterior axis in a manner that correlates with the gene positions within the cluster (a feature called collinearity). The ParaHox cluster is however a simpler system to study because it is composed of only three genes. We provide a detailed analysis of the amphioxus ParaHox cluster and, for the first time in a single species, examine the regulation of the cluster in response to a single developmental signalling molecule, retinoic acid (RA). Embryos treated with either RA or RA antagonist display altered ParaHox gene expression: AmphiGsx expression shifts in the neural tube, and the endodermal boundary between AmphiXlox and AmphiCdx shifts its anterior/posterior position. We identified several putative retinoic acid response elements and in vitro assays suggest some may participate in RA regulation of the ParaHox genes. By comparison to vertebrate ParaHox gene regulation we explore the evolutionary implications. This work highlights how insights into the regulation and evolution of more complex vertebrate arrangements can be obtained through studies of a simpler, unduplicated amphioxus gene cluster.

Cluster and Multiple Correspondence Analyses in Rheumatology: Paths to Uncovering Relationships in a Sea of Data.

PubMed

Han, Lu; Benseler, Susanne M; Tyrrell, Pascal N

2018-05-01

Rheumatic diseases encompass a wide range of conditions caused by inflammation and dysregulation of the immune system resulting in organ damage. Research in these heterogeneous diseases benefits from multivariate methods. The aim of this review was to describe and evaluate current literature in rheumatology regarding cluster analysis and correspondence analysis. A systematic review showed an increase in studies making use of these 2 methods. However, standardization in how these methods are applied and reported is needed. Researcher expertise was determined to be the main barrier to considering these approaches, whereas education and collaborating with a biostatistician were suggested ways forward. Copyright © 2018 Elsevier Inc. All rights reserved.

Low Back Pain Subgroups using Fear-Avoidance Model Measures: Results of a Cluster Analysis

PubMed Central

Beneciuk, Jason M.; Robinson, Michael E.; George, Steven Z.

2012-01-01

Objectives The purpose of this secondary analysis was to test the hypothesis that an empirically derived psychological subgrouping scheme based on multiple Fear-Avoidance Model (FAM) constructs would provide additional capabilities for clinical outcomes in comparison to a single FAM construct. Methods Patients (n = 108) with acute or sub-acute low back pain (LBP) enrolled in a clinical trial comparing behavioral physical therapy interventions to classification based physical therapy completed baseline questionnaires for pain catastrophizing (PCS), fear-avoidance beliefs (FABQ-PA, FABQ-W), and patient-specific fear (FDAQ). Clinical outcomes were pain intensity and disability measured at baseline, 4-weeks, and 6-months. A hierarchical agglomerative cluster analysis was used to create distinct cluster profiles among FAM measures and discriminant analysis was used to interpret clusters. Changes in clinical outcomes were investigated with repeated measures ANOVA and differences in results based on cluster membership were compared to FABQ-PA subgrouping used in the original trial. Results Three distinct FAM subgroups (Low Risk, High Specific Fear, and High Fear & Catastrophizing) emerged from cluster analysis. Subgroups differed on baseline pain and disability (p’s<.01) with the High Fear & Catastrophizing subgroup associated with greater pain than the Low Risk subgroup (p<.01) and the greatest disability (p’s<.05). Subgroup × time interactions were detected for both pain and disability (p’s<.05) with the High Fear & Catastrophizing subgroup reporting greater changes in pain and disability than other subgroups (p’s<.05). In contrast, FABQ-PA subgroups used in the original trial were not associated with interactions for clinical outcomes. Discussion These data suggest that subgrouping based on multiple FAM measures may provide additional information on clinical outcomes in comparison to determining subgroup status by FABQ-PA alone. Subgrouping methods for patients with LBP should include multiple psychological factors to further explore if patients can be matched with appropriate interventions. PMID:22510537

State of stress and crustal fluid migration related to west-dipping structures in the slab-forearc system in the northern Chilean subduction zone

NASA Astrophysics Data System (ADS)

Salazar, P.; Kummerow, J.; Wigger, P.; Shapiro, S.; Asch, G.

2017-03-01

Previous studies in the forearc of the northern Chilean subduction zone have identified important tectonic features in the upper crust. As a result of these works, the West Fissure Fault System (WFFS) has recently been imaged using microseismic events. The WFFS is the westward-dipping, sharp lower boundary of the northern Chilean forearc and is geometrically opposed to subduction of the Nazca plate. The present article builds on this previous work and is novel in that it characterizes this structure's stress distribution using focal mechanisms and stress tensor analysis. The results of the stress tensor analysis show that the state of stress in the WFFS is related to its strike-slip tectonic context and likely represents a manifestation of local forces associated with the highest areas in the Andes. Two seismic clusters have also been identified; these clusters may be associated with a blind branch of the WFFS. We studied these clusters in order to determine their sources and possible connection with fluid migration across the upper plate. We observed that the two clusters differ from one another in some regards. The central cluster has characteristics consistent with an earthquake swarm with two clearly identifiable phases. Conversely, the SW cluster has a clear main shock associated with it, and it can be separated into two subclusters (A and A΄). In contrast, similarities among the two clusters suggest that the clusters may have a common origin. The b-values for both clusters are characteristic of tectonic plate boundaries. The spatial spreading, which is approximately confined to one plane, reflects progressive growth of the main fracture underlying the swarm and subcluster A. We also find that earthquakes themselves trigger aftershocks near the borders of their rupture areas. In addition, the spatio-temporal migration of hypocentres, as well as their spatial correlation with areas that are interpreted to be fluid migration zones, suggest that there is a close relationship between fluid movement and the earthquake sources associated with the swarm and subcluster A. These observations point to stick-slip behaviour of the rupture propagation, which can be explained by earthquake-induced stress transfer and fluid flow in a fluid-permeated, critically loaded fault zone.

Hox gene cluster of the ascidian, Halocynthia roretzi, reveals multiple ancient steps of cluster disintegration during ascidian evolution.

PubMed

Sekigami, Yuka; Kobayashi, Takuya; Omi, Ai; Nishitsuji, Koki; Ikuta, Tetsuro; Fujiyama, Asao; Satoh, Noriyuki; Saiga, Hidetoshi

2017-01-01

Hox gene clusters with at least 13 paralog group (PG) members are common in vertebrate genomes and in that of amphioxus. Ascidians, which belong to the subphylum Tunicata (Urochordata), are phylogenetically positioned between vertebrates and amphioxus, and traditionally divided into two groups: the Pleurogona and the Enterogona. An enterogonan ascidian, Ciona intestinalis ( Ci ), possesses nine Hox genes localized on two chromosomes; thus, the Hox gene cluster is disintegrated. We investigated the Hox gene cluster of a pleurogonan ascidian, Halocynthia roretzi ( Hr ) to investigate whether Hox gene cluster disintegration is common among ascidians, and if so, how such disintegration occurred during ascidian or tunicate evolution. Our phylogenetic analysis reveals that the Hr Hox gene complement comprises nine members, including one with a relatively divergent Hox homeodomain sequence. Eight of nine Hr Hox genes were orthologous to Ci-Hox1 , 2, 3, 4, 5, 10, 12 and 13. Following the phylogenetic classification into 13 PGs, we designated Hr Hox genes as Hox1, 2, 3, 4, 5, 10, 11/12/13.a , 11/12/13.b and HoxX . To address the chromosomal arrangement of the nine Hox genes, we performed two-color chromosomal fluorescent in situ hybridization, which revealed that the nine Hox genes are localized on a single chromosome in Hr , distinct from their arrangement in Ci . We further examined the order of the nine Hox genes on the chromosome by chromosome/scaffold walking. This analysis suggested a gene order of Hox1 , 11/12/13.b, 11/12/13.a, 10, 5, X, followed by either Hox4, 3, 2 or Hox2, 3, 4 on the chromosome. Based on the present results and those previously reported in Ci , we discuss the establishment of the Hox gene complement and disintegration of Hox gene clusters during the course of ascidian or tunicate evolution. The Hox gene cluster and the genome must have experienced extensive reorganization during the course of evolution from the ancestral tunicate to Hr and Ci . Nevertheless, some features are shared in Hox gene components and gene arrangement on the chromosomes, suggesting that Hox gene cluster disintegration in ascidians involved early events common to tunicates as well as later ascidian lineage-specific events.

Development of deformation band clusters in porous quartz sandstones - Contribution from microstructural analysis and numerical modeling

NASA Astrophysics Data System (ADS)

Philit, S.; Soliva, R.; Chemenda, A. I.

2017-12-01

Because sandstones form good reservoirs for hydrocarbon, water or C02 storage, the understanding of the deformation processes in sandstones is major. The deformation band clusters result from the localization of the deformation in porous sandstones under the form of gathered low-permeability cataclastic deformation bands. It has recently been shown that this localization is favored in extensional tectonics. The clusters measure tens to hundreds of meters in extent and propagate vertically as long as the sandstone is clean. Because the clusters can form several kilometers long networks, they are likely to hamper fluid flow during reservoir exploitation. Yet, the processes of band accumulation linked to the evolution of the clusters to a potential faulting are poorly understood. An integrated study coupling a microscopic analysis of the deformed granular material in clusters from 7 sites in the world and distinct element numerical modeling permits to propose a model for cluster growth. Our microscopic analysis reveals that the clusters display varying degree of cataclasis, with the most important degrees in the bands. This cataclasis is accompanied by porosity reduction (more reduced in thrust Andersonian regime), and increased Particle Size Distribution. This testifies of an important packing and implies an increased number of particle coordination. During deformation, the grain shape is both smoothened and roughened; the averaged values of the roundness and circularity indicate a rapid roughening of the clasts at the first stages of deformation followed by a slight smoothening. The roughening of the clasts in densely packed material induces high friction and strengthens the material. High residual porosity at some band edges suggests a local dilatant behavior of sheared material. Our distinct element numerical models and other particle models in the literature confirm this observation. The development of force chains with low particle coordination at these locations would weaken the stress resistance at the contact points. Hence, the cluster growth would be promoted by the successive localization of bands the edges of preexisting bands. Faulting could occur at any stage of the cluster development, probably favored along interfaces of minimized strength with smooth geometry.

Functional analysis of the upstream regulatory region of chicken miR-17-92 cluster.

PubMed

Cheng, Min; Zhang, Wen-jian; Xing, Tian-yu; Yan, Xiao-hong; Li, Yu-mao; Li, Hui; Wang, Ning

2016-08-01

miR-17-92 cluster plays important roles in cell proliferation, differentiation, apoptosis, animal development and tumorigenesis. The transcriptional regulation of miR-17-92 cluster has been extensively studied in mammals, but not in birds. To date, avian miR-17-92 cluster genomic structure has not been fully determined. The promoter location and sequence of miR-17-92 cluster have not been determined, due to the existence of a genomic gap sequence upstream of miR-17-92 cluster in all the birds whose genomes have been sequenced. In this study, genome walking was used to close the genomic gap upstream of chicken miR-17-92 cluster. In addition, bioinformatics analysis, reporter gene assay and truncation mutagenesis were used to investigate functional role of the genomic gap sequence. Genome walking analysis showed that the gap region was 1704 bp long, and its GC content was 80.11%. Bioinformatics analysis showed that in the gap region, there was a 200 bp conserved sequence among the tested 10 species (Gallus gallus, Homo sapiens, Pan troglodytes, Bos taurus, Sus scrofa, Rattus norvegicus, Mus musculus, Possum, Danio rerio, Rana nigromaculata), which is core promoter region of mammalian miR-17-92 host gene (MIR17HG). Promoter luciferase reporter gene vector of the gap region was constructed and reporter assay was performed. The result showed that the promoter activity of pGL3-cMIR17HG (-4228/-2506) was 417 times than that of negative control (empty pGL3 basic vector), suggesting that chicken miR-17-92 cluster promoter exists in the gap region. To further gain insight into the promoter structure, two different truncations for the cloned gap sequence were generated by PCR. One had a truncation of 448 bp at the 5'-end and the other had a truncation of 894 bp at the 3'-end. Further reporter analysis showed that compared with the promoter activity of pGL3-cMIR17HG (-4228/-2506), the reporter activities of the 5'-end truncation and the 3'-end truncation were reduced by 19.82% and 60.14%, respectively. These data demonstrated that the important promoter region of chicken miR-17-92 cluster is located in the -3400/-2506 bp region. Our results lay the foundation for revealing the transcriptional regulatory mechanisms of chicken miR-17-92 cluster.

Extraction of heavy metals characteristics of the 2011 Tohoku tsunami deposits using multiple classification analysis.

PubMed

Nakamura, Kengo; Kuwatani, Tatsu; Kawabe, Yoshishige; Komai, Takeshi

2016-02-01

Tsunami deposits accumulated on the Tohoku coastal area in Japan due to the impact of the Tohoku-oki earthquake. In the study reported in this paper, we applied principal component analysis (PCA) and cluster analysis (CA) to determine the concentrations of heavy metals in tsunami deposits that had been diluted with water or digested using 1 M HCl. The results suggest that the environmental risk is relatively low, evidenced by the following geometric mean concentrations: Pb, 16 mg kg(-1) and 0.003 ml L(-1); As, 1.8 mg kg(-1) and 0.004 ml L(-1); and Cd, 0.17 mg kg(-1) and 0.0001 ml L(-1). CA was performed after outliers were excluded using PCA. The analysis grouped the concentrations of heavy metals for leaching in water and acid. For the acid case, the first cluster contained Ni, Fe, Cd, Cu, Al, Cr, Zn, and Mn; while the second contained Pb, Sb, As, and Mo. For water, the first cluster contained Ni, Fe, Al, and Cr; and the second cluster contained Mo, Sb, As, Cu, Zn, Pb, and Mn. Statistical analysis revealed that the typical toxic elements, As, Pb, and Cd have steady correlations for acid leaching but are relatively sparse for water leaching. Pb and As from the tsunami deposits seemed to reveal a kind of redox elution mechanism using 1 M HCl. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Genetic polymorphism of Tulipa gesneriana L. evaluated on the basis of the ISSR marking data].

PubMed

Kashin, A S; Kritskaya, T A; Schanzer, I A

2016-10-01

Using the method of ISSR analysis, the genetic diversity of 18 natural populations of Tulipa gesneriana L. from the north of the Lower Volga region was examined. The ten ISSR primers used in the study provided identification of 102 PCR fragments, of which 50 were polymorphic (49.0%). According to the proportion of polymorphic markers, two population groups were distinguished: (1) the populations in which the proportion of polymorphic markers ranged from 0.35 to 0.41; (2) the populations in which the proportion of polymorphic markers ranged from 0.64 to 0.85. UPGMA clustering analysis provided subdivision of the sample into two large clusters. The unrooted tree constructed using the Neighbor Joining algorithm had similar topology. The first cluster included slightly variable populations and the second cluster included highly variable populations. The AMOVA analysis showed statistically significant differences (F CT = 0.430; p = 0.000) between the two groups. Local populations are considerably genetically differentiated from each other (F ST = 0.632) and have almost no links via modern gene flow, as evidenced by the results of the Mantel test (r =–0.118; p = 0.819). It is suggested that the degree of genetic similarities and differences between the populations depends on the time and the species dispersal patterns on these territories.

Using Cluster Analysis to Examine Husband-Wife Decision Making

ERIC Educational Resources Information Center

Bonds-Raacke, Jennifer M.

2006-01-01

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

Architecture of the Yeast Mitochondrial Iron-Sulfur Cluster Assembly Machinery

PubMed Central

Ranatunga, Wasantha; Gakh, Oleksandr; Galeano, Belinda K.; Smith, Douglas Y.; Söderberg, Christopher A. G.; Al-Karadaghi, Salam; Thompson, James R.; Isaya, Grazia

2016-01-01

The biosynthesis of Fe-S clusters is a vital process involving the delivery of elemental iron and sulfur to scaffold proteins via molecular interactions that are still poorly defined. We reconstituted a stable, functional complex consisting of the iron donor, Yfh1 (yeast frataxin homologue 1), and the Fe-S cluster scaffold, Isu1, with 1:1 stoichiometry, [Yfh1]24·[Isu1]24. Using negative staining transmission EM and single particle analysis, we obtained a three-dimensional reconstruction of this complex at a resolution of ∼17 Å. In addition, via chemical cross-linking, limited proteolysis, and mass spectrometry, we identified protein-protein interaction surfaces within the complex. The data together reveal that [Yfh1]24·[Isu1]24 is a roughly cubic macromolecule consisting of one symmetric Isu1 trimer binding on top of one symmetric Yfh1 trimer at each of its eight vertices. Furthermore, molecular modeling suggests that two subunits of the cysteine desulfurase, Nfs1, may bind symmetrically on top of two adjacent Isu1 trimers in a manner that creates two putative [2Fe-2S] cluster assembly centers. In each center, conserved amino acids known to be involved in sulfur and iron donation by Nfs1 and Yfh1, respectively, are in close proximity to the Fe-S cluster-coordinating residues of Isu1. We suggest that this architecture is suitable to ensure concerted and protected transfer of potentially toxic iron and sulfur atoms to Isu1 during Fe-S cluster assembly. PMID:26941001

Rapid diversification of FoxP2 in teleosts through gene duplication in the teleost-specific whole genome duplication event.

PubMed

Song, Xiaowei; Wang, Yajun; Tang, Yezhong

2013-01-01

As one of the most conserved genes in vertebrates, FoxP2 is widely involved in a number of important physiological and developmental processes. We systematically studied the evolutionary history and functional adaptations of FoxP2 in teleosts. The duplicated FoxP2 genes (FoxP2a and FoxP2b), which were identified in teleosts using synteny and paralogon analysis on genome databases of eight organisms, were probably generated in the teleost-specific whole genome duplication event. A credible classification with FoxP2, FoxP2a and FoxP2b in phylogenetic reconstructions confirmed the teleost-specific FoxP2 duplication. The unavailability of FoxP2b in Danio rerio suggests that the gene was deleted through nonfunctionalization of the redundant copy after the Otocephala-Euteleostei split. Heterogeneity in evolutionary rates among clusters consisting of FoxP2 in Sarcopterygii (Cluster 1), FoxP2a in Teleostei (Cluster 2) and FoxP2b in Teleostei (Cluster 3), particularly between Clusters 2 and 3, reveals asymmetric functional divergence after the gene duplication. Hierarchical cluster analyses of hydrophobicity profiles demonstrated significant structural divergence among the three clusters with verification of subsequent stepwise discriminant analysis, in which FoxP2 of Leucoraja erinacea and Lepisosteus oculatus were classified into Cluster 1, whereas FoxP2b of Salmo salar was grouped into Cluster 2 rather than Cluster 3. The simulated thermodynamic stability variations of the forkhead box domain (monomer and homodimer) showed remarkable divergence in FoxP2, FoxP2a and FoxP2b clusters. Relaxed purifying selection and positive Darwinian selection probably were complementary driving forces for the accelerated evolution of FoxP2 in ray-finned fishes, especially for the adaptive evolution of FoxP2a and FoxP2b in teleosts subsequent to the teleost-specific gene duplication.

Rapid Diversification of FoxP2 in Teleosts through Gene Duplication in the Teleost-Specific Whole Genome Duplication Event

PubMed Central

Song, Xiaowei; Wang, Yajun; Tang, Yezhong

2013-01-01

As one of the most conserved genes in vertebrates, FoxP2 is widely involved in a number of important physiological and developmental processes. We systematically studied the evolutionary history and functional adaptations of FoxP2 in teleosts. The duplicated FoxP2 genes (FoxP2a and FoxP2b), which were identified in teleosts using synteny and paralogon analysis on genome databases of eight organisms, were probably generated in the teleost-specific whole genome duplication event. A credible classification with FoxP2, FoxP2a and FoxP2b in phylogenetic reconstructions confirmed the teleost-specific FoxP2 duplication. The unavailability of FoxP2b in Danio rerio suggests that the gene was deleted through nonfunctionalization of the redundant copy after the Otocephala-Euteleostei split. Heterogeneity in evolutionary rates among clusters consisting of FoxP2 in Sarcopterygii (Cluster 1), FoxP2a in Teleostei (Cluster 2) and FoxP2b in Teleostei (Cluster 3), particularly between Clusters 2 and 3, reveals asymmetric functional divergence after the gene duplication. Hierarchical cluster analyses of hydrophobicity profiles demonstrated significant structural divergence among the three clusters with verification of subsequent stepwise discriminant analysis, in which FoxP2 of Leucoraja erinacea and Lepisosteus oculatus were classified into Cluster 1, whereas FoxP2b of Salmo salar was grouped into Cluster 2 rather than Cluster 3. The simulated thermodynamic stability variations of the forkhead box domain (monomer and homodimer) showed remarkable divergence in FoxP2, FoxP2a and FoxP2b clusters. Relaxed purifying selection and positive Darwinian selection probably were complementary driving forces for the accelerated evolution of FoxP2 in ray-finned fishes, especially for the adaptive evolution of FoxP2a and FoxP2b in teleosts subsequent to the teleost-specific gene duplication. PMID:24349554

Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI)

PubMed Central

Fyffe, Denise; Kalpakjian, Claire Z.; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C.; Tulsky, David S.; Jette, Alan M.

2016-01-01

Objective: To provide validation of functional ability levels for the Spinal Cord Injury – Functional Index (SCI-FI). Design: Cross-sectional. Setting: Inpatient rehabilitation hospital and community settings. Participants: A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Interventions: Not Applicable. Main Outcome Measures: Spinal Cord Injury-Functional Index (SCI-FI). Results: Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. Conclusions: These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed. PMID:26781769

A New Approach to Identify High Burnout Medical Staffs by Kernel K-Means Cluster Analysis in a Regional Teaching Hospital in Taiwan.

PubMed

Lee, Yii-Ching; Huang, Shian-Chang; Huang, Chih-Hsuan; Wu, Hsin-Hung

2016-01-01

This study uses kernel k-means cluster analysis to identify medical staffs with high burnout. The data collected in October to November 2014 are from the emotional exhaustion dimension of the Chinese version of Safety Attitudes Questionnaire in a regional teaching hospital in Taiwan. The number of effective questionnaires including the entire staffs such as physicians, nurses, technicians, pharmacists, medical administrators, and respiratory therapists is 680. The results show that 8 clusters are generated by kernel k-means method. Employees in clusters 1, 4, and 5 are relatively in good conditions, whereas employees in clusters 2, 3, 6, 7, and 8 need to be closely monitored from time to time because they have relatively higher degree of burnout. When employees with higher degree of burnout are identified, the hospital management can take actions to improve the resilience, reduce the potential medical errors, and, eventually, enhance the patient safety. This study also suggests that the hospital management needs to keep track of medical staffs' fatigue conditions and provide timely assistance for burnout recovery through employee assistance programs, mindfulness-based stress reduction programs, positivity currency buildup, and forming appreciative inquiry groups. © The Author(s) 2016.

ALMA-SZ Detection of a Galaxy Cluster Merger Shock at Half the Age of the Universe

NASA Astrophysics Data System (ADS)

Basu, K.; Sommer, M.; Erler, J.; Eckert, D.; Vazza, F.; Magnelli, B.; Bertoldi, F.; Tozzi, P.

2016-10-01

We present ALMA measurements of a merger shock using the thermal Sunyaev-Zel’dovich (SZ) effect signal, at the location of a radio relic in the famous El Gordo galaxy cluster at z≈ 0.9. Multi-wavelength analysis in combination with the archival Chandra data and a high-resolution radio image provides a consistent picture of the thermal and non-thermal signal variation across the shock front and helps to put robust constraints on the shock Mach number as well as the relic magnetic field. We employ a Bayesian analysis technique for modeling the SZ and X-ray data self-consistently, illustrating respective parameter degeneracies. Combined results indicate a shock with Mach number { M }={2.4}-0.6+1.3, which in turn suggests a high value of the magnetic field (of the order of 4-10 μ {{G}}) to account for the observed relic width at 2 GHz. At roughly half the current age of the universe, this is the highest-redshift direct detection of a cluster shock to date, and one of the first instances of an ALMA-SZ observation in a galaxy cluster. It shows the tremendous potential for future ALMA-SZ observations to detect merger shocks and other cluster substructures out to the highest redshifts.

In vivo imaging of CD8+ T cell-mediated elimination of malaria liver stages

PubMed Central

Cockburn, Ian A.; Amino, Rogerio; Kelemen, Reka K.; Kuo, Scot C.; Tse, Sze-Wah; Radtke, Andrea; Mac-Daniel, Laura; Ganusov, Vitaly V.; Zavala, Fidel; Ménard, Robert

2013-01-01

CD8+ T cells are specialized cells of the adaptive immune system capable of finding and eliminating pathogen-infected cells. To date it has not been possible to observe the destruction of any pathogen by CD8+ T cells in vivo. Here we demonstrate a technique for imaging the killing of liver-stage malaria parasites by CD8+ T cells bearing a transgenic T cell receptor specific for a parasite epitope. We report several features that have not been described by in vitro analysis of the process, chiefly the formation of large clusters of effector CD8+ T cells around infected hepatocytes. The formation of clusters requires antigen-specific CD8+ T cells and signaling by G protein-coupled receptors, although CD8+ T cells of unrelated specificity are also recruited to clusters. By combining mathematical modeling and data analysis, we suggest that formation of clusters is mainly driven by enhanced recruitment of T cells into larger clusters. We further show various death phenotypes of the parasite, which typically follow prolonged interactions between infected hepatocytes and CD8+ T cells. These findings stress the need for intravital imaging for dissecting the fine mechanisms of pathogen recognition and killing by CD8+ T cells. PMID:23674673

Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae).

PubMed

Van Cann, Joannes; Virgilio, Massimiliano; Jordaens, Kurt; De Meyer, Marc

2015-01-01

Previous attempts to resolve the Ceratitis FAR complex (Ceratitis fasciventris, Ceratitis anonae, Ceratitis rosa, Diptera, Tephritidae) showed contrasting results and revealed the occurrence of five microsatellite genotypic clusters (A, F1, F2, R1, R2). In this paper we explore the potential of wing morphometrics for the diagnosis of FAR morphospecies and genotypic clusters. We considered a set of 227 specimens previously morphologically identified and genotyped at 16 microsatellite loci. Seventeen wing landmarks and 6 wing band areas were used for morphometric analyses. Permutational multivariate analysis of variance detected significant differences both across morphospecies and genotypic clusters (for both males and females). Unconstrained and constrained ordinations did not properly resolve groups corresponding to morphospecies or genotypic clusters. However, posterior group membership probabilities (PGMPs) of the Discriminant Analysis of Principal Components (DAPC) allowed the consistent identification of a relevant proportion of specimens (but with performances differing across morphospecies and genotypic clusters). This study suggests that wing morphometrics and PGMPs might represent a possible tool for the diagnosis of species within the FAR complex. Here, we propose a tentative diagnostic method and provide a first reference library of morphometric measures that might be used for the identification of additional and unidentified FAR specimens.

Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region

USGS Publications Warehouse

Hummel, Michelle; Wood, Nathan J.; Schweikert, Amy; Stacey, Mark T.; Jones, Jeanne; Barnard, Patrick L.; Erikson, Li H.

2018-01-01

Sea level is projected to rise over the coming decades, further increasing the extent of flooding hazards in coastal communities. Efforts to address potential impacts from climate-driven coastal hazards have called for collaboration among communities to strengthen the application of best practices. However, communities currently lack practical tools for identifying potential partner communities based on similar hazard exposure characteristics. This study uses statistical cluster analysis to identify similarities in community exposure to flooding hazards for a suite of sea level rise and storm scenarios. We demonstrate this approach using 63 jurisdictions in the San Francisco Bay region of California (USA) and compare 21 distinct exposure variables related to residents, employees, and structures for six hazard scenario combinations of sea level rise and storms. Results indicate that cluster analysis can provide an effective mechanism for identifying community groupings. Cluster compositions changed based on the selected societal variables and sea level rise scenarios, suggesting that a community could participate in multiple networks to target specific issues or policy interventions. The proposed clustering approach can serve as a data-driven foundation to help communities identify other communities with similar adaptation challenges and to enhance regional efforts that aim to facilitate adaptation planning and investment prioritization.

Meso-zooplankton abundance and spatial distribution off Lützow-Holm Bay during austral summer 2007-2008

NASA Astrophysics Data System (ADS)

Makabe, Ryosuke; Tanimura, Atsushi; Tamura, Takeshi; Hirano, Daisuke; Shimada, Keishi; Hashihama, Fuminori; Fukuchi, Mitsuo

2017-06-01

To elucidate spatial differences in mesozooplankton community structure in local scale, vertical hauls using a 60-μm mesh closing net were carried out off Lützow-Holm Bay in January 2008. All of the zooplankton samples collected from three layers (0-100, 100-200, and 200-500 m) at seven stations were dominated by Oithona spp., Oncaea spp., Ctenocalanus citer, Microcalanus pygmaeus, and copepod nauplii. The cluster analysis of mesozooplankton abundances showed three distinct groups according to sampling depth, which appeared to be due to the preferential vertical distribution of dominant copepods. The other cluster analysis on integrated abundance upper 500 m revealed that mesozooplankton community structures at stations located on the western and eastern edges of the observation area (Cluster A) differed from those at the central stations (Cluster B). Abundance of copepod nauplii, Oithona spp., and C. citer differed between Clusters A and B, which was likely caused by differences in recruitment and early development in the dominant copepods, being associated with the timing and duration of ice edge blooms. This suggests that such heterogeneity in abundance and recruitment/development of dominant taxa was likely caused by local heterogeneity in sea ice dynamics. This may affect our understanding of zooplankton distribution.

