Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

PubMed

He, Yan; Caporaso, J Gregory; Jiang, Xiao-Tao; Sheng, Hua-Fang; Huse, Susan M; Rideout, Jai Ram; Edgar, Robert C; Kopylova, Evguenia; Walters, William A; Knight, Rob; Zhou, Hong-Wei

2015-01-01

The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.

Welcome to pandoraviruses at the ‘Fourth TRUC’ club

PubMed Central

Sharma, Vikas; Colson, Philippe; Chabrol, Olivier; Scheid, Patrick; Pontarotti, Pierre; Raoult, Didier

2015-01-01

Nucleocytoplasmic large DNA viruses, or representatives of the proposed order Megavirales, belong to families of giant viruses that infect a broad range of eukaryotic hosts. Megaviruses have been previously described to comprise a fourth monophylogenetic TRUC (things resisting uncompleted classification) together with cellular domains in the universal tree of life. Recently described pandoraviruses have large (1.9–2.5 MB) and highly divergent genomes. In the present study, we updated the classification of pandoraviruses and other reported giant viruses. Phylogenetic trees were constructed based on six informational genes. Hierarchical clustering was performed based on a set of informational genes from Megavirales members and cellular organisms. Homologous sequences were selected from cellular organisms using TimeTree software, comprising comprehensive, and representative sets of members from Bacteria, Archaea, and Eukarya. Phylogenetic analyses based on three conserved core genes clustered pandoraviruses with phycodnaviruses, exhibiting their close relatedness. Additionally, hierarchical clustering analyses based on informational genes grouped pandoraviruses with Megavirales members as a super group distinct from cellular organisms. Thus, the analyses based on core conserved genes revealed that pandoraviruses are new genuine members of the ‘Fourth TRUC’ club, encompassing distinct life forms compared with cellular organisms. PMID:26042093

Welcome to pandoraviruses at the 'Fourth TRUC' club.

PubMed

Sharma, Vikas; Colson, Philippe; Chabrol, Olivier; Scheid, Patrick; Pontarotti, Pierre; Raoult, Didier

2015-01-01

Nucleocytoplasmic large DNA viruses, or representatives of the proposed order Megavirales, belong to families of giant viruses that infect a broad range of eukaryotic hosts. Megaviruses have been previously described to comprise a fourth monophylogenetic TRUC (things resisting uncompleted classification) together with cellular domains in the universal tree of life. Recently described pandoraviruses have large (1.9-2.5 MB) and highly divergent genomes. In the present study, we updated the classification of pandoraviruses and other reported giant viruses. Phylogenetic trees were constructed based on six informational genes. Hierarchical clustering was performed based on a set of informational genes from Megavirales members and cellular organisms. Homologous sequences were selected from cellular organisms using TimeTree software, comprising comprehensive, and representative sets of members from Bacteria, Archaea, and Eukarya. Phylogenetic analyses based on three conserved core genes clustered pandoraviruses with phycodnaviruses, exhibiting their close relatedness. Additionally, hierarchical clustering analyses based on informational genes grouped pandoraviruses with Megavirales members as a super group distinct from cellular organisms. Thus, the analyses based on core conserved genes revealed that pandoraviruses are new genuine members of the 'Fourth TRUC' club, encompassing distinct life forms compared with cellular organisms.

Canonical PSO Based K-Means Clustering Approach for Real Datasets.

PubMed

Dey, Lopamudra; Chakraborty, Sanjay

2014-01-01

"Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Galaxy Cluster Mass Reconstruction Project - II. Quantifying scatter and bias using contrasting mock catalogues

DOE PAGES

Old, L.; Wojtak, R.; Mamon, G. A.; ...

2015-03-26

Our paper is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilize the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the rms errors in log M200c delivered by the different methods (0.18–1.08 dex, i.e. a factor of ~1.5–12), with abundance-matchingmore » and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under- or overestimated by a factor greater than 10. Given the steeply falling high-mass end of the cluster mass function, we recommend that richness- or abundance-matching-based methods are used in conjunction with these methods as a sanity check for studies selecting high-mass clusters. We also see a stronger correlation of the recovered to input number of galaxies for both catalogues in comparison with the group/cluster mass, however, this does not guarantee that the correct member galaxies are being selected. Finally, we did not observe significantly higher scatter for either mock galaxy catalogues. These results have implications for cosmological analyses that utilize the masses, richnesses, or abundances of clusters, which have different uncertainties when different methods are used.« less

Canonical PSO Based K-Means Clustering Approach for Real Datasets

PubMed Central

Dey, Lopamudra; Chakraborty, Sanjay

2014-01-01

“Clustering” the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms. PMID:27355083

Multilocus microsatellite typing shows three different genetic clusters of Leishmania major in Iran.

PubMed

Mahnaz, Tashakori; Al-Jawabreh, Amer; Kuhls, Katrin; Schönian, Gabriele

2011-10-01

Ten polymorphic microsatellite markers were used to analyse 25 strains of Leishmania major collected from cutaneous leishmaniasis cases in different endemic areas in Iran. Nine of the markers were polymorphic, revealing 21 different genotypes. The data displayed significant microsatellite polymorphism with rare allelic heterozygosity. Bayesian statistic and distance based analyses identified three genetic clusters among the 25 strains analysed. Cluster I represented mainly strains isolated in the west and south-west of Iran, with the exception of four strains originating from central Iran. Cluster II comprised strains from the central part of Iran, and cluster III included only strains from north Iran. The geographical distribution of L. major in Iran was supported by comparing the microsatellite profiles of the 25 Iranian strains to those of 105 strains collected in 19 Asian and African countries. The Iranian clusters I and II were separated from three previously described populations comprising strains from Africa, the Middle East and Central Asia whereas cluster III grouped together with the Central Asian population. The considerable genetic variability of L. major might be related to the existence of different populations of Phlebotomus papatasi and/or to differences in reservoir host abundance in different parts of Iran. Copyright © 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

KinFin: Software for Taxon-Aware Analysis of Clustered Protein Sequences.

PubMed

Laetsch, Dominik R; Blaxter, Mark L

2017-10-05

The field of comparative genomics is concerned with the study of similarities and differences between the information encoded in the genomes of organisms. A common approach is to define gene families by clustering protein sequences based on sequence similarity, and analyze protein cluster presence and absence in different species groups as a guide to biology. Due to the high dimensionality of these data, downstream analysis of protein clusters inferred from large numbers of species, or species with many genes, is nontrivial, and few solutions exist for transparent, reproducible, and customizable analyses. We present KinFin, a streamlined software solution capable of integrating data from common file formats and delivering aggregative annotation of protein clusters. KinFin delivers analyses based on systematic taxonomy of the species analyzed, or on user-defined, groupings of taxa, for example, sets based on attributes such as life history traits, organismal phenotypes, or competing phylogenetic hypotheses. Results are reported through graphical and detailed text output files. We illustrate the utility of the KinFin pipeline by addressing questions regarding the biology of filarial nematodes, which include parasites of veterinary and medical importance. We resolve the phylogenetic relationships between the species and explore functional annotation of proteins in clusters in key lineages and between custom taxon sets, identifying gene families of interest. KinFin can easily be integrated into existing comparative genomic workflows, and promotes transparent and reproducible analysis of clustered protein data. Copyright © 2017 Laetsch and Blaxter.

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.

Substructures in DAFT/FADA survey clusters based on XMM and optical data

NASA Astrophysics Data System (ADS)

Durret, F.; DAFT/FADA Team

2014-07-01

The DAFT/FADA survey was initiated to perform weak lensing tomography on a sample of 90 massive clusters in the redshift range [0.4,0.9] with HST imaging available. The complementary deep multiband imaging constitutes a high quality imaging data base for these clusters. In X-rays, we have analysed the XMM-Newton and/or Chandra data available for 32 clusters, and for 23 clusters we fit the X-ray emissivity with a beta-model and subtract it to search for substructures in the X-ray gas. This study was coupled with a dynamical analysis for the 18 clusters with at least 15 spectroscopic galaxy redshifts in the cluster range, based on a Serna & Gerbal (SG) analysis. We detected ten substructures in eight clusters by both methods (X-rays and SG). The percentage of mass included in substructures is found to be roughly constant with redshift, with values of 5-15%. Most of the substructures detected both in X-rays and with the SG method are found to be relatively recent infalls, probably at their first cluster pericenter approach.

Irradiation-induced microchemical changes in highly irradiated 316 stainless steel

NASA Astrophysics Data System (ADS)

Fujii, K.; Fukuya, K.

2016-02-01

Cold-worked 316 stainless steel specimens irradiated to 74 dpa in a pressurized water reactor (PWR) were analyzed by atom probe tomography (APT) to extend knowledge of solute clusters and segregation at higher doses. The analyses confirmed that those clusters mainly enriched in Ni-Si or Ni-Si-Mn were formed at high number density. The clusters were divided into three types based on their size and Mn content; small Ni-Si clusters (3-4 nm in diameter), and large Ni-Si and Ni-Si-Mn clusters (8-10 nm in diameter). The total cluster number density was 7.7 × 1023 m-3. The fraction of large clusters was almost 1/10 of the total density. The average composition (in at%) for small clusters was: Fe, 54; Cr, 12; Mn, 1; Ni, 22; Si, 11; Mo, 1, and for large clusters it was: Fe, 44; Cr, 9; Mn, 2; Ni, 29; Si, 14; Mo,1. It was likely that some of the Ni-Si clusters correspond to γ‧ phase precipitates while the Ni-Si-Mn clusters were precursors of G phase precipitates. The APT analyses at grain boundaries confirmed enrichment of Ni, Si, P and Cu and depletion of Fe, Cr, Mo and Mn. The segregation behavior was consistent with previous knowledge of radiation induced segregation.

Butyrate production in phylogenetically diverse Firmicutes isolated from the chicken caecum

PubMed Central

Eeckhaut, Venessa; Van Immerseel, Filip; Croubels, Siska; De Baere, Siegrid; Haesebrouck, Freddy; Ducatelle, Richard; Louis, Petra; Vandamme, Peter

2011-01-01

Summary Sixteen butyrate‐producing bacteria were isolated from the caecal content of chickens and analysed phylogenetically. They did not represent a coherent phylogenetic group, but were allied to four different lineages in the Firmicutes phylum. Fourteen strains appeared to represent novel species, based on a level of ≤ 98.5% 16S rRNA gene sequence similarity towards their nearest validly named neighbours. The highest butyrate concentrations were produced by the strains belonging to clostridial clusters IV and XIVa, clusters which are predominant in the chicken caecal microbiota. In only one of the 16 strains tested, the butyrate kinase operon could be amplified, while the butyryl‐CoA : acetate CoA‐transferase gene was detected in eight strains belonging to clostridial clusters IV, XIVa and XIVb. None of the clostridial cluster XVI isolates carried this gene based on degenerate PCR analyses. However, another CoA‐transferase gene more similar to propionate CoA‐transferase was detected in the majority of the clostridial cluster XVI isolates. Since this gene is located directly downstream of the remaining butyrate pathway genes in several human cluster XVI bacteria, it may be involved in butyrate formation in these bacteria. The present study indicates that butyrate producers related to cluster XVI may play a more important role in the chicken gut than in the human gut. PMID:21375722

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

NASA Astrophysics Data System (ADS)

Salimi, F.; Ristovski, Z.; Mazaheri, M.; Laiman, R.; Crilley, L. R.; He, C.; Clifford, S.; Morawska, L.

2014-06-01

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

NASA Astrophysics Data System (ADS)

Salimi, F.; Ristovski, Z.; Mazaheri, M.; Laiman, R.; Crilley, L. R.; He, C.; Clifford, S.; Morawska, L.

2014-11-01

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods that have been recently employed to analyse PNSD data; however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectrum to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Deciphering the Cryptic Genome: Genome-wide Analyses of the Rice Pathogen Fusarium fujikuroi Reveal Complex Regulation of Secondary Metabolism and Novel Metabolites

PubMed Central

Studt, Lena; Niehaus, Eva-Maria; Espino, Jose J.; Huß, Kathleen; Michielse, Caroline B.; Albermann, Sabine; Wagner, Dominik; Bergner, Sonja V.; Connolly, Lanelle R.; Fischer, Andreas; Reuter, Gunter; Kleigrewe, Karin; Bald, Till; Wingfield, Brenda D.; Ophir, Ron; Freeman, Stanley; Hippler, Michael; Smith, Kristina M.; Brown, Daren W.; Proctor, Robert H.; Münsterkötter, Martin; Freitag, Michael; Humpf, Hans-Ulrich; Güldener, Ulrich; Tudzynski, Bettina

2013-01-01

The fungus Fusarium fujikuroi causes “bakanae” disease of rice due to its ability to produce gibberellins (GAs), but it is also known for producing harmful mycotoxins. However, the genetic capacity for the whole arsenal of natural compounds and their role in the fungus' interaction with rice remained unknown. Here, we present a high-quality genome sequence of F. fujikuroi that was assembled into 12 scaffolds corresponding to the 12 chromosomes described for the fungus. We used the genome sequence along with ChIP-seq, transcriptome, proteome, and HPLC-FTMS-based metabolome analyses to identify the potential secondary metabolite biosynthetic gene clusters and to examine their regulation in response to nitrogen availability and plant signals. The results indicate that expression of most but not all gene clusters correlate with proteome and ChIP-seq data. Comparison of the F. fujikuroi genome to those of six other fusaria revealed that only a small number of gene clusters are conserved among these species, thus providing new insights into the divergence of secondary metabolism in the genus Fusarium. Noteworthy, GA biosynthetic genes are present in some related species, but GA biosynthesis is limited to F. fujikuroi, suggesting that this provides a selective advantage during infection of the preferred host plant rice. Among the genome sequences analyzed, one cluster that includes a polyketide synthase gene (PKS19) and another that includes a non-ribosomal peptide synthetase gene (NRPS31) are unique to F. fujikuroi. The metabolites derived from these clusters were identified by HPLC-FTMS-based analyses of engineered F. fujikuroi strains overexpressing cluster genes. In planta expression studies suggest a specific role for the PKS19-derived product during rice infection. Thus, our results indicate that combined comparative genomics and genome-wide experimental analyses identified novel genes and secondary metabolites that contribute to the evolutionary success of F. fujikuroi as a rice pathogen. PMID:23825955

Multilevel models for cost-effectiveness analyses that use cluster randomised trial data: An approach to model choice.

PubMed

Ng, Edmond S-W; Diaz-Ordaz, Karla; Grieve, Richard; Nixon, Richard M; Thompson, Simon G; Carpenter, James R

2016-10-01

Multilevel models provide a flexible modelling framework for cost-effectiveness analyses that use cluster randomised trial data. However, there is a lack of guidance on how to choose the most appropriate multilevel models. This paper illustrates an approach for deciding what level of model complexity is warranted; in particular how best to accommodate complex variance-covariance structures, right-skewed costs and missing data. Our proposed models differ according to whether or not they allow individual-level variances and correlations to differ across treatment arms or clusters and by the assumed cost distribution (Normal, Gamma, Inverse Gaussian). The models are fitted by Markov chain Monte Carlo methods. Our approach to model choice is based on four main criteria: the characteristics of the data, model pre-specification informed by the previous literature, diagnostic plots and assessment of model appropriateness. This is illustrated by re-analysing a previous cost-effectiveness analysis that uses data from a cluster randomised trial. We find that the most useful criterion for model choice was the deviance information criterion, which distinguishes amongst models with alternative variance-covariance structures, as well as between those with different cost distributions. This strategy for model choice can help cost-effectiveness analyses provide reliable inferences for policy-making when using cluster trials, including those with missing data. © The Author(s) 2013.

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

PubMed

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

A comparison of visual search strategies of elite and non-elite tennis players through cluster analysis.

PubMed

Murray, Nicholas P; Hunfalvay, Melissa

2017-02-01

Considerable research has documented that successful performance in interceptive tasks (such as return of serve in tennis) is based on the performers' capability to capture appropriate anticipatory information prior to the flight path of the approaching object. Athletes of higher skill tend to fixate on different locations in the playing environment prior to initiation of a skill than their lesser skilled counterparts. The purpose of this study was to examine visual search behaviour strategies of elite (world ranked) tennis players and non-ranked competitive tennis players (n = 43) utilising cluster analysis. The results of hierarchical (Ward's method) and nonhierarchical (k means) cluster analyses revealed three different clusters. The clustering method distinguished visual behaviour of high, middle-and low-ranked players. Specifically, high-ranked players demonstrated longer mean fixation duration and lower variation of visual search than middle-and low-ranked players. In conclusion, the results demonstrated that cluster analysis is a useful tool for detecting and analysing the areas of interest for use in experimental analysis of expertise and to distinguish visual search variables among participants'.