Experimental verification of the cluster model of CH3F-(ortho-H2)n in solid para-H2 by using mid-infrared pump-probe laser spectroscopy

NASA Astrophysics Data System (ADS)

Miyamoto, Yuki; Mizoguchi, Asao; Kanamori, Hideto

2017-03-01

The bleaching process in the C-F stretching mode (ν3 band) of CH3F-(ortho-H2)n [n = 0 and 1] clusters in solid para-H2 was monitored using pump and probe laser spectroscopy on the C-H stretching mode (ν1 and 2ν5 bands). From an analysis of the depleted spectral profiles, the transition frequency and linewidth of each cluster were directly determined. The results agree with the values previously derived from a deconvolution analysis of the broadened ν1/2ν5 spectrum observed by FTIR spectroscopy. The complementary increase and decrease between the n = 0 and 1 components were also verified through monitoring the ν1 and 2ν5 bands, which suggests a closed system among the CH3F-(ortho-H2)n clusters. These observations provide experimental verification of the CH3F-(ortho-H2)n cluster model. On the other hand, a trial to observe the bleaching process by pumping the C-H stretching mode was not successful. This result may be important for understanding the dynamics of vibrational relaxation processes in CH3F-(ortho-H2)n in solid para-H2.

Experimental verification of the cluster model of CH3F-(ortho-H2)n in solid para-H2 by using mid-infrared pump-probe laser spectroscopy.

PubMed

Miyamoto, Yuki; Mizoguchi, Asao; Kanamori, Hideto

2017-03-21

The bleaching process in the C-F stretching mode (ν 3 band) of CH 3 F-(ortho-H 2 ) n [n = 0 and 1] clusters in solid para-H 2 was monitored using pump and probe laser spectroscopy on the C-H stretching mode (ν 1 and 2ν 5 bands). From an analysis of the depleted spectral profiles, the transition frequency and linewidth of each cluster were directly determined. The results agree with the values previously derived from a deconvolution analysis of the broadened ν 1 /2ν 5 spectrum observed by FTIR spectroscopy. The complementary increase and decrease between the n = 0 and 1 components were also verified through monitoring the ν 1 and 2ν 5 bands, which suggests a closed system among the CH 3 F-(ortho-H 2 ) n clusters. These observations provide experimental verification of the CH 3 F-(ortho-H 2 ) n cluster model. On the other hand, a trial to observe the bleaching process by pumping the C-H stretching mode was not successful. This result may be important for understanding the dynamics of vibrational relaxation processes in CH 3 F-(ortho-H 2 ) n in solid para-H 2 .

A sequential-move game for enhancing safety and security cooperation within chemical clusters.

PubMed

Pavlova, Yulia; Reniers, Genserik

2011-02-15

The present paper provides a game theoretic analysis of strategic cooperation on safety and security among chemical companies within a chemical industrial cluster. We suggest a two-stage sequential move game between adjacent chemical plants and the so-called Multi-Plant Council (MPC). The MPC is considered in the game as a leader player who makes the first move, and the individual chemical companies are the followers. The MPC's objective is to achieve full cooperation among players through establishing a subsidy system at minimum expense. The rest of the players rationally react to the subsidies proposed by the MPC and play Nash equilibrium. We show that such a case of conflict between safety and security, and social cooperation, belongs to the 'coordination with assurance' class of games, and we explore the role of cluster governance (fulfilled by the MPC) in achieving a full cooperative outcome in domino effects prevention negotiations. The paper proposes an algorithm that can be used by the MPC to develop the subsidy system. Furthermore, a stepwise plan to improve cross-company safety and security management in a chemical industrial cluster is suggested and an illustrative example is provided. Copyright © 2010 Elsevier B.V. All rights reserved.

Self-catalyzed growth of S layers via an amorphous-to-crystalline transition limited by folding kinetics.

PubMed

Chung, Sungwook; Shin, Seong-Ho; Bertozzi, Carolyn R; De Yoreo, James J

2010-09-21

The importance of nonclassical, multistage crystallization pathways is increasingly evident from theoretical studies on colloidal systems and experimental investigations of proteins and biomineral phases. Although theoretical predictions suggest that proteins follow these pathways as a result of fluctuations that create unstable dense-liquid states, microscopic studies indicate these states are long-lived. Using in situ atomic force microscopy to follow 2D assembly of S-layer proteins on supported lipid bilayers, we have obtained a molecular-scale picture of multistage protein crystallization that reveals the importance of conformational transformations in directing the pathway of assembly. We find that monomers with an extended conformation first form a mobile adsorbed phase, from which they condense into amorphous clusters. These clusters undergo a phase transition through S-layer folding into crystalline clusters composed of compact tetramers. Growth then proceeds by formation of new tetramers exclusively at cluster edges, implying tetramer formation is autocatalytic. Analysis of the growth kinetics leads to a quantitative model in which tetramer creation is rate limiting. However, the estimated barrier is much smaller than expected for folding of isolated S-layer proteins, suggesting an energetic rationale for this multistage pathway.

The peculiar velocities of rich clusters in the hot and cold dark matter scenarios

NASA Technical Reports Server (NTRS)

Rhee, George F.; West, Michael J.; Villumsen, Jens V.

1993-01-01

We present the results of a study of the peculiar velocities of rich clusters of galaxies. The peculiar motion of rich clusters in various cosmological scenarios is of interest for a number of reasons. Observationally, one can measure the peculiar motion of clusters to greater distances than galaxies because cluster peculiar motions can be determined to greater accuracy. One can also test the slope of distance indicator relations using clusters to see if galaxy properties vary with environment. We have used N-body simulations to measure the amplitude and rms cluster peculiar velocity as a function of bias parameter in the hot and cold dark matter scenarios. In addition to measuring the mean and rms peculiar velocity of clusters in the two models, we determined whether the peculiar velocity vector of a given cluster is well aligned with the gravity vector due to all the particles in the simulation and the gravity vector due to the particles present only in the clusters. We have investigated the peculiar velocities of rich clusters of galaxies in the cold dark matter and hot dark matter galaxy formation scenarios. We have derived peculiar velocities and associated errors for the scenarios using four values of the bias parameter ranging from b = 1 to b = 2.5. The growth of the mean peculiar velocity with scale factor has been determined and compared to that predicted by linear theory. In addition, we have compared the orientation of force and velocity in these simulations to see if a program such as that proposed by Bertschinger and Dekel (1989) for elliptical galaxy peculiar motions can be applied to clusters. The method they describe enables one to recover the density field from large scale redshift distance samples. The method makes it possible to do this when only radial velocities are known by assuming that the velocity field is curl free. Our analysis suggests that this program if applied to clusters is only realizable for models with a low value of the bias parameter, i.e., models in which the peculiar velocities of clusters are large enough that the errors do not render the analysis impracticable.

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

Towards a comprehensive knowledge of the open cluster Haffner 9

NASA Astrophysics Data System (ADS)

Piatti, Andrés E.

2017-03-01

We turn our attention to Haffner 9, a Milky Way open cluster whose previous fundamental parameter estimates are far from being in agreement. In order to provide with accurate estimates, we present high-quality Washington CT1 and Johnson BVI photometry of the cluster field. We put particular care in statistically cleaning the colour-magnitude diagrams (CMDs) from field star contamination, which was found a common source in previous works for the discordant fundamental parameter estimates. The resulting cluster CMD fiducial features were confirmed from a proper motion membership analysis. Haffner 9 is a moderately young object (age ∼350 Myr), placed in the Perseus arm - at a heliocentric distance of ∼3.2 kpc - , with a lower limit for its present mass of ∼160 M⊙ and of nearly metal solar content. The combination of the cluster structural and fundamental parameters suggest that it is in an advanced stage of internal dynamical evolution, possibly in the phase typical of those with mass segregation in their core regions. However, the cluster still keeps its mass function close to that of the Salpeter's law.

Analysis of Spectral-type A/B Stars in Five Open Clusters

NASA Astrophysics Data System (ADS)

Wilhelm, Ronald J.; Rafuil Islam, M.

2014-01-01

We have obtained low resolution (R = 1000) spectroscopy of N=68, spectral-type A/B stars in five nearby open star clusters using the McDonald Observatory, 2.1m telescope. The sample of blue stars in various clusters were selected to test our new technique for determining interstellar reddening and distances in areas where interstellar reddening is high. We use a Bayesian approach to find the posterior distribution for Teff, Logg and [Fe/H] from a combination of reddened, photometric colors and spectroscopic line strengths. We will present calibration results for this technique using open cluster star data with known reddening and distances. Preliminary results suggest our technique can produce both reddening and distance determinations to within 10% of cluster values. Our technique opens the possibility of determining distances for blue stars at low Galactic latitudes where extinction can be large and differential. We will also compare our stellar parameter determinations to previously reported MK spectral classifications and discuss the probability that some of our stars are not members of their reported clusters.

Analyzing ZnO clusters through the density-functional theory.

PubMed

Zaragoza, Irineo-Pedro; Soriano-Agueda, Luis-Antonio; Hernández-Esparza, Raymundo; Vargas, Rubicelia; Garza, Jorge

2018-06-16

The potential energy surface of Zn n O n clusters (n = 2, 4, 6, 8) has been explored by using a simulated annealing method. For n = 2, 4, and 6, the CCSD(T)/TZP method was used as the reference, and from here it is shown that the M06-2X/TZP method gives the lowest deviations over PBE, PBE0, B3LYP, M06, and MP2 methods. Thus, with the M06-2X method we predict isomers of Zn n O n clusters, which coincide with some isomers reported previously. By using the atoms in molecules analysis, possible contacts between Zn and O atoms were found for all structures studied in this article. The bond paths involved in several clusters suggest that Zn n O n clusters can be obtained from the zincite (ZnO crystal), such an observation was confirmed for clusters with n = 2 - 9,18 and 20. The structure with n = 23 was obtained by the procedure presented here, from crystal information, which could be important to confirm experimental data delivered for n = 18 and 23.

Efficient generation of low-energy folded states of a model protein

NASA Astrophysics Data System (ADS)

Gordon, Heather L.; Kwan, Wai Kei; Gong, Chunhang; Larrass, Stefan; Rothstein, Stuart M.

2003-01-01

A number of short simulated annealing runs are performed on a highly-frustrated 46-"residue" off-lattice model protein. We perform, in an iterative fashion, a principal component analysis of the 946 nonbonded interbead distances, followed by two varieties of cluster analyses: hierarchical and k-means clustering. We identify several distinct sets of conformations with reasonably consistent cluster membership. Nonbonded distance constraints are derived for each cluster and are employed within a distance geometry approach to generate many new conformations, previously unidentified by the simulated annealing experiments. Subsequent analyses suggest that these new conformations are members of the parent clusters from which they were generated. Furthermore, several novel, previously unobserved structures with low energy were uncovered, augmenting the ensemble of simulated annealing results, and providing a complete distribution of low-energy states. The computational cost of this approach to generating low-energy conformations is small when compared to the expense of further Monte Carlo simulated annealing runs.

Determining the Ages and Distances of 4 Open Clusters

NASA Astrophysics Data System (ADS)

Sawczynec, Erica A.; James D. Armstrong, Joe M. Ritter, Jeff Kuhn

2018-01-01

The study of nearby young open clusters can give insight into star formation and potentially the local rate of metal enrichment. Presented is a BVRI photometric analysis of 4 open clusters; NGC 2509, NGC 2483, NGC 2482, and NGC 6705, in order to reevaluate previously published ages and distances using modern CCD photometry, and newer stellar models. Observations were obtained from the Cerro Tololo node of the Las Cumbres Observatory 1.0 meter network. Color magnitude diagrams were compared to modeled isochrones and the updated ages and distances determined. An interesting stellar association was found in the color magnitude diagram of NGC 6705. The structure is suggestive of two epochs of stellar formation. Members of this structure were evaluated using the Gaia Archive in order to explore the possibility of a heterogeneous population. The status of NGC 2483 as an open cluster has been debated; however, it has been noted that there is a high concentration of Be stars found in the region. It is concluded that NGC 2483 is an open cluster.

Large clusters of co-expressed genes in the Drosophila genome.

PubMed

Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

Genetic diversity and variation of Chinese fir from Fujian province and Taiwan, China, based on ISSR markers

PubMed Central

Chen, Yu; Peng, Zhuqing; Wu, Chao; Ma, Zhihui; Ding, Guochang; Cao, Guangqiu; Ruan, Shaoning; Lin, Sizu

2017-01-01

Genetic diversity and variation among 11 populations of Chinese fir from Fujian province and Taiwan were assessed using inter-simple sequence repeat (ISSR) markers to reveal the evolutionary relationship in their distribution range in this report. Analysis of genetic parameters of the different populations showed that populations in Fujian province exhibited a greater level of genetic diversity than did the populations in Taiwan. Compared to Taiwan populations, significant limited gene flow were observed among Fujian populations. An UPGMA cluster analysis showed that the most individuals of Taiwan populations formed a single cluster, whereas 6 discrete clusters were formed by each population from Fujian. All populations were divided into 3 main groups and that all 5 populations from Taiwan were gathered into a subgroup combined with 2 populations, Dehua and Liancheng, formed one of the 3 main groups, which indicated relative stronger relatedness. It is supported by a genetic structure analysis. All those results are suggesting different levels of genetic diversity and variation of Chinese fir between Fujian and Taiwan, and indicating different patterns of evolutionary process and local environmental adaption. PMID:28406956

Genetic diversity and variation of Chinese fir from Fujian province and Taiwan, China, based on ISSR markers.

PubMed

Chen, Yu; Peng, Zhuqing; Wu, Chao; Ma, Zhihui; Ding, Guochang; Cao, Guangqiu; Ruan, Shaoning; Lin, Sizu

2017-01-01

Genetic diversity and variation among 11 populations of Chinese fir from Fujian province and Taiwan were assessed using inter-simple sequence repeat (ISSR) markers to reveal the evolutionary relationship in their distribution range in this report. Analysis of genetic parameters of the different populations showed that populations in Fujian province exhibited a greater level of genetic diversity than did the populations in Taiwan. Compared to Taiwan populations, significant limited gene flow were observed among Fujian populations. An UPGMA cluster analysis showed that the most individuals of Taiwan populations formed a single cluster, whereas 6 discrete clusters were formed by each population from Fujian. All populations were divided into 3 main groups and that all 5 populations from Taiwan were gathered into a subgroup combined with 2 populations, Dehua and Liancheng, formed one of the 3 main groups, which indicated relative stronger relatedness. It is supported by a genetic structure analysis. All those results are suggesting different levels of genetic diversity and variation of Chinese fir between Fujian and Taiwan, and indicating different patterns of evolutionary process and local environmental adaption.

Molecular analysis of hepatitis A virus strains obtained from patients with acute hepatitis A in Mongolia, 2004-2013.

PubMed

Tsatsralt-Od, Bira; Baasanjav, Nachin; Nyamkhuu, Dulmaa; Ohnishi, Hiroshi; Takahashi, Masaharu; Kobayashi, Tominari; Nagashima, Shigeo; Nishizawa, Tsutomu; Okamoto, Hiroaki

2016-04-01

Despite the high endemicity of hepatitis A virus (HAV) in Mongolia, the genetic information on those HAV strains is limited. Serum samples obtained from 935 patients with acute hepatitis in Ulaanbaatar, Mongolia during 2004-2013 were tested for the presence of HAV RNA using reverse transcription-PCR with primers targeting the VP1-2B region (481 nucleotides, primer sequences at both ends excluded). Overall, 180 patients (19.3%) had detectable HAV RNA. These 180 isolates shared 94.6-100% identity and formed four phylogenetic clusters within subgenotype IA. One or three representative HAV isolates from each cluster exhibited 2.6-3.9% difference between clusters over the entire genome. Cluster 1 accounted for 65.0% of the total, followed by Cluster 2 (30.6%), Cluster 3 (3.3%), and Cluster 4 (1.1%). Clusters 1 and 2 were predominant throughout the observation period, whereas Cluster 3 was undetectable in 2009 and 2013 and Cluster 4 became undetectable after 2009. The Mongolian HAV isolates were closest to those of Chinese or Japanese origin (97.7-98.5% identities over the entire genome), suggesting the evolution from a common ancestor with those circulating in China and Japan. Further molecular epidemiological analyses of HAV infection are necessary to investigate the factors underlying the spread of HAV and to implement appropriate prevention measures in Mongolia. © 2015 Wiley Periodicals, Inc.

Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods.

PubMed

Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

2016-01-01

Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community.

Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods

PubMed Central

Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

2016-01-01

Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community. PMID:27124610

Sample size calculations for the design of cluster randomized trials: A summary of methodology.

PubMed

Gao, Fei; Earnest, Arul; Matchar, David B; Campbell, Michael J; Machin, David

2015-05-01

Cluster randomized trial designs are growing in popularity in, for example, cardiovascular medicine research and other clinical areas and parallel statistical developments concerned with the design and analysis of these trials have been stimulated. Nevertheless, reviews suggest that design issues associated with cluster randomized trials are often poorly appreciated and there remain inadequacies in, for example, describing how the trial size is determined and the associated results are presented. In this paper, our aim is to provide pragmatic guidance for researchers on the methods of calculating sample sizes. We focus attention on designs with the primary purpose of comparing two interventions with respect to continuous, binary, ordered categorical, incidence rate and time-to-event outcome variables. Issues of aggregate and non-aggregate cluster trials, adjustment for variation in cluster size and the effect size are detailed. The problem of establishing the anticipated magnitude of between- and within-cluster variation to enable planning values of the intra-cluster correlation coefficient and the coefficient of variation are also described. Illustrative examples of calculations of trial sizes for each endpoint type are included. Copyright © 2015 Elsevier Inc. All rights reserved.

Supra-galactic colour patterns in globular cluster systems

NASA Astrophysics Data System (ADS)

Forte, Juan C.

2017-07-01

An analysis of globular cluster systems associated with galaxies included in the Virgo and Fornax Hubble Space Telescope-Advanced Camera Surveys reveals distinct (g - z) colour modulation patterns. These features appear on composite samples of globular clusters and, most evidently, in galaxies with absolute magnitudes Mg in the range from -20.2 to -19.2. These colour modulations are also detectable on some samples of globular clusters in the central galaxies NGC 1399 and NGC 4486 (and confirmed on data sets obtained with different instruments and photometric systems), as well as in other bright galaxies in these clusters. After discarding field contamination, photometric errors and statistical effects, we conclude that these supra-galactic colour patterns are real and reflect some previously unknown characteristic. These features suggest that the globular cluster formation process was not entirely stochastic but included a fraction of clusters that formed in a rather synchronized fashion over large spatial scales, and in a tentative time lapse of about 1.5 Gy at redshifts z between 2 and 4. We speculate that the putative mechanism leading to that synchronism may be associated with large scale feedback effects connected with violent star-forming events and/or with supermassive black holes.

Whole-Genome Sequencing Analysis of Salmonella enterica Serovar Enteritidis Isolates in Chile Provides Insights into Possible Transmission between Gulls, Poultry, and Humans.

PubMed

Toro, Magaly; Retamal, Patricio; Ayers, Sherry; Barreto, Marlen; Allard, Marc; Brown, Eric W; Gonzalez-Escalona, Narjol

2016-10-15

Salmonella enterica subsp. enterica serotype Enteritidis is a major cause of human salmonellosis worldwide; however, little is known about the genetic relationships between S Enteritidis clinical strains and S Enteritidis strains from other sources in Chile. We compared the whole genomes of 30 S Enteritidis strains isolated from gulls, domestic chicken eggs, and humans in Chile, to investigate their phylogenetic relationships and to establish their relatedness to international strains. Core genome multilocus sequence typing (cgMLST) analysis showed that only 246/4,065 shared loci differed among these Chilean strains, separating them into two clusters (I and II), with cluster II being further divided into five subclusters. One subcluster (subcluster 2) contained strains from all surveyed sources that differed at 1 to 18 loci (of 4,065 loci) with 1 to 18 single-nucleotide polymorphisms (SNPs), suggesting interspecies transmission of S Enteritidis in Chile. Moreover, clusters were formed by strains that were distant geographically, which could imply that gulls might be spreading the pathogen throughout the country. Our cgMLST analysis, using other S Enteritidis genomes available in the National Center for Biotechnology Information (NCBI) database, showed that S Enteritidis strains from Chile and the United States belonged to different lineages, which suggests that S Enteritidis regional markers might exist and could be used for trace-back investigations. This study highlights the importance of gulls in the spread of Salmonella Enteritidis in Chile. We revealed a close genetic relationship between some human and gull S Enteritidis strains (with as few as 2 of 4,065 genes being different), and we also found that gull strains were present in clusters formed by strains isolated from other sources or distant locations. Together with previously published evidence, this suggests that gulls might be spreading this pathogen between different regions in Chile and that some of those strains have been transmitted to humans. Moreover, we discovered that Chilean S Enteritidis strains clustered separately from most of S Enteritidis strains isolated throughout the world (in the GenBank database) and thus it might be possible to distinguish the geographical origins of strains based on specific genomic features. This could be useful for trace-back investigations of foodborne illnesses throughout the world. Copyright © 2016 Toro et al.

Whole-Genome Sequencing Analysis of Salmonella enterica Serovar Enteritidis Isolates in Chile Provides Insights into Possible Transmission between Gulls, Poultry, and Humans

PubMed Central

Ayers, Sherry; Barreto, Marlen; Allard, Marc; Brown, Eric W.

2016-01-01

ABSTRACT Salmonella enterica subsp. enterica serotype Enteritidis is a major cause of human salmonellosis worldwide; however, little is known about the genetic relationships between S. Enteritidis clinical strains and S. Enteritidis strains from other sources in Chile. We compared the whole genomes of 30 S. Enteritidis strains isolated from gulls, domestic chicken eggs, and humans in Chile, to investigate their phylogenetic relationships and to establish their relatedness to international strains. Core genome multilocus sequence typing (cgMLST) analysis showed that only 246/4,065 shared loci differed among these Chilean strains, separating them into two clusters (I and II), with cluster II being further divided into five subclusters. One subcluster (subcluster 2) contained strains from all surveyed sources that differed at 1 to 18 loci (of 4,065 loci) with 1 to 18 single-nucleotide polymorphisms (SNPs), suggesting interspecies transmission of S. Enteritidis in Chile. Moreover, clusters were formed by strains that were distant geographically, which could imply that gulls might be spreading the pathogen throughout the country. Our cgMLST analysis, using other S. Enteritidis genomes available in the National Center for Biotechnology Information (NCBI) database, showed that S. Enteritidis strains from Chile and the United States belonged to different lineages, which suggests that S. Enteritidis regional markers might exist and could be used for trace-back investigations. IMPORTANCE This study highlights the importance of gulls in the spread of Salmonella Enteritidis in Chile. We revealed a close genetic relationship between some human and gull S. Enteritidis strains (with as few as 2 of 4,065 genes being different), and we also found that gull strains were present in clusters formed by strains isolated from other sources or distant locations. Together with previously published evidence, this suggests that gulls might be spreading this pathogen between different regions in Chile and that some of those strains have been transmitted to humans. Moreover, we discovered that Chilean S. Enteritidis strains clustered separately from most of S. Enteritidis strains isolated throughout the world (in the GenBank database) and thus it might be possible to distinguish the geographical origins of strains based on specific genomic features. This could be useful for trace-back investigations of foodborne illnesses throughout the world. PMID:27520817

Symptoms and subjective quality of life in post-traumatic stress disorder: a longitudinal study.

PubMed

Giacco, Domenico; Matanov, Aleksandra; Priebe, Stefan

2013-01-01

Evidence suggests that post-traumatic stress disorder (PTSD) is associated with substantially reduced subjective quality of life (SQOL). This study aimed to explore whether and how changes in the levels of PTSD symptom clusters of intrusion, avoidance and hyperarousal are associated with changes in SQOL. Two samples with PTSD following the war in former Yugoslavia were studied, i.e. a representative sample of 530 people in five Balkan countries and a non-representative sample of 215 refugees in three Western European countries. They were assessed on average eight years after the war and re-interviewed one year later. PTSD symptoms were assessed on the Impact of Event Scale - Revised and SQOL on the Manchester Short Assessment of Quality of Life. Linear regression and a two-wave cross lagged panel analysis were used to explore the association between PTSD symptom clusters and SQOL. The findings in the two samples were consistent. Symptom reduction over time was associated with improved SQOL. In multivariable analyses adjusted for the influence of all three clusters, gender and time since war exposure, only changes in hyperarousal symptoms were significantly associated with changes in SQOL. The two-wave cross-lagged panel analysis suggested that the link between hyperarousal symptoms and SQOL is bidirectional. Low SQOL of patients with war-related PTSD is particularly associated with hyperarousal symptoms. The findings suggest a bidirectional influence: a reduction in hyperarousal symptoms may result in improved SQOL, and improvements in SQOL may lead to reduced hyperarousal symptoms.

Tissue-specific promoter utilisation of the kallikrein-related peptidase genes, KLK5 and KLK7, and cellular localisation of the encoded proteins suggest roles in exocrine pancreatic function.

PubMed

Dong, Ying; Matigian, Nick; Harvey, Tracey J; Samaratunga, Hemamali; Hooper, John D; Clements, Judith A

2008-02-01

Abstract Tissue kallikrein (kallikrein 1) was first identified in pancreas and is the namesake of the kallikrein-related peptidase (KLK) family. KLK1 and the other 14 members of the human KLK family are encoded by 15 serine protease genes clustered at chromosome 19q13.4. Our Northern blot analysis of 19 normal human tissues for expression of KLK4 to KLK15 identified pancreas as a common expression site for the gene cluster spanning KLK5 to KLK13, as well as for KLK15 which is located adjacent to KLK1. Consistent with previous reports detailing the ability of KLK genes to generate organ- and disease-specific transcripts, detailed molecular and in silico analyses indicated that KLK5 and KLK7 generate transcripts in pancreas variant from those in skin or ovary. Consistently, we identified in the promoters of these KLK genes motifs which conform with consensus binding sites for transcription factors conferring pancreatic expression. In addition, immunohistochemical analysis revealed predominant localisation of KLK5 and KLK7 in acinar cells of the exocrine pancreas, suggesting roles for these enzymes in digestion. Our data also support expression patterns derived from gene duplication events in the human KLK cluster. These findings suggest that, in addition to KLK1, other related KLK enzymes will function in the exocrine pancreas.

Asian Students' Conceptions of Future Civic Engagement: Comparing Clusters Using Person-Centered Analysis

ERIC Educational Resources Information Center

Chow, Joseph Kui Foon; Kennedy, Kerry J.

2015-01-01

Researchers in comparative education have suggested different ways in which their field of study can be enhanced by considering units of analysis at different levels rather than focusing on a single level such as the nation-state (Bray and Thomas, 1995; Torney-Purta and Barber, 2011). The study reported here seeks to contribute to this area of…

Kinetics of Forming Aldehydes in Frying Oils and Their Distribution in French Fries Revealed by LC-MS-Based Chemometrics.

PubMed

Wang, Lei; Csallany, A Saari; Kerr, Brian J; Shurson, Gerald C; Chen, Chi

2016-05-18

In this study, the kinetics of aldehyde formation in heated frying oils was characterized by 2-hydrazinoquinoline derivatization, liquid chromatography-mass spectrometry (LC-MS) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA). The aldehydes contributing to time-dependent separation of heated soybean oil (HSO) in a PCA model were grouped by the HCA into three clusters (A1, A2, and B) on the basis of their kinetics and fatty acid precursors. The increases of 4-hydroxynonenal (4-HNE) and the A2-to-B ratio in HSO were well-correlated with the duration of thermal stress. Chemometric and quantitative analysis of three frying oils (soybean, corn, and canola oils) and French fry extracts further supported the associations between aldehyde profiles and fatty acid precursors and also revealed that the concentrations of pentanal, hexanal, acrolein, and the A2-to-B ratio in French fry extracts were more comparable to their values in the frying oils than other unsaturated aldehydes. All of these results suggest the roles of specific aldehydes or aldehyde clusters as novel markers of the lipid oxidation status for frying oils or fried foods.

Zonation in the deep benthic megafauna : Application of a general test.

PubMed

Gardiner, Frederick P; Haedrich, Richard L

1978-01-01

A test based on Maxwell-Boltzman statistics, instead of the formerly suggested but inappropriate Bose-Einstein statistics (Pielou and Routledge, 1976), examines the distribution of the boundaries of species' ranges distributed along a gradient, and indicates whether they are random or clustered (zoned). The test is most useful as a preliminary to the application of more instructive but less statistically rigorous methods such as cluster analysis. The test indicates zonation is marked in the deep benthic megafauna living between 200 and 3000 m, but below 3000 m little zonation may be found.

A relational structure of voluntary visual-attention abilities

PubMed Central

Skogsberg, KatieAnn; Grabowecky, Marcia; Wilt, Joshua; Revelle, William; Iordanescu, Lucica; Suzuki, Satoru

2015-01-01

Many studies have examined attention mechanisms involved in specific behavioral tasks (e.g., search, tracking, distractor inhibition). However, relatively little is known about the relationships among those attention mechanisms. Is there a fundamental attention faculty that makes a person superior or inferior at most types of attention tasks, or do relatively independent processes mediate different attention skills? We focused on individual differences in voluntary visual-attention abilities using a battery of eleven representative tasks. An application of parallel analysis, hierarchical-cluster analysis, and multidimensional scaling to the inter-task correlation matrix revealed four functional clusters, representing spatiotemporal attention, global attention, transient attention, and sustained attention, organized along two dimensions, one contrasting spatiotemporal and global attention and the other contrasting transient and sustained attention. Comparison with the neuroscience literature suggests that the spatiotemporal-global dimension corresponds to the dorsal frontoparietal circuit and the transient-sustained dimension corresponds to the ventral frontoparietal circuit, with distinct sub-regions mediating the separate clusters within each dimension. We also obtained highly specific patterns of gender difference, and of deficits for college students with elevated ADHD traits. These group differences suggest that different mechanisms of voluntary visual attention can be selectively strengthened or weakened based on genetic, experiential, and/or pathological factors. PMID:25867505

Prokaryotic diversity, distribution, and insights into their role in biogeochemical cycling in marine basalts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mason, Olivia U.; Di Meo-Savoie, Carol A.; Van Nostrand, Joy D.

2008-09-30

We used molecular techniques to analyze basalts of varying ages that were collected from the East Pacific Rise, 9 oN, from the rift axis of the Juan de Fuca Ridge, and from neighboring seamounts. Cluster analysis of 16S rDNA Terminal Restriction Fragment Polymorphism data revealed that basalt endoliths are distinct from seawater and that communities clustered, to some degree, based on the age of the host rock. This age-based clustering suggests that alteration processes may affect community structure. Cloning and sequencing of bacterial and archaeal 16S rRNA genes revealed twelve different phyla and sub-phyla associated with basalts. These include themore » Gemmatimonadetes, Nitrospirae, the candidate phylum SBR1093 in the c, andin the Archaea Marine Benthic Group B, none of which have been previously reported in basalts. We delineated novel ocean crust clades in the gamma-Proteobacteria, Planctomycetes, and Actinobacteria that are composed entirely of basalt associated microflora, and may represent basalt ecotypes. Finally, microarray analysis of functional genes in basalt revealed that genes coding for previously unreported processes such as carbon fixation, methane-oxidation, methanogenesis, and nitrogen fixation are present, suggesting that basalts harbor previously unrecognized metabolic diversity. These novel processes could exert a profound influence on ocean chemistry.« less

[Perception of odor quality by Free Image-Association Test].

PubMed

Ueno, Y

1992-10-01

A method was devised for evaluating odor quality. Subjects were requested to freely describe the images elicited by smelling odors. This test was named the "Free Image-Association Test (FIT)". The test was applied for 20 flavors of various foods, five odors from the standards of T&T olfactometer (Japanese standard olfactory test), butter of yak milk, and incense from Lamaism temples. The words for expressing imagery were analyzed by multidimensional scaling and cluster analysis. Seven clusters of odors were obtained. The feature of these clusters were quite similar to that of primary odors which have been suggested by previous studies. However, the clustering of odors can not be explained on the basis of the primary-odor theory, but the information processing theory originally proposed by Miller (1956). These results support the usefulness of the Free Image-Association Test for investigating odor perception based on the images associated with odors.

On the X-ray spectrum of the volume emissivity arising from Abell clusters

NASA Technical Reports Server (NTRS)

Stottlemyer, A. R.; Boldt, E. A.

1984-01-01

HEAO 1 A-2 X-ray spectra (2-15 keV) for an optically selected sample of Abell clusters of galaxies with z less than 0.1 have been analyzed to determine the energy dependence of the cosmological X-ray volume emissivity arising from such clusters. This spectrum is well fitted by an isothermal-bremsstrahlung model with kT = 7.4 + or - 1.5 KeV. This result is a test of the isothermal-volume-emissivity spectrum to be inferred from the conjecture that all contributing clusters may be characterized by kT = 7 keV, as assumed by McKee et al. (1980) in estimating the underlying luminosity function for the same sample. Although satisfied at the statistical level indicated, the analysis of a low-luminosity subsample suggests that this assumption of identical isothermal spectra would lead to a systematic error for a more statistically precise determination of the luminosity function's form.

REMOVING COOL CORES AND CENTRAL METALLICITY PEAKS IN GALAXY CLUSTERS WITH POWERFUL ACTIVE GALACTIC NUCLEUS OUTBURSTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo Fulai; Mathews, William G., E-mail: fulai@ucolick.or

2010-07-10

Recent X-ray observations of galaxy clusters suggest that cluster populations are bimodally distributed according to central gas entropy and are separated into two distinct classes: cool core (CC) and non-cool core (NCC) clusters. While it is widely accepted that active galactic nucleus (AGN) feedback plays a key role in offsetting radiative losses and maintaining many clusters in the CC state, the origin of NCC clusters is much less clear. At the same time, a handful of extremely powerful AGN outbursts have recently been detected in clusters, with a total energy {approx}10{sup 61}-10{sup 62} erg. Using two-dimensional hydrodynamic simulations, we showmore » that if a large fraction of this energy is deposited near the centers of CC clusters, which is likely common due to dense cores, these AGN outbursts can completely remove CCs, transforming them to NCC clusters. Our model also has interesting implications for cluster abundance profiles, which usually show a central peak in CC systems. Our calculations indicate that during the CC to NCC transformation, AGN outbursts efficiently mix metals in cluster central regions and may even remove central abundance peaks if they are not broad enough. For CC clusters with broad central abundance peaks, AGN outbursts decrease peak abundances, but cannot effectively destroy the peaks. Our model may simultaneously explain the contradictory (possibly bimodal) results of abundance profiles in NCC clusters, some of which are nearly flat, while others have strong central peaks similar to those in CC clusters. A statistical analysis of the sizes of central abundance peaks and their redshift evolution may shed interesting insights on the origin of both types of NCC clusters and the evolution history of thermodynamics and AGN activity in clusters.« less

THE SWIFT AGN AND CLUSTER SURVEY. II. CLUSTER CONFIRMATION WITH SDSS DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Griffin, Rhiannon D.; Dai, Xinyu; Kochanek, Christopher S.

2016-01-15

We study 203 (of 442) Swift AGN and Cluster Survey extended X-ray sources located in the SDSS DR8 footprint to search for galaxy over-densities in three-dimensional space using SDSS galaxy photometric redshifts and positions near the Swift cluster candidates. We find 104 Swift clusters with a >3σ galaxy over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmation as galaxy clusters. We present a series of cluster properties including the redshift, brightest cluster galaxy (BCG) magnitude, BCG-to-X-ray center offset, optical richness, and X-ray luminosity. We also detect red sequences in ∼85% ofmore » the 104 confirmed clusters. The X-ray luminosity and optical richness for the SDSS confirmed Swift clusters are correlated and follow previously established relations. The distribution of the separations between the X-ray centroids and the most likely BCG is also consistent with expectation. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≲ 0.3 and is still 80% complete up to z ≃ 0.4, consistent with the SDSS survey depth. These analysis results suggest that our Swift cluster selection algorithm has yielded a statistically well-defined cluster sample for further study of cluster evolution and cosmology. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 23, and 1 matches in optical, X-ray, and Sunyaev–Zel’dovich catalogs, respectively, and so the majority of these clusters are new detections.« less

Novel genomic island modifies DNA with 7-deazaguanine derivatives

PubMed Central

Thiaville, Jennifer J.; Kellner, Stefanie M.; Yuan, Yifeng; Hutinet, Geoffrey; Thiaville, Patrick C.; Jumpathong, Watthanachai; Mohapatra, Susovan; Brochier-Armanet, Celine; Letarov, Andrey V.; Hillebrand, Roman; Malik, Chanchal K.; Rizzo, Carmelo J.; Dedon, Peter C.; de Crécy-Lagard, Valérie

2016-01-01

The discovery of ∼20-kb gene clusters containing a family of paralogs of tRNA guanosine transglycosylase genes, called tgtA5, alongside 7-cyano-7-deazaguanine (preQ0) synthesis and DNA metabolism genes, led to the hypothesis that 7-deazaguanine derivatives are inserted in DNA. This was established by detecting 2’-deoxy-preQ0 and 2’-deoxy-7-amido-7-deazaguanosine in enzymatic hydrolysates of DNA extracted from the pathogenic, Gram-negative bacteria Salmonella enterica serovar Montevideo. These modifications were absent in the closely related S. enterica serovar Typhimurium LT2 and from a mutant of S. Montevideo, each lacking the gene cluster. This led us to rename the genes of the S. Montevideo cluster as dpdA-K for 7-deazapurine in DNA. Similar gene clusters were analyzed in ∼150 phylogenetically diverse bacteria, and the modifications were detected in DNA from other organisms containing these clusters, including Kineococcus radiotolerans, Comamonas testosteroni, and Sphingopyxis alaskensis. Comparative genomic analysis shows that, in Enterobacteriaceae, the cluster is a genomic island integrated at the leuX locus, and the phylogenetic analysis of the TgtA5 family is consistent with widespread horizontal gene transfer. Comparison of transformation efficiencies of modified or unmodified plasmids into isogenic S. Montevideo strains containing or lacking the cluster strongly suggests a restriction–modification role for the cluster in Enterobacteriaceae. Another preQ0 derivative, 2’-deoxy-7-formamidino-7-deazaguanosine, was found in the Escherichia coli bacteriophage 9g, as predicted from the presence of homologs of genes involved in the synthesis of the archaeosine tRNA modification. These results illustrate a deep and unexpected evolutionary connection between DNA and tRNA metabolism. PMID:26929322

Characterization of HIV Transmission in South-East Austria

PubMed Central

Kessler, Harald H.; Haas, Bernhard; Stelzl, Evelyn; Weninger, Karin; Little, Susan J.; Mehta, Sanjay R.

2016-01-01

To gain deeper insight into the epidemiology of HIV-1 transmission in South-East Austria we performed a retrospective analysis of 259 HIV-1 partial pol sequences obtained from unique individuals newly diagnosed with HIV infection in South-East Austria from 2008 through 2014. After quality filtering, putative transmission linkages were inferred when two sequences were ≤1.5% genetically different. Multiple linkages were resolved into putative transmission clusters. Further phylogenetic analyses were performed using BEAST v1.8.1. Finally, we investigated putative links between the 259 sequences from South-East Austria and all publicly available HIV polymerase sequences in the Los Alamos National Laboratory HIV sequence database. We found that 45.6% (118/259) of the sampled sequences were genetically linked with at least one other sequence from South-East Austria forming putative transmission clusters. Clustering individuals were more likely to be men who have sex with men (MSM; p<0.001), infected with subtype B (p<0.001) or subtype F (p = 0.02). Among clustered males who reported only heterosexual (HSX) sex as an HIV risk, 47% clustered closely with MSM (either as pairs or within larger MSM clusters). One hundred and seven of the 259 sequences (41.3%) from South-East Austria had at least one putative inferred linkage with sequences from a total of 69 other countries. In conclusion, analysis of HIV-1 sequences from newly diagnosed individuals residing in South-East Austria revealed a high degree of national and international clustering mainly within MSM. Interestingly, we found that a high number of heterosexual males clustered within MSM networks, suggesting either linkage between risk groups or misrepresentation of sexual risk behaviors by subjects. PMID:26967154

Characterization of HIV Transmission in South-East Austria.

PubMed

Hoenigl, Martin; Chaillon, Antoine; Kessler, Harald H; Haas, Bernhard; Stelzl, Evelyn; Weninger, Karin; Little, Susan J; Mehta, Sanjay R

2016-01-01

To gain deeper insight into the epidemiology of HIV-1 transmission in South-East Austria we performed a retrospective analysis of 259 HIV-1 partial pol sequences obtained from unique individuals newly diagnosed with HIV infection in South-East Austria from 2008 through 2014. After quality filtering, putative transmission linkages were inferred when two sequences were ≤1.5% genetically different. Multiple linkages were resolved into putative transmission clusters. Further phylogenetic analyses were performed using BEAST v1.8.1. Finally, we investigated putative links between the 259 sequences from South-East Austria and all publicly available HIV polymerase sequences in the Los Alamos National Laboratory HIV sequence database. We found that 45.6% (118/259) of the sampled sequences were genetically linked with at least one other sequence from South-East Austria forming putative transmission clusters. Clustering individuals were more likely to be men who have sex with men (MSM; p<0.001), infected with subtype B (p<0.001) or subtype F (p = 0.02). Among clustered males who reported only heterosexual (HSX) sex as an HIV risk, 47% clustered closely with MSM (either as pairs or within larger MSM clusters). One hundred and seven of the 259 sequences (41.3%) from South-East Austria had at least one putative inferred linkage with sequences from a total of 69 other countries. In conclusion, analysis of HIV-1 sequences from newly diagnosed individuals residing in South-East Austria revealed a high degree of national and international clustering mainly within MSM. Interestingly, we found that a high number of heterosexual males clustered within MSM networks, suggesting either linkage between risk groups or misrepresentation of sexual risk behaviors by subjects.

Degree-based statistic and center persistency for brain connectivity analysis.

PubMed

Yoo, Kwangsun; Lee, Peter; Chung, Moo K; Sohn, William S; Chung, Sun Ju; Na, Duk L; Ju, Daheen; Jeong, Yong

2017-01-01

Brain connectivity analyses have been widely performed to investigate the organization and functioning of the brain, or to observe changes in neurological or psychiatric conditions. However, connectivity analysis inevitably introduces the problem of mass-univariate hypothesis testing. Although, several cluster-wise correction methods have been suggested to address this problem and shown to provide high sensitivity, these approaches fundamentally have two drawbacks: the lack of spatial specificity (localization power) and the arbitrariness of an initial cluster-forming threshold. In this study, we propose a novel method, degree-based statistic (DBS), performing cluster-wise inference. DBS is designed to overcome the above-mentioned two shortcomings. From a network perspective, a few brain regions are of critical importance and considered to play pivotal roles in network integration. Regarding this notion, DBS defines a cluster as a set of edges of which one ending node is shared. This definition enables the efficient detection of clusters and their center nodes. Furthermore, a new measure of a cluster, center persistency (CP) was introduced. The efficiency of DBS with a known "ground truth" simulation was demonstrated. Then they applied DBS to two experimental datasets and showed that DBS successfully detects the persistent clusters. In conclusion, by adopting a graph theoretical concept of degrees and borrowing the concept of persistence from algebraic topology, DBS could sensitively identify clusters with centric nodes that would play pivotal roles in an effect of interest. DBS is potentially widely applicable to variable cognitive or clinical situations and allows us to obtain statistically reliable and easily interpretable results. Hum Brain Mapp 38:165-181, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Analysis of heterogeneous water vapor uptake by metal iodide cluster ions via differential mobility analysis-mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oberreit, Derek; Fluid Measurement Technologies, Inc., Saint Paul, Minnesota 55110; Rawat, Vivek K.

The sorption of vapor molecules onto pre-existing nanometer sized clusters is of importance in understanding particle formation and growth in gas phase environments and devising gas phase separation schemes. Here, we apply a differential mobility analyzer-mass spectrometer based approach to observe directly the sorption of vapor molecules onto iodide cluster ions of the form (MI){sub x}M{sup +} (x = 1-13, M = Na, K, Rb, or Cs) in air at 300 K and with water saturation ratios in the 0.01-0.64 range. The extent of vapor sorption is quantified in measurements by the shift in collision cross section (CCS) for eachmore » ion. We find that CCS measurements are sensitive enough to detect the transient binding of several vapor molecules to clusters, which shift CCSs by only several percent. At the same time, for the highest saturation ratios examined, we observed CCS shifts of up to 45%. For x < 4, cesium, rubidium, and potassium iodide cluster ions are found to uptake water to a similar extent, while sodium iodide clusters uptake less water. For x ≥ 4, sodium iodide cluster ions uptake proportionally more water vapor than rubidium and potassium iodide cluster ions, while cesium iodide ions exhibit less uptake. Measured CCS shifts are compared to predictions based upon a Kelvin-Thomson-Raoult (KTR) model as well as a Langmuir adsorption model. We find that the Langmuir adsorption model can be fit well to measurements. Meanwhile, KTR predictions deviate from measurements, which suggests that the earliest stages of vapor uptake by nanometer scale species are not well described by the KTR model.« less

Poor Prognosis Indicated by Venous Circulating Tumor Cell Clusters in Early-Stage Lung Cancers.

PubMed

Murlidhar, Vasudha; Reddy, Rishindra M; Fouladdel, Shamileh; Zhao, Lili; Ishikawa, Martin K; Grabauskiene, Svetlana; Zhang, Zhuo; Lin, Jules; Chang, Andrew C; Carrott, Philip; Lynch, William R; Orringer, Mark B; Kumar-Sinha, Chandan; Palanisamy, Nallasivam; Beer, David G; Wicha, Max S; Ramnath, Nithya; Azizi, Ebrahim; Nagrath, Sunitha

2017-09-15

Early detection of metastasis can be aided by circulating tumor cells (CTC), which also show potential to predict early relapse. Because of the limited CTC numbers in peripheral blood in early stages, we investigated CTCs in pulmonary vein blood accessed during surgical resection of tumors. Pulmonary vein (PV) and peripheral vein (Pe) blood specimens from patients with lung cancer were drawn during the perioperative period and assessed for CTC burden using a microfluidic device. From 108 blood samples analyzed from 36 patients, PV had significantly higher number of CTCs compared with preoperative Pe ( P < 0.0001) and intraoperative Pe ( P < 0.001) blood. CTC clusters with large number of CTCs were observed in 50% of patients, with PV often revealing larger clusters. Long-term surveillance indicated that presence of clusters in preoperative Pe blood predicted a trend toward poor prognosis. Gene expression analysis by RT-qPCR revealed enrichment of p53 signaling and extracellular matrix involvement in PV and Pe samples. Ki67 expression was detected in 62.5% of PV samples and 59.2% of Pe samples, with the majority (72.7%) of patients positive for Ki67 expression in PV having single CTCs as opposed to clusters. Gene ontology analysis revealed enrichment of cell migration and immune-related pathways in CTC clusters, suggesting survival advantage of clusters in circulation. Clusters display characteristics of therapeutic resistance, indicating the aggressive nature of these cells. Thus, CTCs isolated from early stages of lung cancer are predictive of poor prognosis and can be interrogated to determine biomarkers predictive of recurrence. Cancer Res; 77(18); 5194-206. ©2017 AACR . ©2017 American Association for Cancer Research.

Characterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum.

PubMed

Van Rheenen, T E; Lewandowski, K E; Tan, E J; Ospina, L H; Ongur, D; Neill, E; Gurvich, C; Pantelis, C; Malhotra, A K; Rossell, S L; Burdick, K E

2017-07-01

Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.

Genetic k-Means Clustering Approach for Mapping Human Vulnerability to Chemical Hazards in the Industrialized City: A Case Study of Shanghai, China

PubMed Central

Shi, Weifang; Zeng, Weihua

2013-01-01

Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster. PMID:23787337

Differential global structural changes in the core particle of yeast and mouse proteasome induced by ligand binding

PubMed Central

Arciniega, Marcelino; Beck, Philipp; Lange, Oliver F.; Groll, Michael; Huber, Robert

2014-01-01

Two clusters of configurations of the main proteolytic subunit β5 were identified by principal component analysis of crystal structures of the yeast proteasome core particle (yCP). The apo-cluster encompasses unliganded species and complexes with nonpeptidic ligands, and the pep-cluster comprises complexes with peptidic ligands. The murine constitutive CP structures conform to the yeast system, with the apo-form settled in the apo-cluster and the PR-957 (a peptidic ligand) complex in the pep-cluster. In striking contrast, the murine immune CP classifies into the pep-cluster in both the apo and the PR-957–liganded species. The two clusters differ essentially by multiple small structural changes and a domain motion enabling enclosure of the peptidic ligand and formation of specific hydrogen bonds in the pep-cluster. The immune CP species is in optimal peptide binding configuration also in its apo form. This favors productive ligand binding and may help to explain the generally increased functional activity of the immunoproteasome. Molecular dynamics simulations of the representative murine species are consistent with the experimentally observed configurations. A comparison of all 28 subunits of the unliganded species with the peptidic liganded forms demonstrates a greatly enhanced plasticity of β5 and suggests specific signaling pathways to other subunits. PMID:24979800

β-globin gene cluster haplotypes in ethnic minority populations of southwest China

PubMed Central

Sun, Hao; Liu, Hongxian; Huang, Kai; Lin, Keqin; Huang, Xiaoqin; Chu, Jiayou; Ma, Shaohui; Yang, Zhaoqing

2017-01-01

The genetic diversity and relationships among ethnic minority populations of southwest China were investigated using seven polymorphic restriction enzyme sites in the β-globin gene cluster. The haplotypes of 1392 chromosomes from ten ethnic populations living in southwest China were determined. Linkage equilibrium and recombination hotspot were found between the 5′ sites and 3′ sites of the β-globin gene cluster. 5′ haplotypes 2 (+−−−), 6 (−++−+), 9 (−++++) and 3′ haplotype FW3 (−+) were the predominant haplotypes. Notably, haplotype 9 frequency was significantly high in the southwest populations, indicating their difference with other Chinese. The interpopulation differentiation of southwest Chinese minority populations is less than those in populations of northern China and other continents. Phylogenetic analysis shows that populations sharing same ethnic origin or language clustered to each other, indicating current β-globin cluster diversity in the Chinese populations reflects their ethnic origin and linguistic affiliations to a great extent. This study characterizes β-globin gene cluster haplotypes in southwest Chinese minorities for the first time, and reveals the genetic variability and affinity of these populations using β-globin cluster haplotype frequencies. The results suggest that ethnic origin plays an important role in shaping variations of the β-globin gene cluster in the southwestern ethnic populations of China. PMID:28205625

Chronic Obstructive Pulmonary Disease heterogeneity: challenges for health risk assessment, stratification and management.

PubMed

Roca, Josep; Vargas, Claudia; Cano, Isaac; Selivanov, Vitaly; Barreiro, Esther; Maier, Dieter; Falciani, Francesco; Wagner, Peter; Cascante, Marta; Garcia-Aymerich, Judith; Kalko, Susana; De Mas, Igor; Tegnér, Jesper; Escarrabill, Joan; Agustí, Alvar; Gomez-Cabrero, David

2014-11-28

Heterogeneity in clinical manifestations and disease progression in Chronic Obstructive Pulmonary Disease (COPD) lead to consequences for patient health risk assessment, stratification and management. Implicit with the classical "spill over" hypothesis is that COPD heterogeneity is driven by the pulmonary events of the disease. Alternatively, we hypothesized that COPD heterogeneities result from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering, each of them with their own dynamics. To explore the potential of a systems analysis of COPD heterogeneity focused on skeletal muscle dysfunction and on co-morbidity clustering aiming at generating predictive modeling with impact on patient management. To this end, strategies combining deterministic modeling and network medicine analyses of the Biobridge dataset were used to investigate the mechanisms of skeletal muscle dysfunction. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was performed using a large dataset (ICD9-CM data from Medicare, 13 million people). Finally, a targeted network analysis using the outcomes of the two approaches (skeletal muscle dysfunction and co-morbidity clustering) explored shared pathways between these phenomena. (1) Evidence of abnormal regulation of skeletal muscle bioenergetics and skeletal muscle remodeling showing a significant association with nitroso-redox disequilibrium was observed in COPD; (2) COPD patients presented higher risk for co-morbidity clustering than non-COPD patients increasing with ageing; and, (3) the on-going targeted network analyses suggests shared pathways between skeletal muscle dysfunction and co-morbidity clustering. The results indicate the high potential of a systems approach to address COPD heterogeneity. Significant knowledge gaps were identified that are relevant to shape strategies aiming at fostering 4P Medicine for patients with COPD.

Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

PubMed

Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

2013-01-01

Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

Hunting for origins of migraine pain: cluster analysis of spontaneous and capsaicin-induced firing in meningeal trigeminal nerve fibers

PubMed Central

Zakharov, A.; Vitale, C.; Kilinc, E.; Koroleva, K.; Fayuk, D.; Shelukhina, I.; Naumenko, N.; Skorinkin, A.; Khazipov, R.; Giniatullin, R.

2015-01-01

Trigeminal nerves in meninges are implicated in generation of nociceptive firing underlying migraine pain. However, the neurochemical mechanisms of nociceptive firing in meningeal trigeminal nerves are little understood. In this study, using suction electrode recordings from peripheral branches of the trigeminal nerve in isolated rat meninges, we analyzed spontaneous and capsaicin-induced orthodromic spiking activity. In control, biphasic single spikes with variable amplitude and shapes were observed. Application of the transient receptor potential vanilloid 1 (TRPV1) agonist capsaicin to meninges dramatically increased firing whereas the amplitudes and shapes of spikes remained essentially unchanged. This effect was antagonized by the specific TRPV1 antagonist capsazepine. Using the clustering approach, several groups of uniform spikes (clusters) were identified. The clustering approach combined with capsaicin application allowed us to detect and to distinguish “responder” (65%) from “non-responder” clusters (35%). Notably, responders fired spikes at frequencies exceeding 10 Hz, high enough to provide postsynaptic temporal summation of excitation at brainstem and spinal cord level. Almost all spikes were suppressed by tetrodotoxin (TTX) suggesting an involvement of the TTX-sensitive sodium channels in nociceptive signaling at the peripheral branches of trigeminal neurons. Our analysis also identified transient (desensitizing) and long-lasting (slowly desensitizing) responses to the continuous application of capsaicin. Thus, the persistent activation of nociceptors in capsaicin-sensitive nerve fibers shown here may be involved in trigeminal pain signaling and plasticity along with the release of migraine-related neuropeptides from TRPV1 positive neurons. Furthermore, cluster analysis could be widely used to characterize the temporal and neurochemical profiles of other pain transducers likely implicated in migraine. PMID:26283923

Structural analysis of the PSD-95 cluster by electron tomography and CEMOVIS: a proposal for the application of the genetically encoded metallothionein tag.

PubMed

Hirabayashi, Ai; Fukunaga, Yuko; Miyazawa, Atsuo

2014-06-01

Postsynaptic density-95 (PSD-95) accumulates at excitatory postsynapses and plays important roles in the clustering and anchoring of numerous proteins at the PSD. However, a detailed ultrastructural analysis of clusters exclusively consisting of PSD-95 has never been performed. Here, we employed a genetically encoded tag, three tandem repeats of metallothionein (3MT), to study the structure of PSD-95 clusters in cells by electron tomography and cryo-electron microscopy of vitreous sections. We also performed conventional transmission electron microscopy (TEM). Cultured hippocampal neurons expressing a fusion protein of PSD-95 coupled to 3MT (PDS-95-3MT) were incubated with CdCl2 to result in the formation of Cd-bound PSD-95-3MT. Two types of electron-dense deposits composed of Cd-bound PSD-95-3MT were observed in these cells by TEM, as reported previously. Electron tomography revealed the presence of membrane-shaped structures representing PSD-95 clusters at the PSD and an ellipsoidal structure located in the non-synaptic cytoplasm. By TEM, the PSD-95 clusters appeared to be composed of a number of dense cores. In frozen hydrated sections, these dense cores were also found beneath the postsynaptic membrane. Taken together, our findings suggest that dense cores of PSD-95 aggregate to form the larger clusters present in the PSD and the non-synaptic cytoplasm. © The Author 2014. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Women Prisoners' Mental Health: Vulnerabilities, Risks and Resilience.

ERIC Educational Resources Information Center

Martin, Margaret E.; Hesselbrock, Michie N.

2001-01-01

Studies 49 incarcerated women to examine the complex relationship among women's criminal history, victimization, relational supports, personal strengths and their mental health. A cluster analysis produced four typologies shaping recommendations for assessment and treatment. Findings suggest that women with the greatest mental health needs have…

Igs expressed by chronic lymphocytic leukemia B cells show limited binding-site structure variability.

PubMed

Marcatili, Paolo; Ghiotto, Fabio; Tenca, Claudya; Chailyan, Anna; Mazzarello, Andrea N; Yan, Xiao-Jie; Colombo, Monica; Albesiano, Emilia; Bagnara, Davide; Cutrona, Giovanna; Morabito, Fortunato; Bruno, Silvia; Ferrarini, Manlio; Chiorazzi, Nicholas; Tramontano, Anna; Fais, Franco

2013-06-01

Ag selection has been suggested to play a role in chronic lymphocytic leukemia (CLL) pathogenesis, but no large-scale analysis has been performed so far on the structure of the Ag-binding sites (ABSs) of leukemic cell Igs. We sequenced both H and L chain V(D)J rearrangements from 366 CLL patients and modeled their three-dimensional structures. The resulting ABS structures were clustered into a small number of discrete sets, each containing ABSs with similar shapes and physicochemical properties. This structural classification correlates well with other known prognostic factors such as Ig mutation status and recurrent (stereotyped) receptors, but it shows a better prognostic value, at least in the case of one structural cluster for which clinical data were available. These findings suggest, for the first time, to our knowledge, on the basis of a structural analysis of the Ab-binding sites, that selection by a finite quota of antigenic structures operates on most CLL cases, whether mutated or unmutated.