Characteristics of airflow and particle deposition in COPD current smokers

NASA Astrophysics Data System (ADS)

Zou, Chunrui; Choi, Jiwoong; Haghighi, Babak; Choi, Sanghun; Hoffman, Eric A.; Lin, Ching-Long

2017-11-01

A recent imaging-based cluster analysis of computed tomography (CT) lung images in a chronic obstructive pulmonary disease (COPD) cohort identified four clusters, viz. disease sub-populations. Cluster 1 had relatively normal airway structures; Cluster 2 had wall thickening; Cluster 3 exhibited decreased wall thickness and luminal narrowing; Cluster 4 had a significant decrease of luminal diameter and a significant reduction of lung deformation, thus having relatively low pulmonary functions. To better understand the characteristics of airflow and particle deposition in these clusters, we performed computational fluid and particle dynamics analyses on representative cluster patients and healthy controls using CT-based airway models and subject-specific 3D-1D coupled boundary conditions. The results show that particle deposition in central airways of cluster 4 patients was noticeably increased especially with increasing particle size despite reduced vital capacity as compared to other clusters and healthy controls. This may be attributable in part to significant airway constriction in cluster 4. This study demonstrates the potential application of cluster-guided CFD analysis in disease populations. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837.

Thermodynamically accessible titanium clusters TiN, N = 2-32.

PubMed

Lazauskas, Tomas; Sokol, Alexey A; Buckeridge, John; Catlow, C Richard A; Escher, Susanne G E T; Farrow, Matthew R; Mora-Fonz, David; Blum, Volker W; Phaahla, Tshegofatso M; Chauke, Hasani R; Ngoepe, Phuti E; Woodley, Scott M

2018-05-10

We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2-32) clusters. The low energy candidate clusters were further refined using density functional theory (DFT) calculations with the PBEsol exchange-correlation functional and evaluated with the PBEsol0 hybrid functional. The resulting clusters were analysed in terms of their structural features, growth mechanism and surface area. The results suggest a growth mechanism that is based on forming coordination centres by interpenetrating icosahedra, icositetrahedra and Frank-Kasper polyhedra. We identify centres of coordination, which act as centres of bulk nucleation in medium sized clusters and determine the morphological features of the cluster.

Does the cognitive dispute of psychotic symptoms do harm to the therapeutic alliance?

PubMed

Wittorf, Andreas; Jakobi, Ute E; Bannert, Kerstin K; Bechdolf, Andreas; Müller, Bernhard W; Sartory, Gudrun; Wagner, Michael; Wiedemann, Georg; Wölwer, Wolfgang; Herrlich, Jutta; Buchkremer, Gerhard; Klingberg, Stefan

2010-07-01

We examined whether the cognitive dispute of psychotic symptoms has a negative impact on the course of the therapeutic alliance. Sixty-seven patients with persistent psychotic symptoms received either cognitive behavioral therapy (CBT) or supportive therapy. Questionnaire-based alliance ratings were repeatedly obtained throughout the course of therapy. Patient and therapist alliance ratings were examined separately. Data analyses comprised repeated measurement analyses of variance and cluster analytic procedures. Neither patient nor therapist alliance ratings showed a differential course throughout the treatments. This was despite the implementation of disputing strategies in later stages of CBT. Irrespective of the treatment condition a cluster with a positive alliance rating and a cluster with a poorer rating were found for therapist and patient ratings, respectively. Baseline symptoms and insight differentiated between the types of clusters. In conclusion, CBT-specific interventions that challenge psychotic symptoms do not necessarily negatively influence the course of the alliance.

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.

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

Assessment of cluster yield components by image analysis.

PubMed

Diago, Maria P; Tardaguila, Javier; Aleixos, Nuria; Millan, Borja; Prats-Montalban, Jose M; Cubero, Sergio; Blasco, Jose

2015-04-01

Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry.

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma.

PubMed

Aoki, Shuichiro; Murata, Hiroshi; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Hirasawa, Kazunori; Shoji, Nobuyuki; Asaoka, Ryo

2017-12-01

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma. Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis. Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters. Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

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

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

Probing high-redshift clusters with HST/ACS gravitational weak-lensing and Chandra x-ray observations

NASA Astrophysics Data System (ADS)

Jee, Myungkook James

2006-06-01

Clusters of galaxies, the largest gravitationally bound objects in the Universe, are useful tracers of cosmic evolution, and particularly detailed studies of still-forming clusters at high-redshifts can considerably enhance our understanding of the structure formation. We use two powerful methods that have become recently available for the study of these distant clusters: spaced- based gravitational weak-lensing and high-resolution X-ray observations. Detailed analyses of five high-redshift (0.8 < z < 1.3) clusters are presented based on the deep Advanced Camera for Surveys (ACS) and Chandra X-ray images. We show that, when the instrumental characteristics are properly understood, the newly installed ACS on the Hubble Space Telescope (HST) can detect subtle shape distortions of background galaxies down to the limiting magnitudes of the observations, which enables the mapping of the cluster dark matter in unprecedented high-resolution. The cluster masses derived from this HST /ACS weak-lensing study have been compared with those from the re-analyses of the archival Chandra X-ray data. We find that there are interesting offsets between the cluster galaxy, intracluster medium (ICM), and dark matter centroids, and possible scenarios are discussed. If the offset is confirmed to be uniquitous in other clusters, the explanation may necessitate major refinements in our current understanding of the nature of dark matter, as well as the cluster galaxy dynamics. CL0848+4452, the highest-redshift ( z = 1.27) cluster yet detected in weak-lensing, has a significant discrepancy between the weak- lensing and X-ray masses. If this trend is found to be severe and common also for other X-ray weak clusters at redshifts beyond the unity, the conventional X-ray determination of cluster mass functions, often inferred from their immediate X-ray properties such as the X-ray luminosity and temperature via the so-called mass-luminosity (M-L) and mass-temperature (M-T) relations, will become highly unstable in this redshift regime. Therefore, the relatively unbiased weak-lensing measurements of the cluster mass properties can be used to adequately calibrate the scaling relations in future high-redshift cluster investigations.

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

Algorithmic localisation of noise sources in the tip region of a low-speed axial flow fan

NASA Astrophysics Data System (ADS)

Tóth, Bence; Vad, János

2017-04-01

An objective and algorithmised methodology is proposed to analyse beamform data obtained for axial fans. Its application is demonstrated in a case study regarding the tip region of a low-speed cooling fan. First, beamforming is carried out in a co-rotating frame of reference. Then, a distribution of source strength is extracted along the circumference of the rotor at the blade tip radius in each analysed third-octave band. The circumferential distributions are expanded into Fourier series, which allows for filtering out the effects of perturbations, on the basis of an objective criterion. The remaining Fourier components are then considered as base sources to determine the blade-passage-periodic flow mechanisms responsible for the broadband noise. Based on their frequency and angular location, the base sources are grouped together. This is done using the fuzzy c-means clustering method to allow the overlap of the source mechanisms. The number of clusters is determined in a validity analysis. Finally, the obtained clusters are assigned to source mechanisms based on the literature. Thus, turbulent boundary layer - trailing edge interaction noise, tip leakage flow noise, and double leakage flow noise are identified.

Health and Human Services Cluster. Task Analyses. Physical Therapist Aide and Physical Therapist Assistant. A Competency-Based Curriculum Guide.

ERIC Educational Resources Information Center

Henrico County Public Schools, Glen Allen, VA. Virginia Vocational Curriculum and Resource Center.

Developed in Virginia, this publication contains task analysis guides to support selected tech prep programs that prepare students for careers in the health and human services cluster. Occupations profiled are physical therapist aide and physical therapist assistant. Each guide contains the following elements: (1) an occupational task list derived…

A segmentation method for lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise

PubMed Central

Zhang, Wei; Zhang, Xiaolong; Qiang, Yan; Tian, Qi; Tang, Xiaoxian

2017-01-01

The fast and accurate segmentation of lung nodule image sequences is the basis of subsequent processing and diagnostic analyses. However, previous research investigating nodule segmentation algorithms cannot entirely segment cavitary nodules, and the segmentation of juxta-vascular nodules is inaccurate and inefficient. To solve these problems, we propose a new method for the segmentation of lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise (DBSCAN). First, our method uses three-dimensional computed tomography image features of the average intensity projection combined with multi-scale dot enhancement for preprocessing. Hexagonal clustering and morphological optimized sequential linear iterative clustering (HMSLIC) for sequence image oversegmentation is then proposed to obtain superpixel blocks. The adaptive weight coefficient is then constructed to calculate the distance required between superpixels to achieve precise lung nodules positioning and to obtain the subsequent clustering starting block. Moreover, by fitting the distance and detecting the change in slope, an accurate clustering threshold is obtained. Thereafter, a fast DBSCAN superpixel sequence clustering algorithm, which is optimized by the strategy of only clustering the lung nodules and adaptive threshold, is then used to obtain lung nodule mask sequences. Finally, the lung nodule image sequences are obtained. The experimental results show that our method rapidly, completely and accurately segments various types of lung nodule image sequences. PMID:28880916

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

Intracluster age gradients in numerous young stellar clusters

NASA Astrophysics Data System (ADS)

Getman, K. V.; Feigelson, E. D.; Kuhn, M. A.; Bate, M. R.; Broos, P. S.; Garmire, G. P.

2018-05-01

The pace and pattern of star formation leading to rich young stellar clusters is quite uncertain. In this context, we analyse the spatial distribution of ages within 19 young (median t ≲ 3 Myr on the Siess et al. time-scale), morphologically simple, isolated, and relatively rich stellar clusters. Our analysis is based on young stellar object (YSO) samples from the Massive Young Star-Forming Complex Study in Infrared and X-ray and Star Formation in Nearby Clouds surveys, and a new estimator of pre-main sequence (PMS) stellar ages, AgeJX, derived from X-ray and near-infrared photometric data. Median cluster ages are computed within four annular subregions of the clusters. We confirm and extend the earlier result of Getman et al. (2014): 80 per cent of the clusters show age trends where stars in cluster cores are younger than in outer regions. Our cluster stacking analyses establish the existence of an age gradient to high statistical significance in several ways. Time-scales vary with the choice of PMS evolutionary model; the inferred median age gradient across the studied clusters ranges from 0.75 to 1.5 Myr pc-1. The empirical finding reported in the present study - late or continuing formation of stars in the cores of star clusters with older stars dispersed in the outer regions - has a strong foundation with other observational studies and with the astrophysical models like the global hierarchical collapse model of Vázquez-Semadeni et al.

Parcellation of left parietal tool representations by functional connectivity

PubMed Central

Garcea, Frank E.; Z. Mahon, Bradford

2014-01-01

Manipulating a tool according to its function requires the integration of visual, conceptual, and motor information, a process subserved in part by left parietal cortex. How these different types of information are integrated and how their integration is reflected in neural responses in the parietal lobule remains an open question. Here, participants viewed images of tools and animals during functional magnetic resonance imaging (fMRI). K-means clustering over time series data was used to parcellate left parietal cortex into subregions based on functional connectivity to a whole brain network of regions involved in tool processing. One cluster, in the inferior parietal cortex, expressed privileged functional connectivity to the left ventral premotor cortex. A second cluster, in the vicinity of the anterior intraparietal sulcus, expressed privileged functional connectivity with the left medial fusiform gyrus. A third cluster in the superior parietal lobe expressed privileged functional connectivity with dorsal occipital cortex. Control analyses using Monte Carlo style permutation tests demonstrated that the clustering solutions were outside the range of what would be observed based on chance ‘lumpiness’ in random data, or mere anatomical proximity. Finally, hierarchical clustering analyses were used to formally relate the resulting parcellation scheme of left parietal tool representations to previous work that has parcellated the left parietal lobule on purely anatomical grounds. These findings demonstrate significant heterogeneity in the functional organization of manipulable object representations in left parietal cortex, and outline a framework that generates novel predictions about the causes of some forms of upper limb apraxia. PMID:24892224

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: combining correlated Gaussian posterior distributions

DOE PAGES

Sánchez, Ariel G.; Grieb, Jan Niklas; Salazar-Albornoz, Salvador; ...

2016-09-30

The cosmological information contained in anisotropic galaxy clustering measurements can often be compressed into a small number of parameters whose posterior distribution is well described by a Gaussian. Here, we present a general methodology to combine these estimates into a single set of consensus constraints that encode the total information of the individual measurements, taking into account the full covariance between the different methods. We also illustrate this technique by applying it to combine the results obtained from different clustering analyses, including measurements of the signature of baryon acoustic oscillations and redshift-space distortions, based on a set of mock cataloguesmore » of the final SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Our results show that the region of the parameter space allowed by the consensus constraints is smaller than that of the individual methods, highlighting the importance of performing multiple analyses on galaxy surveys even when the measurements are highly correlated. Our paper is part of a set that analyses the final galaxy clustering data set from BOSS. The methodology presented here is used in Alam et al. to produce the final cosmological constraints from BOSS.« less

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Galaxy clusters in the cosmic web

NASA Astrophysics Data System (ADS)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4

Text-mining analysis of mHealth research.

PubMed

Ozaydin, Bunyamin; Zengul, Ferhat; Oner, Nurettin; Delen, Dursun

2017-01-01

In recent years, because of the advancements in communication and networking technologies, mobile technologies have been developing at an unprecedented rate. mHealth, the use of mobile technologies in medicine, and the related research has also surged parallel to these technological advancements. Although there have been several attempts to review mHealth research through manual processes such as systematic reviews, the sheer magnitude of the number of studies published in recent years makes this task very challenging. The most recent developments in machine learning and text mining offer some potential solutions to address this challenge by allowing analyses of large volumes of texts through semi-automated processes. The objective of this study is to analyze the evolution of mHealth research by utilizing text-mining and natural language processing (NLP) analyses. The study sample included abstracts of 5,644 mHealth research articles, which were gathered from five academic search engines by using search terms such as mobile health, and mHealth. The analysis used the Text Explorer module of JMP Pro 13 and an iterative semi-automated process involving tokenizing, phrasing, and terming. After developing the document term matrix (DTM) analyses such as single value decomposition (SVD), topic, and hierarchical document clustering were performed, along with the topic-informed document clustering approach. The results were presented in the form of word-clouds and trend analyses. There were several major findings regarding research clusters and trends. First, our results confirmed time-dependent nature of terminology use in mHealth research. For example, in earlier versus recent years the use of terminology changed from "mobile phone" to "smartphone" and from "applications" to "apps". Second, ten clusters for mHealth research were identified including (I) Clinical Research on Lifestyle Management, (II) Community Health, (III) Literature Review, (IV) Medical Interventions, (V) Research Design, (VI) Infrastructure, (VII) Applications, (VIII) Research and Innovation in Health Technologies, (IX) Sensor-based Devices and Measurement Algorithms, (X) Survey-based Research. Third, the trend analyses indicated the infrastructure cluster as the highest percentage researched area until 2014. The Research and Innovation in Health Technologies cluster experienced the largest increase in numbers of publications in recent years, especially after 2014. This study is unique because it is the only known study utilizing text-mining analyses to reveal the streams and trends for mHealth research. The fast growth in mobile technologies is expected to lead to higher numbers of studies focusing on mHealth and its implications for various healthcare outcomes. Findings of this study can be utilized by researchers in identifying areas for future studies.

Text-mining analysis of mHealth research

PubMed Central

Zengul, Ferhat; Oner, Nurettin; Delen, Dursun

2017-01-01

In recent years, because of the advancements in communication and networking technologies, mobile technologies have been developing at an unprecedented rate. mHealth, the use of mobile technologies in medicine, and the related research has also surged parallel to these technological advancements. Although there have been several attempts to review mHealth research through manual processes such as systematic reviews, the sheer magnitude of the number of studies published in recent years makes this task very challenging. The most recent developments in machine learning and text mining offer some potential solutions to address this challenge by allowing analyses of large volumes of texts through semi-automated processes. The objective of this study is to analyze the evolution of mHealth research by utilizing text-mining and natural language processing (NLP) analyses. The study sample included abstracts of 5,644 mHealth research articles, which were gathered from five academic search engines by using search terms such as mobile health, and mHealth. The analysis used the Text Explorer module of JMP Pro 13 and an iterative semi-automated process involving tokenizing, phrasing, and terming. After developing the document term matrix (DTM) analyses such as single value decomposition (SVD), topic, and hierarchical document clustering were performed, along with the topic-informed document clustering approach. The results were presented in the form of word-clouds and trend analyses. There were several major findings regarding research clusters and trends. First, our results confirmed time-dependent nature of terminology use in mHealth research. For example, in earlier versus recent years the use of terminology changed from “mobile phone” to “smartphone” and from “applications” to “apps”. Second, ten clusters for mHealth research were identified including (I) Clinical Research on Lifestyle Management, (II) Community Health, (III) Literature Review, (IV) Medical Interventions, (V) Research Design, (VI) Infrastructure, (VII) Applications, (VIII) Research and Innovation in Health Technologies, (IX) Sensor-based Devices and Measurement Algorithms, (X) Survey-based Research. Third, the trend analyses indicated the infrastructure cluster as the highest percentage researched area until 2014. The Research and Innovation in Health Technologies cluster experienced the largest increase in numbers of publications in recent years, especially after 2014. This study is unique because it is the only known study utilizing text-mining analyses to reveal the streams and trends for mHealth research. The fast growth in mobile technologies is expected to lead to higher numbers of studies focusing on mHealth and its implications for various healthcare outcomes. Findings of this study can be utilized by researchers in identifying areas for future studies. PMID:29430456

Profiling physical activity motivation based on self-determination theory: a cluster analysis approach.