Characteristics of communication among Japanese children with autism spectrum disorder: A cluster analysis using the Children's Communication Checklist-2.

PubMed

Tanaka, Sanae; Oi, Manabu; Fujino, Hiroshi; Kikuchi, Mitsuru; Yoshimura, Yuko; Miura, Yui; Tsujii, Masatsugu; Ohoka, Harue

2017-01-01

Some overlap has been suggested among the subtypes of autism spectrum disorder (ASD) in children. The Japanese version of the Children's Communication Checklist-2 (CCC-2) is a useful measure for identifying profiles in relation to communication impairments in children with ASD. The aim of this study was to investigate whether the CCC-2 could identify subtypes in relation to communication impairments in Japanese children with ASD. The study participants were 113 children with ASD but without intellectual disabilities aged 3-12 years. Parents were given the Japanese version of the CCC-2 and asked to rate their children, who were then classified into two groups based on statistical analysis. Significant differences were found between clusters in mean CCC-2 subscales. These results suggest that one subtype was associated with low language competence and strong characteristics of autism, while the other was associated with relatively high language competence and milder characteristics of autism.

Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

PubMed

Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

PubMed Central

Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032

A Polyphasic and Taxogenomic Evaluation Uncovers Arcobacter cryaerophilus as a Species Complex That Embraces Four Genomovars

PubMed Central

Pérez-Cataluña, Alba; Collado, Luis; Salgado, Oscar; Lefiñanco, Violeta; Figueras, María J.

2018-01-01

The species Arcobacter cryaerophilus is found in many food products of animal origin and is the dominating species in wastewater. In addition, it is associated with cases of farm animal and human infectious diseases,. The species embraces two subgroups i.e., 1A (LMG 24291T = LMG 9904T) and 1B (LMG 10829) that can be differentiated by their 16S rRNA-RFLP pattern. However, some authors, on the basis of the shared intermediate levels of DNA-DNA hybridization, have suggested abandoning the subgroup classification. This contradiction indicates that the taxonomy of this species is not yet resolved. The objective of the present study was to perform a taxonomic evaluation of the diversity of A. cryaerophilus. Genomic information was used along with a Multilocus Phylogenetic Analysis (MLPA) and phenotypic characterization on a group of 52 temporally and geographically dispersed strains, coming from different types of samples and hosts from nine countries. The MLPA analysis showed that those strains formed four clusters (I–IV). Values of Average Nucleotide Identity (ANI) and in silico DNA-DNA Hybridization (isDDH) obtained between 13 genomes representing strains of the four clusters were below the proposed cut-offs of 96 and 70%, respectively, confirming that each of the clusters represented a different genomic species. However, none of the evaluated phenotypic tests enabled their unequivocal differentiation into species. Therefore, the genomic delimited clusters should be considered genomovars of the species A. cryaerophilus. These genomovars could have different clinical importance, since only the cluster I included strains isolated from human specimens. The discovery of at least one stable distinctive phenotypic character would be needed to define each cluster or genomovar as a different species. Until then, we propose naming them “A. cryaerophilus gv. pseudocryaerophilus” (Cluster I = LMG 10229T), “A. cryaerophilus gv. crypticus” (Cluster II = LMG 9065T), “A. cryaerophilus gv. cryaerophilus” (Cluster III = LMG 24291T) and “A. cryaerophilus gv. occultus” (Cluster IV = LMG 29976T).

Expression level of miRNAs on chromosome 14q32.31 region correlates with tumor aggressiveness and survival of glioblastoma patients.

PubMed

Shahar, Tal; Granit, Avital; Zrihan, Daniel; Canello, Tamar; Charbit, Hanna; Einstein, Ofira; Rozovski, Uri; Elgavish, Sharona; Ram, Zvi; Siegal, Tali; Lavon, Iris

2016-12-01

The 54 microRNAs (miRNAs) within the DLK-DIO3 genomic region on chromosome 14q32.31 (cluster-14-miRNAs) are organized into sub-clusters 14A and 14B. These miRNAs are downregulated in glioblastomas and might have a tumor suppressive role. Any association between the expression levels of cluster-14-miRNAs with overall survival (OS) is undetermined. We randomly selected miR-433, belonging to sub-cluster 14A and miR-323a-3p and miR-369-3p, belonging to sub-cluster 14B, and assessed their role in glioblastomas in vitro and in vivo. We also determined the expression level of cluster-14-miRNAs in 27 patients with newly diagnosed glioblastoma, and analyzed the association between their level of expression and OS. Overexpression of miR-323a-3p and miR-369-3p, but not miR-433, in glioblastoma cells inhibited their proliferation and migration in vitro. Mice implanted with glioblastoma cells overexpressing miR323a-3p and miR369-3p, but not miR433, exhibited prolonged survival compared to controls (P = .003). Bioinformatics analysis identified 13 putative target genes of cluster-14-miRNAs, and real-time RT-PCR validated these findings. Pathway analysis of the putative target genes identified neuregulin as the most enriched pathway. The expression level of cluster-14-miRNAs correlated with patients' OS. The median OS was 8.5 months for patients with low expression levels and 52.7 months for patients with high expression levels (HR 0.34; 95 % CI 0.12-0.59, P = .003). The expression level of cluster-14-miRNAs correlates directly with OS, suggesting a role for this cluster in promoting aggressive behavior of glioblastoma, possibly through ErBb/neuregulin signaling.

Autism spectrum disorder in Down syndrome: cluster analysis of Aberrant Behaviour Checklist data supports diagnosis.

PubMed

Ji, N Y; Capone, G T; Kaufmann, W E

2011-11-01

The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS + ASD, DS + None (no DSM diagnosis), DS + DBD (disruptive behaviour disorder) and DS + SMD (stereotypic movement disorder), the latter two as comparison groups. Two clusters were identified with DS + ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS + None (71.9%) and DS + DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS + SMD were relatively evenly distributed throughout the four clusters. Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS + ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.

[Cluster analysis in biomedical researches].

PubMed

Akopov, A S; Moskovtsev, A A; Dolenko, S A; Savina, G D

2013-01-01

Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research.

Evolutionary analysis of groundwater flow: Application of multivariate statistical analysis to hydrochemical data in the Densu Basin, Ghana

NASA Astrophysics Data System (ADS)

Yidana, Sandow Mark; Bawoyobie, Patrick; Sakyi, Patrick; Fynn, Obed Fiifi

2018-02-01

An evolutionary trend has been postulated through the analysis of hydrochemical data of a crystalline rock aquifer system in the Densu Basin, Southern Ghana. Hydrochemcial data from 63 groundwater samples, taken from two main groundwater outlets (Boreholes and hand dug wells) were used to postulate an evolutionary theory for the basin. Sequential factor and hierarchical cluster analysis were used to disintegrate the data into three factors and five clusters (spatial associations). These were used to characterize the controls on groundwater hydrochemistry and its evolution in the terrain. The dissolution of soluble salts and cation exchange processes are the dominant processes controlling groundwater hydrochemistry in the terrain. The trend of evolution of this set of processes follows the pattern of groundwater flow predicted by a calibrated transient groundwater model in the area. The data suggest that anthropogenic activities represent the second most important process in the hydrochemistry. Silicate mineral weathering is the third most important set of processes. Groundwater associations resulting from Q-mode hierarchical cluster analysis indicate an evolutionary pattern consistent with the general groundwater flow pattern in the basin. These key findings are at variance with results of previous investigations and indicate that when carefully done, groundwater hydrochemical data can be very useful for conceptualizing groundwater flow in basins.

Signatures of cytoplasmic proteins in the exoproteome distinguish community- and hospital-associated methicillin-resistant Staphylococcus aureus USA300 lineages.

PubMed

Mekonnen, Solomon A; Palma Medina, Laura M; Glasner, Corinna; Tsompanidou, Eleni; de Jong, Anne; Grasso, Stefano; Schaffer, Marc; Mäder, Ulrike; Larsen, Anders R; Gumpert, Heidi; Westh, Henrik; Völker, Uwe; Otto, Andreas; Becher, Dörte; van Dijl, Jan Maarten

2017-08-18

Methicillin-resistant Staphylococcus aureus (MRSA) is the common name for a heterogeneous group of highly drug-resistant staphylococci. Two major MRSA classes are distinguished based on epidemiology, namely community-associated (CA) and hospital-associated (HA) MRSA. Notably, the distinction of CA- and HA-MRSA based on molecular traits remains difficult due to the high genomic plasticity of S. aureus. Here we sought to pinpoint global distinguishing features of CA- and HA-MRSA through a comparative genome and proteome analysis of the notorious MRSA lineage USA300. We show for the first time that CA- and HA-MRSA isolates can be distinguished by 2 distinct extracellular protein abundance clusters that are predictive not only for epidemiologic behavior, but also for their growth and survival within epithelial cells. This 'exoproteome profiling' also groups more distantly related HA-MRSA isolates into the HA exoproteome cluster. Comparative genome analysis suggests that these distinctive features of CA- and HA-MRSA isolates relate predominantly to the accessory genome. Intriguingly, the identified exoproteome clusters differ in the relative abundance of typical cytoplasmic proteins, suggesting that signatures of cytoplasmic proteins in the exoproteome represent a new distinguishing feature of CA- and HA-MRSA. Our comparative genome and proteome analysis focuses attention on potentially distinctive roles of 'liberated' cytoplasmic proteins in the epidemiology and intracellular survival of CA- and HA-MRSA isolates. Such extracellular cytoplasmic proteins were recently invoked in staphylococcal virulence, but their implication in the epidemiology of MRSA is unprecedented.

Psychological effects of chemical weapons: a follow-up study of First World War veterans.

PubMed

Jones, E; Everitt, B; Ironside, S; Palmer, I; Wessely, S

2008-10-01

Chemical weapons exercise an enduring and often powerful psychological effect. This had been recognized during the First World War when it was shown that the symptoms of stress mimicked those of mild exposure to gas. Debate about long-term effects followed the suggestion that gassing triggered latent tuberculosis. A random sample of 103 First World War servicemen awarded a war pension for the effects of gas, but without evidence of chronic respiratory pathology, were subjected to cluster analysis using 25 common symptoms. The consistency of symptom reporting was also investigated across repeated follow-ups. Cluster analysis identified four groups: one (n=56) with a range of somatic symptoms, a second (n=30) with a focus on the respiratory system, a third (n=12) with a predominance of neuropsychiatric symptoms, and a fourth (n=5) with a narrow band of symptoms related to the throat and breathing difficulties. Veterans from the neuropsychiatric cluster had multiple diagnoses including neurasthenia and disordered action of the heart, and reported many more symptoms than those in the three somatic clusters. Mild or intermittent respiratory disorders in the post-war period supported beliefs about the damaging effects of gas in the three somatic clusters. By contrast, the neuropsychiatric group did not report new respiratory illnesses. For this cluster, the experience of gassing in a context of extreme danger may have been responsible for the intensity of their symptoms, which showed no sign of diminution over the 12-year follow-up.

Denaturing gradient gel electrophoresis profiles of bacteria from the saliva of twenty four different individuals form clusters that showed no relationship to the yeasts present.

PubMed

M Weerasekera, Manjula; H Sissons, Chris; Wong, Lisa; A Anderson, Sally; R Holmes, Ann; D Cannon, Richard

2017-10-01

The aim was to investigate the relationship between groups of bacteria identified by cluster analysis of the DGGE fingerprints and the amounts and diversity of yeast present. Bacterial and yeast populations in saliva samples from 24 adults were analysed using denaturing gradient gel electrophoresis (DGGE) of the bacteria present and by yeast culture. Eubacterial DGGE banding patterns showed considerable variation between individuals. Seventy one different amplicon bands were detected, the band number per saliva sample ranged from 21 to 39 (mean±SD=29.3±4.9). Cluster and principal component analysis of the bacterial DGGE patterns yielded three major clusters containing 20 of the samples. Seventeen of the 24 (71%) saliva samples were yeast positive with concentrations up to 10 3 cfu/mL. Candida albicans was the predominant species in saliva samples although six other yeast species, including Candida dubliniensis, Candida tropicalis, Candida krusei, Candida guilliermondii, Candida rugosa and Saccharomyces cerevisiae, were identified. The presence, concentration, and species of yeast in samples showed no clear relationship to the bacterial clusters. Despite indications of in vitro bacteria-yeast interactions, there was a lack of association between the presence, identity and diversity of yeasts and the bacterial DGGE fingerprint clusters in saliva. This suggests significant ecological individual-specificity of these associations in highly complex in vivo oral biofilm systems under normal oral conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of nitrogen-fixing genes and gene clusters from metagenomic library of acid mine drainage.

PubMed

Dai, Zhimin; Guo, Xue; Yin, Huaqun; Liang, Yili; Cong, Jing; Liu, Xueduan

2014-01-01

Biological nitrogen fixation is an essential function of acid mine drainage (AMD) microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community.

Identification of Nitrogen-Fixing Genes and Gene Clusters from Metagenomic Library of Acid Mine Drainage

PubMed Central

Yin, Huaqun; Liang, Yili; Cong, Jing; Liu, Xueduan

2014-01-01

Biological nitrogen fixation is an essential function of acid mine drainage (AMD) microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community. PMID:24498417

Efficient Synthesis of Ir-Polyoxometalate Cluster Using a Continuous Flow Apparatus and STM Investigation of Its Coassembly Behavior on HOPG Surface.

PubMed

Zhang, Junyong; Chang, Shaoqing; Suryanto, Bryan H R; Gong, Chunhua; Zeng, Xianghua; Zhao, Chuan; Zeng, Qingdao; Xie, Jingli

2016-06-06

Taking advantage of a continuous-flow apparatus, the iridium(III)-containing polytungstate cluster K12Na2H2[Ir2Cl8P2W20O72]·37H2O (1) was obtained in a reasonable yield (13% based on IrCl3·H2O). Compound 1 was characterized by Fourier transform IR, UV-visible, (31)P NMR, electrospray ionization mass spectrometry (ESI-MS), and thermogravimetric analysis measurements. (31)P NMR, ESI-MS, and elemental analysis all indicated 1 was a new polytungstate cluster compared with the reported K14[(IrCl4)KP2W20O72] compound. Intriguingly, the successful isolation of 1 relied on the custom-built flow apparatus, demonstrating the uniqueness of continuous-flow chemistry to achieve crystalline materials. The catalytic properties of 1 were assessed by investigating the activity on catalyzing the electro-oxidation of ruthenium tris-2,2'-bipyridine [Ru(bpy)3](2+/3+). The voltammetric behavior suggested a coupled catalytic behavior between [Ru(bpy)3](3+/2+) and 1. Furthermore, on the highly oriented pyrolytic graphite surface, 1,3,5-tris(10-carboxydecyloxy) benzene (TCDB) was used as the two-dimensional host network to coassemble cluster 1; the surface morphology was observed by scanning tunneling microscope technique. "S"-shape of 1 was observed, indicating that the cluster could be accommodated in the cavity formed by two TCDB host molecules, leading to a TCDB/cluster binary structure.

Demographic but not geographic insularity in HIV transmission among young black MSM.

PubMed

Oster, Alexandra M; Pieniazek, Danuta; Zhang, Xinjian; Switzer, William M; Ziebell, Rebecca A; Mena, Leandro A; Wei, Xierong; Johnson, Kendra L; Singh, Sonita K; Thomas, Peter E; Elmore, Kimberlee A; Heffelfinger, James D

2011-11-13

To understand patterns of HIV transmission among young black MSM and others in Mississippi. Phylogenetic analysis of HIV-1 polymerase (pol) sequences from 799 antiretroviral-naive persons newly diagnosed with HIV infection in Mississippi during 2005-2008, 130 (16%) of whom were black MSM aged 16-25 years. We identified phylogenetic clusters and used surveillance data to evaluate demographic attributes and risk factors of all persons in clusters that included black MSM aged 16-25 years. We identified 82 phylogenetic clusters, 21 (26%) of which included HIV strains from at least one young black MSM. Of the 69 persons in these clusters, 59 were black MSM and seven were black men with unknown transmission category; the remaining three were MSM of white or Hispanic race/ethnicity. Of these 21 clusters, 10 included residents of one geographic region of Mississippi, whereas 11 included residents of multiple regions or outside of the state. Phylogenetic clusters involving HIV-infected young black MSM were homogeneous with respect to demographic and risk characteristics, suggesting insularity of this population with respect to HIV transmission, but were geographically heterogeneous. Reducing HIV transmission among young black MSM in Mississippi may require prevention strategies that are tailored to young black MSM and those in their sexual networks, and prevention interventions should be delivered in a manner to reach young black MSM throughout the state. Phylogenetic analysis can be a tool for local jurisdictions to understand the transmission dynamics in their areas.

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

PubMed

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

Associations of racial discrimination and parental discrimination coping messages with African American adolescent racial identity.

PubMed

Richardson, Bridget L; Macon, Tamarie A; Mustafaa, Faheemah N; Bogan, Erin D; Cole-Lewis, Yasmin; Chavous, Tabbye M

2015-06-01

Research links racial identity to important developmental outcomes among African American adolescents, but less is known about the contextual experiences that shape youths' racial identity. In a sample of 491 African American adolescents (48% female), associations of youth-reported experiences of racial discrimination and parental messages about preparation for racial bias with adolescents' later racial identity were examined. Cluster analysis resulted in four profiles of adolescents varying in reported frequency of racial discrimination from teachers and peers at school and frequency of parental racial discrimination coping messages during adolescents' 8th grade year. Boys were disproportionately over-represented in the cluster of youth experiencing more frequent discrimination but receiving fewer parental discrimination coping messages, relative to the overall sample. Also examined were clusters of adolescents' 11th grade racial identity attitudes about the importance of race (centrality), personal group affect (private regard), and perceptions of societal beliefs about African Americans (public regard). Girls and boys did not differ in their representation in racial identity clusters, but 8th grade discrimination/parent messages clusters were associated with 11th grade racial identity cluster membership, and these associations varied across gender groups. Boys experiencing more frequent discrimination but fewer parental coping messages were over-represented in the racial identity cluster characterized by low centrality, low private regard, and average public regard. The findings suggest that adolescents who experience racial discrimination but receive fewer parental supports for negotiating and coping with discrimination may be at heightened risk for internalizing stigmatizing experiences. Also, the findings suggest the need to consider the context of gender in adolescents' racial discrimination and parental racial socialization.

FRONTIER FIELDS CLUSTERS: CHANDRA AND JVLA VIEW OF THE PRE-MERGING CLUSTER MACS J0416.1-2403

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ogrean, G. A.; Weeren, R. J. van; Jones, C.

2015-10-20

Merging galaxy clusters leave long-lasting signatures on the baryonic and non-baryonic cluster constituents, including shock fronts, cold fronts, X-ray substructure, radio halos, and offsets between the dark matter (DM) and the gas components. Using observations from Chandra, the Jansky Very Large Array, the Giant Metrewave Radio Telescope, and the Hubble Space Telescope, we present a multiwavelength analysis of the merging Frontier Fields cluster MACS J0416.1-2403 (z = 0.396), which consists of NE and SW subclusters whose cores are separated on the sky by ∼250 kpc. We find that the NE subcluster has a compact core and hosts an X-ray cavity,more » yet it is not a cool core. Approximately 450 kpc south–southwest of the SW subcluster, we detect a density discontinuity that corresponds to a compression factor of ∼1.5. The discontinuity was most likely caused by the interaction of the SW subcluster with a less massive structure detected in the lensing maps SW of the subcluster's center. For both the NE and the SW subclusters, the DM and the gas components are well-aligned, suggesting that MACS J0416.1-2403 is a pre-merging system. The cluster also hosts a radio halo, which is unusual for a pre-merging system. The halo has a 1.4 GHz power of (1.3 ± 0.3) × 10{sup 24} W Hz{sup −1}, which is somewhat lower than expected based on the X-ray luminosity of the cluster if the spectrum of the halo is not ultra-steep. We suggest that we are either witnessing the birth of a radio halo, or have discovered a rare ultra-steep spectrum halo.« less

Title: Chimeras in small, globally coupled networks: Experiments and stability analysis

NASA Astrophysics Data System (ADS)

Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi

Since the initial observation of chimera states, there has been much discussion of the conditions under which these states emerge. The emphasis thus far has mainly been to analyze large networks of coupled oscillators; however, recent studies have begun to focus on the opposite limit: what is the smallest system of coupled oscillators in which chimeras can exist? We experimentally observe chimeras and other partially synchronous patterns in a network of four globally-coupled chaotic opto-electronic oscillators. By examining the equations of motion, we demonstrate that symmetries in the network topology allow a variety of synchronous states to exist, including cluster synchronous states and a chimera state. Using the group theoretical approach recently developed for analyzing cluster synchronization, we show how to derive the variational equations for these synchronous patterns and calculate their linear stability. The stability analysis gives good agreement with our experimental results. Both experiments and simulations suggest that these chimera states often appear in regions of multistability between global, cluster, and desynchronized states.

Semimicroscopic analysis of 6Li+28Si elastic scattering at 76 to 318 MeV

NASA Astrophysics Data System (ADS)

Hassanain, M. A.; Anwar, M.; Behairy, Kassem O.

2018-04-01

Using the α-cluster structure of colliding nuclei, the elastic scattering of 6Li+28Si at energies from 76 to 318 MeV has been investigated by the use of the real folding cluster approach. The results of the cluster analysis are compared with those obtained by the CDM3Y6 effective density- and energy-dependent nucleon-nucleon (NN) interaction based upon G -matrix elements of the M3Y-Paris potential. A Woods-Saxon (WS) form was used for the imaginary potential. For all energies and derived potentials, the diffraction region was well reproduced, except at Elab=135 and 154 MeV at large angle. These results suggest that the addition of the surface (DWS) imaginary potential term to the volume imaginary potential is essential for a correct description of the refractive structure of the 6Li elastic scattering distribution at these energies. The energy dependence of the total reaction cross sections and that of the real and imaginary volume integrals is also discussed.

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

The bacterial species definition in the genomic era

PubMed Central

Konstantinidis, Konstantinos T; Ramette, Alban; Tiedje, James M

2006-01-01

The bacterial species definition, despite its eminent practical significance for identification, diagnosis, quarantine and diversity surveys, remains a very difficult issue to advance. Genomics now offers novel insights into intra-species diversity and the potential for emergence of a more soundly based system. Although we share the excitement, we argue that it is premature for a universal change to the definition because current knowledge is based on too few phylogenetic groups and too few samples of natural populations. Our analysis of five important bacterial groups suggests, however, that more stringent standards for species may be justifiable when a solid understanding of gene content and ecological distinctiveness becomes available. Our analysis also reveals what is actually encompassed in a species according to the current standards, in terms of whole-genome sequence and gene-content diversity, and shows that this does not correspond to coherent clusters for the environmental Burkholderia and Shewanella genera examined. In contrast, the obligatory pathogens, which have a very restricted ecological niche, do exhibit clusters. Therefore, the idea of biologically meaningful clusters of diversity that applies to most eukaryotes may not be universally applicable in the microbial world, or if such clusters exist, they may be found at different levels of distinction. PMID:17062412

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE PAGES

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-06-24

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Spatial analysis of malaria in Anhui province, China

PubMed Central

Zhang, Wenyi; Wang, Liping; Fang, Liqun; Ma, Jiaqi; Xu, Youfu; Jiang, Jiafu; Hui, Fengming; Wang, Jianjun; Liang, Song; Yang, Hong; Cao, Wuchun

2008-01-01

Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. PMID:18847489

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vasylkivska, Veronika S.; Huerta, Nicolas J.

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis.

PubMed

Fernández-Arjona, María Del Mar; Grondona, Jesús M; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

PubMed Central

Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. PMID:28848398

The adsorption of Run (n = 1-4) on γ-Al2O3 Surface: A DFT study

NASA Astrophysics Data System (ADS)

Liu, Zhe; Guo, Yafei; Chen, Yu; Shen, Rong

2018-05-01

The density functional theory (DFT) was adopted to study the adsorption and growth of Run (n = 1-4) clusters on γ-Al2O3 surface, which is of great significances for the design of many important catalysts, especially for carbon dioxide methanation. It is found that both the Rusbnd Ru bond length and adsorption energy Eads of Ru clusters with the surface increase with the Run clusters increasing. The growth ability of the supported Run cluster is weaker than the gas phase Run clusters through comparing their respective growth process, which ascribes to the stabilization of γ-Al2O3 support. An interesting discovery is that the basin structure was supposed to be the most favorable adsorption geometry for Run clusters. Additionally, the distances between Ru atoms in the adsorbed clusters are longer than that in their isolated counterparts. Bader charge analysis was conducted for the most stable configurations of Run (n = 1-4) clusters on γ-Al2O3 surface as well. And the results suggest that Run (n = 1-4) clusters serve as the electron donators. The result of projected density of states (PDOS) shows that strong adsorption of Ru atom on the γ-Al2O3 surface correlates with strong interaction between d orbital of Ru atom and p orbital of Al or O atom of the Al2O3 support.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

PubMed Central

Babbitt, Patricia C.; Ferrin, Thomas E.

2017-01-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially—MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method’s novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences. PMID:28187133

Correlation of shallow marine, deep marine, and coastal terrestrial records of central California: asynchronous responses to paleoceanographic and paleoclimatic change during the past 19,000 years

NASA Astrophysics Data System (ADS)

McGann, M.

2016-12-01

Benthic and planktic foraminiferal census data combined with pollen data acquired from the continental margin off central California (core S3-15G, 3491 m depth from the western levy of the Monterey Fan; 36°23.53'N, 123°20.52'W) provide a unique opportunity to document concurrent paleoceanographic and paleoclimatic changes in the region during the late Quaternary. Radiocarbon dates and the ratio of the planktic foraminiferal species Neogloboquardrina pachyderma (Ehrenberg) to Neogloboquardrina incompta (Cifelli) provide a good age-depth model for the last 19,000 years. Q-mode cluster analysis of the benthic foraminifera grouped the fauna into two clusters reflecting faunal adaptation to changing climatic conditions during the Pleistocene and Holocene, whereas the R-mode cluster analysis identified glacial (Uvigerina senticosa and Globobulimina auriculata) and interglacial (Melonis pompilioides and Gyroidina planulata) faunas. A slight increase in oxygen concentration in the deep sea across the Pleistocene-Holocene transition is suggested by a reduction in abundance of G. auriculata and increased frequency of M. pompilioides. Q-mode cluster analysis of the planktic foraminifera indicates a change in the surface water from a glacial subpolar fauna in the Pleistocene to a transitional fauna in the Holocene. The pollen flora separated into three clusters by Q-mode cluster analysis, two of Pleistocene age (glacial and transitional) and one in the Holocene (interglacial), reflecting adaptation of the flora in the California Coast Ranges of central California to the warmer climate in the Holocene. Decoupling is evident between the benthic foraminiferal, planktic foraminiferal, and terrestrial floral responses to changing oceanographic and climatic conditions. The floral response leads the surface-dwelling planktic fauna by several millennia, and is followed by the deep-dwelling benthic fauna a millennium later.

Image-driven Population Analysis through Mixture Modeling

PubMed Central

Sabuncu, Mert R.; Balci, Serdar K.; Shenton, Martha E.; Golland, Polina

2009-01-01

We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The output of the algorithm is a small number of template images that represent different modes in a population. This is in contrast with traditional, hypothesis-driven computational anatomy approaches that assume a single template to construct an atlas. We derive the algorithm based on a generative model of an image population as a mixture of deformable template images. We validate and explore our method in four experiments. In the first experiment, we use synthetic data to explore the behavior of the algorithm and inform a design choice on parameter settings. In the second experiment, we demonstrate the utility of having multiple atlases for the application of localizing temporal lobe brain structures in a pool of subjects that contains healthy controls and schizophrenia patients. Next, we employ iCluster to partition a data set of 415 whole brain MR volumes of subjects aged 18 through 96 years into three anatomical subgroups. Our analysis suggests that these subgroups mainly correspond to age groups. The templates reveal significant structural differences across these age groups that confirm previous findings in aging research. In the final experiment, we run iCluster on a group of 15 patients with dementia and 15 age-matched healthy controls. The algorithm produces two modes, one of which contains dementia patients only. These results suggest that the algorithm can be used to discover sub-populations that correspond to interesting structural or functional “modes.” PMID:19336293

CHARACTERIZATION OF INFLAMMATORY GENE EXPRESSION AND GALECTIN-3 FUNCTION AFTER SPINAL CORD INJURY IN MICE

PubMed Central

Pajoohesh-Ganji, Ahdeah; Knoblach, Susan M.; Faden, Alan I.; Byrnes, Kimberly R.