PubMed

Friederichs, Stijn Ah; Bolman, Catherine; Oenema, Anke; Lechner, Lilian

2015-01-01

In order to promote physical activity uptake and maintenance in individuals who do not comply with physical activity guidelines, it is important to increase our understanding of physical activity motivation among this group. The present study aimed to examine motivational profiles in a large sample of adults who do not comply with physical activity guidelines. The sample for this study consisted of 2473 individuals (31.4% male; age 44.6 ± 12.9). In order to generate motivational profiles based on motivational regulation, a cluster analysis was conducted. One-way analyses of variance were then used to compare the clusters in terms of demographics, physical activity level, motivation to be active and subjective experience while being active. Three motivational clusters were derived based on motivational regulation scores: a low motivation cluster, a controlled motivation cluster and an autonomous motivation cluster. These clusters differed significantly from each other with respect to physical activity behavior, motivation to be active and subjective experience while being active. Overall, the autonomous motivation cluster displayed more favorable characteristics compared to the other two clusters. The results of this study provide additional support for the importance of autonomous motivation in the context of physical activity behavior. The three derived clusters may be relevant in the context of physical activity interventions as individuals within the different clusters might benefit most from different intervention approaches. In addition, this study shows that cluster analysis is a useful method for differentiating between motivational profiles in large groups of individuals who do not comply with physical activity guidelines.

Probabilistic Analysis of Hierarchical Cluster Protocols for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kaj, Ingemar

Wireless sensor networks are designed to extract data from the deployment environment and combine sensing, data processing and wireless communication to provide useful information for the network users. Hundreds or thousands of small embedded units, which operate under low-energy supply and with limited access to central network control, rely on interconnecting protocols to coordinate data aggregation and transmission. Energy efficiency is crucial and it has been proposed that cluster based and distributed architectures such as LEACH are particularly suitable. We analyse the random cluster hierarchy in this protocol and provide a solution for low-energy and limited-loss optimization. Moreover, we extend these results to a multi-level version of LEACH, where clusters of nodes again self-organize to form clusters of clusters, and so on.

Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer.

PubMed

Hoadley, Katherine A; Yau, Christina; Hinoue, Toshinori; Wolf, Denise M; Lazar, Alexander J; Drill, Esther; Shen, Ronglai; Taylor, Alison M; Cherniack, Andrew D; Thorsson, Vésteinn; Akbani, Rehan; Bowlby, Reanne; Wong, Christopher K; Wiznerowicz, Maciej; Sanchez-Vega, Francisco; Robertson, A Gordon; Schneider, Barbara G; Lawrence, Michael S; Noushmehr, Houtan; Malta, Tathiane M; Stuart, Joshua M; Benz, Christopher C; Laird, Peter W

2018-04-05

We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Copyright © 2018 Elsevier Inc. All rights reserved.

Analysis of genetic diversity in banana cultivars (Musa cvs.) from the South of Oman using AFLP markers and classification by phylogenetic, hierarchical clustering and principal component analyses*

PubMed Central

Opara, Umezuruike Linus; Jacobson, Dan; Al-Saady, Nadiya Abubakar

2010-01-01

Banana is an important crop grown in Oman and there is a dearth of information on its genetic diversity to assist in crop breeding and improvement programs. This study employed amplified fragment length polymorphism (AFLP) to investigate the genetic variation in local banana cultivars from the southern region of Oman. Using 12 primer combinations, a total of 1094 bands were scored, of which 1012 were polymorphic. Eighty-two unique markers were identified, which revealed the distinct separation of the seven cultivars. The results obtained show that AFLP can be used to differentiate the banana cultivars. Further classification by phylogenetic, hierarchical clustering and principal component analyses showed significant differences between the clusters found with molecular markers and those clusters created by previous studies using morphological analysis. Based on the analytical results, a consensus dendrogram of the banana cultivars is presented. PMID:20443211

Pressure of the hot gas in simulations of galaxy clusters

NASA Astrophysics Data System (ADS)

Planelles, S.; Fabjan, D.; Borgani, S.; Murante, G.; Rasia, E.; Biffi, V.; Truong, N.; Ragone-Figueroa, C.; Granato, G. L.; Dolag, K.; Pierpaoli, E.; Beck, A. M.; Steinborn, Lisa K.; Gaspari, M.

2017-06-01

We analyse the radial pressure profiles, the intracluster medium (ICM) clumping factor and the Sunyaev-Zel'dovich (SZ) scaling relations of a sample of simulated galaxy clusters and groups identified in a set of hydrodynamical simulations based on an updated version of the treepm-SPH GADGET-3 code. Three different sets of simulations are performed: the first assumes non-radiative physics, the others include, among other processes, active galactic nucleus (AGN) and/or stellar feedback. Our results are analysed as a function of redshift, ICM physics, cluster mass and cluster cool-coreness or dynamical state. In general, the mean pressure profiles obtained for our sample of groups and clusters show a good agreement with X-ray and SZ observations. Simulated cool-core (CC) and non-cool-core (NCC) clusters also show a good match with real data. We obtain in all cases a small (if any) redshift evolution of the pressure profiles of massive clusters, at least back to z = 1. We find that the clumpiness of gas density and pressure increases with the distance from the cluster centre and with the dynamical activity. The inclusion of AGN feedback in our simulations generates values for the gas clumping (√{C}_{ρ }˜ 1.2 at R200) in good agreement with recent observational estimates. The simulated YSZ-M scaling relations are in good accordance with several observed samples, especially for massive clusters. As for the scatter of these relations, we obtain a clear dependence on the cluster dynamical state, whereas this distinction is not so evident when looking at the subsamples of CC and NCC clusters.

Patterns of Physical and Relational Aggression in a School-Based Sample of Boys and Girls

ERIC Educational Resources Information Center

Crapanzano, Ann Marie; Frick, Paul J.; Terranova, Andrew M.

2010-01-01

The current study investigated the patterns of aggressive behavior displayed in a sample of 282 students in the 4th through 7th grades (M age = 11.28; SD = 1.82). Using cluster analyses, two distinct patterns of physical aggression emerged for both boys and girls with one aggressive cluster showing mild levels of reactive aggression and one group…

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

PubMed

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

2014-11-01

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

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

Predicting stabilizing treatment outcomes for complex posttraumatic stress disorder and dissociative identity disorder: an expertise-based prognostic model.

PubMed

Baars, Erik W; van der Hart, Onno; Nijenhuis, Ellert R S; Chu, James A; Glas, Gerrit; Draijer, Nel

2011-01-01

The purpose of this study was to develop an expertise-based prognostic model for the treatment of complex posttraumatic stress disorder (PTSD) and dissociative identity disorder (DID). We developed a survey in 2 rounds: In the first round we surveyed 42 experienced therapists (22 DID and 20 complex PTSD therapists), and in the second round we surveyed a subset of 22 of the 42 therapists (13 DID and 9 complex PTSD therapists). First, we drew on therapists' knowledge of prognostic factors for stabilization-oriented treatment of complex PTSD and DID. Second, therapists prioritized a list of prognostic factors by estimating the size of each variable's prognostic effect; we clustered these factors according to content and named the clusters. Next, concept mapping methodology and statistical analyses (including principal components analyses) were used to transform individual judgments into weighted group judgments for clusters of items. A prognostic model, based on consensually determined estimates of effect sizes, of 8 clusters containing 51 factors for both complex PTSD and DID was formed. It includes the clusters lack of motivation, lack of healthy relationships, lack of healthy therapeutic relationships, lack of other internal and external resources, serious Axis I comorbidity, serious Axis II comorbidity, poor attachment, and self-destruction. In addition, a set of 5 DID-specific items was constructed. The model is supportive of the current phase-oriented treatment model, emphasizing the strengthening of the therapeutic relationship and the patient's resources in the initial stabilization phase. Further research is needed to test the model's statistical and clinical validity.

A multilevel analysis of gatekeeper characteristics and consistent condom use among establishment-based female sex workers in Guangxi, China.

PubMed

Li, Qing; Li, Xiaoming; Stanton, Bonita; Fang, Xiaoyi; Zhao, Ran

2010-11-01

Multilevel analytical techniques are being applied in condom use research to ensure the validity of investigation on environmental/structural influences and clustered data from venue-based sampling. The literature contains reports of consistent associations between perceived gatekeeper support and condom use among entertainment establishment-based female sex workers (FSWs) in Guangxi, China. However, the clustering inherent in the data (FSWs being clustered within establishment) has not been accounted in most of the analyses. We used multilevel analyses to examine perceived features of gatekeepers and individual correlates of consistent condom use among FSWs and to validate the findings in the existing literature. We analyzed cross-sectional data from 318 FSWs from 29 entertainment establishments in Guangxi, China in 2004, with a minimum of 5 FSWs per establishment. The Hierarchical Linear Models program with Laplace estimation was used to estimate the parameters in models containing random effects and binary outcomes. About 11.6% of women reported consistent condom use with clients. The intraclass correlation coefficient indicated 18.5% of the variance in condom use could be attributed to their similarity between FSWs within the same establishments. Women's perceived gatekeeper support and education remained positively associated with condom use (P < 0.05), after controlling for other individual characteristics and clustering. After adjusting for data clustering, perceived gatekeeper support remains associated with consistent condom use with clients among FSWs in China. The results imply that combined interventions to intervene both gatekeepers and individual FSW may effectively promote consistent condom use.

A Multilevel Analysis of Gatekeeper Characteristics and Consistent Condom Use Among Establishment-Based Female Sex Workers in Guangxi, China

PubMed Central

Li, Qing; Li, Xiaoming; Stanton, Bonita; Fang, Xiaoyi; Zhao, Ran

2010-01-01

Background Multilevel analytical techniques are being applied in condom use research to ensure the validity of investigation on environmental/structural influences and clustered data from venue-based sampling. The literature contains reports of consistent associations between perceived gatekeeper support and condom use among entertainments establishment-based female sex workers (FSWs) in Guangxi, China. However, the clustering inherent in the data (FSWs being clustered within establishment) has not been accounted in most of the analyses. We used multilevel analyses to examine perceived features of gatekeepers and individual correlates of consistent condom use among FSWs and to validate the findings in the existing literature. Methods We analyzed cross-sectional data from 318 FSWs from 29 entertainment establishments in Guangxi, China in 2004, with a minimum of 5 FSWs per establishment. The Hierarchical Linear Models program with Laplace estimation was used to estimate the parameters in models containing random effects and binary outcomes. Results About 11.6% of women reported consistent condom use with clients. The intraclass correlation coefficient indicated 18.5% of the variance in condom use could be attributed to their similarity between FSWs within the same establishments. Women’s perceived gatekeeper support and education remained positively associated with condom use (P < 0.05), after controlling for other individual characteristics and clustering. Conclusions After adjusting for data clustering, perceived gatekeeper support remains associated with consistent condom use with clients among FSWs in China. The results imply that combined interventions to intervene both gatekeepers and individual FSW may effectively promote consistent condom use. PMID:20539262

The anterior hypothalamus in cluster headache.

PubMed

Arkink, Enrico B; Schmitz, Nicole; Schoonman, Guus G; van Vliet, Jorine A; Haan, Joost; van Buchem, Mark A; Ferrari, Michel D; Kruit, Mark C

2017-10-01

Objective To evaluate the presence, localization, and specificity of structural hypothalamic and whole brain changes in cluster headache and chronic paroxysmal hemicrania (CPH). Methods We compared T1-weighted magnetic resonance images of subjects with cluster headache (episodic n = 24; chronic n = 23; probable n = 14), CPH ( n = 9), migraine (with aura n = 14; without aura n = 19), and no headache ( n = 48). We applied whole brain voxel-based morphometry (VBM) using two complementary methods to analyze structural changes in the hypothalamus: region-of-interest analyses in whole brain VBM, and manual segmentation of the hypothalamus to calculate volumes. We used both conservative VBM thresholds, correcting for multiple comparisons, and less conservative thresholds for exploratory purposes. Results Using region-of-interest VBM analyses mirrored to the headache side, we found enlargement ( p < 0.05, small volume correction) in the anterior hypothalamic gray matter in subjects with chronic cluster headache compared to controls, and in all participants with episodic or chronic cluster headache taken together compared to migraineurs. After manual segmentation, hypothalamic volume (mean±SD) was larger ( p < 0.05) both in subjects with episodic (1.89 ± 0.18 ml) and chronic (1.87 ± 0.21 ml) cluster headache compared to controls (1.72 ± 0.15 ml) and migraineurs (1.68 ± 0.19 ml). Similar but non-significant trends were observed for participants with probable cluster headache (1.82 ± 0.19 ml; p = 0.07) and CPH (1.79 ± 0.20 ml; p = 0.15). Increased hypothalamic volume was primarily explained by bilateral enlargement of the anterior hypothalamus. Exploratory whole brain VBM analyses showed widespread changes in pain-modulating areas in all subjects with headache. Interpretation The anterior hypothalamus is enlarged in episodic and chronic cluster headache and possibly also in probable cluster headache or CPH, but not in migraine.

Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster

NASA Astrophysics Data System (ADS)

Syakur, M. A.; Khotimah, B. K.; Rochman, E. M. S.; Satoto, B. D.

2018-04-01

Clustering is a data mining technique used to analyse data that has variations and the number of lots. Clustering was process of grouping data into a cluster, so they contained data that is as similar as possible and different from other cluster objects. SMEs Indonesia has a variety of customers, but SMEs do not have the mapping of these customers so they did not know which customers are loyal or otherwise. Customer mapping is a grouping of customer profiling to facilitate analysis and policy of SMEs in the production of goods, especially batik sales. Researchers will use a combination of K-Means method with elbow to improve efficient and effective k-means performance in processing large amounts of data. K-Means Clustering is a localized optimization method that is sensitive to the selection of the starting position from the midpoint of the cluster. So choosing the starting position from the midpoint of a bad cluster will result in K-Means Clustering algorithm resulting in high errors and poor cluster results. The K-means algorithm has problems in determining the best number of clusters. So Elbow looks for the best number of clusters on the K-means method. Based on the results obtained from the process in determining the best number of clusters with elbow method can produce the same number of clusters K on the amount of different data. The result of determining the best number of clusters with elbow method will be the default for characteristic process based on case study. Measurement of k-means value of k-means has resulted in the best clusters based on SSE values on 500 clusters of batik visitors. The result shows the cluster has a sharp decrease is at K = 3, so K as the cut-off point as the best cluster.

Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study.

PubMed

Meghani, Salimah H; Knafl, George J

2017-02-10

To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership. This was a 3-mo prospective observational study ( n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors or multiple myelomas, and had at least one prescription of around-the-clock pain medication for cancer or cancer-treatment-related pain. Patients were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). Patients employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). Patients were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership. The analyses found 4 unique clusters: Most patients made trade-offs based on the expectation of pain relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e ., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including pain relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e ., pain medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)]. Most patients appear to be driven by a single salient concern in using analgesia for cancer pain. Addressing these concerns, perhaps through real time clinical assessments, may improve patients' analgesic adherence patterns and cancer pain outcomes.

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma

PubMed Central

Wasito, Ito; Hashim, Siti Zaiton M; Sukmaningrum, Sri

2007-01-01

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis. PMID:18305825

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma.

PubMed

Wasito, Ito; Hashim, Siti Zaiton M; Sukmaningrum, Sri

2007-12-30

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis.

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

NASA Astrophysics Data System (ADS)

Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.

2018-04-01

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

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.

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

PubMed Central

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data. PMID:20937082

Fast simulation of electromagnetic and hadronic showers in SpaCal calorimeter at the H1 experiment

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

Raičević, Nataša, E-mail: raicevic@mail.desy.de; Glazov, Alexandre

2016-03-25

The fast simulation of showers induced by electrons (positrons) in the H1 lead/scintillating-fiber calorimeter, SpaCal, based on shower library technique has been presented previously. In this paper we show the results on linearity and uniformity of the reconstructed electron/positron cluster energy in electromagnetic section of Spacal for the simulations based on shower library and GFLASH shower parametrisation. The shapes of the clusters originating from photon and hadron candidates in SpaCal are analysed and experimental distributions compared with the two simulations.

Spatial-temporal clustering of companion animal enteric syndrome: detection and investigation through the use of electronic medical records from participating private practices.

PubMed

Anholt, R M; Berezowski, J; Robertson, C; Stephen, C

2015-09-01

There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

Analysis of ambient SO 2 concentrations and winds in the complex surroundings of a thermal power plant

NASA Astrophysics Data System (ADS)

Mlakar, P.

2004-11-01

SO2 pollution is still a significant problem in Slovenia, especially around large thermal power plants (TPPs), like the one at Šoštanj. The Šoštanj TPP is the exclusive source of SO2 in the area and is therefore a perfect example for air pollution studies. In order to understand air pollution around the Šoštanj TPP in detail, some analyses of emissions and ambient concentrations of SO2 at six automated monitoring stations in the surroundings of the TPP were made. The data base from 1991 to 1993 was used when there were no desulfurisation plants in operation. Statistical analyses of the influence of the emissions from the three TPP stacks at different measuring points were made. The analyses prove that the smallest stack (100 m) mainly pollutes villages and towns near the TPP within a radius of a few kilometres. The medium stack's (150 m) influence is noticed at shorter as well as at longer distances up to more than ten kilometres. The highest stack (230 m) pollutes mainly at longer distances, where the plume reaches the higher hills. Detailed analyses of ambient SO2 concentrations were made. They show the temporal and spatial distribution of different classes of SO2 concentrations from very low to alarming values. These analyses show that pollution patterns at a particular station remain the same if observed on a yearly basis, but can vary very much if observed on a monthly basis, mainly because of different weather patterns. Therefore the winds in the basin (as the most important feature influencing air pollution dispersion) were further analysed in detail to find clusters of similar patterns. For cluster analysis of ground-level winds patterns in the basin around the Šoštanj Thermal Power Plant, the Kohonen neural network and Leaders' method were used. Furthermore, the dependence of ambient SO2 concentrations on the clusters obtained was analysed. The results proved that effective cluster analysis can be a useful tool for compressing a huge wind data base in order to find the correlation between winds and pollutant concentrations. The analyses made provide a better insight into air pollution over complex terrain.

Space-time analysis of Down syndrome: results consistent with transient pre-disposing contagious agent.

PubMed

McNally, Richard J Q; Rankin, Judith; Shirley, Mark D F; Rushton, Stephen P; Pless-Mulloli, Tanja

2008-10-01

Whilst maternal age is an established risk factor for Patau syndrome (trisomy 13), Edwards syndrome (trisomy 18) and Down syndrome (trisomy 21), the aetiology and contribution of genetic and environmental factors remains unclear. We analysed for space-time clustering using high quality fully population-based data from a geographically defined region. The study included all cases of Patau, Edwards and Down syndrome, delivered during 1985-2003 and resident in the former Northern Region of England, including terminations of pregnancy for fetal anomaly. We applied the K-function test for space-time clustering with fixed thresholds of close in space and time using residential addresses at time of delivery. The Knox test was used to indicate the range over which the clustering effect occurred. Tests were repeated using nearest neighbour (NN) thresholds to adjust for variable population density. The study analysed 116 cases of Patau syndrome, 240 cases of Edwards syndrome and 1084 cases of Down syndrome. There was evidence of space-time clustering for Down syndrome (fixed threshold of close in space: P = 0.01, NN threshold: P = 0.02), but little or no clustering for Patau (P = 0.57, P = 0.19) or Edwards (P = 0.37, P = 0.06) syndromes. Clustering of Down syndrome was associated with cases from more densely populated areas and evidence of clustering persisted when cases were restricted to maternal age <40 years. The highly novel space-time clustering for Down syndrome suggests an aetiological role for transient environmental factors, such as infections.

Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a population-based survey.

PubMed

Fens, Niki; van Rossum, Annelot G J; Zanen, Pieter; van Ginneken, Bram; van Klaveren, Rob J; Zwinderman, Aeilko H; Sterk, Peter J

2013-06-01

Classification of COPD is currently based on the presence and severity of airways obstruction. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical, radiological and exhaled breath metabolomic features identifies subphenotypes of COPD in a community-based population of heavy (ex-) smokers. Adults between 50-75 years with a smoking history of at least 15 pack-years derived from a random population-based survey as part of the NELSON study underwent detailed assessment of pulmonary function, chest CT scanning, questionnaires and exhaled breath molecular profiling using an electronic nose. Factor and cluster analyses were performed on the subgroup of subjects fulfilling the GOLD criteria for COPD (post-BD FEV1/FVC < 0.70). Three hundred subjects were recruited, of which 157 fulfilled the criteria for COPD and were included in the factor and cluster analysis. Four clusters were identified: cluster 1 (n = 35; 22%): mild COPD, limited symptoms and good quality of life. Cluster 2 (n = 48; 31%): low lung function, combined emphysema and chronic bronchitis and a distinct breath molecular profile. Cluster 3 (n = 60; 38%): emphysema predominant COPD with preserved lung function. Cluster 4 (n = 14; 9%): highly symptomatic COPD with mildly impaired lung function. In a leave-one-out validation analysis an accuracy of 97.4% was reached. This unbiased taxonomy for mild to moderate COPD reinforces clusters found in previous studies and thereby allows better phenotyping of COPD in the general (ex-) smoking population.

The Use of Web 2.0 Tools by Students in Learning and Leisure Contexts: A Study in a Portuguese Institution of Higher Education

ERIC Educational Resources Information Center

Costa, Carolina; Alvelos, Helena; Teixeira, Leonor

2016-01-01

This study analyses and compares the use of Web 2.0 tools by students in both learning and leisure contexts. Data were collected based on a questionnaire applied to 234 students from the University of Aveiro (Portugal) and the results were analysed by using descriptive analysis, paired samples t-tests, cluster analyses and Kruskal-Wallis tests.…

DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer.

PubMed

Saha, Abhijoy; Banerjee, Sayantan; Kurtek, Sebastian; Narang, Shivali; Lee, Joonsang; Rao, Ganesh; Martinez, Juan; Bharath, Karthik; Rao, Arvind U K; Baladandayuthapani, Veerabhadran

2016-01-01

Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

Morphological and Inter Simple Sequence Repeat (ISSR) markers analyses of Corynespora cassiicola isolates from rubber plantations in Malaysia.

PubMed

Nghia, Nguyen Anh; Kadir, Jugah; Sunderasan, E; Puad Abdullah, Mohd; Malik, Adam; Napis, Suhaimi

2008-10-01

Morphological features and Inter Simple Sequence Repeat (ISSR) polymorphism were employed to analyse 21 Corynespora cassiicola isolates obtained from a number of Hevea clones grown in rubber plantations in Malaysia. The C. cassiicola isolates used in this study were collected from several states in Malaysia from 1998 to 2005. The morphology of the isolates was characteristic of that previously described for C. cassiicola. Variations in colony and conidial morphology were observed not only among isolates but also within a single isolate with no inclination to either clonal or geographical origin of the isolates. ISSR analysis delineated the isolates into two distinct clusters. The dendrogram created from UPGMA analysis based on Nei and Li's coefficient (calculated from the binary matrix data of 106 amplified DNA bands generated from 8 ISSR primers) showed that cluster 1 encompasses 12 isolates from the states of Johor and Selangor (this cluster was further split into 2 sub clusters (1A, 1B), sub cluster 1B consists of a unique isolate, CKT05D); while cluster 2 comprises of 9 isolates that were obtained from the other states. Detached leaf assay performed on selected Hevea clones showed that the pathogenicity of representative isolates from cluster 1 (with the exception of CKT05D) resembled that of race 1; and isolates in cluster 2 showed pathogenicity similar to race 2 of the fungus that was previously identified in Malaysia. The isolate CKT05D from sub cluster 1B showed pathogenicity dissimilar to either race 1 or race 2.

Lattice and Valence Electronic Structures of Crystalline Octahedral Molybdenum Halide Clusters-Based Compounds, Cs2[Mo6X14] (X = Cl, Br, I), Studied by Density Functional Theory Calculations.

PubMed

Saito, Norio; Cordier, Stéphane; Lemoine, Pierric; Ohsawa, Takeo; Wada, Yoshiki; Grasset, Fabien; Cross, Jeffrey S; Ohashi, Naoki

2017-06-05

The electronic and crystal structures of Cs 2 [Mo 6 X 14 ] (X = Cl, Br, I) cluster-based compounds were investigated by density functional theory (DFT) simulations and experimental methods such as powder X-ray diffraction, ultraviolet-visible spectroscopy, and X-ray photoemission spectroscopy (XPS). The experimentally determined lattice parameters were in good agreement with theoretically optimized ones, indicating the usefulness of DFT calculations for the structural investigation of these clusters. The calculated band gaps of these compounds reproduced those experimentally determined by UV-vis reflectance within an error of a few tenths of an eV. Core-level XPS and effective charge analyses indicated bonding states of the halogens changed according to their sites. The XPS valence spectra were fairly well reproduced by simulations based on the projected electron density of states weighted with cross sections of Al K α , suggesting that DFT calculations can predict the electronic properties of metal-cluster-based crystals with good accuracy.

Cluster Physics with Merging Galaxy Clusters

NASA Astrophysics Data System (ADS)

Molnar, Sandor

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

DMINDA: an integrated web server for DNA motif identification and analyses

PubMed Central

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-01-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. PMID:24753419

Assessing the genome level diversity of Listeria monocytogenes from contaminated ice cream and environmental samples linked to a listeriosis outbreak in the United States.

PubMed

Chen, Yi; Luo, Yan; Curry, Phillip; Timme, Ruth; Melka, David; Doyle, Matthew; Parish, Mickey; Hammack, Thomas S; Allard, Marc W; Brown, Eric W; Strain, Errol A

2017-01-01

A listeriosis outbreak in the United States implicated contaminated ice cream produced by one company, which operated 3 facilities. We performed single nucleotide polymorphism (SNP)-based whole genome sequencing (WGS) analysis on Listeria monocytogenes from food, environmental and clinical sources, identifying two clusters and a single branch, belonging to PCR serogroup IIb and genetic lineage I. WGS Cluster I, representing one outbreak strain, contained 82 food and environmental isolates from Facility I and 4 clinical isolates. These isolates differed by up to 29 SNPs, exhibited 9 pulsed-field gel electrophoresis (PFGE) profiles and multilocus sequence typing (MLST) sequence type (ST) 5 of clonal complex 5 (CC5). WGS Cluster II contained 51 food and environmental isolates from Facility II, 4 food isolates from Facility I and 5 clinical isolates. Among them the isolates from Facility II and clinical isolates formed a clade and represented another outbreak strain. Isolates in this clade differed by up to 29 SNPs, exhibited 3 PFGE profiles and ST5. The only isolate collected from Facility III belonged to singleton ST489, which was in a single branch separate from Clusters I and II, and was not associated with the outbreak. WGS analyses clustered together outbreak-associated isolates exhibiting multiple PFGE profiles, while differentiating them from epidemiologically unrelated isolates that exhibited outbreak PFGE profiles. The complete genome of a Cluster I isolate allowed the identification and analyses of putative prophages, revealing that Cluster I isolates differed by the gain or loss of three putative prophages, causing the banding pattern differences among all 3 AscI-PFGE profiles observed in Cluster I isolates. WGS data suggested that certain ice cream varieties and/or production lines might have contamination sources unique to them. The SNP-based analysis was able to distinguish CC5 as a group from non-CC5 isolates and differentiate among CC5 isolates from different outbreaks/incidents.

Assessing the genome level diversity of Listeria monocytogenes from contaminated ice cream and environmental samples linked to a listeriosis outbreak in the United States

PubMed Central

Chen, Yi; Luo, Yan; Curry, Phillip; Timme, Ruth; Melka, David; Doyle, Matthew; Parish, Mickey; Hammack, Thomas S.; Allard, Marc W.; Brown, Eric W.; Strain, Errol A.

2017-01-01

A listeriosis outbreak in the United States implicated contaminated ice cream produced by one company, which operated 3 facilities. We performed single nucleotide polymorphism (SNP)-based whole genome sequencing (WGS) analysis on Listeria monocytogenes from food, environmental and clinical sources, identifying two clusters and a single branch, belonging to PCR serogroup IIb and genetic lineage I. WGS Cluster I, representing one outbreak strain, contained 82 food and environmental isolates from Facility I and 4 clinical isolates. These isolates differed by up to 29 SNPs, exhibited 9 pulsed-field gel electrophoresis (PFGE) profiles and multilocus sequence typing (MLST) sequence type (ST) 5 of clonal complex 5 (CC5). WGS Cluster II contained 51 food and environmental isolates from Facility II, 4 food isolates from Facility I and 5 clinical isolates. Among them the isolates from Facility II and clinical isolates formed a clade and represented another outbreak strain. Isolates in this clade differed by up to 29 SNPs, exhibited 3 PFGE profiles and ST5. The only isolate collected from Facility III belonged to singleton ST489, which was in a single branch separate from Clusters I and II, and was not associated with the outbreak. WGS analyses clustered together outbreak-associated isolates exhibiting multiple PFGE profiles, while differentiating them from epidemiologically unrelated isolates that exhibited outbreak PFGE profiles. The complete genome of a Cluster I isolate allowed the identification and analyses of putative prophages, revealing that Cluster I isolates differed by the gain or loss of three putative prophages, causing the banding pattern differences among all 3 AscI-PFGE profiles observed in Cluster I isolates. WGS data suggested that certain ice cream varieties and/or production lines might have contamination sources unique to them. The SNP-based analysis was able to distinguish CC5 as a group from non-CC5 isolates and differentiate among CC5 isolates from different outbreaks/incidents. PMID:28166293

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Cosmological implications of the Fourier space wedges of the final sample

NASA Astrophysics Data System (ADS)

Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Scoccimarro, Román; Crocce, Martín; Dalla Vecchia, Claudio; Montesano, Francesco; Gil-Marín, Héctor; Ross, Ashley J.; Beutler, Florian; Rodríguez-Torres, Sergio; Chuang, Chia-Hsun; Prada, Francisco; Kitaura, Francisco-Shu; Cuesta, Antonio J.; Eisenstein, Daniel J.; Percival, Will J.; Vargas-Magaña, Mariana; Tinker, Jeremy L.; Tojeiro, Rita; Brownstein, Joel R.; Maraston, Claudia; Nichol, Robert C.; Olmstead, Matthew D.; Samushia, Lado; Seo, Hee-Jong; Streblyanska, Alina; Zhao, Gong-bo

2017-05-01

We extract cosmological information from the anisotropic power-spectrum measurements from the recently completed Baryon Oscillation Spectroscopic Survey (BOSS), extending the concept of clustering wedges to Fourier space. Making use of new fast-Fourier-transform-based estimators, we measure the power-spectrum clustering wedges of the BOSS sample by filtering out the information of Legendre multipoles ℓ > 4. Our modelling of these measurements is based on novel approaches to describe non-linear evolution, bias and redshift-space distortions, which we test using synthetic catalogues based on large-volume N-body simulations. We are able to include smaller scales than in previous analyses, resulting in tighter cosmological constraints. Using three overlapping redshift bins, we measure the angular-diameter distance, the Hubble parameter and the cosmic growth rate, and explore the cosmological implications of our full-shape clustering measurements in combination with cosmic microwave background and Type Ia supernova data. Assuming a Λ cold dark matter (ΛCDM) cosmology, we constrain the matter density to Ω M= 0.311_{-0.010}^{+0.009} and the Hubble parameter to H_0 = 67.6_{-0.6}^{+0.7} km s^{-1 Mpc^{-1}}, at a confidence level of 68 per cent. We also allow for non-standard dark energy models and modifications of the growth rate, finding good agreement with the ΛCDM paradigm. For example, we constrain the equation-of-state parameter to w = -1.019_{-0.039}^{+0.048}. This paper is part of a set that analyses the final galaxy-clustering data set from BOSS. The measurements and likelihoods presented here are combined with others in Alam et al. to produce the final cosmological constraints from BOSS.

Resemblance profiles as clustering decision criteria: Estimating statistical power, error, and correspondence for a hypothesis test for multivariate structure.

PubMed

Kilborn, Joshua P; Jones, David L; Peebles, Ernst B; Naar, David F

2017-04-01

Clustering data continues to be a highly active area of data analysis, and resemblance profiles are being incorporated into ecological methodologies as a hypothesis testing-based approach to clustering multivariate data. However, these new clustering techniques have not been rigorously tested to determine the performance variability based on the algorithm's assumptions or any underlying data structures. Here, we use simulation studies to estimate the statistical error rates for the hypothesis test for multivariate structure based on dissimilarity profiles (DISPROF). We concurrently tested a widely used algorithm that employs the unweighted pair group method with arithmetic mean (UPGMA) to estimate the proficiency of clustering with DISPROF as a decision criterion. We simulated unstructured multivariate data from different probability distributions with increasing numbers of objects and descriptors, and grouped data with increasing overlap, overdispersion for ecological data, and correlation among descriptors within groups. Using simulated data, we measured the resolution and correspondence of clustering solutions achieved by DISPROF with UPGMA against the reference grouping partitions used to simulate the structured test datasets. Our results highlight the dynamic interactions between dataset dimensionality, group overlap, and the properties of the descriptors within a group (i.e., overdispersion or correlation structure) that are relevant to resemblance profiles as a clustering criterion for multivariate data. These methods are particularly useful for multivariate ecological datasets that benefit from distance-based statistical analyses. We propose guidelines for using DISPROF as a clustering decision tool that will help future users avoid potential pitfalls during the application of methods and the interpretation of results.

Some Psychometric and Design Implications of Game-Based Learning Analytics

ERIC Educational Resources Information Center

Gibson, David; Clarke-Midura, Jody

2013-01-01

The rise of digital game and simulation-based learning applications has led to new approaches in educational measurement that take account of patterns in time, high resolution paths of action, and clusters of virtual performance artifacts. The new approaches, which depart from traditional statistical analyses, include data mining, machine…

An Empirical Typology of Perfectionism in Academically Talented Children.

ERIC Educational Resources Information Center

Parker, Wayne D.

1997-01-01

A national sample of 820 academically talented children took the Multidimensional Perfectionism Scale. Cluster analyses of scores found a three-cluster solution. Further analyses indicated that these clusters were: nonperfectionistic (32.%), healthy perfectionistic (41.7%), and dysfunctional perfectionistic (25.5%). The construct of perfectionism…

PuReD-MCL: a graph-based PubMed document clustering methodology.