2012-01-01

Inflammation has long been implicated in secondary tissue damage after spinal cord injury (SCI). Our previous studies of inflammatory gene expression in rats after SCI revealed two temporally correlated clusters: the first was expressed early after injury and the second was up-regulated later, with peak expression at 1–2 weeks and persistent up-regulation through 6 months. To further address the role of inflammation after SCI, we examined inflammatory genes in a second species, mice, through 28 days after SCI. Using anchor gene clustering analysis, we found similar expression patterns for both the acute and chronic gene clusters previously identified after rat SCI. The acute group returned to normal expression levels by 7 days post-injury. The chronic group, which included C1qB, p22phox and galectin-3, showed peak expression at 7 days and remained up-regulated through 28 days. Immunohistochemistry and western blot analysis showed that the protein expression of these genes was consistent with the mRNA expression. Further exploration of the role of one of these genes, galectin-3, suggests that galectin-3 may contribute to secondary injury. In summary, our findings extend our prior gene profiling data by demonstrating the chronic expression of a cluster of microglial associated inflammatory genes after SCI in mice. Moreover, by demonstrating that inhibition of one such factor improves recovery, the findings suggest that such chronic up-regulation of inflammatory processes may contribute to secondary tissue damage after SCI, and that there may be a broader therapeutic window for neuroprotection than generally accepted. PMID:22884909

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

PubMed

Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.

Comparison of a non-stationary voxelation-corrected cluster-size test with TFCE for group-Level MRI inference.

PubMed

Li, Huanjie; Nickerson, Lisa D; Nichols, Thomas E; Gao, Jia-Hong

2017-03-01

Two powerful methods for statistical inference on MRI brain images have been proposed recently, a non-stationary voxelation-corrected cluster-size test (CST) based on random field theory and threshold-free cluster enhancement (TFCE) based on calculating the level of local support for a cluster, then using permutation testing for inference. Unlike other statistical approaches, these two methods do not rest on the assumptions of a uniform and high degree of spatial smoothness of the statistic image. Thus, they are strongly recommended for group-level fMRI analysis compared to other statistical methods. In this work, the non-stationary voxelation-corrected CST and TFCE methods for group-level analysis were evaluated for both stationary and non-stationary images under varying smoothness levels, degrees of freedom and signal to noise ratios. Our results suggest that, both methods provide adequate control for the number of voxel-wise statistical tests being performed during inference on fMRI data and they are both superior to current CSTs implemented in popular MRI data analysis software packages. However, TFCE is more sensitive and stable for group-level analysis of VBM data. Thus, the voxelation-corrected CST approach may confer some advantages by being computationally less demanding for fMRI data analysis than TFCE with permutation testing and by also being applicable for single-subject fMRI analyses, while the TFCE approach is advantageous for VBM data. Hum Brain Mapp 38:1269-1280, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Multidimensional Structure of the Hypomanic Personality Scale

ERIC Educational Resources Information Center

Schalet, Benjamin D.; Durbin, C. Emily; Revelle, William

2011-01-01

The structure of the Hypomanic Personality Scale was explored in a sample of young adults (N = 884); resulting structures were validated on subsamples with measures of personality traits, internalizing symptoms, and externalizing behaviors. Hierarchical cluster analysis and estimates of general factor saturation suggested the presence of a weak…

Neither insects nor wind: ambophily in dioecious Chamaedorea palms (Arecaceae).

PubMed

Rios, L D; Fuchs, E J; Hodel, D R; Cascante-Marín, A

2014-07-01

Pollination of Neotropical dioecious trees is commonly related to generalist insects. Similar data for non-tree species with separated genders are inconclusive. Recent studies on pollination of dioecious Chamaedorea palms (Arecaceae) suggest that species are either insect- or wind-pollinated. However, the wide variety of inflorescence and floral attributes within the genus suggests mixed pollination mode involving entomophily and anemophily. To evaluate this hypothesis, we studied the pollination of Chamaedorea costaricana, C. macrospadix, C. pinnatifrons and C. tepejilote in two montane forests in Costa Rica. A complementary morphological analysis of floral traits was carried out to distinguish species groups within the genus according to their most probable pollination mechanism. We conducted pollinator exclusion experiments, field observations on visitors to pistillate and staminate inflorescences, and trapped airborne pollen. A cluster analysis using 18 floral traits selected for their association with wind and insect pollination syndromes was carried out using 52 Chamaedorea species. Exclusion experiments showed that both wind and insects, mostly thrips (Thysanoptera), pollinated the studied species. Thrips used staminate inflorescences as brood sites and pollinated pistillate flowers by deception. Insects caught on pistillate inflorescences transported pollen, while traps proved that pollen is wind-borne. Our empirical findings clearly suggest that pollination of dioecious Chamaedorea palms is likely to involve both insects and wind. A cluster analysis showed that the majority of studied species have a combination of floral traits that allow for both pollination modes. Our pollination experiments and morphological analysis both suggest that while some species may be completely entomophilous or anemophilous, ambophily might be a common condition within Chamaedorea. Our results propose a higher diversity of pollination mechanisms of Neotropical dioecious species than previously suggested. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

Modelling the Kampungkota: A quantitative approach in defining Indonesian informal settlements

NASA Astrophysics Data System (ADS)

Anindito, D. B.; Maula, F. K.; Akbar, R.

2018-02-01

Bandung City is home to 2.5 million inhabitants, some of which are living in slums and squatter. However, the terms conveying this type of housing is not adequate to describe that of Indonesian called as kampungkota. Several studies suggest various variables in constituting kampungkota qualitatively. This study delves to define kampungkota in a quantitative manner, using the characteristics of slums and squatter. The samples for this study are 151 villages (kelurahan) in Bandung City. Ordinary Least Squares, Geographically Weighted Regression, and Spatial Cluster and Outlier Analysis are employed. It is suggested that kampungkota may have distinguished variables regarding to its location. As kampungkota may be smaller than administrative area of kelurahan, it can develop beyond the jurisdiction of kelurahan, as indicated by the clustering pattern of kampungkota.

A fuzzy adaptive network approach to parameter estimation in cases where independent variables come from an exponential distribution

NASA Astrophysics Data System (ADS)

Dalkilic, Turkan Erbay; Apaydin, Aysen

2009-11-01

In a regression analysis, it is assumed that the observations come from a single class in a data cluster and the simple functional relationship between the dependent and independent variables can be expressed using the general model; Y=f(X)+[epsilon]. However; a data cluster may consist of a combination of observations that have different distributions that are derived from different clusters. When faced with issues of estimating a regression model for fuzzy inputs that have been derived from different distributions, this regression model has been termed the [`]switching regression model' and it is expressed with . Here li indicates the class number of each independent variable and p is indicative of the number of independent variables [J.R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transaction on Systems, Man and Cybernetics 23 (3) (1993) 665-685; M. Michel, Fuzzy clustering and switching regression models using ambiguity and distance rejects, Fuzzy Sets and Systems 122 (2001) 363-399; E.Q. Richard, A new approach to estimating switching regressions, Journal of the American Statistical Association 67 (338) (1972) 306-310]. In this study, adaptive networks have been used to construct a model that has been formed by gathering obtained models. There are methods that suggest the class numbers of independent variables heuristically. Alternatively, in defining the optimal class number of independent variables, the use of suggested validity criterion for fuzzy clustering has been aimed. In the case that independent variables have an exponential distribution, an algorithm has been suggested for defining the unknown parameter of the switching regression model and for obtaining the estimated values after obtaining an optimal membership function, which is suitable for exponential distribution.

A taxonomy of epithelial human cancer and their metastases

PubMed Central

2009-01-01

Background Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination. Methods We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures. Results Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination. Conclusion Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile. PMID:20017941

Distinct phenotype clusters in childhood inflammatory brain diseases: implications for diagnostic evaluation.

PubMed

Cellucci, Tania; Tyrrell, Pascal N; Twilt, Marinka; Sheikh, Shehla; Benseler, Susanne M

2014-03-01

To identify distinct clusters of children with inflammatory brain diseases based on clinical, laboratory, and imaging features at presentation, to assess which features contribute strongly to the development of clusters, and to compare additional features between the identified clusters. A single-center cohort study was performed with children who had been diagnosed as having an inflammatory brain disease between June 1, 1989 and December 31, 2010. Demographic, clinical, laboratory, neuroimaging, and histologic data at diagnosis were collected. K-means cluster analysis was performed to identify clusters of patients based on their presenting features. Associations between the clusters and patient variables, such as diagnoses, were determined. A total of 147 children (50% female; median age 8.8 years) were identified: 105 with primary central nervous system (CNS) vasculitis, 11 with secondary CNS vasculitis, 8 with neuronal antibody syndromes, 6 with postinfectious syndromes, and 17 with other inflammatory brain diseases. Three distinct clusters were identified. Paresis and speech deficits were the most common presenting features in cluster 1. Children in cluster 2 were likely to present with behavior changes, cognitive dysfunction, and seizures, while those in cluster 3 experienced ataxia, vision abnormalities, and seizures. Lesions seen on T2/fluid-attenuated inversion recovery sequences of magnetic resonance imaging were common in all clusters, but unilateral ischemic lesions were more prominent in cluster 1. The clusters were associated with specific diagnoses and diagnostic test results. Children with inflammatory brain diseases presented with distinct phenotypical patterns that are associated with specific diagnoses. This information may inform the development of a diagnostic classification of childhood inflammatory brain diseases and suggest that specific pathways of diagnostic evaluation are warranted. Copyright © 2014 by the American College of Rheumatology.

ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network.

PubMed

Wang, Jianxin; Zhong, Jiancheng; Chen, Gang; Li, Min; Wu, Fang-xiang; Pan, Yi

2015-01-01

Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks.

Classification of Cowpox Viruses into Several Distinct Clades and Identification of a Novel Lineage

PubMed Central

Franke, Annika; Pfaff, Florian; Jenckel, Maria; Hoffmann, Bernd; Höper, Dirk; Antwerpen, Markus; Meyer, Hermann; Beer, Martin; Hoffmann, Donata

2017-01-01

Cowpox virus (CPXV) was considered as uniform species within the genus Orthopoxvirus (OPV). Previous phylogenetic analysis indicated that CPXV is polyphyletic and isolates may cluster into different clades with two of these clades showing genetic similarities to either variola (VARV) or vaccinia viruses (VACV). Further analyses were initiated to assess both the genetic diversity and the evolutionary background of circulating CPXVs. Here we report the full-length sequences of 20 CPXV strains isolated from different animal species and humans in Germany. A phylogenetic analysis of altogether 83 full-length OPV genomes confirmed the polyphyletic character of the species CPXV and suggested at least four different clades. The German isolates from this study mainly clustered into two CPXV-like clades, and VARV- and VACV-like strains were not observed. A single strain, isolated from a cotton-top tamarin, clustered distantly from all other CPXVs and might represent a novel and unique evolutionary lineage. The classification of CPXV strains into clades roughly followed their geographic origin, with the highest clade diversity so far observed for Germany. Furthermore, we found evidence for recombination between OPV clades without significant disruption of the observed clustering. In conclusion, this analysis markedly expands the number of available CPXV full-length sequences and confirms the co-circulation of several CPXV clades in Germany, and provides the first data about a new evolutionary CPXV lineage. PMID:28604604

Identification of a current hot spot of HIV type 1 transmission in Mongolia by molecular epidemiological analysis.

PubMed

Davaalkham, Jagdagsuren; Unenchimeg, Puntsag; Baigalmaa, Chultem; Erdenetuya, Gombo; Nyamkhuu, Dulmaa; Shiino, Teiichiro; Tsuchiya, Kiyoto; Hayashida, Tsunefusa; Gatanaga, Hiroyuki; Oka, Shinichi

2011-10-01

We investigated the current molecular epidemiological status of HIV-1 in Mongolia, a country with very low incidence of HIV-1 though with rapid expansion in recent years. HIV-1 pol (1065 nt) and env (447 nt) genes were sequenced to construct phylogenetic trees. The evolutionary rates, molecular clock phylogenies, and other evolutionary parameters were estimated from heterochronous genomic sequences of HIV-1 subtype B by the Bayesian Markov chain Monte Carlo method. We obtained 41 sera from 56 reported HIV-1-positive cases as of May 2009. The main route of infection was men who have sex with men (MSM). Dominant subtypes were subtype B in 32 cases (78%) followed by subtype CRF02_AG (9.8%). The phylogenetic analysis of the pol gene identified two clusters in subtype B sequences. Cluster 1 consisted of 21 cases including MSM and other routes of infection, and cluster 2 consisted of eight MSM cases. The tree analyses demonstrated very short branch lengths in cluster 1, suggesting a surprisingly active expansion of HIV-1 transmission during a short period with the same ancestor virus. Evolutionary analysis indicated that the outbreak started around the early 2000s. This study identified a current hot spot of HIV-1 transmission and potential seed of the epidemic in Mongolia. Comprehensive preventive measures targeting this group are urgently needed.

HPLC-DAD-ESI-MS Analysis of Flavonoids from Leaves of Different Cultivars of Sweet Osmanthus.

PubMed

Wang, Yiguang; Fu, Jianxin; Zhang, Chao; Zhao, Hongbo

2016-09-14

Osmanthus fragrans Lour. has traditionally been a popular ornamental plant in China. In this study, ethanol extracts of the leaves of four cultivar groups of O. fragrans were analyzed by high-performance liquid chromatography coupled with diode array detection (HPLC-DAD) and high-performance liquid chromatography with electrospray ionization and mass spectrometry (HPLC-ESI-MS). The results suggest that variation in flavonoids among O. fragrans cultivars is quantitative, rather than qualitative. Fifteen components were detected and separated, among which, the structures of 11 flavonoids and two coumarins were identified or tentatively identified. According to principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on the abundance of these components (expressed as rutin equivalents), 22 selected cultivars were classified into four clusters. The seven cultivars from Cluster III ('Xiaoye Sugui', 'Boye Jingui', 'Wuyi Dangui', 'Yingye Dangui', 'Danzhuang', 'Foding Zhu', and 'Tianxiang Taige'), which are enriched in rutin and total flavonoids, and 'Sijigui' from Cluster II which contained the highest amounts of kaempferol glycosides and apigenin 7-O-glucoside, could be selected as potential pharmaceutical resources. However, the chemotaxonomy in this paper does not correlate with the distribution of the existing cultivar groups, demonstrating that the distribution of flavonoids in O. fragrans leaves does not provide an effective means of classification for O. fragrans cultivars based on flower color.

Differentiation of Trichophyton rubrum clinical isolates from Japanese and Chinese patients by randomly amplified polymorphic DNA and DNA sequence analysis of the non-transcribed spacer region of the rRNA gene.

PubMed

Yang, Xiumin; Sugita, Takashi; Takashima, Masako; Hiruma, Masataro; Li, Ruoyu; Sudo, Hajime; Ogawa, Hideoki; Ikeda, Shigaku

2009-04-01

Trichophyton rubrum is the most common pathogen causing dermatophytosis worldwide. Recent genetic investigations showed that the microorganism originated in Africa and then spread to Europe and North America via Asia. We investigated the intraspecific diversity of T. rubrum isolated from two closely located Asian countries, Japan and China. A total of 150 clinical isolates of T. rubrum obtained from Japanese and Chinese patients were analyzed by randomly amplified polymorphic DNA (RAPD) and DNA sequence analysis of the non-transcribed spacer (NTS) region in the rRNA gene. RAPD analysis divided the 150 strains into two major clusters, A and B. Of the Japanese isolates, 30% belonged to cluster A and 70% belonged to cluster B, whereas 91% of the Chinese isolates were in cluster A. The NTS region of the rRNA gene was divided into four major groups (I-IV) based on DNA sequencing. The majority of Japanese isolates were type IV (51%), and the majority of Chinese isolates were type III (75%). These results suggest that although Japan and China are neighboring countries, the origins of T. rubrum isolates from these countries may not be identical. These findings provide information useful for tracing the global transmission routes of T. rubrum.

The Projected Dark and Baryonic Ellipsoidal Structure of 20 CLASH Galaxy Clusters

NASA Astrophysics Data System (ADS)

Umetsu, Keiichi; Sereno, Mauro; Tam, Sut-Ieng; Chiu, I.-Non; Fan, Zuhui; Ettori, Stefano; Gruen, Daniel; Okumura, Teppei; Medezinski, Elinor; Donahue, Megan; Meneghetti, Massimo; Frye, Brenda; Koekemoer, Anton; Broadhurst, Tom; Zitrin, Adi; Balestra, Italo; Benítez, Narciso; Higuchi, Yuichi; Melchior, Peter; Mercurio, Amata; Merten, Julian; Molino, Alberto; Nonino, Mario; Postman, Marc; Rosati, Piero; Sayers, Jack; Seitz, Stella

2018-06-01

We reconstruct the two-dimensional (2D) matter distributions in 20 high-mass galaxy clusters selected from the CLASH survey by using the new approach of performing a joint weak gravitational lensing analysis of 2D shear and azimuthally averaged magnification measurements. This combination allows for a complete analysis of the field, effectively breaking the mass-sheet degeneracy. In a Bayesian framework, we simultaneously constrain the mass profile and morphology of each individual cluster, assuming an elliptical Navarro–Frenk–White halo characterized by the mass, concentration, projected axis ratio, and position angle (PA) of the projected major axis. We find that spherical mass estimates of the clusters from azimuthally averaged weak-lensing measurements in previous work are in excellent agreement with our results from a full 2D analysis. Combining all 20 clusters in our sample, we detect the elliptical shape of weak-lensing halos at the 5σ significance level within a scale of 2 {Mpc} {h}-1. The median projected axis ratio is 0.67 ± 0.07 at a virial mass of {M}vir}=(15.2+/- 2.8)× {10}14 {M}ȯ , which is in agreement with theoretical predictions from recent numerical simulations of the standard collisionless cold dark matter model. We also study misalignment statistics of the brightest cluster galaxy, X-ray, thermal Sunyaev–Zel’dovich effect, and strong-lensing morphologies with respect to the weak-lensing signal. Among the three baryonic tracers studied here, we find that the X-ray morphology is best aligned with the weak-lensing mass distribution, with a median misalignment angle of | {{Δ }}{PA}| =21^\\circ +/- 7^\\circ . We also conduct a stacked quadrupole shear analysis of the 20 clusters assuming that the X-ray major axis is aligned with that of the projected mass distribution. This yields a consistent axis ratio of 0.67 ± 0.10, suggesting again a tight alignment between the intracluster gas and dark matter. Based in part on data collected at the Subaru Telescope, which is operated by the National Astronomical Society of Japan.

Soil chemistry and pollution study of a closed landfill site at Ampar Tenang, Selangor, Malaysia.

PubMed

Mohd Adnan, Siti Nur Syahirah Binti; Yusoff, Sumiani; Piaw, Chua Yan

2013-06-01

A total of 20 landfills are located in State of Selangor, Malaysia. This includes the Ampar Tenang landfill site, which was closed on 26 January 2010. It was reported that the landfill has been upgraded to a level I type of sanitary classification. However, the dumpsite area is not being covered according to the classification. In addition, municipal solid waste was dumped directly on top of the unlined natural alluvium formation. This does not only contaminate surface and subsurface soils, but also initiates the potential risk of groundwater pollution. Based on previous studies, the Ampar Tenang soil has been proven to no longer be capable of preventing pollution migration. In this study, metal concentrations of soil samples up to 30 m depth were analyzed based on statistical analysis. It is very significant because research of this type has not been carried out before. The subsurface soils were significantly polluted by arsenic (As), lead (Pb), iron (Fe), copper (Cu) and aluminium (Al). As and Pb exceeded the safe limit values of 5.90 mg/kg and 31.00 mg/kg, respectively, based on Provincial Sediment Quality Guidelines for Metals and the Interim Sediment Quality Values. Furthermore, only Cu concentrations showed a significantly decreasing trend with increasing depth. Most metals were found on clay-type soils based on the cluster analysis method. Moreover, the analysis also differentiates two clusters: cluster I-Pb, As, zinc, Cu, manganese, calcium, sodium, magnesium, potassium and Fe; cluster II-Al. Different clustering may suggest a different contamination source of metals.

On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

PubMed

Haneuse, Sebastien; Rivera-Rodriguez, Claudia

2018-01-01

In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma.

PubMed

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; Lim, Jing Quan; Huang, Mi Ni; Padmanabhan, Nisha; Nellore, Vishwa; Kongpetch, Sarinya; Ng, Alvin Wei Tian; Ng, Ley Moy; Choo, Su Pin; Myint, Swe Swe; Thanan, Raynoo; Nagarajan, Sanjanaa; Lim, Weng Khong; Ng, Cedric Chuan Young; Boot, Arnoud; Liu, Mo; Ong, Choon Kiat; Rajasegaran, Vikneswari; Lie, Stefanus; Lim, Alvin Soon Tiong; Lim, Tse Hui; Tan, Jing; Loh, Jia Liang; McPherson, John R; Khuntikeo, Narong; Bhudhisawasdi, Vajaraphongsa; Yongvanit, Puangrat; Wongkham, Sopit; Totoki, Yasushi; Nakamura, Hiromi; Arai, Yasuhito; Yamasaki, Satoshi; Chow, Pierce Kah-Hoe; Chung, Alexander Yaw Fui; Ooi, London Lucien Peng Jin; Lim, Kiat Hon; Dima, Simona; Duda, Dan G; Popescu, Irinel; Broet, Philippe; Hsieh, Sen-Yung; Yu, Ming-Chin; Scarpa, Aldo; Lai, Jiaming; Luo, Di-Xian; Carvalho, André Lopes; Vettore, André Luiz; Rhee, Hyungjin; Park, Young Nyun; Alexandrov, Ludmil B; Gordân, Raluca; Rozen, Steven G; Shibata, Tatsuhiro; Pairojkul, Chawalit; Teh, Bin Tean; Tan, Patrick

2017-10-01

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1 / PD-L2 expression, or epigenetic mutations ( IDH1/2, BAP1 ) and FGFR / PRKA -related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116-35. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1047 . ©2017 American Association for Cancer Research.

Structure-Based Phylogenetic Analysis of the Lipocalin Superfamily.

PubMed

Lakshmi, Balasubramanian; Mishra, Madhulika; Srinivasan, Narayanaswamy; Archunan, Govindaraju

2015-01-01

Lipocalins constitute a superfamily of extracellular proteins that are found in all three kingdoms of life. Although very divergent in their sequences and functions, they show remarkable similarity in 3-D structures. Lipocalins bind and transport small hydrophobic molecules. Earlier sequence-based phylogenetic studies of lipocalins highlighted that they have a long evolutionary history. However the molecular and structural basis of their functional diversity is not completely understood. The main objective of the present study is to understand functional diversity of the lipocalins using a structure-based phylogenetic approach. The present study with 39 protein domains from the lipocalin superfamily suggests that the clusters of lipocalins obtained by structure-based phylogeny correspond well with the functional diversity. The detailed analysis on each of the clusters and sub-clusters reveals that the 39 lipocalin domains cluster based on their mode of ligand binding though the clustering was performed on the basis of gross domain structure. The outliers in the phylogenetic tree are often from single member families. Also structure-based phylogenetic approach has provided pointers to assign putative function for the domains of unknown function in lipocalin family. The approach employed in the present study can be used in the future for the functional identification of new lipocalin proteins and may be extended to other protein families where members show poor sequence similarity but high structural similarity.

Social phobia subtypes in the general population revealed by cluster analysis.

PubMed

Furmark, T; Tillfors, M; Stattin, H; Ekselius, L; Fredrikson, M

2000-11-01

Epidemiological data on subtypes of social phobia are scarce and their defining features are debated. Hence, the present study explored the prevalence and descriptive characteristics of empirically derived social phobia subgroups in the general population. To reveal subtypes, data on social distress, functional impairment, number of social fears and criteria fulfilled for avoidant personality disorder were extracted from a previously published epidemiological study of 188 social phobics and entered into an hierarchical cluster analysis. Criterion validity was evaluated by comparing clusters on the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). Finally, profile analyses were performed in which clusters were compared on a set of sociodemographic and descriptive characteristics. Three clusters emerged, consisting of phobics scoring either high (generalized subtype), intermediate (non-generalized subtype) or low (discrete subtype) on all variables. Point prevalence rates were 2.0%, 5.9% and 7.7% respectively. All subtypes were distinguished on both SPS and SIAS. Generalized or severe social phobia tended to be over-represented among individuals with low levels of educational attainment and social support. Overall, public-speaking was the most common fear. Although categorical distinctions may be used, the present data suggest that social phobia subtypes in the general population mainly differ dimensionally along a mild moderate-severe continuum, and that the number of cases declines with increasing severity.

A broad survey reveals substitution tolerance of residues ligating FeS clusters in [NiFe] hydrogenase

PubMed Central

2014-01-01

Background In order to understand the effects of FeS cluster attachment in [NiFe] hydrogenase, we undertook a study to substitute all 12 amino acid positions normally ligating the three FeS clusters in the hydrogenase small subunit. Using the hydrogenase from Alteromonas macleodii “deep ecotype” as a model, we substituted one of four amino acids (Asp, His, Asn, Gln) at each of the 12 ligating positions because these amino acids are alternative coordinating residues in otherwise conserved-cysteine positions found in a broad survey of NiFe hydrogenase sequences. We also hoped to discover an enzyme with elevated hydrogen evolution activity relative to a previously reported “G1” (H230C/P285C) improved enzyme in which the medial FeS cluster Pro and the distal FeS cluster His were each substituted for Cys. Results Among all the substitutions screened, aspartic acid substitutions were generally well-tolerated, and examination suggests that the observed deficiency in enzyme activity may be largely due to misprocessing of the small subunit of the enzyme. Alignment of hydrogenase sequences from sequence databases revealed many rare substitutions; the five substitutions present in databases that we tested all exhibited measurable hydrogen evolution activity. Select substitutions were purified and tested, supporting the results of the screening assay. Analysis of these results confirms the importance of small subunit processing. Normalizing activity to quantity of mature small subunit, indicative of total enzyme maturation, weakly suggests an improvement over the “G1” enzyme. Conclusions We have comprehensively screened 48 amino acid substitutions of the hydrogenase from A. macleodii “deep ecotype”, to understand non-canonical ligations of amino acids to FeS clusters and to improve hydrogen evolution activity of this class of hydrogenase. Our studies show that non-canonical ligations can be functional and also suggests a new limiting factor in the production of active enzyme. PMID:24934472

Targeting Clusters, Achieving Excellence.

ERIC Educational Resources Information Center

Rosenfeld, Stuart; Jacobs, Jim; Liston, Cynthia

2003-01-01

Suggests that groups, or clusters, of industries form partnerships with community colleges in order to positively impact economic development. Asserts that a cluster-oriented community college system requires innovation, specialized resources and expertise, knowledge of trends, and links to industry. Offers suggestions for developing such a…

Alcohol outlets and clusters of violence

PubMed Central

2011-01-01

Background Alcohol related violence continues to be a major public health problem in the United States. In particular, there is substantial evidence of an association between alcohol outlets and assault. However, because the specific geographic relationships between alcohol outlets and the distribution of violence remains obscured, it is important to identify the spatial linkages that may exist, enhancing public health efforts to curb both violence and morbidity. Methods The present study utilizes police-recorded data on simple and aggravated assaults in Cincinnati, Ohio. Addresses of alcohol outlets for Cincinnati, including all bars, alcohol-serving restaurants, and off-premise liquor and convenience stores were obtained from the Ohio Division of Liquor Control and geocoded for analysis. A combination of proximity analysis, spatial cluster detection approaches and a geographic information system were used to identify clusters of alcohol outlets and the distribution of violence around them. Results A brief review of the empirical work relating to alcohol outlet density and violence is provided, noting that the majority of this literature is cross-sectional and ecological in nature, yielding a somewhat haphazard and aggregate view of how outlet type(s) and neighborhood characteristics like social organization and land use are related to assaultive violence. The results of the statistical analysis for Cincinnati suggest that while alcohol outlets are not problematic per se, assaultive violence has a propensity to cluster around agglomerations of alcohol outlets. This spatial relationship varies by distance and is also related to the characteristics of the alcohol outlet agglomeration. Specifically, spatially dense distributions of outlets appear to be more prone to clusters of assaultive violence when compared to agglomerations with a lower density of outlets. Conclusion With a more thorough understanding of the spatial relationships between alcohol outlets and the distribution of assaults, policymakers in urban areas can make more informed regulatory decisions regarding alcohol licenses. Further, this research suggests that public health officials and epidemiologists need to develop a better understanding of what actually occurs in and around alcohol outlets, determining what factors (whether outlet, neighborhood, or spatially related) help fuel their relationship with violence and other alcohol-related harm. PMID:21542932

A physical map of the human regulator of complement activation gene cluster linking the complement genes CR1, CR2, DAF, and C4BP

PubMed Central

1988-01-01

We report the organization of the human genes encoding the complement components C4-binding protein (C4BP), C3b/C4b receptor (CR1), decay accelerating factor (DAF), and C3dg receptor (CR2) within the regulator of complement activation (RCA) gene cluster. Using pulsed field gel electrophoresis analysis these genes have been physically linked and aligned as CR1-CR2-DAF-C4BP in an 800-kb DNA segment. The very tight linkage between the CR1 and the C4BP loci, contrasted with the relative long DNA distance between these genes, suggests the existence of mechanisms interfering with recombination within the RCA gene cluster. PMID:2450163

A Clustering-Based Approach to Enriching Code Foraging Environment.