PubMed

Theodosiou, T; Darzentas, N; Angelis, L; Ouzounis, C A

2008-09-01

Biomedical literature is the principal repository of biomedical knowledge, with PubMed being the most complete database collecting, organizing and analyzing such textual knowledge. There are numerous efforts that attempt to exploit this information by using text mining and machine learning techniques. We developed a novel approach, called PuReD-MCL (Pubmed Related Documents-MCL), which is based on the graph clustering algorithm MCL and relevant resources from PubMed. PuReD-MCL avoids using natural language processing (NLP) techniques directly; instead, it takes advantage of existing resources, available from PubMed. PuReD-MCL then clusters documents efficiently using the MCL graph clustering algorithm, which is based on graph flow simulation. This process allows users to analyse the results by highlighting important clues, and finally to visualize the clusters and all relevant information using an interactive graph layout algorithm, for instance BioLayout Express 3D. The methodology was applied to two different datasets, previously used for the validation of the document clustering tool TextQuest. The first dataset involves the organisms Escherichia coli and yeast, whereas the second is related to Drosophila development. PuReD-MCL successfully reproduces the annotated results obtained from TextQuest, while at the same time provides additional insights into the clusters and the corresponding documents. Source code in perl and R are available from http://tartara.csd.auth.gr/~theodos/

Two Zn coordination polymers with meso-helical chains based on mononuclear or dinuclear cluster units

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

Qin, Ling, E-mail: qinling@hfut.edu.cn; Jiangsu Engineering Technology Research Center of Environmental Cleaning Materials; State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing National Laboratory of Microstructures, Nanjing University, Nanjing 210093

2016-07-15

Two zinc coordination polymers {[Zn_2(TPPBDA)(oba)_2]·DMF·1.5H_2O}{sub n} (1), {[Zn(TPPBDA)_1_/_2(tpdc)]·DMF}{sub n} (2) have been synthesized by zinc metal salt, nanosized tetradentate pyridine ligand with flexible or rigid V-shaped carboxylate co-ligands. These complexes were characterized by elemental analyses and X-ray single-crystal diffraction analyses. Compound 1 is a 2-fold interpenetrated 3D framework with [Zn{sub 2}(CO{sub 2}){sub 4}] clusters. Compound 2 can be defined as a five folded interpenetrating bbf topology with mononuclear Zn{sup 2+}. These mononuclear or dinuclear cluster units are linked by mix-ligands, resulting in various degrees of interpenetration. In addition, the photoluminescent properties for TPPBDA ligand under different state and coordination polymersmore » have been investigated in detail. - Graphical abstract: Two zinc coordination polymers have been synthesized by zinc metal salt, nanosized tetradentate pyridine ligand with flexible or rigid V-shaped carboxylate co-ligands. Compound 1 is a 2-fold interpenetrated 3D framework with [Zn{sub 2}(CO{sub 2}){sub 4}] clusters. Compound 2 can be defined as a five folded interpenetrating bbf topology with mononuclear Zn{sup 2+}. In addition, the photoluminescent properties for TPPBDA ligand under different status and coordination polymers have been investigated in detail. Display Omitted - Highlights: • Two Zn coordination polymers based on mononuclear or dinuclear cluster units have been synthesized. • Compound 1 is a 2-fold interpenetrated 3D framework with [Zn{sub 2}(CO{sub 2}){sub 4}] clusters. • Compound 2 is a five folded interpenetrating bbf topology with mononuclear Zn{sup 2+}. • The photoluminescent properties for TPPBDA with different state and two coordination polymers have been investigated.« less

Clustering of dietary intake and sedentary behavior in 2-year-old children.

PubMed

Gubbels, Jessica S; Kremers, Stef P J; Stafleu, Annette; Dagnelie, Pieter C; de Vries, Sanne I; de Vries, Nanne K; Thijs, Carel

2009-08-01

To examine clustering of energy balance-related behaviors (EBRBs) in young children. This is crucial because lifestyle habits are formed at an early age and track in later life. This study is the first to examine EBRB clustering in children as young as 2 years. Cross-sectional data originated from the Child, Parent and Health: Lifestyle and Genetic Constitution (KOALA) Birth Cohort Study. Parents of 2578 2-year-old children completed a questionnaire. Correlation analyses, principal component analyses, and linear regression analyses were performed to examine clustering of EBRBs. We found modest but consistent correlations in EBRBs. Two clusters emerged: a "sedentary-snacking cluster" and a "fiber cluster." Television viewing clustered with computer use and unhealthy dietary behaviors. Children who frequently consumed vegetables also consumed fruit and brown bread more often and white bread less often. Lower maternal education and maternal obesity were associated with high scores on the sedentary-snacking cluster, whereas higher educational level was associated with high fiber cluster scores. Obesity-prone behavioral clusters are already visible in 2-year-old children and are related to maternal characteristics. The findings suggest that obesity prevention should apply an integrated approach to physical activity and dietary intake in early childhood.

Catchment classification by runoff behaviour with self-organizing maps (SOM)

NASA Astrophysics Data System (ADS)

Ley, R.; Casper, M. C.; Hellebrand, H.; Merz, R.

2011-09-01

Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisation, prediction in ungauged catchments, model parameterisation. In this study, we investigate hydrological similarity of catchments with respect to their response behaviour. We analyse more than 8200 event runoff coefficients (ERCs) and flow duration curves of 53 gauged catchments in Rhineland-Palatinate, Germany, for the period from 1993 to 2008, covering a huge variability of weather and runoff conditions. The spatio-temporal variability of event-runoff coefficients and flow duration curves are assumed to represent how different catchments "transform" rainfall into runoff. From the runoff coefficients and flow duration curves we derive 12 signature indices describing various aspects of catchment response behaviour to characterise each catchment. Hydrological similarity of catchments is defined by high similarities of their indices. We identify, analyse and describe hydrologically similar catchments by cluster analysis using Self-Organizing Maps (SOM). As a result of the cluster analysis we get five clusters of similarly behaving catchments where each cluster represents one differentiated class of catchments. As catchment response behaviour is supposed to be dependent on its physiographic and climatic characteristics, we compare groups of catchments clustered by response behaviour with clusters of catchments based on catchment properties. Results show an overlap of 67% between these two pools of clustered catchments which can be improved using the topologic correctness of SOMs.

Catchment classification by runoff behaviour with self-organizing maps (SOM)

NASA Astrophysics Data System (ADS)

Ley, R.; Casper, M. C.; Hellebrand, H.; Merz, R.

2011-03-01

Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisation, prediction in ungauged catchments, model parameterisation. In this study, we investigate hydrological similarity of catchments with respect to their response behaviour. We analyse more than 8200 event runoff coefficients (ERCs) and flow duration curves of 53 gauged catchments in Rhineland-Palatinate, Germany, for the period from 1993 to 2008, covering a huge variability of weather and runoff conditions. The spatio-temporal variability of event-runoff coefficients and flow duration curves are assumed to represent how different catchments "transform" rainfall into runoff. From the runoff coefficients and flow duration curves we derive 12 signature indices describing various aspects of catchment response behaviour to characterise each catchment. Hydrological similarity of catchments is defined by high similarities of their indices. We identify, analyse and describe hydrologically similar catchments by cluster analysis using Self-Organizing Maps (SOM). As a result of the cluster analysis we get five clusters of similarly behaving catchments where each cluster represents one differentiated class of catchments. As catchment response behaviour is supposed to be dependent on its physiographic and climatic characteristics, we compare groups of catchments clustered by response behaviour with clusters of catchments based on catchment properties. Results show an overlap of 67% between these two pools of clustered catchments which can be improved using the topologic correctness of SOMs.

Weak lensing calibration of mass bias in the REFLEX+BCS X-ray galaxy cluster catalogue

NASA Astrophysics Data System (ADS)

Simet, Melanie; Battaglia, Nicholas; Mandelbaum, Rachel; Seljak, Uroš

2017-04-01

The use of large, X-ray-selected Galaxy cluster catalogues for cosmological analyses requires a thorough understanding of the X-ray mass estimates. Weak gravitational lensing is an ideal method to shed light on such issues, due to its insensitivity to the cluster dynamical state. We perform a weak lensing calibration of 166 galaxy clusters from the REFLEX and BCS cluster catalogue and compare our results to the X-ray masses based on scaled luminosities from that catalogue. To interpret the weak lensing signal in terms of cluster masses, we compare the lensing signal to simple theoretical Navarro-Frenk-White models and to simulated cluster lensing profiles, including complications such as cluster substructure, projected large-scale structure and Eddington bias. We find evidence of underestimation in the X-ray masses, as expected, with = 0.75 ± 0.07 stat. ±0.05 sys. for our best-fitting model. The biases in cosmological parameters in a typical cluster abundance measurement that ignores this mass bias will typically exceed the statistical errors.

Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

Update of membership and mean proper motion of open clusters from UCAC5 catalog

NASA Astrophysics Data System (ADS)

Dias, W. S.; Monteiro, H.; Assafin, M.

2018-06-01

We present mean proper motions and membership probabilities of individual stars for optically visible open clusters, which have been determined using data from the UCAC5 catalog. This follows our previous studies with the UCAC2 and UCAC4 catalogs, but now using improved proper motions in the GAIA reference frame. In the present study results were obtained for a sample of 1108 open clusters. For five clusters, this is the first determination of mean proper motion, and for the whole sample, we present results with a much larger number of identified astrometric member stars than on previous studies. It is the last update of our Open cluster Catalog based on proper motion data only. Future updates will count on astrometric, photometric and spectroscopic GAIA data as input for analyses.

Clustering of Pan- and Core-genome of Lactobacillus provides Novel Evolutionary Insights for Differentiation.

PubMed

Inglin, Raffael C; Meile, Leo; Stevens, Marc J A

2018-04-24

Bacterial taxonomy aims to classify bacteria based on true evolutionary events and relies on a polyphasic approach that includes phenotypic, genotypic and chemotaxonomic analyses. Until now, complete genomes are largely ignored in taxonomy. The genus Lactobacillus consists of 173 species and many genomes are available to study taxonomy and evolutionary events. We analyzed and clustered 98 completely sequenced genomes of the genus Lactobacillus and 234 draft genomes of 5 different Lactobacillus species, i.e. L. reuteri, L. delbrueckii, L. plantarum, L. rhamnosus and L. helveticus. The core-genome of the genus Lactobacillus contains 266 genes and the pan-genome 20'800 genes. Clustering of the Lactobacillus pan- and core-genome resulted in two highly similar trees. This shows that evolutionary history is traceable in the core-genome and that clustering of the core-genome is sufficient to explore relationships. Clustering of core- and pan-genomes at species' level resulted in similar trees as well. Detailed analyses of the core-genomes showed that the functional class "genetic information processing" is conserved in the core-genome but that "signaling and cellular processes" is not. The latter class encodes functions that are involved in environmental interactions. Evolution of lactobacilli seems therefore directed by the environment. The type species L. delbrueckii was analyzed in detail and its pan-genome based tree contained two major clades whose members contained different genes yet identical functions. In addition, evidence for horizontal gene transfer between strains of L. delbrueckii, L. plantarum, and L. rhamnosus, and between species of the genus Lactobacillus is presented. Our data provide evidence for evolution of some lactobacilli according to a parapatric-like model for species differentiation. Core-genome trees are useful to detect evolutionary relationships in lactobacilli and might be useful in taxonomic analyses. Lactobacillus' evolution is directed by the environment and HGT.

Childhood antecedents of adolescent personality disorders.

PubMed

Bernstein, D P; Cohen, P; Skodol, A; Bezirganian, S; Brook, J S

1996-07-01

The purpose of this study was to investigate the childhood antecedents of personality disorders that are diagnosed in adolescence. A randomly selected community sample of 641 youths was assessed initially in childhood and followed longitudinally over 10 years. Childhood behavior ratings were based on maternal report; diagnoses of adolescent personality disorders were based on data obtained from both maternal and youth informants. Four composite measures of childhood behavior problems were used: conduct problems, depressive symptoms, anxiety/fear, and immaturity. Adolescent personality disorders were considered present only if the disorders persisted over a 2-year period. For all analyses, personality disorders were grouped into the three clusters (A, B, and C) of DSM-III-R. Logistic regression analyses indicated that all four of the putative childhood antecedents were associated with greater odds of an adolescent personality disorder 10 years later. Childhood conduct problems remained an independent predictor of personality disorders in all three clusters, even when other childhood problems were included in the same regression model. Additionally, depressive symptoms emerged as an independent predictor of cluster A personality disorders in boys, while immaturity was an independent predictor of cluster B personality disorders in girls. No moderating effects of age at time of childhood assessment were found. These results support the view that personality disorders can be traced to childhood emotional and behavioral disturbances and suggest that these problems have both general and specific relationships to adolescent personality functioning.

Analysis of Chromobacterium sp. natural isolates from different Brazilian ecosystems

PubMed Central

Lima-Bittencourt, Cláudia I; Astolfi-Filho, Spartaco; Chartone-Souza, Edmar; Santos, Fabrício R; Nascimento, Andréa MA

2007-01-01

Background Chromobacterium violaceum is a free-living bacterium able to survive under diverse environmental conditions. In this study we evaluate the genetic and physiological diversity of Chromobacterium sp. isolates from three Brazilian ecosystems: Brazilian Savannah (Cerrado), Atlantic Rain Forest and Amazon Rain Forest. We have analyzed the diversity with molecular approaches (16S rRNA gene sequences and amplified ribosomal DNA restriction analysis) and phenotypic surveys of antibiotic resistance and biochemistry profiles. Results In general, the clusters based on physiological profiles included isolates from two or more geographical locations indicating that they are not restricted to a single ecosystem. The isolates from Brazilian Savannah presented greater physiologic diversity and their biochemical profile was the most variable of all groupings. The isolates recovered from Amazon and Atlantic Rain Forests presented the most similar biochemical characteristics to the Chromobacterium violaceum ATCC 12472 strain. Clusters based on biochemical profiles were congruent with clusters obtained by the 16S rRNA gene tree. According to the phylogenetic analyses, isolates from the Amazon Rain Forest and Savannah displayed a closer relationship to the Chromobacterium violaceum ATCC 12472. Furthermore, 16S rRNA gene tree revealed a good correlation between phylogenetic clustering and geographic origin. Conclusion The physiological analyses clearly demonstrate the high biochemical versatility found in the C. violaceum genome and molecular methods allowed to detect the intra and inter-population diversity of isolates from three Brazilian ecosystems. PMID:17584942

Characterization and Evolution of Cell Division and Cell Wall Synthesis Genes in the Bacterial Phyla Verrucomicrobia, Lentisphaerae, Chlamydiae, and Planctomycetes and Phylogenetic Comparison with rRNA Genes▿ †

PubMed Central

Pilhofer, Martin; Rappl, Kristina; Eckl, Christina; Bauer, Andreas Peter; Ludwig, Wolfgang; Schleifer, Karl-Heinz; Petroni, Giulio

2008-01-01

In the past, studies on the relationships of the bacterial phyla Planctomycetes, Chlamydiae, Lentisphaerae, and Verrucomicrobia using different phylogenetic markers have been controversial. Investigations based on 16S rRNA sequence analyses suggested a relationship of the four phyla, showing the branching order Planctomycetes, Chlamydiae, Verrucomicrobia/Lentisphaerae. Phylogenetic analyses of 23S rRNA genes in this study also support a monophyletic grouping and their branching order—this grouping is significant for understanding cell division, since the major bacterial cell division protein FtsZ is absent from members of two of the phyla Chlamydiae and Planctomycetes. In Verrucomicrobia, knowledge about cell division is mainly restricted to the recent report of ftsZ in the closely related genera Prosthecobacter and Verrucomicrobium. In this study, genes of the conserved division and cell wall (dcw) cluster (ddl, ftsQ, ftsA, and ftsZ) were characterized in all verrucomicrobial subdivisions (1 to 4) with cultivable representatives (1 to 4). Sequence analyses and transcriptional analyses in Verrucomicrobia and genome data analyses in Lentisphaerae suggested that cell division is based on FtsZ in all verrucomicrobial subdivisions and possibly also in the sister phylum Lentisphaerae. Comprehensive sequence analyses of available genome data for representatives of Verrucomicrobia, Lentisphaerae, Chlamydiae, and Planctomycetes strongly indicate that their last common ancestor possessed a conserved, ancestral type of dcw gene cluster and an FtsZ-based cell division mechanism. This implies that Planctomycetes and Chlamydiae may have shifted independently to a non-FtsZ-based cell division mechanism after their separate branchings from their last common ancestor with Verrucomicrobia. PMID:18310338

Pan-genome and phylogeny of Bacillus cereus sensu lato.

PubMed

Bazinet, Adam L

2017-08-02

Bacillus cereus sensu lato (s. l.) is an ecologically diverse bacterial group of medical and agricultural significance. In this study, I use publicly available genomes and novel bioinformatic workflows to characterize the B. cereus s. l. pan-genome and perform the largest phylogenetic and population genetic analyses of this group to date in terms of the number of genes and taxa included. With these fundamental data in hand, I identify genes associated with particular phenotypic traits (i.e., "pan-GWAS" analysis), and quantify the degree to which taxa sharing common attributes are phylogenetically clustered. A rapid k-mer based approach (Mash) was used to create reduced representations of selected Bacillus genomes, and a fast distance-based phylogenetic analysis of this data (FastME) was performed to determine which species should be included in B. cereus s. l. The complete genomes of eight B. cereus s. l. species were annotated de novo with Prokka, and these annotations were used by Roary to produce the B. cereus s. l. pan-genome. Scoary was used to associate gene presence and absence patterns with various phenotypes. The orthologous protein sequence clusters produced by Roary were filtered and used to build HaMStR databases of gene models that were used in turn to construct phylogenetic data matrices. Phylogenetic analyses used RAxML, DendroPy, ClonalFrameML, PAUP*, and SplitsTree. Bayesian model-based population genetic analysis assigned taxa to clusters using hierBAPS. The genealogical sorting index was used to quantify the phylogenetic clustering of taxa sharing common attributes. The B. cereus s. l. pan-genome currently consists of ≈60,000 genes, ≈600 of which are "core" (common to at least 99% of taxa sampled). Pan-GWAS analysis revealed genes associated with phenotypes such as isolation source, oxygen requirement, and ability to cause diseases such as anthrax or food poisoning. Extensive phylogenetic analyses using an unprecedented amount of data produced phylogenies that were largely concordant with each other and with previous studies. Phylogenetic support as measured by bootstrap probabilities increased markedly when all suitable pan-genome data was included in phylogenetic analyses, as opposed to when only core genes were used. Bayesian population genetic analysis recommended subdividing the three major clades of B. cereus s. l. into nine clusters. Taxa sharing common traits and species designations exhibited varying degrees of phylogenetic clustering. All phylogenetic analyses recapitulated two previously used classification systems, and taxa were consistently assigned to the same major clade and group. By including accessory genes from the pan-genome in the phylogenetic analyses, I produced an exceptionally well-supported phylogeny of 114 complete B. cereus s. l. genomes. The best-performing methods were used to produce a phylogeny of all 498 publicly available B. cereus s. l. genomes, which was in turn used to compare three different classification systems and to test the monophyly status of various B. cereus s. l. species. The majority of the methodology used in this study is generic and could be leveraged to produce pan-genome estimates and similarly robust phylogenetic hypotheses for other bacterial groups.

Organic Food Market Segmentation in Lebanon

NASA Astrophysics Data System (ADS)

Tleis, Malak; Roma, Rocco; Callieris, Roberta

2015-04-01

Organic farming in Lebanon is not a new concept. It started with the efforts of the private sector more than a decade ago and is still present even with the limited agricultural production. The local market is quite developed in comparison to neighboring countries, depending mainly on imports. Few studies were addressed to organic consumption in Lebanon, were none of them dealt with organic consumers analysis. Therefore, our objectives were to identify the profiles of Lebanese organic consumer and non organic consumer and to propose appropriate marketing strategies for each segment of consumer with the final aim of developing the Lebanese organic market. A survey, based on the use of closed-ended questionnaire, was addressed to 400 consumers in the capital, Beirut, from the end of February till the end of March 2014. Data underwent descriptive analyses, principal component analyses (PCA) and cluster analyses (k-means method) through the statistical software SPSS. Four cluster were obtained based on psychographic characteristics and willingness to pay (WTP) for the principal organic products purchased. "Localists" and "Health conscious" clusters constituted the largest proportion of the selected sample, thus were the most critical to be addressed by specific marketing strategies emphasizing the combination of local and organic food and the healthy properties of organic products. "Rational" and "Irregular" cluster were relatively small groups, addressed by pricing and promotional strategies. This study showed a positive attitude among Lebanese consumer towards organic food, where egoistic motives are prevailing over altruistic motives. High prices of organic commodities and low trust in organic farming, remain a constraint to levitating organic consumption. The combined efforts of the public and the private sector are required to spread the knowledge about positive environmental payback of organic agriculture and for the promotion of locally produced organic goods.

Quasi-Likelihood Techniques in a Logistic Regression Equation for Identifying Simulium damnosum s.l. Larval Habitats Intra-cluster Covariates in Togo.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R

2012-01-01

The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.

Using coordinate-based meta-analyses to explore structural imaging genetics.

PubMed

Janouschek, Hildegard; Eickhoff, Claudia R; Mühleisen, Thomas W; Eickhoff, Simon B; Nickl-Jockschat, Thomas

2018-05-05

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Individual participant data meta-analyses should not ignore clustering

PubMed Central

Abo-Zaid, Ghada; Guo, Boliang; Deeks, Jonathan J.; Debray, Thomas P.A.; Steyerberg, Ewout W.; Moons, Karel G.M.; Riley, Richard David

2013-01-01

Objectives Individual participant data (IPD) meta-analyses often analyze their IPD as if coming from a single study. We compare this approach with analyses that rather account for clustering of patients within studies. Study Design and Setting Comparison of effect estimates from logistic regression models in real and simulated examples. Results The estimated prognostic effect of age in patients with traumatic brain injury is similar, regardless of whether clustering is accounted for. However, a family history of thrombophilia is found to be a diagnostic marker of deep vein thrombosis [odds ratio, 1.30; 95% confidence interval (CI): 1.00, 1.70; P = 0.05] when clustering is accounted for but not when it is ignored (odds ratio, 1.06; 95% CI: 0.83, 1.37; P = 0.64). Similarly, the treatment effect of nicotine gum on smoking cessation is severely attenuated when clustering is ignored (odds ratio, 1.40; 95% CI: 1.02, 1.92) rather than accounted for (odds ratio, 1.80; 95% CI: 1.29, 2.52). Simulations show models accounting for clustering perform consistently well, but downwardly biased effect estimates and low coverage can occur when ignoring clustering. Conclusion Researchers must routinely account for clustering in IPD meta-analyses; otherwise, misleading effect estimates and conclusions may arise. PMID:23651765

A hot X-ray filament associated with A3017 galaxy cluster

NASA Astrophysics Data System (ADS)

Parekh, V.; Durret, F.; Padmanabh, P.; Pandge, M. B.

2017-09-01

Recent simulations and observations have shown large-scale filaments in the cosmic web connecting nodes, with accreting materials (baryonic and dark matter) flowing through them. Current high-sensitivity observations also show that the propagation of shocks through filaments can heat them up and make filaments visible between two or more galaxy clusters or around massive clusters, based on optical and/or X-ray observations. We are reporting here the special case of the cluster A3017 associated with a hot filament. The temperature of the filament is 3.4^{-0.77}_{+1.30} keV and its length is ∼1 Mpc. We have analysed its archival Chandra data and report various properties. We also analysed GMRT 235/610 MHz radio data. Radio observations have revealed symmetric two-sided lobes that fill cavities in the A3017 cluster core region, associated with central active galactic nucleus. In the radio map, we also noticed a peculiar linear vertical radio structure in the X-ray filament region which might be associated with a cosmic filament shock. This radio structure could be a radio phoenix or old plasma where an old relativistic population is re-accelerated by shock propagation. Finally, we put an upper limit on the radio luminosity of the filament region.

Spatial location influences vocal interactions in bullfrog choruses

PubMed Central

Bates, Mary E.; Cropp, Brett F.; Gonchar, Marina; Knowles, Jeffrey; Simmons, James A.; Simmons, Andrea Megela

2010-01-01

A multiple sensor array was employed to identify the spatial locations of all vocalizing male bullfrogs (Rana catesbeiana) in five natural choruses. Patterns of vocal activity collected with this array were compared with computer simulations of chorus activity. Bullfrogs were not randomly spaced within choruses, but tended to cluster into closely spaced groups of two to five vocalizing males. There were nonrandom, differing patterns of vocal interactions within clusters of closely spaced males and between different clusters. Bullfrogs located within the same cluster tended to overlap or alternate call notes with two or more other males in that cluster. These near-simultaneous calling bouts produced advertisement calls with more pronounced amplitude modulation than occurred in nonoverlapping notes or calls. Bullfrogs located in different clusters more often alternated entire calls or overlapped only small segments of their calls. They also tended to respond sequentially to calls of their farther neighbors compared to their nearer neighbors. Results of computational analyses showed that the observed patterns of vocal interactions were significantly different than expected based on random activity. The use of a multiple sensor array provides a richer view of the dynamics of choruses than available based on single microphone techniques. PMID:20370047

5S ribosomal ribonucleic acid sequences in Bacteroides and Fusobacterium: evolutionary relationships within these genera and among eubacteria in general

NASA Technical Reports Server (NTRS)

Van den Eynde, H.; De Baere, R.; Shah, H. N.; Gharbia, S. E.; Fox, G. E.; Michalik, J.; Van de Peer, Y.; De Wachter, R.

1989-01-01

The 5S ribosomal ribonucleic acid (rRNA) sequences were determined for Bacteroides fragilis, Bacteroides thetaiotaomicron, Bacteroides capillosus, Bacteroides veroralis, Porphyromonas gingivalis, Anaerorhabdus furcosus, Fusobacterium nucleatum, Fusobacterium mortiferum, and Fusobacterium varium. A dendrogram constructed by a clustering algorithm from these sequences, which were aligned with all other hitherto known eubacterial 5S rRNA sequences, showed differences as well as similarities with respect to results derived from 16S rRNA analyses. In the 5S rRNA dendrogram, Bacteroides clustered together with Cytophaga and Fusobacterium, as in 16S rRNA analyses. Intraphylum relationships deduced from 5S rRNAs suggested that Bacteroides is specifically related to Cytophaga rather than to Fusobacterium, as was suggested by 16S rRNA analyses. Previous taxonomic considerations concerning the genus Bacteroides, based on biochemical and physiological data, were confirmed by the 5S rRNA sequence analysis.

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

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method.

PubMed

Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

2014-07-01

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous studies. We also compared pairwise distances (between geographically separated samples) with those obtained using the AMOVA method and found good agreement. Further analyses that are impossible with AMOVA were made using the discrete Laplace method: analysis of the homogeneity in two different ways and calculating marginal STR distributions. We found that the Y-STR haplotypes from e.g. Finland were relatively homogeneous as opposed to the relatively heterogeneous Y-STR haplotypes from e.g. Lublin, Eastern Poland and Berlin, Germany. We demonstrated that the observed distributions of alleles at each locus were similar to the expected ones. We also compared pairwise distances between geographically separated samples from Africa with those obtained using the AMOVA method and found good agreement. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

[Cluster analysis applicability to fitness evaluation of cosmonauts on long-term missions of the International space station].

PubMed

Egorov, A D; Stepantsov, V I; Nosovskiĭ, A M; Shipov, A A

2009-01-01

Cluster analysis was applied to evaluate locomotion training (running and running intermingled with walking) of 13 cosmonauts on long-term ISS missions by the parameters of duration (min), distance (m) and intensity (km/h). Based on the results of analyses, the cosmonauts were distributed into three steady groups of 2, 5 and 6 persons. Distance and speed showed a statistical rise (p < 0.03) from group 1 to group 3. Duration of physical locomotion training was not statistically different in the groups (p = 0.125). Therefore, cluster analysis is an adequate method of evaluating fitness of cosmonauts on long-term missions.

A new clustering of antibody CDR loop conformations

PubMed Central

North, Benjamin; Lehmann, Andreas; Dunbrack, Roland L.

2010-01-01

Previous analyses of the complementarity determining regions (CDRs) of antibodies have focused on a small number of “canonical” conformations for each loop. This is primarily the result of the work of Chothia and colleagues, most recently in 1997. Because of the widespread utility of antibodies, we have revisited the clustering of conformations of the six CDR loops with the much larger amount of structural information currently available. In this work, we were careful to use a high-quality data set by eliminating low-resolution structures and CDRs with high B-factors or high conformational energies. We used a distance function based on directional statistics and an effective clustering algorithm using affinity propagation. With this data set of over 300 non-redundant antibody structures, we were able to cover 28 CDR-length combinations (e.g., L1 length 11, or “L1-11” in our nomenclature) for L1, L2, L3, H1 and H2. The Chothia analysis covered only 20 CDR-lengths. Only four of these had more than one conformational cluster, of which two could easily be distinguished by gene source (mouse/human; κ/λ) and one purely by the presence and positions of Pro residues (L3-9). Thus using the Chothia analysis does not require the complicated set of “structure-determining residues” that is often assumed. Of our 28 CDR-lengths, 15 of them have multiple conformational clusters including ten for which Chothia had only one canonical class. We have a total of 72 clusters for the non-H3 CDRs; approximately 85% of the non-H3 sequences can be assigned to a conformational cluster based on gene source and/or sequence. We found that earlier predictions of “bulged” vs. “non-bulged” conformations based on the presence or absence of anchor residues Arg/Lys94 and Asp101 of H3 have not held up, since all four combinations lead to a majority of conformations that are bulged. Thus the earlier analyses have been significantly enhanced by the increased data. We believe the new classification will lead to improved methods for antibody structure prediction and design. PMID:21035459

Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife

PubMed Central

Racine, Annie M.; Koscik, Rebecca L.; Berman, Sara E.; Nicholas, Christopher R.; Clark, Lindsay R.; Okonkwo, Ozioma C.; Rowley, Howard A.; Asthana, Sanjay; Bendlin, Barbara B.; Blennow, Kaj; Zetterberg, Henrik; Gleason, Carey E.; Carlsson, Cynthia M.

2016-01-01

The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials. PMID:27324877

Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife.

PubMed

Racine, Annie M; Koscik, Rebecca L; Berman, Sara E; Nicholas, Christopher R; Clark, Lindsay R; Okonkwo, Ozioma C; Rowley, Howard A; Asthana, Sanjay; Bendlin, Barbara B; Blennow, Kaj; Zetterberg, Henrik; Gleason, Carey E; Carlsson, Cynthia M; Johnson, Sterling C

2016-08-01

The ability to detect preclinical Alzheimer's disease is of great importance, as this stage of the Alzheimer's continuum is believed to provide a key window for intervention and prevention. As Alzheimer's disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer's disease; (ii) mixed Alzheimer's disease and vascular aetiology; (iii) suspected non-Alzheimer's disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Science Teaching Based on Cognitive Load Theory: Engaged Students, but Cognitive Deficiencies

ERIC Educational Resources Information Center

Meissner, Barbara; Bogner, Franz X.

2012-01-01

To improve science learning under demanding conditions, we designed an out-of-school lesson in compliance with cognitive load theory (CLT). We extracted student clusters based on individual effectiveness, and compared instructional efficiency, mental effort, and persistence of learning. The present study analyses students' engagement. 50.0% of our…

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

PubMed

Schramm, Catherine; Vial, Céline; Bachoud-Lévi, Anne-Catherine; Katsahian, Sandrine

2018-01-01

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

Intersection Detection Based on Qualitative Spatial Reasoning on Stopping Point Clusters

NASA Astrophysics Data System (ADS)

Zourlidou, S.; Sester, M.

2016-06-01

The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location - thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster) and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

Genetic differences in the two main groups of the Japanese population based on autosomal SNPs and haplotypes.

PubMed

Yamaguchi-Kabata, Yumi; Tsunoda, Tatsuhiko; Kumasaka, Natsuhiko; Takahashi, Atsushi; Hosono, Naoya; Kubo, Michiaki; Nakamura, Yusuke; Kamatani, Naoyuki

2012-05-01

Although the Japanese population has a rather low genetic diversity, we recently confirmed the presence of two main clusters (the Hondo and Ryukyu clusters) through principal component analysis of genome-wide single-nucleotide polymorphism (SNP) genotypes. Understanding the genetic differences between the two main clusters requires further genome-wide analyses based on a dense SNP set and comparison of haplotype frequencies. In the present study, we determined haplotypes for the Hondo cluster of the Japanese population by detecting SNP homozygotes with 388,591 autosomal SNPs from 18,379 individuals and estimated the haplotype frequencies. Haplotypes for the Ryukyu cluster were inferred by a statistical approach using the genotype data from 504 individuals. We then compared the haplotype frequencies between the Hondo and Ryukyu clusters. In most genomic regions, the haplotype frequencies in the Hondo and Ryukyu clusters were very similar. However, in addition to the human leukocyte antigen region on chromosome 6, other genomic regions (chromosomes 3, 4, 5, 7, 10 and 12) showed dissimilarities in haplotype frequency. These regions were enriched for genes involved in the immune system, cell-cell adhesion and the intracellular signaling cascade. These differentiated genomic regions between the Hondo and Ryukyu clusters are of interest because they (1) should be examined carefully in association studies and (2) likely contain genes responsible for morphological or physiological differences between the two groups.

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.

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

Andersson, Gunther G., E-mail: gunther.andersson@flinders.edu.au, E-mail: vladimir.golovko@canterbury.ac.nz, E-mail: greg.metha@adelaide.edu.au; Al Qahtani, Hassan S.; Golovko, Vladimir B., E-mail: gunther.andersson@flinders.edu.au, E-mail: vladimir.golovko@canterbury.ac.nz, E-mail: greg.metha@adelaide.edu.au

Chemically made, atomically precise phosphine-stabilized clusters Au{sub 9}(PPh{sub 3}){sub 8}(NO{sub 3}){sub 3} were deposited on titania and silica from solutions at various concentrations and the samples heated under vacuum to remove the ligands. Metastable induced electron spectroscopy was used to determine the density of states at the surface, and X-ray photoelectron spectroscopy for analysing the composition of the surface. It was found for the Au{sub 9} cluster deposited on titania that the ligands react with the titania substrate. Based on analysis using the singular value decomposition algorithm, the series of MIE spectra can be described as a linear combination ofmore » 3 base spectra that are assigned to the spectra of the substrate, the phosphine ligands on the substrate, and the Au clusters anchored to titania after removal of the ligands. On silica, the Au clusters show significant agglomeration after heat treatment and no interaction of the ligands with the substrate can be identified.« less

Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach

NASA Astrophysics Data System (ADS)

Aminzare, Zahra; Dey, Biswadip; Davison, Elizabeth N.; Leonard, Naomi Ehrich

2018-04-01

Finding the conditions that foster synchronization in networked nonlinear systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal networks, are in general not strict enough to accurately determine the system behavior. We leverage contraction theory to derive new sufficient conditions for cluster synchronization in terms of the network structure, for a network where the intrinsic nonlinear dynamics of each node may differ. Our result requires that network connections satisfy a cluster-input-equivalence condition, and we explore the influence of this requirement on network dynamics. For application to networks of nodes with FitzHugh-Nagumo dynamics, we show that our new sufficient condition is tighter than those found in previous analyses that used smooth or nonsmooth Lyapunov functions. Improving the analytical conditions for when cluster synchronization will occur based on network configuration is a significant step toward facilitating understanding and control of complex networked systems.