PubMed

Niu, Nan; Jin, Xiaoyu; Niu, Zhendong; Cheng, Jing-Ru C; Li, Ling; Kataev, Mikhail Yu

2016-09-01

Developers often spend valuable time navigating and seeking relevant code in software maintenance. Currently, there is a lack of theoretical foundations to guide tool design and evaluation to best shape the code base to developers. This paper contributes a unified code navigation theory in light of the optimal food-foraging principles. We further develop a novel framework for automatically assessing the foraging mechanisms in the context of program investigation. We use the framework to examine to what extent the clustering of software entities affects code foraging. Our quantitative analysis of long-lived open-source projects suggests that clustering enriches the software environment and improves foraging efficiency. Our qualitative inquiry reveals concrete insights into real developer's behavior. Our research opens the avenue toward building a new set of ecologically valid code navigation tools.

Abell 1763: A Giant Gas Sloshing Spiral But No Cool Core

NASA Astrophysics Data System (ADS)

Douglass, Edmund

2017-09-01

We propose a 76 ksec observation of the z=0.23 galaxy cluster Abell 1763. Previous Chandra data reveals the system as host to a large 950 kpc gas sloshing spiral. Atypical of spiral-hosting clusters, an intact cool core is not detected. Its absence suggests the interaction has led to significant disruption since the onset of core sloshing. The primary cluster is accompanied by two X-ray emitting subsystems. Given the orientation of the spiral, both systems are strong candidates for being the perturber responsible for its formation. Abell 1763 provides us with the rare opportunity to examine an infall event (primary + perturber) resulting in sloshing to the point of core disintegration. Detailed analysis will be performed on the disrupted core, the spiral, and the perturber candidates.

Patterns of comorbidity in community-dwelling older people hospitalised for fall-related injury: A cluster analysis

PubMed Central

2011-01-01

Background Community-dwelling older people aged 65+ years sustain falls frequently; these can result in physical injuries necessitating medical attention including emergency department care and hospitalisation. Certain health conditions and impairments have been shown to contribute independently to the risk of falling or experiencing a fall injury, suggesting that individuals with these conditions or impairments should be the focus of falls prevention. Since older people commonly have multiple conditions/impairments, knowledge about which conditions/impairments coexist in at-risk individuals would be valuable in the implementation of a targeted prevention approach. The objective of this study was therefore to examine the prevalence and patterns of comorbidity in this population group. Methods We analysed hospitalisation data from Victoria, Australia's second most populous state, to estimate the prevalence of comorbidity in patients hospitalised at least once between 2005-6 and 2007-8 for treatment of acute fall-related injuries. In patients with two or more comorbid conditions (multicomorbidity) we used an agglomerative hierarchical clustering method to cluster comorbidity variables and identify constellations of conditions. Results More than one in four patients had at least one comorbid condition and among patients with comorbidity one in three had multicomorbidity (range 2-7). The prevalence of comorbidity varied by gender, age group, ethnicity and injury type; it was also associated with a significant increase in the average cumulative length of stay per patient. The cluster analysis identified five distinct, biologically plausible clusters of comorbidity: cardiopulmonary/metabolic, neurological, sensory, stroke and cancer. The cardiopulmonary/metabolic cluster was the largest cluster among the clusters identified. Conclusions The consequences of comorbidity clustering in terms of falls and/or injury outcomes of hospitalised patients should be investigated by future studies. Our findings have particular relevance for falls prevention strategies, clinical practice and planning of follow-up services for these patients. PMID:21851627

Patterns of comorbidity in community-dwelling older people hospitalised for fall-related injury: a cluster analysis.

PubMed

Vu, Trang; Finch, Caroline F; Day, Lesley

2011-08-18

Community-dwelling older people aged 65+ years sustain falls frequently; these can result in physical injuries necessitating medical attention including emergency department care and hospitalisation. Certain health conditions and impairments have been shown to contribute independently to the risk of falling or experiencing a fall injury, suggesting that individuals with these conditions or impairments should be the focus of falls prevention. Since older people commonly have multiple conditions/impairments, knowledge about which conditions/impairments coexist in at-risk individuals would be valuable in the implementation of a targeted prevention approach. The objective of this study was therefore to examine the prevalence and patterns of comorbidity in this population group. We analysed hospitalisation data from Victoria, Australia's second most populous state, to estimate the prevalence of comorbidity in patients hospitalised at least once between 2005-6 and 2007-8 for treatment of acute fall-related injuries. In patients with two or more comorbid conditions (multicomorbidity) we used an agglomerative hierarchical clustering method to cluster comorbidity variables and identify constellations of conditions. More than one in four patients had at least one comorbid condition and among patients with comorbidity one in three had multicomorbidity (range 2-7). The prevalence of comorbidity varied by gender, age group, ethnicity and injury type; it was also associated with a significant increase in the average cumulative length of stay per patient. The cluster analysis identified five distinct, biologically plausible clusters of comorbidity: cardiopulmonary/metabolic, neurological, sensory, stroke and cancer. The cardiopulmonary/metabolic cluster was the largest cluster among the clusters identified. The consequences of comorbidity clustering in terms of falls and/or injury outcomes of hospitalised patients should be investigated by future studies. Our findings have particular relevance for falls prevention strategies, clinical practice and planning of follow-up services for these patients.

Novel clustering of items from the Autism Diagnostic Interview-Revised to define phenotypes within autism spectrum disorders

PubMed Central

Hu, Valerie W.; Steinberg, Mara E.

2009-01-01

Heterogeneity in phenotypic presentation of ASD has been cited as one explanation for the difficulty in pinpointing specific genes involved in autism. Recent studies have attempted to reduce the “noise” in genetic and other biological data by reducing the phenotypic heterogeneity of the sample population. The current study employs multiple clustering algorithms on 123 item scores from the Autism Diagnostic Interview-Revised (ADI-R) diagnostic instrument of nearly 2000 autistic individuals to identify subgroups of autistic probands with clinically relevant behavioral phenotypes in order to isolate more homogeneous groups of subjects for gene expression analyses. Our combined cluster analyses suggest optimal division of the autistic probands into 4 phenotypic clusters based on similarity of symptom severity across the 123 selected item scores. One cluster is characterized by severe language deficits, while another exhibits milder symptoms across the domains. A third group possesses a higher frequency of savant skills while the fourth group exhibited intermediate severity across all domains. Grouping autistic individuals by multivariate cluster analysis of ADI-R scores reveals meaningful phenotypes of subgroups within the autistic spectrum which we show, in a related (accompanying) study, to be associated with distinct gene expression profiles. PMID:19455643

Stellar Clusters in the NGC 6334 Star-Forming Complex

NASA Astrophysics Data System (ADS)

Feigelson, Eric D.; Martin, Amanda L.; McNeill, Collin J.; Broos, Patrick S.; Garmire, Gordon P.

2009-07-01

The full stellar population of NGC 6334, one of the most spectacular regions of massive star formation in the nearby Galaxy, has not been well sampled in past studies. We analyze here a mosaic of two Chandra X-ray Observatory images of the region using sensitive data analysis methods, giving a list of 1607 faint X-ray sources with arcsecond positions and approximate line-of-sight absorption. About 95% of these are expected to be cluster members, most lower mass pre-main-sequence stars. Extrapolating to low X-ray levels, the total stellar population is estimated to be 20,000-30,000 pre-main-sequence stars. The X-ray sources show a complicated spatial pattern with ~10 distinct star clusters. The heavily obscured clusters are mostly associated with previously known far-infrared sources and radio H II regions. The lightly obscured clusters are mostly newly identified in the X-ray images. Dozens of likely OB stars are found, both in clusters and dispersed throughout the region, suggesting that star formation in the complex has proceeded over millions of years. A number of extraordinarily heavily absorbed X-ray sources are associated with the active regions of star formation.

Economic and Demographic Factors Impacting Placement of Students with Autism

ERIC Educational Resources Information Center

Kurth, Jennifer A.; Mastergeorge, Ann M.; Paschall, Katherine

2016-01-01

Educational placement of students with autism is often associated with child factors, such as IQ and communication skills. However, variability in placement patterns across states suggests that other factors are at play. This study used hierarchical cluster analysis techniques to identify demographic, economic, and educational covariates…

Initial Career and Work Meanings in Seven European Countries.

ERIC Educational Resources Information Center

Claes, Rita; Quintanilla, S. Antonio R.

1994-01-01

Explores initial careers of two target groups of young adults in seven European countries. Career patterns were constructed through cluster analysis on data gathered via self-report. Six career patterns were identified. Offers suggestions for further research and implications for career counseling, career education, and organizational career…

Risk Profiles of Children Entering Residential Care: A Cluster Analysis

ERIC Educational Resources Information Center

Hagaman, Jessica L.; Trout, Alexandra L.; Chmelka, M. Beth; Thompson, Ronald W.; Reid, Robert

2010-01-01

Children in residential care are a heterogeneous population, presenting various combinations of risks. Existing studies on these children suggest high variability across multiple domains (e.g., academics, behavior). Given this heterogeneity, it is important to begin to identify the combinations and patterns of multiple risks, or risk profiles,…

Academic Performance and Lifestyle Behaviors in Australian School Children: A Cluster Analysis.

PubMed

Dumuid, Dorothea; Olds, Timothy; Martín-Fernández, Josep-Antoni; Lewis, Lucy K; Cassidy, Leah; Maher, Carol

2017-12-01

Poor academic performance has been linked with particular lifestyle behaviors, such as unhealthy diet, short sleep duration, high screen time, and low physical activity. However, little is known about how lifestyle behavior patterns (or combinations of behaviors) contribute to children's academic performance. We aimed to compare academic performance across clusters of children with common lifestyle behavior patterns. We clustered participants (Australian children aged 9-11 years, n = 284) into four mutually exclusive groups of distinct lifestyle behavior patterns, using the following lifestyle behaviors as cluster inputs: light, moderate, and vigorous physical activity; sedentary behavior and sleep, derived from 24-hour accelerometry; self-reported screen time and diet. Differences in academic performance (measured by a nationally administered standardized test) were detected across the clusters, with scores being lowest in the Junk Food Screenies cluster (unhealthy diet/high screen time) and highest in the Sitters cluster (high nonscreen sedentary behavior/low physical activity). These findings suggest that reduction in screen time and an improved diet may contribute positively to academic performance. While children with high nonscreen sedentary time performed better academically in this study, they also accumulated low levels of physical activity. This warrants further investigation, given the known physical and mental benefits of physical activity.

Structural evolution of atomically precise thiolated bimetallic [Au(12+n)Cu₃₂(SR)(30+n)]⁴⁻ (n = 0, 2, 4, 6) nanoclusters.

PubMed

Yang, Huayan; Wang, Yu; Yan, Juanzhu; Chen, Xi; Zhang, Xin; Häkkinen, Hannu; Zheng, Nanfeng

2014-05-21

A series of all-thiol stabilized bimetallic Au-Cu nanoclusters, [Au(12+n)Cu32(SR)(30+n)](4-) (n = 0, 2, 4, 6 and SR = SPhCF3), are successfully synthesized and characterized by X-ray single-crystal analysis and density functional theory (DFT) calculations. Each cluster consists of a Keplerate two-shell Au12@Cu20 core protected by (6 - n) units of Cu2(SR)5 and n units of Cu2Au(SR)6 (n = 0, 2, 4, 6) motifs on its surface. The size and structural evolution of the clusters is atomically controlled by the Au precursors and countercations used in the syntheses. The clusters exhibit similar optical absorption properties that are not dependent on the number of surface Cu2Au(SR)6 units. Although DFT suggests an electronic structure with an 18-electron superatom shell closure, the clusters display different thermal stabilities. [Au(12+n)Cu32(SR)(30+n)](4-) clusters with n = 0 and 2 are more stable than those with n = 4 and 6. Moreover, an oxidation product of the clusters, [Au13Cu12(SR)20](4-), is structurally identified to gain insight into how the clusters are oxidized.

Analysis of the electron density features of small boron clusters and the effects of doping with C, P, Al, Si, and Zn: Magic B7P and B8Si clusters

NASA Astrophysics Data System (ADS)

Saha, P.; Rahane, A. B.; Kumar, V.; Sukumar, N.

2016-05-01

Boron atomic clusters show several interesting and unusual size-dependent features due to the small covalent radius, electron deficiency, and higher coordination number of boron as compared to carbon. These include aromaticity and a diverse array of structures such as quasi-planar, ring or tubular shaped, and fullerene-like. In the present work, we have analyzed features of the computed electron density distributions of small boron clusters having up to 11 boron atoms, and investigated the effect of doping with C, P, Al, Si, and Zn atoms on their structural and physical properties, in order to understand the bonding characteristics and discern trends in bonding and stability. We find that in general there are covalent bonds as well as delocalized charge distribution in these clusters. We associate the strong stability of some of these planar/quasiplanar disc-type clusters with the electronic shell closing with effectively twelve delocalized valence electrons using a disc-shaped jellium model. {{{{B}}}9}-, B10, B7P, and B8Si, in particular, are found to be exceptional with very large gaps between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, and these are suggested to be magic clusters.

Classification of Neurons in the Primate Reticular Formation and Changes After Recovery From Pyramidal Tract Lesion.

PubMed

Zaaimi, Boubker; Soteropoulos, Demetris S; Fisher, Karen M; Riddle, C Nicholas; Baker, Stuart N

2018-05-23

The reticular formation is important in primate motor control, both in health and during recovery after brain damage. Little is known about the different neurons present in the reticular nuclei. Here we recorded extracellular spikes from the reticular formation in five healthy female awake behaving monkeys (193 cells), and in two female monkeys one year after recovery from a unilateral pyramidal tract lesion (125 cells). Analysis of spike shape, and four measures derived from the inter-spike interval distribution identified four clusters of neurons in control animals. Cluster 1 cells had slow firing rate; Cluster 2 had narrow spikes, and irregular firing which often included high frequency bursts. Cluster 3 were highly rhythmic and fast firing. Cluster 4 showed negative spikes. A separate population of 42 cells were antidromically identified as reticulospinal neurons in five anesthetized female monkeys. The distribution of spike width in these cells closely overlaid the distribution for cluster 2, leading us tentatively to suggest that cluster 2 included neurons with reticulospinal projections. In animals after corticospinal lesion, cells could be identified in all four clusters. The firing rate of cells in clusters 1 and 2 was increased in lesioned relative to control animals (by 52% and 60%, respectively); cells in cluster 2 were also more regular and more bursting in the lesioned animals. We suggest that changes in both membrane properties and local circuits within the reticular formation occur following lesion, potentially increasing reticulospinal output to help compensate for lost corticospinal descending drive. SIGNIFICANCE STATEMENT This work is the first to sub-classify neurons in the reticular formation, providing insights into the local circuitry of this important but little-understood structure. The approach developed can be applied to any extracellular recording from this region, allowing future studies to place their data within our current framework of four neural types. Changes in reticular neurons may be important to subserve functional recovery after damage in human patients, such as after stroke or spinal cord injury. Copyright © 2018 Zaaimi et al.

On the physical nature of six galactic open cluster candidates

NASA Astrophysics Data System (ADS)

Piatti, A. E.; Clariá, J. J.; Ahumada, A. V.

We present CCD UBVI_(KC) photometry in the fields of the unstudied open cluster (OC) candidates Haffner 3, Haffner 5, NGC 2368, Haffner 25, Hogg 3 and Hogg 4. Our analysis shows that none of these objects are genuine OCs since no clear main sequences or other typical features can be seen in their colour-magnitude and colour-colour diagrams. Star counts performed within and outside the OC candidate fields not only support these results but also suggest that these objects are not OC remnants. A detailed version of this work can be seen in New Astronomy, 16, 161 (2011).

Coupled-cluster treatment of molecular strong-field ionization

NASA Astrophysics Data System (ADS)

Jagau, Thomas-C.

2018-05-01

Ionization rates and Stark shifts of H2, CO, O2, H2O, and CH4 in static electric fields have been computed with coupled-cluster methods in a basis set of atom-centered Gaussian functions with a complex-scaled exponent. Consideration of electron correlation is found to be of great importance even for a qualitatively correct description of the dependence of ionization rates and Stark shifts on the strength and orientation of the external field. The analysis of the second moments of the molecular charge distribution suggests a simple criterion for distinguishing tunnel and barrier suppression ionization in polyatomic molecules.

Bayesian Analysis and Characterization of Multiple Populations in Galactic Globular Clusters

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, Rachel A.; Stenning, David; Sarajedini, Ata; von Hippel, Ted; van Dyk, David A.; Robinson, Elliot; Stein, Nathan; Jefferys, William H.; BASE-9, HST UVIS Globular Cluster Treasury Program

2017-01-01

Globular clusters have long been important tools to unlock the early history of galaxies. Thus, it is crucial we understand the formation and characteristics of the globular clusters (GCs) themselves. Historically, GCs were thought to be simple and largely homogeneous populations, formed via collapse of a single molecular cloud. However, this classical view has been overwhelmingly invalidated by recent work. It is now clear that the vast majority of globular clusters in our Galaxy host two or more chemically distinct populations of stars, with variations in helium and light elements at discrete abundance levels. No coherent story has arisen that is able to fully explain the formation of multiple populations in globular clusters nor the mechanisms that drive stochastic variations from cluster to cluster.We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic Globular Clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of 0.04 to 0.11. Because adequate models varying in CNO are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster. We also find that the proportion of the first population of stars increases with mass. Our results are examined in the context of proposed globular cluster formation scenarios.

Where are Low Mass X-ray Binaries Formed?

NASA Astrophysics Data System (ADS)

Kundu, A.; Maccarone, T. J.; Zepf, S. E.

2004-08-01

Chandra images of nearby galaxies reveal large numbers of low mass X-ray binaries (LMXBs). As in the Galaxy, a significant fraction of these are associated with globular clusters. We exploit the LMXB-globular cluster link in order to probe both the physical properties of globular clusters that promote the formation of LMXBs within clusters with specific characteristics, and to study whether the non-cluster field LMXB population was originally formed in clusters and then released into the field. The large population of globular clusters around nearby galaxies and the range of properties such as age, metallicity and host galaxy environment spanned by these objects enables us to identify and probe the link between these characteristics and the formation of LMXBs. We present the results of our study of a large sample of elliptical and S0 galaxies which reveals among other things that bright LMXBs definitively prefer metal-rich cluster hosts and that this relationship is unlikely to be driven by age effects. The ancestry of the non-cluster field LMXBs is a matter of some debate with suggestions that they they might have formed in the field, or created in globular clusters and then subsequently released into the field either by being ejected from clusters by dynamical processes or as remnants of dynamically destroyed clusters. Each of these scenarios has a specific spatial signature that can be tested by our combined optical and X-ray study. Furthermore, these scenarios predict additional statistical variations that may be driven by the specific host galaxy environment. We present a detailed analysis of our sample galaxies and comment on the probability that the field sources were actually formed in clusters.

Analysis of NFU-1 metallocofactor binding-site substitutions-impacts on iron-sulfur cluster coordination and protein structure and function.

PubMed

Wesley, Nathaniel A; Wachnowsky, Christine; Fidai, Insiya; Cowan, J A

2017-11-01

Iron-sulfur (Fe/S) clusters are ancient prosthetic groups found in numerous metalloproteins and are conserved across all kingdoms of life due to their diverse, yet essential functional roles. Genetic mutations to a specific subset of mitochondrial Fe/S cluster delivery proteins are broadly categorized as disease-related under multiple mitochondrial dysfunction syndrome (MMDS), with symptoms indicative of a general failure of the metabolic system. Multiple mitochondrial dysfunction syndrome 1 (MMDS1) arises as a result of the missense mutation in NFU1, an Fe/S cluster scaffold protein, which substitutes a glycine near the Fe/S cluster-binding pocket to a cysteine (p.Gly208Cys). This substitution has been shown to promote protein dimerization such that cluster delivery to NFU1 is blocked, preventing downstream cluster trafficking. However, the possibility of this additional cysteine, located adjacent to the cluster-binding site, serving as an Fe/S cluster ligand has not yet been explored. To fully understand the consequences of this Gly208Cys replacement, complementary substitutions at the Fe/S cluster-binding pocket for native and Gly208Cys NFU1 were made, along with six other variants. Herein, we report the results of an investigation on the effect of these substitutions on both cluster coordination and NFU1 structure and function. The data suggest that the G208C substitution does not contribute to cluster binding. Rather, replacement of the glycine at position 208 changes the oligomerization state as a result of global structural alterations that result in the downstream effects manifest as MMDS1, but does not perturb the coordination chemistry of the Fe-S cluster. © 2017 Federation of European Biochemical Societies.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Analysis of initial changes in the proteins of soybean root tip under flooding stress using gel-free and gel-based proteomic techniques.

PubMed

Yin, Xiaojian; Sakata, Katsumi; Nanjo, Yohei; Komatsu, Setsuko

2014-06-25

Flooding has a severe negative effect on soybean cultivation in the early stages of growth. To obtain a better understanding of the response mechanisms of soybean to flooding stress, initial changes in root tip proteins under flooding were analyzed using two proteomic techniques. Two-day-old soybeans were treated with flooding for 3, 6, 12, and 24h. The weight of soybeans increased during the first 3h of flooding, but root elongation was not observed. Using gel-based and gel-free proteomic techniques, 115 proteins were identified in root tips, of which 9 proteins were commonly detected by both methods. The 71 proteins identified by the gel-free proteomics were analyzed by a hierarchical clustering method based on induction levels during the flooding, and the proteins were divided into 5 clusters. Additional interaction analysis of the proteins revealed that ten proteins belonging to cluster I formed the center of a protein interaction network. mRNA expression analysis of these ten proteins showed that citrate lyase and heat shock protein 70 were down-regulated, whereas calreticulin was up-regulated in initial phase of flooding. These results suggest that flooding stress to soybean induces calcium-related signal transduction, which might play important roles in the early responses to flooding. Flooding has a severe negative effect on soybean cultivation, particularly in the early stages of growth. To better understand the response mechanisms of soybean to the early stages of flooding stress, two proteomic techniques were used. Two-day-old soybeans were treated without or with flooding for 3, 6, 12, and 24h. The fresh weight of soybeans increased during the first 3h of flooding stress, but the growth then slowed and no root elongation was observed. Using gel-based and gel-free proteomic techniques, 115 proteins were identified in root tips, of which 9 proteins were commonly detected by both methods. The 71 proteins identified by the gel-free proteomics were analyzed by a hierarchical clustering method based on induction levels during the flooding stress, and 5 protein clusters were recognized. Protein interaction analysis revealed that ten proteins belonging to cluster I formed the center of a protein interaction network. mRNA expression analysis of these ten proteins showed that citrate lyase and heat shock protein 70 were down-regulated in response to flooding stress, whereas calreticulin was up-regulated. These results suggest that flooding stress to soybean induces calcium-related signal transduction, which might play important roles in the early responses to flooding. Copyright © 2014 Elsevier B.V. All rights reserved.

Poly-Small Ubiquitin-like Modifier (PolySUMO)-binding Proteins Identified through a String Search*

PubMed Central

Sun, Huaiyu; Hunter, Tony

2012-01-01

Polysumoylation is a crucial cellular response to stresses against genomic integrity or proteostasis. Like the small ubiquitin-like modifier (SUMO)-targeted ubiquitin ligase RNF4, proteins with clustered SUMO-interacting motifs (SIMs) can be important signal transducers downstream of polysumoylation. To identify novel polySUMO-binding proteins, we conducted a computational string search with a custom Python script. We found clustered SIMs in another RING domain protein Arkadia/RNF111. Detailed biochemical analysis of the Arkadia SIMs revealed that dominant SIMs in a SIM cluster often contain a pentameric VIDLT ((V/I/L/F/Y)(V/I)DLT) core sequence that is also found in the SIMs in PIAS family E3s and is likely the best-fitted structure for SUMO recognition. This idea led to the identification of additional novel SIM clusters in FLASH/CASP8AP2, C5orf25, and SOBP/JXC1. We suggest that the clustered SIMs in these proteins form distinct SUMO binding domains to recognize diverse forms of protein sumoylation. PMID:23086935

Analysis of genetic association in Listeria and Diabetes using Hierarchical Clustering and Silhouette Index

NASA Astrophysics Data System (ADS)

Pagnuco, Inti A.; Pastore, Juan I.; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L.

2016-04-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, where significative groups of genes are defined based on some criteria. This task is usually performed by clustering algorithms, where the whole family of genes, or a subset of them, are clustered into meaningful groups based on their expression values in a set of experiment. In this work we used a methodology based on the Silhouette index as a measure of cluster quality for individual gene groups, and a combination of several variants of hierarchical clustering to generate the candidate groups, to obtain sets of co-expressed genes for two real data examples. We analyzed the quality of the best ranked groups, obtained by the algorithm, using an online bioinformatics tool that provides network information for the selected genes. Moreover, to verify the performance of the algorithm, considering the fact that it doesn’t find all possible subsets, we compared its results against a full search, to determine the amount of good co-regulated sets not detected.

STRONG GRAVITATIONAL LENSING BY THE SUPER-MASSIVE cD GALAXY IN ABELL 3827

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carrasco, E. R.; Gomez, P. L.; Lee, H.

2010-06-01

We have discovered strong gravitational lensing features in the core of the nearby cluster Abell 3827 by analyzing Gemini South GMOS images. The most prominent strong lensing feature is a highly magnified, ring-shaped configuration of four images around the central cD galaxy. GMOS spectroscopic analysis puts this source at z {approx} 0.2. Located {approx}20'' away from the central galaxy is a secondary tangential arc feature which has been identified as a background galaxy with z {approx} 0.4. We have modeled the gravitational potential of the cluster core, taking into account the mass from the cluster, the brightest cluster galaxy (BCG),more » and other galaxies. We derive a total mass of (2.7 {+-} 0.4) x 10{sup 13} M {sub sun} within 37 h {sup -1} kpc. This mass is an order of magnitude larger than that derived from X-ray observations. The total mass derived from lensing data suggests that the BCG in this cluster is perhaps the most massive galaxy in the nearby universe.« less

An inventory of publications on electronic medical records revisited.

PubMed

Moorman, P W; Schuemie, M J; van der Lei, J

2009-01-01

In this short review we provide an update of our earlier inventories of publications indexed in MedLine with the MeSH term 'Medical Records Systems, Computerized'. We retrieved and analyzed all references to English articles published before January 1, 2008, and indexed in PubMed with the MeSH term 'Medical Records Systems, Computerized'. We retrieved a total of 11,924 publications, of which 3937 (33%) appeared in a journal with an impact factor. Since 2002 the number of yearly publications, and the number of journals in which those publications appeared, increased. A cluster analysis revealed three clusters: an organizational issues cluster, a technically oriented cluster and a cluster about order-entry and research. Although our previous inventory in 2003 suggested a constant yearly production of publications on electronic medical records since 1998, the current inventory shows another rise in production since 2002. In addition, many new journals and countries have shown interest during the last five years. In the last 15 years, interest in organizational issues remained fairly constant, order entry and research with systems gained attention, while interest in technical issues relatively decreased.

Amplification of the entire kanamycin biosynthetic gene cluster during empirical strain improvement of Streptomyces kanamyceticus.

PubMed

Yanai, Koji; Murakami, Takeshi; Bibb, Mervyn

2006-06-20

Streptomyces kanamyceticus 12-6 is a derivative of the wild-type strain developed for industrial kanamycin (Km) production. Southern analysis and DNA sequencing revealed amplification of a large genomic segment including the entire Km biosynthetic gene cluster in the chromosome of strain 12-6. At 145 kb, the amplifiable unit of DNA (AUD) is the largest AUD reported in Streptomyces. Striking repetitive DNA sequences belonging to the clustered regularly interspaced short palindromic repeats family were found in the AUD and may play a role in its amplification. Strain 12-6 contains a mixture of different chromosomes with varying numbers of AUDs, sometimes exceeding 36 copies and producing an amplified region >5.7 Mb. The level of Km production depended on the copy number of the Km biosynthetic gene cluster, suggesting that DNA amplification occurred during strain improvement as a consequence of selection for increased Km resistance. Amplification of DNA segments including entire antibiotic biosynthetic gene clusters might be a common mechanism leading to increased antibiotic production in industrial strains.

Using Geographic Information Systems and Spatial Analysis Methods to Assess Household Water Access and Sanitation Coverage in the SHINE Trial.

PubMed

Ntozini, Robert; Marks, Sara J; Mangwadu, Goldberg; Mbuya, Mduduzi N N; Gerema, Grace; Mutasa, Batsirai; Julian, Timothy R; Schwab, Kellogg J; Humphrey, Jean H; Zungu, Lindiwe I

2015-12-15

Access to water and sanitation are important determinants of behavioral responses to hygiene and sanitation interventions. We estimated cluster-specific water access and sanitation coverage to inform a constrained randomization technique in the SHINE trial. Technicians and engineers inspected all public access water sources to ascertain seasonality, function, and geospatial coordinates. Households and water sources were mapped using open-source geospatial software. The distance from each household to the nearest perennial, functional, protected water source was calculated, and for each cluster, the median distance and the proportion of households within <500 m and >1500 m of such a water source. Cluster-specific sanitation coverage was ascertained using a random sample of 13 households per cluster. These parameters were included as covariates in randomization to optimize balance in water and sanitation access across treatment arms at the start of the trial. The observed high variability between clusters in both parameters suggests that constraining on these factors was needed to reduce risk of bias. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America.

Viscous self interacting dark matter and cosmic acceleration

NASA Astrophysics Data System (ADS)

Atreya, Abhishek; Bhatt, Jitesh R.; Mishra, Arvind

2018-02-01

Self interacting dark matter (SIDM) provides us with a consistent solution to certain astrophysical observations in conflict with collision-less cold DM paradigm. In this work we estimate the shear viscosity (η) and bulk viscosity (ζ) of SIDM, within kinetic theory formalism, for galactic and cluster size SIDM halos. To that extent we make use of the recent constraints on SIDM cross-section for the dwarf galaxies, LSB galaxies and clusters. We also estimate the change in solution of Einstein's equation due to these viscous effects and find that σ/m constraints on SIDM from astrophysical data provide us with sufficient viscosity to account for the observed cosmic acceleration at present epoch, without the need of any additional dark energy component. Using the estimates of dark matter density for galactic and cluster size halo we find that the mean free path of dark matter ~ few Mpc. Thus the smallest scale at which the viscous effect start playing the role is cluster scale. Astrophysical data for dwarf, LSB galaxies and clusters also seems to suggest the same. The entire analysis is independent of any specific particle physics motivated model for SIDM.

Human avian influenza in Indonesia: are they really clustered?

PubMed

Eyanoer, Putri Chairani; Singhasivanon, Pratap; Kaewkungwal, Jaranit; Apisarnthanarak, Anucha

2011-05-01

Understanding the epidemiology of human H5N1 cases in Indonesia is important. The question of whether cases are clustered or not is unclear. An increase in clustered cases suggests greater transmissibility. In the present study, 107 confirmed and 302 suspected human H5N1 cases in Indonesia during 2005-2007 were analyzed for spatial and temporal distribution. Most confirmed cases (97.2%) occurred on two main islands (Java and Sumatera). There were no patterns of disease occurrence over time. There were also no correlations between occurrence patterns in humans and poultry. Statistical analysis showed confirmed cases were clustered within an area on Java island covered by 8 districts along the border of three neighboring provinces (Jakarta, West Java, and Banten). This study shows human H5N1 cases in Indonesia were clustered at two sites where there was a high rate of infection among poultry. These findings are important since they highlight areas of high risk for possible human H5N1 infection in Indonesia, thus, preventive measures may be taken.

Race, deprivation, and immigrant isolation: The spatial demography of air-toxic clusters in the continental United States.

PubMed

Liévanos, Raoul S

2015-11-01

This article contributes to environmental inequality outcomes research on the spatial and demographic factors associated with cumulative air-toxic health risks at multiple geographic scales across the United States. It employs a rigorous spatial cluster analysis of census tract-level 2005 estimated lifetime cancer risk (LCR) of ambient air-toxic emissions from stationary (e.g., facility) and mobile (e.g., vehicular) sources to locate spatial clusters of air-toxic LCR risk in the continental United States. It then tests intersectional environmental inequality hypotheses on the predictors of tract presence in air-toxic LCR clusters with tract-level principal component factor measures of economic deprivation by race and immigrant status. Logistic regression analyses show that net of controls, isolated Latino immigrant-economic deprivation is the strongest positive demographic predictor of tract presence in air-toxic LCR clusters, followed by black-economic deprivation and isolated Asian/Pacific Islander immigrant-economic deprivation. Findings suggest scholarly and practical implications for future research, advocacy, and policy. Copyright © 2015 Elsevier Inc. All rights reserved.

Rising prevalence of non-B HIV-1 subtypes in North Carolina and evidence for local onward transmission.

PubMed

Dennis, Ann M; Hué, Stephane; Learner, Emily; Sebastian, Joseph; Miller, William C; Eron, Joseph J

2017-01-01

HIV-1 diversity is increasing in North American and European cohorts which may have public health implications. However, little is known about non-B subtype diversity in the southern United States, despite the region being the epicenter of the nation's epidemic. We characterized HIV-1 diversity and transmission clusters to identify the extent to which non-B strains are transmitted locally. We conducted cross-sectional analyses of HIV-1 partial pol sequences collected from 1997 to 2014 from adults accessing routine clinical care in North Carolina (NC). Subtypes were evaluated using COMET and phylogenetic analysis. Putative transmission clusters were identified using maximum-likelihood trees. Clusters involving non-B strains were confirmed and their dates of origin were estimated using Bayesian phylogenetics. Data were combined with demographic information collected at the time of sample collection and country of origin for a subset of patients. Among 24,972 sequences from 15,246 persons, the non-B subtype prevalence increased from 0% to 3.46% over the study period. Of 325 persons with non-B subtypes, diversity was high with over 15 pure subtypes and recombinants; subtype C (28.9%) and CRF02_AG (24.0%) were most common. While identification of transmission clusters was lower for persons with non-B versus B subtypes, several local transmission clusters (≥3 persons) involving non-B subtypes were identified and all were presumably due to heterosexual transmission. Prevalence of non-B subtype diversity remains low in NC but a statistically significant rise was identified over time which likely reflects multiple importation. However, the combined phylogenetic clustering analysis reveals evidence for local onward transmission. Detection of these non-B clusters suggests heterosexual transmission and may guide diagnostic and prevention interventions.

Characterization of distinct Arctic aerosol accumulation modes and their sources

NASA Astrophysics Data System (ADS)

Lange, R.; Dall'Osto, M.; Skov, H.; Nøjgaard, J. K.; Nielsen, I. E.; Beddows, D. C. S.; Simo, R.; Harrison, R. M.; Massling, A.

2018-06-01

In this work we use cluster analysis of long term particle size distribution data to expand an array of different shorter term atmospheric measurements, thereby gaining insights into longer term patterns and properties of Arctic aerosol. Measurements of aerosol number size distributions (9-915 nm) were conducted at Villum Research Station (VRS), Station Nord in North Greenland during a 5 year record (2012-2016). Alongside this, measurements of aerosol composition, meteorological parameters, gaseous compounds and cloud condensation nuclei (CCN) activity were performed during different shorter occasions. K-means clustering analysis of particle number size distributions on daily basis identified several clusters. Clusters of accumulation mode aerosols (main size modes > 100 nm) accounted for 56% of the total aerosol during the sampling period (89-91% during February-April, 1-3% during June-August). By association to chemical composition, cloud condensation nuclei properties, and meteorological variables, three typical accumulation mode aerosol clusters were identified: Haze (32% of the time), Bimodal (14%) and Aged (6%). In brief: (1) Haze accumulation mode aerosol shows a single mode at 150 nm, peaking in February-April, with highest loadings of sulfate and black carbon concentrations. (2) Accumulation mode Bimodal aerosol shows two modes, at 38 nm and 150 nm, peaking in June-August, with the highest ratio of organics to sulfate concentrations. (3) Aged accumulation mode aerosol shows a single mode at 213 nm, peaking in September-October and is associated with cloudy and humid weather conditions during autumn. The three aerosol clusters were considered alongside CCN concentrations. We suggest that organic compounds, that are likely marine biogenic in nature, greatly influence the Bimodal cluster and contribute significantly to its CCN activity. This stresses the importance of better characterizing the marine ecosystem and the aerosol-mediated climate effects in the Arctic.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra

NASA Astrophysics Data System (ADS)

Unglert, K.; Radić, V.; Jellinek, A. M.

2016-06-01

Variations in the spectral content of volcano seismicity related to changes in volcanic activity are commonly identified manually in spectrograms. However, long time series of monitoring data at volcano observatories require tools to facilitate automated and rapid processing. Techniques such as self-organizing maps (SOM) and principal component analysis (PCA) can help to quickly and automatically identify important patterns related to impending eruptions. For the first time, we evaluate the performance of SOM and PCA on synthetic volcano seismic spectra constructed from observations during two well-studied eruptions at Klauea Volcano, Hawai'i, that include features observed in many volcanic settings. In particular, our objective is to test which of the techniques can best retrieve a set of three spectral patterns that we used to compose a synthetic spectrogram. We find that, without a priori knowledge of the given set of patterns, neither SOM nor PCA can directly recover the spectra. We thus test hierarchical clustering, a commonly used method, to investigate whether clustering in the space of the principal components and on the SOM, respectively, can retrieve the known patterns. Our clustering method applied to the SOM fails to detect the correct number and shape of the known input spectra. In contrast, clustering of the data reconstructed by the first three PCA modes reproduces these patterns and their occurrence in time more consistently. This result suggests that PCA in combination with hierarchical clustering is a powerful practical tool for automated identification of characteristic patterns in volcano seismic spectra. Our results indicate that, in contrast to PCA, common clustering algorithms may not be ideal to group patterns on the SOM and that it is crucial to evaluate the performance of these tools on a control dataset prior to their application to real data.

Time-dependent risks of cancer clustering among couples: a nationwide population-based cohort study in Taiwan.

PubMed

Wang, Jong-Yi; Liang, Yia-Wen; Yeh, Chun-Chen; Liu, Chiu-Shong; Wang, Chen-Yu

2018-02-21

Spousal clustering of cancer warrants attention. Whether the common environment or high-age vulnerability determines cancer clustering is unclear. The risk of clustering in couples versus non-couples is undetermined. The time to cancer clustering after the first cancer diagnosis is yet to be reported. This study investigated cancer clustering over time among couples by using nationwide data. A cohort of 5643 married couples in the 2002-2013 Taiwan National Health Insurance Research Database was identified and randomly matched with 5643 non-couple pairs through dual propensity score matching. Factors associated with clustering (both spouses with tumours) were analysed by using the Cox proportional hazard model. Propensity-matched analysis revealed that the risk of clustering of all tumours among couples (13.70%) was significantly higher than that among non-couples (11.84%) (OR=1.182, 95% CI 1.058 to 1.321, P=0.0031). The median time to clustering of all tumours and of malignant tumours was 2.92 and 2.32 years, respectively. Risk characteristics associated with clustering included high age and comorbidity. Shared environmental factors among spouses might be linked to a high incidence of cancer clustering. Cancer incidence in one spouse may signal cancer vulnerability in the other spouse. Promoting family-oriented cancer care in vulnerable families and preventing shared lifestyle risk factors for cancer are suggested. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Enhancement of numeric cognition in children with low achievement in mathematic after a non-instrumental musical training.

PubMed

Ribeiro, Fabiana Silva; Santos, Flávia H

2017-03-01

Studies suggest that musical training enhances spatial-temporal reasoning and leads to greater learning of mathematical concepts. The aim of this prospective study was to verify the efficacy of a Non-Instrumental Musical Training (NIMT) on the Numerical Cognition systems in children with low achievement in math. For this purpose, we examined, with a cluster analysis, whether children with low scores on Numerical Cognition would be grouped in the same cluster at pre and post-NIMT. Participants were primary school children divided into two groups according to their scores on an Arithmetic test. Results with a specialized battery of Numerical Cognition revealed improvements for Cluster 2 (children with low achievement in math) especially for number production capacity compared to normative data. Besides, the number of children with low scores in Numerical Cognition decreased at post-NIMT. These findings suggest that NIMT enhances Numerical Cognition and seems to be a useful tool for rehabilitation of children with low achievement in math. Copyright © 2016 Elsevier Ltd. All rights reserved.

ICAP - An Interactive Cluster Analysis Procedure for analyzing remotely sensed data

NASA Technical Reports Server (NTRS)

Wharton, S. W.; Turner, B. J.

1981-01-01

An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. ICAP differs from conventional clustering algorithms by allowing the analyst to optimize the cluster configuration by inspection, rather than by manipulating process parameters. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters, and the analyst, who can evaluate and elect to modify the cluster structure. Clusters can be deleted, or lumped together pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The principal advantage of this approach is that it allows prior information (when available) to be used directly in the analysis, since the analyst interacts with ICAP in a straightforward manner, using basic terms with which he is more likely to be familiar. Results from testing ICAP showed that an informed use of ICAP can improve classification, as compared to an existing cluster analysis procedure.

White Matter Tract Integrity in Alzheimer's Disease vs. Late Onset Bipolar Disorder and Its Correlation with Systemic Inflammation and Oxidative Stress Biomarkers.

PubMed

Besga, Ariadna; Chyzhyk, Darya; Gonzalez-Ortega, Itxaso; Echeveste, Jon; Graña-Lecuona, Marina; Graña, Manuel; Gonzalez-Pinto, Ana

2017-01-01

Background: Late Onset Bipolar Disorder (LOBD) is the development of Bipolar Disorder (BD) at an age above 50 years old. It is often difficult to differentiate from other aging dementias, such as Alzheimer's Disease (AD), because they share cognitive and behavioral impairment symptoms. Objectives: We look for WM tract voxel clusters showing significant differences when comparing of AD vs. LOBD, and its correlations with systemic blood plasma biomarkers (inflammatory, neurotrophic factors, and oxidative stress). Materials: A sample of healthy controls (HC) ( n = 19), AD patients ( n = 35), and LOBD patients ( n = 24) was recruited at the Alava University Hospital. Blood plasma samples were obtained at recruitment time and analyzed to extract the inflammatory, oxidative stress, and neurotrophic factors. Several modalities of MRI were acquired for each subject, Methods: Fractional anisotropy (FA) coefficients are obtained from diffusion weighted imaging (DWI). Tract based spatial statistics (TBSS) finds FA skeleton clusters of WM tract voxels showing significant differences for all possible contrasts between HC, AD, and LOBD. An ANOVA F -test over all contrasts is carried out. Results of F -test are used to mask TBSS detected clusters for the AD > LOBD and LOBD > AD contrast to select the image clusters used for correlation analysis. Finally, Pearson's correlation coefficients between FA values at cluster sites and systemic blood plasma biomarker values are computed. Results: The TBSS contrasts with by ANOVA F -test has identified strongly significant clusters in the forceps minor, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and cingulum gyrus. The correlation analysis of these tract clusters found strong negative correlation of AD with the nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) blood biomarkers. Negative correlation of AD and positive correlation of LOBD with inflammation biomarker IL6 was also found. Conclusion: TBSS voxel clusters tract atlas localizations are consistent with greater behavioral impairment and mood disorders in LOBD than in AD. Correlation analysis confirms that neurotrophic factors (i.e., NGF, BDNF) play a great role in AD while are absent in LOBD pathophysiology. Also, correlation results of IL1 and IL6 suggest stronger inflammatory effects in LOBD than in AD.

The relationship between leadership, teamworking, structure, burnout and attitude to patients on acute psychiatric wards

PubMed Central

Nijman, Henk; Simpson, Alan; Jones, Julia

2010-01-01

Background Conflict (aggression, substance use, absconding, etc.) and containment (coerced medication, manual restraint, etc.) threaten the safety of patients and staff on psychiatric wards. Previous work has suggested that staff variables may be significant in explaining differences between wards in their rates of these behaviours, and that structure (ward organisation, rules and daily routines) might be the most critical of these. This paper describes the exploration of a large dataset to assess the relationship between structure and other staff variables. Methods A multivariate cross-sectional design was utilised. Data were collected from staff on 136 acute psychiatric wards in 26 NHS Trusts in England, measuring leadership, teamwork, structure, burnout and attitudes towards difficult patients. Relationships between these variables were explored through principal components analysis (PCA), structural equation modelling and cluster analysis. Results Principal components analysis resulted in the identification of each questionnaire as a separate factor, indicating that the selected instruments assessed a number of non-overlapping items relevant for ward functioning. Structural equation modelling suggested a linear model in which leadership influenced teamwork, teamwork structure; structure burnout; and burnout feelings about difficult patients. Finally, cluster analysis identified two significantly distinct groups of wards: the larger of which had particularly good leadership, teamwork, structure, attitudes towards patients and low burnout; and the second smaller proportion which was poor on all variables and high on burnout. The better functioning cluster of wards had significantly lower rates of containment events. Conclusion The overall performance of staff teams is associated with differing rates of containment on wards. Interventions to reduce rates of containment on wards may need to address staff issues at every level, from leadership through to staff attitudes. PMID:20082064

U.S. consumer demand for restaurant calorie information: targeting demographic and behavioral segments in labeling initiatives.

PubMed

Kolodinsky, Jane; Reynolds, Travis William; Cannella, Mark; Timmons, David; Bromberg, Daniel

2009-01-01

To identify different segments of U.S. consumers based on food choices, exercise patterns, and desire for restaurant calorie labeling. Using a stratified (by region) random sample of the U.S. population, trained interviewers collected data for this cross-sectional study through telephone surveys. Center for Rural Studies U.S. national health survey. The final sample included 580 responses (22% response rate); data were weighted to be representative of age and gender characteristics of the U.S. population. Self-reported behaviors related to food choices, exercise patterns, desire for calorie information in restaurants, and sample demographics. Clusters were identified using Schwartz Bayesian criteria. Impacts of demographic characteristics on cluster membership were analyzed using bivariate tests of association and multinomial logit regression. Cluster analysis revealed three clusters based on respondents' food choices, activity levels, and desire for restaurant labeling. Two clusters, comprising three quarters of the sample, desired calorie labeling in restaurants. The remaining cluster opposed restaurant labeling. Demographic variables significantly predicting cluster membership included region of residence (p < .10), income (p < .05), gender (p < .01), and age (p < .10). Though limited by a low response and potential self-reporting bias in the phone survey, this study suggests that several groups are likely to benefit from restaurant calorie labeling. Specific demographic clusters could be targeted through labeling initiatives.

Gas Sloshing Regulates and Records the Evolution of the Fornax Cluster

NASA Astrophysics Data System (ADS)

Su, Yuanyuan; Nulsen, Paul E. J.; Kraft, Ralph P.; Roediger, Elke; ZuHone, John A.; Jones, Christine; Forman, William R.; Sheardown, Alex; Irwin, Jimmy A.; Randall, Scott W.

2017-12-01

We present results of a joint Chandra and XMM-Newton analysis of the Fornax Cluster, the nearest galaxy cluster in the southern sky. Signatures of merger-induced gas sloshing can be seen in the X-ray image. We identify four sloshing cold fronts in the intracluster medium, residing at radii of 3 kpc (west), 10 kpc (northeast), 30 kpc (southwest), and 200 kpc (east). Despite spanning over two orders of magnitude in radius, all four cold fronts fall onto the same spiral pattern that wraps around the BCG NGC 1399, likely all initiated by the infall of NGC 1404. The most evident front is to the northeast, 10 kpc from the cluster center, which separates low-entropy high-metallicity gas and high-entropy low-metallicity gas. The metallicity map suggests that gas sloshing, rather than an AGN outburst, is the driving force behind the redistribution of the enriched gas in this cluster. The innermost cold front resides within the radius of the strong cool core. The sloshing timescale within the cooling radius, calculated from the Brunt–Väsälä frequency, is an order of magnitude shorter than the cooling time. It is plausible that gas sloshing is contributing to the heating of the cool core, provided that gas of different entropies can be mixed effectively via Kelvin–Helmholtz instability. The estimated age of the outermost front suggests that this is not the first infall of NGC 1404.

The nature, origin and evolution of embedded star clusters

NASA Technical Reports Server (NTRS)

Lada, Charles J.; Lada, Elizabeth A.

1991-01-01

The recent development of imaging infrared array cameras has enabled the first systematic studies of embedded protoclusters in the galaxy. Initial investigations suggest that rich embedded clusters are quite numerous and that a significant fraction of all stars formed in the galaxy may begin their lives in such stellar systems. These clusters contain extremely young stellar objects and are important laboratories for star formation research. However, observational and theoretical considerations suggest that most embedded clusters do not survive emergence from molecular clouds as bound clusters. Understanding the origin, nature, and evolution of embedded clusters requires understanding the intimate physical relation between embedded clusters and the dense molecular cloud cores from which they form.

TWO-STAGE FRAGMENTATION FOR CLUSTER FORMATION: ANALYTICAL MODEL AND OBSERVATIONAL CONSIDERATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Nicole D.; Basu, Shantanu, E-mail: nwityk@uwo.ca, E-mail: basu@uwo.ca

2012-12-10

Linear analysis of the formation of protostellar cores in planar magnetic interstellar clouds shows that molecular clouds exhibit a preferred length scale for collapse that depends on the mass-to-flux ratio and neutral-ion collision time within the cloud. We extend this linear analysis to the context of clustered star formation. By combining the results of the linear analysis with a realistic ionization profile for the cloud, we find that a molecular cloud may evolve through two fragmentation events in the evolution toward the formation of stars. Our model suggests that the initial fragmentation into clumps occurs for a transcritical cloud onmore » parsec scales while the second fragmentation can occur for transcritical and supercritical cores on subparsec scales. Comparison of our results with several star-forming regions (Perseus, Taurus, Pipe Nebula) shows support for a two-stage fragmentation model.« less

A description of how metal pollution occurs in the Tinto-Odiel rias (Huelva-Spain) through the application of cluster analysis.

PubMed

Grande, J A; Borrego, J; Morales, J A; de la Torre, M L

2003-04-01

In the last few decades, the study of space-time distribution and variations of heavy metals in estuaries has been extensively studied as an environmental indicator. In the case described here, the combination of acid water from mines, industrial effluents and sea water plays a determining role in the evolutionary process of the chemical makeup of the water in the estuary of the Tinto and Odiel Rivers, located in the southwest of the Iberian Peninsula. Based on the statistical treatment of the data from the analysis of the water samples from this system, which has been affected by processes of industrial and mining pollution, the 16 variables analyzed can be grouped into two large families. Each family presents high, positive Pearson r values that suggest common origins (fluvial or sea) for the pollutants present in the water analyzed and allow their subsequent contrast through cluster analysis.

Genetic relatedness between oral and intestinal isolates of Porphyromonas endodontalis by analysis of random amplified polymorphic DNA.

PubMed

Gonçalves, R B; Väisänen, M L; Van Steenbergen, T J; Sundqvist, G; Mouton, C

1999-01-01

Genomic fingerprints from the DNA of 27 strains of Porphyromonas endodontalis from diverse clinical and geographic origins were generated as random amplified polymorphic DNA (RAPD) using the technique of PCR amplification with a single primer of arbitrary sequence. Cluster analysis of the combined RAPD data obtained with three selected 9- or 10-mer-long primers identified 25 distinct RAPD types which clustered as three main groups identifying three genogroups. Genogroups I and II included exclusively P. endodontalis isolates of oral origin, while 7/9 human intestinal strains of genogroup III which linked at a similarity level of 52% constituted the most homogeneous group in our study. Genotypic diversity within P. endodontalis, as shown by RAPD analysis, suggests that the taxon is composed of two oral genogroups and one intestinal genogroup. This hypothesis remains to be confirmed.

Genomic analysis of coxsackieviruses A1, A19, A22, enteroviruses 113 and 104: viruses representing two clades with distinct tropism within enterovirus C

PubMed Central

Haq, Saddef; Sameroff, Stephen; Howie, Stephen R. C.; Lipkin, W. Ian

2013-01-01

Coxsackieviruses (CV) A1, CV-A19 and CV-A22 have historically comprised a distinct phylogenetic clade within Enterovirus (EV) C. Several novel serotypes that are genetically similar to these three viruses have been recently discovered and characterized. Here, we report the coding sequence analysis of two genotypes of a previously uncharacterized serotype EV-C113 from Bangladesh and demonstrate that it is most similar to CV-A22 and EV-C116 within the capsid region. We sequenced novel genotypes of CV-A1, CV-A19 and CV-A22 from Bangladesh and observed a high rate of recombination within this group. We also report genomic analysis of the rarely reported EV-C104 circulating in the Gambia in 2009. All available EV-C104 sequences displayed a high degree of similarity within the structural genes but formed two clusters within the non-structural genes. One cluster included the recently reported EV-C117, suggesting an ancestral recombination between these two serotypes. Phylogenetic analysis of all available complete genome sequences indicated the existence of two subgroups within this distinct Enterovirus C clade: one has been exclusively recovered from gastrointestinal samples, while the other cluster has been implicated in respiratory disease. PMID:23761409

A cluster analysis on road traffic accidents using genetic algorithms

NASA Astrophysics Data System (ADS)

Saharan, Sabariah; Baragona, Roberto

2017-04-01

The analysis of traffic road accidents is increasingly important because of the accidents cost and public road safety. The availability or large data sets makes the study of factors that affect the frequency and severity accidents are viable. However, the data are often highly unbalanced and overlapped. We deal with the data set of the road traffic accidents recorded in Christchurch, New Zealand, from 2000-2009 with a total of 26440 accidents. The data is in a binary set and there are 50 factors road traffic accidents with four level of severity. We used genetic algorithm for the analysis because we are in the presence of a large unbalanced data set and standard clustering like k-means algorithm may not be suitable for the task. The genetic algorithm based on clustering for unknown K, (GCUK) has been used to identify the factors associated with accidents of different levels of severity. The results provided us with an interesting insight into the relationship between factors and accidents severity level and suggest that the two main factors that contributes to fatal accidents are "Speed greater than 60 km h" and "Did not see other people until it was too late". A comparison with the k-means algorithm and the independent component analysis is performed to validate the results.

Organic carbon and nitrogen availability determine bacterial community composition in paddy fields of the Indo-Gangetic plain.

PubMed

Kumar, Arvind; Rai, Lal Chand

2017-07-01

Soil quality is an important factor and maintained by inhabited microorganisms. Soil physicochemical characteristics determine indigenous microbial population and rice provides food security to major population of the world. Therefore, this study aimed to assess the impact of physicochemical variables on bacterial community composition and diversity in conventional paddy fields which could reflect a real picture of the bacterial communities operating in the paddy agro-ecosystem. To fulfill the objective; soil physicochemical characterization, bacterial community composition and diversity analysis was carried out using culture-independent PCR-DGGE method from twenty soils distributed across eight districts. Bacterial communities were grouped into three clusters based on UPGMA cluster analysis of DGGE banding pattern. The linkage of measured physicochemical variables with bacterial community composition was analyzed by canonical correspondence analysis (CCA). CCA ordination biplot results were similar to UPGMA cluster analysis. High levels of species-environment correlations (0.989 and 0.959) were observed and the largest proportion of species data variability was explained by total organic carbon (TOC), available nitrogen, total nitrogen and pH. Thus, results suggest that TOC and nitrogen are key regulators of bacterial community composition in the conventional paddy fields. Further, high diversity indices and evenness values demonstrated heterogeneity and co-abundance of the bacterial communities.

High diversity and rapid diversification in the head louse, Pediculus humanus (Pediculidae: Phthiraptera)

PubMed Central

Ashfaq, Muhammad; Prosser, Sean; Nasir, Saima; Masood, Mariyam; Ratnasingham, Sujeevan; Hebert, Paul D. N.

2015-01-01

The study analyzes sequence variation of two mitochondrial genes (COI, cytb) in Pediculus humanus from three countries (Egypt, Pakistan, South Africa) that have received little prior attention, and integrates these results with prior data. Analysis indicates a maximum K2P distance of 10.3% among 960 COI sequences and 13.8% among 479 cytb sequences. Three analytical methods (BIN, PTP, ABGD) reveal five concordant OTUs for COI and cytb. Neighbor-Joining analysis of the COI sequences confirm five clusters; three corresponding to previously recognized mitochondrial clades A, B, C and two new clades, “D” and “E”, showing 2.3% and 2.8% divergence from their nearest neighbors (NN). Cytb data corroborate five clusters showing that clades “D” and “E” are both 4.6% divergent from their respective NN clades. Phylogenetic analysis supports the monophyly of all clusters recovered by NJ analysis. Divergence time estimates suggest that the earliest split of P. humanus clades occured slightly more than one million years ago (MYa) and the latest about 0.3 MYa. Sequence divergences in COI and cytb among the five clades of P. humanus are 10X those in their human host, a difference that likely reflects both rate acceleration and the acquisition of lice clades from several archaic hominid lineages. PMID:26373806

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Genetic Diversity and Geographical Distribution of Indigenous Soybean-Nodulating Bradyrhizobia in the United States

PubMed Central

Shiro, Sokichi; Matsuura, Syota; Saiki, Rina; Sigua, Gilbert C.; Yamamoto, Akihiro; Umehara, Yosuke; Hayashi, Masaki

2013-01-01

We investigated the relationship between the genetic diversity of indigenous soybean-nodulating bradyrhizobia and their geographical distribution in the United States using nine soil isolates from eight states. The bradyrhizobia were inoculated on three soybean Rj genotypes (non-Rj, Rj2Rj3, and Rj4). We analyzed their genetic diversity and community structure by means of restriction fragment length polymorphisms of PCR amplicons to target the 16S-23S rRNA gene internal transcribed spacer region, using 11 USDA Bradyrhizobium strains as reference strains. We also performed diversity analysis, multidimensional scaling analysis based on the Bray-Curtis index, and polar ordination analysis to describe the structure and geographical distribution of the soybean-nodulating bradyrhizobial community. The major clusters were Bradyrhizobium japonicum Bj123, in the northern United States, and Bradyrhizobium elkanii, in the middle to southern regions. Dominance of bradyrhizobia in a community was generally larger for the cluster belonging to B. elkanii than for the cluster belonging to B. japonicum. The indigenous American soybean-nodulating bradyrhizobial community structure was strongly correlated with latitude. Our results suggest that this community varies geographically. PMID:23563944

The effect of heavy metal contamination on the bacterial community structure at Jiaozhou Bay, China.