DMINDA: an integrated web server for DNA motif identification and analyses.

PubMed

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-07-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

PubMed

Gomes, Manuel; Ng, Edmond S-W; Grieve, Richard; Nixon, Richard; Carpenter, James; Thompson, Simon G

2012-01-01

Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering--seemingly unrelated regression (SUR) without a robust standard error (SE)--and 4 methods that recognized clustering--SUR and generalized estimating equations (GEEs), both with robust SE, a "2-stage" nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92-0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters.

The relationship between sleep-wake cycle and cognitive functioning in young people with affective disorders.

PubMed

Carpenter, Joanne S; Robillard, Rébecca; Lee, Rico S C; Hermens, Daniel F; Naismith, Sharon L; White, Django; Whitwell, Bradley; Scott, Elizabeth M; Hickie, Ian B

2015-01-01

Although early-stage affective disorders are associated with both cognitive dysfunction and sleep-wake disruptions, relationships between these factors have not been specifically examined in young adults. Sleep and circadian rhythm disturbances in those with affective disorders are considerably heterogeneous, and may not relate to cognitive dysfunction in a simple linear fashion. This study aimed to characterise profiles of sleep and circadian disturbance in young people with affective disorders and examine associations between these profiles and cognitive performance. Actigraphy monitoring was completed in 152 young people (16-30 years; 66% female) with primary diagnoses of affective disorders, and 69 healthy controls (18-30 years; 57% female). Patients also underwent detailed neuropsychological assessment. Actigraphy data were processed to estimate both sleep and circadian parameters. Overall neuropsychological performance in patients was poor on tasks relating to mental flexibility and visual memory. Two hierarchical cluster analyses identified three distinct patient groups based on sleep variables and three based on circadian variables. Sleep clusters included a 'long sleep' cluster, a 'disrupted sleep' cluster, and a 'delayed and disrupted sleep' cluster. Circadian clusters included a 'strong circadian' cluster, a 'weak circadian' cluster, and a 'delayed circadian' cluster. Medication use differed between clusters. The 'long sleep' cluster displayed significantly worse visual memory performance compared to the 'disrupted sleep' cluster. No other cognitive functions differed between clusters. These results highlight the heterogeneity of sleep and circadian profiles in young people with affective disorders, and provide preliminary evidence in support of a relationship between sleep and visual memory, which may be mediated by use of antipsychotic medication. These findings have implications for the personalisation of treatments and improvement of functioning in young adults early in the course of affective illness.

Compositional classification and sedimentological interpretation of the laminated lacustrine sediments at Baumkrichen (Western Austria) using XRF core scanning data

NASA Astrophysics Data System (ADS)

Barrett, Samuel; Tjallingii, Rik; Bloemsma, Menno; Brauer, Achim; Starnberger, Reinhard; Spötl, Christoph; Dulski, Peter

2015-04-01

The outcrop at Baumkirchen (Austria) encloses part of a unique sequence of laminated lacustrine sediments deposited during the last glacial cycle. A ~250m long composite sediment record recovered at this location now continuously covers the periods ~33 to ~45 ka BP (MIS 3) and ~59 to ~73 ka BP (MIS 4), which are separated by a hiatus. The well-laminated (mm-cm scale) and almost entirely clastic sediments reveal alternations of clayey silt and medium silt to very-fine sand layers. Although radiocarbon and optically stimulated luminescence (OSL) dating provide a robust chronology, accurate dating of the sediment laminations appears to be problematic due to very high sedimentation rates (3-8 cm/yr). X-ray fluorescence (XRF) core scanning provided a detailed ~150m long record of compositional changes of the sediments at Baumkirchen. Changes in the sediments are subtle and classification into different facies based on individual elements is therefore subjective. We applied a statistically robust clustering analysis to provide an objective compositional classification without prior knowledge, based on XRF measurements for 15 analysed elements (all those with an acceptable signal-noise ratio: Zr, Sr, Ca, Mn, Cu, Zn, Rb, Ni, Fe, K, Cr, V, Si, Ba, T). The clustering analysis indicates a distinct compositional change between sediments deposited below and above the stratigraphic hiatus, but also differentiates between individual different laminae. Preliminary results suggest variations in the sequence are largely controlled by the relative occurrence of different kinds of sediment represented by different clusters. Three clusters identify well-laminated sediments, visually similar in appearance, each dominated by an anti-correlation between Ca and one or more of the detrital elements K, Zr, Ti, Si and Fe. Two of these clusters occur throughout the entire sequence, one frequently and the other restricted to short sections, while the third occurs almost exclusively below the hiatus, indicating a geochemically distinct component that possibly represents a specific sediment source. In a similar manner, three other clusters identify event layers with different compositions of which two occur exclusively above the hiatus and one exclusively below. The variations in the occurrence of these clusters revealing distinct event layers suggest variations in dominant sediment source both above and below the hiatus and within the section above it. More detailed comparisons between compositional variations of the individual clusters obtained from biplots and microscopic observations on thin sections, grain-size analyses, and mineralogical analyses are needed to further differentiate between sediment sources and transport mechanisms.

Optimal integrated abundances for chemical tagging of extragalactic globular clusters

NASA Astrophysics Data System (ADS)

Sakari, Charli M.; Venn, Kim; Shetrone, Matthew; Dotter, Aaron; Mackey, Dougal

2014-09-01

High-resolution integrated light (IL) spectroscopy provides detailed abundances of distant globular clusters whose stars cannot be resolved. Abundance comparisons with other systems (e.g. for chemical tagging) require understanding the systematic offsets that can occur between clusters, such as those due to uncertainties in the underlying stellar population. This paper analyses high-resolution IL spectra of the Galactic globular clusters 47 Tuc, M3, M13, NGC 7006, and M15 to (1) quantify potential systematic uncertainties in Fe, Ca, Ti, Ni, Ba, and Eu and (2) identify the most stable abundance ratios that will be useful in future analyses of unresolved targets. When stellar populations are well modelled, uncertainties are ˜0.1-0.2 dex based on sensitivities to the atmospheric parameters alone; in the worst-case scenarios, uncertainties can rise to 0.2-0.4 dex. The [Ca I/Fe I] ratio is identified as the optimal integrated [α/Fe] indicator (with offsets ≲ 0.1 dex), while [Ni I/Fe I] is also extremely stable to within ≲ 0.1 dex. The [Ba II/Eu II] ratios are also stable when the underlying populations are well modelled and may also be useful for chemical tagging.

Whole Genome Sequencing versus Traditional Genotyping for Investigation of a Mycobacterium tuberculosis Outbreak: A Longitudinal Molecular Epidemiological Study

PubMed Central

Rückert, Christian; Nübel, Ulrich; Blom, Jochen; Wirth, Thierry; Jaenicke, Sebastian; Schuback, Sieglinde; Rüsch-Gerdes, Sabine; Supply, Philip; Kalinowski, Jörn; Niemann, Stefan

2013-01-01

Background Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. Methods and Findings During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed “Hamburg clone”) started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. Conclusions Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context. Please see later in the article for the Editors' Summary PMID:23424287

Evidence from Molecular Fingerprinting of Limited Spread of Drug-Resistant Tuberculosis in Texas

PubMed Central

Wilson, Rebecca W.; Yang, Zhenhua; Kelley, Michael; Cave, M. Donald; Pogoda, Janice M.; Wallace, Richard J.; Cegielski, J. Peter; Dunbar, Denise F.; Bergmire-Sweat, David; Elliott, L. Bruce; Barnes, Peter F.

1999-01-01

To determine the contribution of recent transmission to spread of drug-resistant tuberculosis in Texas, we performed IS6110-based and pTBN12-based restriction fragment length polymorphism (RFLP) analyses on Mycobacterium tuberculosis isolates. Isolates collected from 201 patients in Texas between 1992 and 1994 were studied. The distribution of cases was strikingly focal. All cases were reported from 35 of the 254 counties in Texas, and 74% (148 of 201) were reported from only 9 counties. One hundred sixty-one (80%) of the patients had M. tuberculosis isolates with unique RFLP patterns, and 41 (20%) patients were in 20 clusters, each comprising 2 to 3 patients. The largest number of cases of drug-resistant tuberculosis were reported in counties bordering Mexico, but the percentage of clustered cases was highest in northeast Texas and in counties that included the cities of Dallas, Fort Worth, and Houston. Compared to nonclustered patients, clustered patients were more likely to be African American and to have been born in the United States. Clustered patients were significantly more likely to be from the same geographic area, and clustered patients from the same geographic area were more likely to have isolates with identical drug susceptibility patterns, suggesting that they were linked by recent transmission. In 11 of 20 clusters, clustered patients were from geographically separate regions, and most isolates did not have identical drug susceptibility patterns, suggesting that tuberculosis was contracted from a common source in the remote past. Based on the low percentage of clustered cases and the small cluster size, we conclude that there is no evidence for the extensive transmission of drug-resistant tuberculosis in Texas. PMID:10488188

Factors that cause genotype by environment interaction and use of a multiple-trait herd-cluster model for milk yield of Holstein cattle from Brazil and Colombia.

PubMed

Cerón-Muñoz, M F; Tonhati, H; Costa, C N; Rojas-Sarmiento, D; Echeverri Echeverri, D M

2004-08-01

Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use.

PubMed

Babbin, Steven F; Velicer, Wayne F; Paiva, Andrea L; Brick, Leslie Ann D; Redding, Colleen A

2015-01-01

Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N=4059) and alcohol (N=3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. Copyright © 2014. Published by Elsevier Ltd.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use

PubMed Central

Babbin, Steven F.; Velicer, Wayne F.; Paiva, Andrea L.; Brick, Leslie Ann D.; Redding, Colleen A.

2015-01-01

Introduction Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Methods Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N= 4059) and alcohol (N= 3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Results Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Conclusions Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. PMID:25222849

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.

A person-centered approach to the multifaceted nature of young adult sexual behavior.

PubMed

McGuire, Jenifer K; Barber, Bonnie L

2010-07-01

Young adult sexual relationships were examined using a multifaceted, person-centered approach with data from Wave 7 (aged 20-21; N = 1,126) of the Michigan Study of Adolescent Life Transitions. The study utilized hierarchical cluster analyses based on the following measured variables: frequency of sex, importance of regularly having sex, satisfaction with sex life, experience of coercion for sex, and sexual risk reduction. Five distinct clusters emerged for females (Satisfied, Moderate, Active Unprotected, Pressured, and Inactive) and represented patterns such as more partners paired with less risk reduction (Active Unprotected), high satisfaction paired with frequent sex and high-risk reduction (Satisfied), or higher levels of coercion paired with low satisfaction and low-risk reduction (Pressured). Similar clusters emerged for males, with one additional cluster: the Dissatisfied cluster. Clusters differed with respect to relationship status, marital status, and psychological well-being (both males and females) and parental divorce, living situation, and sexual orientation (females only).

Effects of community health interventions on under-5 mortality in rural Guinea-Bissau (EPICS): a cluster-randomised controlled trial.

PubMed

Boone, Peter; Elbourne, Diana; Fazzio, Ila; Fernandes, Samory; Frost, Chris; Jayanty, Chitra; King, Rebecca; Mann, Vera; Piaggio, Gilda; dos Santos, Albino; Walker, Polly R

2016-05-01

Evidence suggests that community-based interventions that promote improved home-based practices and care-seeking behaviour can have a large impact on maternal and child mortality in regions where rates are high. We aimed to assess whether an intervention package based on the WHO Integrated Management of Childhood Illness handbook and community mobilisation could reduce under-5 mortality in rural Guinea-Bissau, where the health service infrastructure is weak. We did a non-masked cluster-randomised controlled trial (EPICS) in the districts of Tombali and Quinara in Guinea-Bissau. Clusters of rural villages were stratified by ethnicity and distance from a regional health centre, and randomly assigned (1:1) to intervention or control using a computerised random number generator. Women were eligible if they lived in one of the clusters at baseline survey prior to randomisation and if they were aged 15-49 years or were primary caregivers of children younger than 5 years. Their children were eligible if they were younger than 5 years or were liveborn after intervention services could be implemented on July 1, 2008. In villages receiving the intervention, community health clubs were established, community health workers were trained in case management, and traditional birth attendants were trained to care for pregnant women and newborn babies, and promote facility-based delivery. Registered nurses supervised community health workers and offered mobile clinic services. Health centres were not improved. The control group received usual services. The primary outcome was the proportion of children dying under age 5 years, and was analysed in all eligible children up to final visits to villages between Jan 1 and March 31, 2011. This trial is registered with ISRCTN, number ISRCTN52433336. On Aug 30, 2007, we randomly assigned 146 clusters to intervention (73 clusters, 5669 women, and 4573 children) or control (73 clusters, 5840 women, and 4675 children). From randomisation until the end of the trial (last visit by June 30, 2011), the intervention clusters had 3093 livebirths and the control clusters had 3194. 6729 children in the intervention group and 6894 in the control group aged 0-5 years on July 1, 2008, or liveborn subsequently were analysed for mortality outcomes. 311 (4·6%) of 6729 children younger than 5 years died in the intervention group compared with 273 (4·0%) of 6894 in the control group (relative risk 1·16 [95% CI 0·99-1·37]). Our package of community-based interventions did not reduce under-5 mortality in rural Guinea-Bissau. The short timeframe and other trial limitations might have affected our results. Community-based health promotion and basic first-line services in fragile contexts with weak secondary health service infrastructure might be insufficient to reduce child deaths. Effective Intervention. Copyright © 2016 Boone et al. Open Access article distributed under the terms of CC BY-NC-ND. Published by Elsevier Ltd.. All rights reserved.

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

Neural network-based multiple robot simultaneous localization and mapping.

PubMed

Saeedi, Sajad; Paull, Liam; Trentini, Michael; Li, Howard

2011-12-01

In this paper, a decentralized platform for simultaneous localization and mapping (SLAM) with multiple robots is developed. Each robot performs single robot view-based SLAM using an extended Kalman filter to fuse data from two encoders and a laser ranger. To extend this approach to multiple robot SLAM, a novel occupancy grid map fusion algorithm is proposed. Map fusion is achieved through a multistep process that includes image preprocessing, map learning (clustering) using neural networks, relative orientation extraction using norm histogram cross correlation and a Radon transform, relative translation extraction using matching norm vectors, and then verification of the results. The proposed map learning method is a process based on the self-organizing map. In the learning phase, the obstacles of the map are learned by clustering the occupied cells of the map into clusters. The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the occupancy grid map so the map fusion problem becomes a task of matching features. Results of the experiments from tests performed on a real environment with multiple robots prove the effectiveness of the proposed solution.

A Scalable Monitoring for the CMS Filter Farm Based on Elasticsearch

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

Andre, J.M.; et al.

2015-12-23

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured informationmore » can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central” es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2.« less

A multifaceted intervention to narrow the evidence-based gap in the treatment of acute coronary syndromes: rationale and design of the Brazilian Intervention to Increase Evidence Usage in Acute Coronary Syndromes (BRIDGE-ACS) cluster-randomized trial.

PubMed

Berwanger, Otávio; Guimarães, Hélio P; Laranjeira, Ligia N; Cavalcanti, Alexandre B; Kodama, Alessandra; Zazula, Ana Denise; Santucci, Eliana; Victor, Elivane; Flato, Uri A; Tenuta, Marcos; Carvalho, Vitor; Mira, Vera Lucia; Pieper, Karen S; Mota, Luiz Henrique; Peterson, Eric D; Lopes, Renato D

2012-03-01

Translating evidence into clinical practice in the management of acute coronary syndromes (ACS) is challenging. Few ACS quality improvement interventions have been rigorously evaluated to determine their impact on patient care and clinical outcomes. We designed a pragmatic, 2-arm, cluster-randomized trial involving 34 clusters (Brazilian public hospitals). Clusters were randomized to receive a multifaceted quality improvement intervention (experimental group) or routine practice (control group). The 6-month educational intervention included reminders, care algorithms, a case manager, and distribution of educational materials to health care providers. The primary end point was a composite of evidence-based post-ACS therapies within 24 hours of admission, with the secondary measure of major cardiovascular clinical events (death, nonfatal myocardial infarction, nonfatal cardiac arrest, and nonfatal stroke). Prescription of evidence-based therapies at hospital discharge were also evaluated as part of the secondary outcomes. All analyses were performed by the intention-to-treat principle and took the cluster design into account using individual-level regression modeling (generalized estimating equations). If proven effective, this multifaceted intervention would have wide use as a means of promoting optimal use of evidence-based interventions for the management of ACS. Copyright © 2012 Mosby, Inc. All rights reserved.