PubMed

Yao, Xie-Feng; Zhang, Jiu-Ming; Tian, Li; Guo, Jian-Hua

In this study, determination of heavy metal parameters and microbiological characterization of marine sediments obtained from two heavily polluted sites and one low-grade contaminated reference station at Jiaozhou Bay in China were carried out. The microbial communities found in the sampled marine sediments were studied using PCR-DGGE (denaturing gradient gel electrophoresis) fingerprinting profiles in combination with multivariate analysis. Clustering analysis of DGGE and matrix of heavy metals displayed similar occurrence patterns. On this basis, 17 samples were classified into two clusters depending on the presence or absence of the high level contamination. Moreover, the cluster of highly contaminated samples was further classified into two sub-groups based on the stations of their origin. These results showed that the composition of the bacterial community is strongly influenced by heavy metal variables present in the sediments found in the Jiaozhou Bay. This study also suggested that metagenomic techniques such as PCR-DGGE fingerprinting in combination with multivariate analysis is an efficient method to examine the effect of metal contamination on the bacterial community structure. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Reliability of resting-state microstate features in electroencephalography.

PubMed

Khanna, Arjun; Pascual-Leone, Alvaro; Farzan, Faranak

2014-01-01

Electroencephalographic (EEG) microstate analysis is a method of identifying quasi-stable functional brain states ("microstates") that are altered in a number of neuropsychiatric disorders, suggesting their potential use as biomarkers of neurophysiological health and disease. However, use of EEG microstates as neurophysiological biomarkers requires assessment of the test-retest reliability of microstate analysis. We analyzed resting-state, eyes-closed, 30-channel EEG from 10 healthy subjects over 3 sessions spaced approximately 48 hours apart. We identified four microstate classes and calculated the average duration, frequency, and coverage fraction of these microstates. Using Cronbach's α and the standard error of measurement (SEM) as indicators of reliability, we examined: (1) the test-retest reliability of microstate features using a variety of different approaches; (2) the consistency between TAAHC and k-means clustering algorithms; and (3) whether microstate analysis can be reliably conducted with 19 and 8 electrodes. The approach of identifying a single set of "global" microstate maps showed the highest reliability (mean Cronbach's α > 0.8, SEM ≈ 10% of mean values) compared to microstates derived by each session or each recording. There was notably low reliability in features calculated from maps extracted individually for each recording, suggesting that the analysis is most reliable when maps are held constant. Features were highly consistent across clustering methods (Cronbach's α > 0.9). All features had high test-retest reliability with 19 and 8 electrodes. High test-retest reliability and cross-method consistency of microstate features suggests their potential as biomarkers for assessment of the brain's neurophysiological health.

[Phylogenetic analysis of tyrosinase gene family in the Pacific oyster (Crassostrea gigas Thunberg)].

PubMed

Yu, Xue; Yu, Hong; Kong, Lingfeng; Li, Qi

2014-02-01

The deduced amino acid sequence characteristics, classification and phylogeny of tyrosinase gene family in the Pacific oyster (Crassostrea gigas Thunberg) were analyzed using bioinformatics methods. The results showed that gene duplication was the major cause of tyrosinase gene expansion in the Pacific oyster. The tyrosinase gene family in the Pacific oyster can be further classified into three types: secreted form (Type A), cytosolic form (Type B) and membrane-bound form (Type C). Based on the topology of the phylogenetic tree of the Pacific oyster tyrosinases, among Type A isoforms, tyr18 seemed divergent from other Type A tyrosinases early, while tyr2 and tyr9 appeared divergent early in Type B. In Type C tyrosinses, tyr8 was divergent early. The cluster of the Pacific oyster tyrosinasesis determined by their classifications and positions in the scaffolds. Further analysis suggested that Type A tyrosinases of C. gigas clustered with those from cephalopods and then with nematodes and cnidarians. Type B tyrosinases were generally clustered with the same type of tyrosinases from molluscas and nematodes, and then with those from platyhelminths, cnidarians and chordates. Type A tyrosinases in the Pacific oyster and the Pearl oyster expanded independently and were divergent from membrane-bound form of tyrosinases in chordata, platyhelminthes and annelida. These observations suggested that Type C tyrosinases in the bivalve had a distinct evolution direction.

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

Theoretical and experimental study of polycyclic aromatic compounds as β-tubulin inhibitors.

PubMed

Olazarán, Fabian E; García-Pérez, Carlos A; Bandyopadhyay, Debasish; Balderas-Rentería, Isaias; Reyes-Figueroa, Angel D; Henschke, Lars; Rivera, Gildardo

2017-03-01

In this work, through a docking analysis of compounds from the ZINC chemical library on human β-tubulin using high performance computer cluster, we report new polycyclic aromatic compounds that bind with high energy on the colchicine binding site of β-tubulin, suggesting three new key amino acids. However, molecular dynamic analysis showed low stability in the interaction between ligand and receptor. Results were confirmed experimentally in in vitro and in vivo models that suggest that molecular dynamics simulation is the best option to find new potential β-tubulin inhibitors. Graphical abstract Bennett's acceptance ratio (BAR) method.

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

PubMed

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

2014-07-01

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. 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. 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 analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard; Wells, R. Glenn

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: Aboutmore » 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 analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). Conclusions: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.« less

Near real-time space-time cluster analysis for detection of enteric disease outbreaks in a community setting.

PubMed

Glatman-Freedman, Aharona; Kaufman, Zalman; Kopel, Eran; Bassal, Ravit; Taran, Diana; Valinsky, Lea; Agmon, Vered; Shpriz, Manor; Cohen, Daniel; Anis, Emilia; Shohat, Tamy

2016-08-01

To enhance timely surveillance of bacterial enteric pathogens, space-time cluster analysis was introduced in Israel in May 2013. Stool isolation data of Salmonella, Shigella, and Campylobacter from patients of a large Health Maintenance Organization were analyzed weekly by ArcGIS and SaTScan, and cluster results were sent promptly to local departments of health (LDOHs). During eighteen months, we identified 52 Shigella sonnei clusters, two Salmonella clusters, and no Campylobacter clusters. S. sonnei clusters lasted from one to 33 days and included three to 30 individuals. Thirty-one (60%) of the S. sonnei clusters were known to LDOHs prior to cluster analysis. Clusters not previously known by the LDOHs prompted epidemiologic investigations. In 31 of the 37 (84%) confirmed clusters, educational institutes (nursery schools, kindergartens, and a primary school) were involved. Cluster analysis demonstrated capability to complement enteric disease surveillance. Scaling up the system can further enhance timely detection and control of outbreaks. Copyright © 2016 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

An effective fuzzy kernel clustering analysis approach for gene expression data.

PubMed

Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

2015-01-01

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

Logical errors on proving theorem

NASA Astrophysics Data System (ADS)

Sari, C. K.; Waluyo, M.; Ainur, C. M.; Darmaningsih, E. N.

2018-01-01

In tertiary level, students of mathematics education department attend some abstract courses, such as Introduction to Real Analysis which needs an ability to prove mathematical statements almost all the time. In fact, many students have not mastered this ability appropriately. In their Introduction to Real Analysis tests, even though they completed their proof of theorems, they achieved an unsatisfactory score. They thought that they succeeded, but their proof was not valid. In this study, a qualitative research was conducted to describe logical errors that students made in proving the theorem of cluster point. The theorem was given to 54 students. Misconceptions on understanding the definitions seem to occur within cluster point, limit of function, and limit of sequences. The habit of using routine symbol might cause these misconceptions. Suggestions to deal with this condition are described as well.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

PubMed

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2015-01-01

Abstract To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice. PMID:25560745

Large-scale dynamics associated with clustering of extratropical cyclones affecting Western Europe

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Gómara, Iñigo; Masato, Giacomo; Dacre, Helen F.; Woollings, Tim; Caballero, Rodrigo

2015-04-01

Some recent winters in Western Europe have been characterized by the occurrence of multiple extratropical cyclones following a similar path. The occurrence of such cyclone clusters leads to large socio-economic impacts due to damaging winds, storm surges, and floods. Recent studies have statistically characterized the clustering of extratropical cyclones over the North Atlantic and Europe and hypothesized potential physical mechanisms responsible for their formation. Here we analyze 4 months characterized by multiple cyclones over Western Europe (February 1990, January 1993, December 1999, and January 2007). The evolution of the eddy driven jet stream, Rossby wave-breaking, and upstream/downstream cyclone development are investigated to infer the role of the large-scale flow and to determine if clustered cyclones are related to each other. Results suggest that optimal conditions for the occurrence of cyclone clusters are provided by a recurrent extension of an intensified eddy driven jet toward Western Europe lasting at least 1 week. Multiple Rossby wave-breaking occurrences on both the poleward and equatorward flanks of the jet contribute to the development of these anomalous large-scale conditions. The analysis of the daily weather charts reveals that upstream cyclone development (secondary cyclogenesis, where new cyclones are generated on the trailing fronts of mature cyclones) is strongly related to cyclone clustering, with multiple cyclones developing on a single jet streak. The present analysis permits a deeper understanding of the physical reasons leading to the occurrence of cyclone families over the North Atlantic, enabling a better estimation of the associated cumulative risk over Europe.

Clustering gene expression regulators: new approach to disease subtyping.

PubMed

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Clustering Gene Expression Regulators: New Approach to Disease Subtyping

PubMed Central

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. PMID:24416320

Pseudomonas aeruginosa in Dairy Goats: Genotypic and Phenotypic Comparison of Intramammary and Environmental Isolates

PubMed Central

Scaccabarozzi, Licia; Leoni, Livia; Ballarini, Annalisa; Barberio, Antonio; Locatelli, Clara; Casula, Antonio; Bronzo, Valerio; Pisoni, Giuliano; Jousson, Olivier; Morandi, Stefano; Rapetti, Luca; García-Fernández, Aurora; Moroni, Paolo

2015-01-01

Following the identification of a case of severe clinical mastitis in a Saanen dairy goat (goat A), an average of 26 lactating goats in the herd was monitored over a period of 11 months. Milk microbiological analysis revealed the presence of Pseudomonas aeruginosa in 7 of the goats. Among these 7 does, only goat A showed clinical signs of mastitis. The 7 P. aeruginosa isolates from the goat milk and 26 P. aeruginosa isolates from environmental samples were clustered by RAPD-PCR and PFGE analyses in 3 genotypes (G1, G2, G3) and 4 clusters (A, B, C, D), respectively. PFGE clusters A and B correlated with the G1 genotype and included the 7 milk isolates. Although it was not possible to identify the infection source, these results strongly suggest a spreading of the infection from goat A. Clusters C and D overlapped with genotypes G2 and G3, respectively, and included only environmental isolates. The outcome of the antimicrobial susceptibility test performed on the isolates revealed 2 main patterns of multiple resistance to beta-lactam antibiotics and macrolides. Virulence related phenotypes were analyzed, such as swarming and swimming motility, production of biofilm and production of secreted virulence factors. The isolates had distinct phenotypic profiles, corresponding to genotypes G1, G2 and G3. Overall, correlation analysis showed a strong correlation between sampling source, RAPD genotype, PFGE clusters, and phenotypic clusters. The comparison of the levels of virulence related phenotypes did not indicate a higher pathogenic potential in the milk isolates as compared to the environmental isolates. PMID:26606430

Characteristics of HIV-infected U.S. Army soldiers linked in molecular transmission clusters, 2001-2012

PubMed Central

Jagodzinski, Linda L.; Liu, Ying; Pham, Peter T.; Kijak, Gustavo H.; Tovanabutra, Sodsai; McCutchan, Francine E.; Scoville, Stephanie L.; Cersovsky, Steven B.; Michael, Nelson L.; Scott, Paul T.; Peel, Sheila A.

2017-01-01

Objective Recent surveillance data suggests the United States (U.S.) Army HIV epidemic is concentrated among men who have sex with men. To identify potential targets for HIV prevention strategies, the relationship between demographic and clinical factors and membership within transmission clusters based on baseline pol sequences of HIV-infected Soldiers from 2001 through 2012 were analyzed. Methods We conducted a retrospective analysis of baseline partial pol sequences, demographic and clinical characteristics available for all Soldiers in active service and newly-diagnosed with HIV-1 infection from January 1, 2001 through December 31, 2012. HIV-1 subtype designations and transmission clusters were identified from phylogenetic analysis of sequences. Univariate and multivariate logistic regression models were used to evaluate and adjust for the association between characteristics and cluster membership. Results Among 518 of 995 HIV-infected Soldiers with available partial pol sequences, 29% were members of a transmission cluster. Assignment to a southern U.S. region at diagnosis and year of diagnosis were independently associated with cluster membership after adjustment for other significant characteristics (p<0.10) of age, race, year of diagnosis, region of duty assignment, sexually transmitted infections, last negative HIV test, antiretroviral therapy, and transmitted drug resistance. Subtyping of the pol fragment indicated HIV-1 subtype B infection predominated (94%) among HIV-infected Soldiers. Conclusion These findings identify areas to explore as HIV prevention targets in the U.S. Army. An increased frequency of current force testing may be justified, especially among Soldiers assigned to duty in installations with high local HIV prevalence such as southern U.S. states. PMID:28759645

Phonologic errors as a clinical marker of the logopenic variant of PPA.

PubMed

Leyton, Cristian E; Ballard, Kirrie J; Piguet, Olivier; Hodges, John R

2014-05-06

To disentangle the clinical heterogeneity of nonsemantic variants of primary progressive aphasia (PPA) and to identify a coherent linguistic-anatomical marker for the logopenic variant of PPA (lv-PPA). Key speech and language features of 14 cases of lv-PPA and 18 cases of nonfluent/agrammatic variant of PPA were systematically evaluated and scored by an independent rater blinded to diagnosis. Every case underwent a structural MRI and a Pittsburgh compound B (PiB)-PET scan, a putative biomarker of Alzheimer disease. Key speech and language features that showed association with the PiB-PET status were entered into a hierarchical cluster analysis. The linguistic features and patterns of cortical thinning in each resultant cluster were analyzed. The cluster analysis revealed 3 coherent clinical groups, each of which was linked to a specific PiB-PET status. The first cluster was linked to high PiB retention and characterized by phonologic errors and cortical thinning focused on the left superior temporal gyrus. The second and third clusters were characterized by grammatical production errors and motor speech disorders, respectively, and were associated with low PiB brain retention. A fourth cluster, however, demonstrated nonspecific language deficits and unpredictable PiB-PET status. These findings suggest that despite the clinical and pathologic heterogeneity of nonsemantic variants, discrete clinical syndromes can be distinguished and linked to specific likelihood of PiB-PET status. Phonologic errors seem to be highly predictive of high amyloid burden in PPA and can provide a specific clinical marker for lv-PPA.

Nine co-localized cytochrome P450 genes of the CYP2N, CYP2AD, and CYP2P gene families in the mangrove killifish Kryptolebias marmoratus genome: Identification and expression in response to B[α]P, BPA, OP, and NP.

PubMed

Puthumana, Jayesh; Kim, Bo-Mi; Jeong, Chang-Bum; Kim, Duck-Hyun; Kang, Hye-Min; Jung, Jee-Hyun; Kim, Il-Chan; Hwang, Un-Ki; Lee, Jae-Seong

2017-06-01

The CYP2 genes are the largest and most diverse cytochrome P450 (CYP) subfamily in vertebrates. We have identified nine co-localized CYP2 genes (∼55kb) in a new cluster in the genome of the highly resilient ecotoxicological fish model Kryptolebias marmoratus. Molecular characterization, temporal and tissue-specific expression pattern, and response to xenobiotics of these genes were examined. The CYP2 gene clusters were characterized and designated CYP2N22-23, CYP2AD12, and CYP2P16-20. Gene synteny analysis confirmed that the cluster in K. marmoratus is similar to that found in other teleost fishes, including zebrafish. A gene duplication event with diverged catalytic function was observed in CYP2AD12. Moreover, a high level of divergence in expression was observed among the co-localized genes. Phylogeny of the cluster suggested an orthologous relationship with similar genes in zebrafish and Japanese medaka. Gene expression analysis showed that CYP2P19 and CYP2N20 were consecutively expressed throughout embryonic development, whereas CYP2P18 was expressed in all adult tissues, suggesting that members of each CYP2 gene family have different physiological roles even though they are located in the same cluster. Among endocrine-disrupting chemicals (EDCs), benzo[α]pyrene (B[α]P) induced expression of CYP2N23, bisphenol A (BPA) induced CYP2P18 and CYP2P19, and 4-octylphenol (OP) induced CYP2AD12, but there was no significant response to 4-nonylphenol (NP), implying differential catalytic roles of the enzyme. In this paper, we identify and characterize a CYP2 gene cluster in the mangrove killifish K. marmoratus with differing catalytic roles toward EDCs. Our findings provide insights on the roles of nine co-localized CYP2 genes and their catalytic functions for better understanding of chemical-biological interactions in fish. Copyright © 2017 Elsevier B.V. All rights reserved.

A comprehensive study of large-scale structures in the GOODS-SOUTH field up to z ˜ 2.5

NASA Astrophysics Data System (ADS)

Salimbeni, S.; Castellano, M.; Pentericci, L.; Trevese, D.; Fiore, F.; Grazian, A.; Fontana, A.; Giallongo, E.; Boutsia, K.; Cristiani, S.; de Santis, C.; Gallozzi, S.; Menci, N.; Nonino, M.; Paris, D.; Santini, P.; Vanzella, E.

2009-07-01

Aims: The aim of the present paper is to identify and study the properties and galactic content of groups and clusters in the GOODS-South field up to z˜ 2.5, and to analyse the physical properties of galaxies as a continuous function of environmental density up to high redshift. Methods: We used the deep (z850˜ 26), multi-wavelength GOODS-MUSIC catalogue, which has a 15% of spectroscopic redshifts and accurate photometric redshifts for the remaining fraction. On these data, we applied a (2+1)D algorithm, previously developed by our group, that provides an adaptive estimate of the 3D density field. We supported our analysis with simulations to evaluate the purity and the completeness of the cluster catalogue produced by our algorithm. Results: We find several high-density peaks embedded in larger structures in the redshift range 0.4-2.5. From the analysis of their physical properties (mass profile, M200, σ_v, L_X, U-B vs. B diagram), we find that most of them are groups of galaxies, while two are poor clusters with masses a few times 1014~M_⊙. For these two clusters we find from the Chandra 2Ms data an X-ray emission significantly lower than expected from their optical properties, suggesting that the two clusters are either not virialised or are gas poor. We find that the slope of the colour magnitude relation, for these groups and clusters, is constant at least up to z ˜ 1. We also analyse the dependence on environment of galaxy colours, luminosities, stellar masses, ages, and star formations. We find that galaxies in high-density regions are, on average, more luminous and massive than field galaxies up to z ˜ 2. The fraction of red galaxies increases with luminosity and with density up to z˜ 1.2. At higher z this dependence on density disappears. The variation of galaxy properties as a function of redshift and density suggests that a significant change occurs at z ˜ 1.5-2.

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

First-principles melting of gallium clusters down to nine atoms: structural and electronic contributions to melting.

PubMed

Steenbergen, Krista G; Gaston, Nicola

2013-10-07

First-principles Born-Oppenheimer molecular dynamics simulations of small gallium clusters, including parallel tempering, probe the distinction between cluster and molecule in the size range of 7-12 atoms. In contrast to the larger sizes, dynamic measures of structural change at finite temperature demonstrate that Ga7 and Ga8 do not melt, suggesting a size limit to melting in gallium exists at 9 atoms. Analysis of electronic structure further supports this size limit, additionally demonstrating that a covalent nature cannot be identified for clusters larger than the gallium dimer. Ga9, Ga10 and Ga11 melt at greater-than-bulk temperatures, with no evident covalent character. As Ga12 represents the first small gallium cluster to melt at a lower-than-bulk temperature, we examine the structural properties of each cluster at finite temperature in order to probe both the origins of greater-than-bulk melting, as well as the significant differences in melting temperatures induced by a single atom addition. Size-sensitive melting temperatures can be explained by both energetic and entropic differences between the solid and liquid phases for each cluster. We show that the lower-than-bulk melting temperature of the 12-atom cluster can be attributed to persistent pair bonding, reminiscent of the pairing observed in α-gallium. This result supports the attribution of greater-than-bulk melting in gallium clusters to the anomalously low melting temperature of the bulk, due to its dimeric structure.

Phylogenetic Network Analysis Revealed the Occurrence of Horizontal Gene Transfer of 16S rRNA in the Genus Enterobacter

PubMed Central

Sato, Mitsuharu; Miyazaki, Kentaro

2017-01-01

Horizontal gene transfer (HGT) is a ubiquitous genetic event in bacterial evolution, but it seldom occurs for genes involved in highly complex supramolecules (or biosystems), which consist of many gene products. The ribosome is one such supramolecule, but several bacteria harbor dissimilar and/or chimeric 16S rRNAs in their genomes, suggesting the occurrence of HGT of this gene. However, we know little about whether the genes actually experience HGT and, if so, the frequency of such a transfer. This is primarily because the methods currently employed for phylogenetic analysis (e.g., neighbor-joining, maximum likelihood, and maximum parsimony) of 16S rRNA genes assume point mutation-driven tree-shape evolution as an evolutionary model, which is intrinsically inappropriate to decipher the evolutionary history for genes driven by recombination. To address this issue, we applied a phylogenetic network analysis, which has been used previously for detection of genetic recombination in homologous alleles, to the 16S rRNA gene. We focused on the genus Enterobacter, whose phylogenetic relationships inferred by multi-locus sequence alignment analysis and 16S rRNA sequences are incompatible. All 10 complete genomic sequences were retrieved from the NCBI database, in which 71 16S rRNA genes were included. Neighbor-joining analysis demonstrated that the genes residing in the same genomes clustered, indicating the occurrence of intragenomic recombination. However, as suggested by the low bootstrap values, evolutionary relationships between the clusters were uncertain. We then applied phylogenetic network analysis to representative sequences from each cluster. We found three ancestral 16S rRNA groups; the others were likely created through recursive recombination between the ancestors and chimeric descendants. Despite the large sequence changes caused by the recombination events, the RNA secondary structures were conserved. Successive intergenomic and intragenomic recombination thus shaped the evolution of 16S rRNA genes in the genus Enterobacter. PMID:29180992

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-Means Cluster Analysis

ERIC Educational Resources Information Center

de Craen, Saskia; Commandeur, Jacques J. F.; Frank, Laurence E.; Heiser, Willem J.

2006-01-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these…

Changing cluster composition in cluster randomised controlled trials: design and analysis considerations

PubMed Central

2014-01-01

Background There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes. Methods We explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis. Results Cluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated. Conclusions Examples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations include avoidance of cluster merges where possible, discontinuation of clusters following heterogeneous merges, allowance for potential loss of clusters and additional variability in cluster size in the original sample size calculation, and use of appropriate ICC estimates that reflect cluster size. PMID:24884591

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

NASA Astrophysics Data System (ADS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

A Geometric and Electrostatic Study of the [4Fe-4S] Cluster of Adenosine-5´-Phosphosulfate Reductase from Broken Symmetry Density Functional Calculations and Extended X-ray Absorption Fine Structure Spectroscopy

PubMed Central

Bhave, Devayani P.; Han, Wen-Ge; Pazicni, Samuel; Penner-Hahn, James E.; Carroll, Kate S.; Noodleman, Louis

2011-01-01

Adenosine-5’-phosphosulfate reductase (APSR) is an iron-sulfur protein that catalyses the reduction of adenosine-5’-phosphosulfate (APS) to sulfite. APSR coordinates to a [4Fe-4S] cluster via a conserved CC-X~80-CXXC motif and the cluster is essential for catalysis. Despite extensive functional, structural and spectroscopic studies, the exact role of the iron-sulfur cluster in APS reduction remains unknown. To gain an understanding into the role of the cluster, density functional theory (DFT) analysis and extended X-ray fine structure spectroscopy (EXAFS) have been performed to reveal insights into the coordination, geometry and electrostatics of the [4Fe-4S] cluster. XANES data confirms that the cluster is in the [4Fe-4S]2+ state in both native and substrate-bound APSR while EXAFS data recorded at ~0.1 Å resolution indicates that there is no significant change in the structure of the [4Fe-4S] cluster between the native and substrate-bound forms of the protein. On the other hand, DFT calculations provide an insight into the subtle differences between the geometry of the cluster in the native and APS-bound forms of APSR. A comparison between models with and without the tandem cysteine pair coordination of the cluster suggests a role for the unique coordination in facilitating a compact geometric structure and ‘fine-tuning’ the electronic structure to prevent reduction of the cluster. Further, calculations using models in which residue Lys144 is mutated to Ala confirm the finding that Lys144 serves as a crucial link in the interactions involving the [4Fe-4S] cluster and APS. PMID:21678934

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Big Bangs in Galaxy Clusters: Using X-ray Temperature Maps to Trace Merger Histories in Clusters with Radio Halos/Relics

NASA Astrophysics Data System (ADS)

Burns, Jack O.; Datta, Abhirup; Hallman, Eric J.

2016-06-01

Galaxy clusters are assembled through large and small mergers which are the most energetic events ("bangs") since the Big Bang. Cluster mergers "stir" the intracluster medium (ICM) creating shocks and turbulence which are illuminated by ~Mpc-sized radio features called relics and halos. These shocks heat the ICM and are detected in x-rays via thermal emission. Disturbed morphologies in x-ray surface brightness and temperatures are direct evidence for cluster mergers. In the radio, relics (in the outskirts of the clusters) and halos (located near the cluster core) are also clear signposts of recent mergers. Our recent ENZO cosmological simulations suggest that around a merger event, radio emission peaks very sharply (and briefly) while the x-ray emission rises and decays slowly. Hence, a sample of galaxy clusters that shows both luminous x-ray emission and radio relics/halos are good candidates for very recent mergers. We are in the early stages of analyzing a unique sample of 48 galaxy clusters with (i) known radio relics and/or halos and (ii) significant archival x-ray observations (>50 ksec) from Chandra and/or XMM. We have developed a new x-ray data analysis pipeline, implemented on parallel processor supercomputers, to create x-ray surface brightness, high fidelity temperature, and pressure maps of these clusters in order to study merging activity. The temperature maps are made using three different map-making techniques: Weighted Voronoi Tessellation, Adaptive Circular Binning, and Contour Binning. In this talk, we will show preliminary results for several clusters, including Abell 2744 and the Bullet cluster. This work is supported by NASA ADAP grant NNX15AE17G.

Hierarchical clustering of HPV genotype patterns in the ASCUS-LSIL triage study

PubMed Central

Wentzensen, Nicolas; Wilson, Lauren E.; Wheeler, Cosette M.; Carreon, Joseph D.; Gravitt, Patti E.; Schiffman, Mark; Castle, Philip E.

2010-01-01

Anogenital cancers are associated with about 13 carcinogenic HPV types in a broader group that cause cervical intraepithelial neoplasia (CIN). Multiple concurrent cervical HPV infections are common which complicate the attribution of HPV types to different grades of CIN. Here we report the analysis of HPV genotype patterns in the ASCUS-LSIL triage study using unsupervised hierarchical clustering. Women who underwent colposcopy at baseline (n = 2780) were grouped into 20 disease categories based on histology and cytology. Disease groups and HPV genotypes were clustered using complete linkage. Risk of 2-year cumulative CIN3+, viral load, colposcopic impression, and age were compared between disease groups and major clusters. Hierarchical clustering yielded four major disease clusters: Cluster 1 included all CIN3 histology with abnormal cytology; Cluster 2 included CIN3 histology with normal cytology and combinations with either CIN2 or high-grade squamous intraepithelial lesion (HSIL) cytology; Cluster 3 included older women with normal or low grade histology/cytology and low viral load; Cluster 4 included younger women with low grade histology/cytology, multiple infections, and the highest viral load. Three major groups of HPV genotypes were identified: Group 1 included only HPV16; Group 2 included nine carcinogenic types plus non-carcinogenic HPV53 and HPV66; and Group 3 included non-carcinogenic types plus carcinogenic HPV33 and HPV45. Clustering results suggested that colposcopy missed a prevalent precancer in many women with no biopsy/normal histology and HSIL. This result was confirmed by an elevated 2-year risk of CIN3+ in these groups. Our novel approach to study multiple genotype infections in cervical disease using unsupervised hierarchical clustering can address complex genotype distributions on a population level. PMID:20959485