Psychopathic Traits in Youth: Is There Evidence for Primary and Secondary Subtypes?

ERIC Educational Resources Information Center

Lee, Zina; Salekin, Randall T.; Iselin, Anne-Marie R.

2010-01-01

The current study employed model-based cluster analysis in a sample of male adolescent offenders (n = 94) to examine subtypes based on psychopathic traits and anxiety. Using the Psychopathy Checklist: Youth Version (PCL:YV; Forth et al. 2003) and the self-report Antisocial Process Screening Device (APSD; Caputo et al. 1999), analyses identified…

a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

NASA Astrophysics Data System (ADS)

Huang, W.; Li, S.; Xu, S.

2016-06-01

How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the approximate 55% spatiotemporal clusters distributed in different locations can be eventually grouped as the same type of clusters with consideration of semantic aspect.

An integrated bioinformatics approach to improve two-color microarray quality-control: impact on biological conclusions.

PubMed

van Haaften, Rachel I M; Luceri, Cristina; van Erk, Arie; Evelo, Chris T A

2009-06-01

Omics technology used for large-scale measurements of gene expression is rapidly evolving. This work pointed out the need of an extensive bioinformatics analyses for array quality assessment before and after gene expression clustering and pathway analysis. A study focused on the effect of red wine polyphenols on rat colon mucosa was used to test the impact of quality control and normalisation steps on the biological conclusions. The integration of data visualization, pathway analysis and clustering revealed an artifact problem that was solved with an adapted normalisation. We propose a possible point to point standard analysis procedure, based on a combination of clustering and data visualization for the analysis of microarray data.

Innovative Strategies to Develop Chemical Categories Using a Combination of Structural and Toxicological Properties.

PubMed

Batke, Monika; Gütlein, Martin; Partosch, Falko; Gundert-Remy, Ursula; Helma, Christoph; Kramer, Stefan; Maunz, Andreas; Seeland, Madeleine; Bitsch, Annette

2016-01-01

Interest is increasing in the development of non-animal methods for toxicological evaluations. These methods are however, particularly challenging for complex toxicological endpoints such as repeated dose toxicity. European Legislation, e.g., the European Union's Cosmetic Directive and REACH, demands the use of alternative methods. Frameworks, such as the Read-across Assessment Framework or the Adverse Outcome Pathway Knowledge Base, support the development of these methods. The aim of the project presented in this publication was to develop substance categories for a read-across with complex endpoints of toxicity based on existing databases. The basic conceptual approach was to combine structural similarity with shared mechanisms of action. Substances with similar chemical structure and toxicological profile form candidate categories suitable for read-across. We combined two databases on repeated dose toxicity, RepDose database, and ELINCS database to form a common database for the identification of categories. The resulting database contained physicochemical, structural, and toxicological data, which were refined and curated for cluster analyses. We applied the Predictive Clustering Tree (PCT) approach for clustering chemicals based on structural and on toxicological information to detect groups of chemicals with similar toxic profiles and pathways/mechanisms of toxicity. As many of the experimental toxicity values were not available, this data was imputed by predicting them with a multi-label classification method, prior to clustering. The clustering results were evaluated by assessing chemical and toxicological similarities with the aim of identifying clusters with a concordance between structural information and toxicity profiles/mechanisms. From these chosen clusters, seven were selected for a quantitative read-across, based on a small ratio of NOAEL of the members with the highest and the lowest NOAEL in the cluster (< 5). We discuss the limitations of the approach. Based on this analysis we propose improvements for a follow-up approach, such as incorporation of metabolic information and more detailed mechanistic information. The software enables the user to allocate a substance in a cluster and to use this information for a possible read- across. The clustering tool is provided as a free web service, accessible at http://mlc-reach.informatik.uni-mainz.de.

Clustering consumers based on trust, confidence and giving behaviour: data-driven model building for charitable involvement in the Australian not-for-profit sector.

PubMed

de Vries, Natalie Jane; Reis, Rodrigo; Moscato, Pablo

2015-01-01

Organisations in the Not-for-Profit and charity sector face increasing competition to win time, money and efforts from a common donor base. Consequently, these organisations need to be more proactive than ever. The increased level of communications between individuals and organisations today, heightens the need for investigating the drivers of charitable giving and understanding the various consumer groups, or donor segments, within a population. It is contended that `trust' is the cornerstone of the not-for-profit sector's survival, making it an inevitable topic for research in this context. It has become imperative for charities and not-for-profit organisations to adopt for-profit's research, marketing and targeting strategies. This study provides the not-for-profit sector with an easily-interpretable segmentation method based on a novel unsupervised clustering technique (MST-kNN) followed by a feature saliency method (the CM1 score). A sample of 1,562 respondents from a survey conducted by the Australian Charities and Not-for-profits Commission is analysed to reveal donor segments. Each cluster's most salient features are identified using the CM1 score. Furthermore, symbolic regression modelling is employed to find cluster-specific models to predict `low' or `high' involvement in clusters. The MST-kNN method found seven clusters. Based on their salient features they were labelled as: the `non-institutionalist charities supporters', the `resource allocation critics', the `information-seeking financial sceptics', the `non-questioning charity supporters', the `non-trusting sceptics', the `charity management believers' and the `institutionalist charity believers'. Each cluster exhibits their own characteristics as well as different drivers of `involvement'. The method in this study provides the not-for-profit sector with a guideline for clustering, segmenting, understanding and potentially targeting their donor base better. If charities and not-for-profit organisations adopt these strategies, they will be more successful in today's competitive environment.

Clustering Consumers Based on Trust, Confidence and Giving Behaviour: Data-Driven Model Building for Charitable Involvement in the Australian Not-For-Profit Sector

PubMed Central

de Vries, Natalie Jane; Reis, Rodrigo; Moscato, Pablo

2015-01-01

Organisations in the Not-for-Profit and charity sector face increasing competition to win time, money and efforts from a common donor base. Consequently, these organisations need to be more proactive than ever. The increased level of communications between individuals and organisations today, heightens the need for investigating the drivers of charitable giving and understanding the various consumer groups, or donor segments, within a population. It is contended that `trust' is the cornerstone of the not-for-profit sector's survival, making it an inevitable topic for research in this context. It has become imperative for charities and not-for-profit organisations to adopt for-profit's research, marketing and targeting strategies. This study provides the not-for-profit sector with an easily-interpretable segmentation method based on a novel unsupervised clustering technique (MST-kNN) followed by a feature saliency method (the CM1 score). A sample of 1,562 respondents from a survey conducted by the Australian Charities and Not-for-profits Commission is analysed to reveal donor segments. Each cluster's most salient features are identified using the CM1 score. Furthermore, symbolic regression modelling is employed to find cluster-specific models to predict `low' or `high' involvement in clusters. The MST-kNN method found seven clusters. Based on their salient features they were labelled as: the `non-institutionalist charities supporters', the `resource allocation critics', the `information-seeking financial sceptics', the `non-questioning charity supporters', the `non-trusting sceptics', the `charity management believers' and the `institutionalist charity believers'. Each cluster exhibits their own characteristics as well as different drivers of `involvement'. The method in this study provides the not-for-profit sector with a guideline for clustering, segmenting, understanding and potentially targeting their donor base better. If charities and not-for-profit organisations adopt these strategies, they will be more successful in today's competitive environment. PMID:25849547

Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology

ERIC Educational Resources Information Center

Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael

2014-01-01

Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…

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

Hadgu, Teklu; Appel, Gordon John

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014) and Hadgu et al. (2015). The TSPA computing hardware (CL2014) and storage system described in Hadgu et al. (2015) were used for the currentmore » analysis. One floating license of GoldSim with Versions 9.60.300, 10.5 and 11.1.6 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA-type analysis on the server cluster. The current tasks included verification of the TSPA-LA uncertainty and sensitivity analyses, and preliminary upgrade of the TSPA-LA from Version 9.60.300 to the latest version 11.1. All the TSPA-LA uncertainty and sensitivity analyses modeling cases were successfully tested and verified for the model reproducibility on the upgraded 2014 server cluster (CL2014). The uncertainty and sensitivity analyses used TSPA-LA modeling cases output generated in FY15 based on GoldSim Version 9.60.300 documented in Hadgu et al. (2015). The model upgrade task successfully converted the Nominal Modeling case to GoldSim Version 11.1. Upgrade of the remaining of the modeling cases and distributed processing tasks will continue. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.« less

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

Cross-national evidence for the clustering and psychosocial correlates of adolescent risk behaviours in 27 countries.

PubMed

de Looze, Margaretha; Ter Bogt, Tom F M; Raaijmakers, Quinten A W; Pickett, William; Kuntsche, Emmanuel; Vollebergh, Wilma A M

2015-02-01

According to Jessor's Problem Behaviour Theory (PBT) and Moffitt's theory of adolescence-limited antisocial behaviour, adolescent risk behaviours cluster and can be predicted by various psychosocial factors including parent, peer and school attachment. This study tested the potential influence of the sociocultural, or macro-level, environment on the clustering and correlates of adolescent risk behaviour across 27 European and North American countries. Analyses were based on data from the 2009-10 Health Behaviour in School-aged Children (HBSC) study. Participants compromised 56,090 adolescents (M(age) = 15.5 years) who self-reported on substance use (tobacco, alcohol, cannabis) and early sexual activity as well as on psychosocial factors (parent, peer and school attachment). Multiple group confirmatory factor analyses (with country as grouping variable) showed that substance use and early sexual activity loaded on a single underlying factor across countries. In addition, multiple group path analyses (with country as grouping variable) showed that associations between this factor and parent, peer and school attachment were identical across countries. Cross-national consistencies exist in the clustering and psychosocial correlates of substance use and early sexual activity across western countries. While Jessor's PBT stresses the problematic aspects of adolescent risk behaviours, Moffitt emphasizes their normative character. Although the problematic nature of risk behaviours overall receives more attention in the literature, it is important to consider both perspectives to fully understand why they cluster and correlate with psychosocial factors. This is essential for the development and implementation of prevention programmes aimed at reducing adolescent risk behaviours across Europe and North America. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Detection of Functional Change Using Cluster Trend Analysis in Glaucoma.

PubMed

Gardiner, Stuart K; Mansberger, Steven L; Demirel, Shaban

2017-05-01

Global analyses using mean deviation (MD) assess visual field progression, but can miss localized changes. Pointwise analyses are more sensitive to localized progression, but more variable so require confirmation. This study assessed whether cluster trend analysis, averaging information across subsets of locations, could improve progression detection. A total of 133 test-retest eyes were tested 7 to 10 times. Rates of change and P values were calculated for possible re-orderings of these series to generate global analysis ("MD worsening faster than x dB/y with P < y"), pointwise and cluster analyses ("n locations [or clusters] worsening faster than x dB/y with P < y") with specificity exactly 95%. These criteria were applied to 505 eyes tested over a mean of 10.5 years, to find how soon each detected "deterioration," and compared using survival models. This was repeated including two subsequent visual fields to determine whether "deterioration" was confirmed. The best global criterion detected deterioration in 25% of eyes in 5.0 years (95% confidence interval [CI], 4.7-5.3 years), compared with 4.8 years (95% CI, 4.2-5.1) for the best cluster analysis criterion, and 4.1 years (95% CI, 4.0-4.5) for the best pointwise criterion. However, for pointwise analysis, only 38% of these changes were confirmed, compared with 61% for clusters and 76% for MD. The time until 25% of eyes showed subsequently confirmed deterioration was 6.3 years (95% CI, 6.0-7.2) for global, 6.3 years (95% CI, 6.0-7.0) for pointwise, and 6.0 years (95% CI, 5.3-6.6) for cluster analyses. Although the specificity is still suboptimal, cluster trend analysis detects subsequently confirmed deterioration sooner than either global or pointwise analyses.

A Direct Comparison of Two Densely Sampled HIV Epidemics: The UK and Switzerland

NASA Astrophysics Data System (ADS)

Ragonnet-Cronin, Manon L.; Shilaih, Mohaned; Günthard, Huldrych F.; Hodcroft, Emma B.; Böni, Jürg; Fearnhill, Esther; Dunn, David; Yerly, Sabine; Klimkait, Thomas; Aubert, Vincent; Yang, Wan-Lin; Brown, Alison E.; Lycett, Samantha J.; Kouyos, Roger; Brown, Andrew J. Leigh

2016-09-01

Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes.

System-wide analysis of the transcriptional network of human myelomonocytic leukemia cells predicts attractor structure and phorbol-ester-induced differentiation and dedifferentiation transitions

NASA Astrophysics Data System (ADS)

Sakata, Katsumi; Ohyanagi, Hajime; Sato, Shinji; Nobori, Hiroya; Hayashi, Akiko; Ishii, Hideshi; Daub, Carsten O.; Kawai, Jun; Suzuki, Harukazu; Saito, Toshiyuki

2015-02-01

We present a system-wide transcriptional network structure that controls cell types in the context of expression pattern transitions that correspond to cell type transitions. Co-expression based analyses uncovered a system-wide, ladder-like transcription factor cluster structure composed of nearly 1,600 transcription factors in a human transcriptional network. Computer simulations based on a transcriptional regulatory model deduced from the system-wide, ladder-like transcription factor cluster structure reproduced expression pattern transitions when human THP-1 myelomonocytic leukaemia cells cease proliferation and differentiate under phorbol myristate acetate stimulation. The behaviour of MYC, a reprogramming Yamanaka factor that was suggested to be essential for induced pluripotent stem cells during dedifferentiation, could be interpreted based on the transcriptional regulation predicted by the system-wide, ladder-like transcription factor cluster structure. This study introduces a novel system-wide structure to transcriptional networks that provides new insights into network topology.

Genetic Markers Analyses and Bioinformatic Approaches to Distinguish Between Olive Tree (Olea europaea L.) Cultivars.

PubMed

Ben Ayed, Rayda; Ben Hassen, Hanen; Ennouri, Karim; Rebai, Ahmed

2016-12-01

The genetic diversity of 22 olive tree cultivars (Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles (average 2.2 per allele). The dendrogram based on cultivar genotypes revealed three clusters consistent with the cultivars classification. Besides, the results obtained with the five SNPs were compared to those obtained with the SSR markers using bioinformatic analyses and by computing a cophenetic correlation coefficient, indicating the usefulness of the UPGMA method for clustering plant genotypes. Based on principal coordinate analysis using a similarity matrix, the first two coordinates, revealed 54.94 % of the total variance. This work provides a more comprehensive explanation of the diversity available in Tunisia olive cultivars, and an important contribution for olive breeding and olive oil authenticity.

Knowledge, attitudes towards and acceptability of genetic modification in Germany.

PubMed

Christoph, Inken B; Bruhn, Maike; Roosen, Jutta

2008-07-01

Genetic modification remains a controversial issue. The aim of this study is to analyse the attitudes towards genetic modification, the knowledge about it and its acceptability in different application areas among German consumers. Results are based on a survey from spring 2005. An exploratory factor analysis is conducted to identify the attitudes towards genetic modification. The identified factors are used in a cluster analysis that identified a cluster of supporters, of opponents and a group of indifferent consumers. Respondents' knowledge of genetics and biotechnology differs among the found clusters without revealing a clear relationship between knowledge and support of genetic modification. The acceptability of genetic modification varies by application area and cluster, and genetically modified non-food products are more widely accepted than food products. The perception of personal health risks has high explanatory power for attitudes and acceptability.

Effects of multiple founder populations on spatial genetic structure of reintroduced American martens.

PubMed

Williams, Bronwyn W; Scribner, Kim T

2010-01-01

Reintroductions and translocations are increasingly used to repatriate or increase probabilities of persistence for animal and plant species. Genetic and demographic characteristics of founding individuals and suitability of habitat at release sites are commonly believed to affect the success of these conservation programs. Genetic divergence among multiple source populations of American martens (Martes americana) and well documented introduction histories permitted analyses of post-introduction dispersion from release sites and development of genetic clusters in the Upper Peninsula (UP) of Michigan <50 years following release. Location and size of spatial genetic clusters and measures of individual-based autocorrelation were inferred using 11 microsatellite loci. We identified three genetic clusters in geographic proximity to original release locations. Estimated distances of effective gene flow based on spatial autocorrelation varied greatly among genetic clusters (30-90 km). Spatial contiguity of genetic clusters has been largely maintained with evidence for admixture primarily in localized regions, suggesting recent contact or locally retarded rates of gene flow. Data provide guidance for future studies of the effects of permeabilities of different land-cover and land-use features to dispersal and of other biotic and environmental factors that may contribute to the colonization process and development of spatial genetic associations.

Health and disease phenotyping in old age using a cluster network analysis.

PubMed

Valenzuela, Jesus Felix; Monterola, Christopher; Tong, Victor Joo Chuan; Ng, Tze Pin; Larbi, Anis

2017-11-15

Human ageing is a complex trait that involves the synergistic action of numerous biological processes that interact to form a complex network. Here we performed a network analysis to examine the interrelationships between physiological and psychological functions, disease, disability, quality of life, lifestyle and behavioural risk factors for ageing in a cohort of 3,270 subjects aged ≥55 years. We considered associations between numerical and categorical descriptors using effect-size measures for each variable pair and identified clusters of variables from the resulting pairwise effect-size network and minimum spanning tree. We show, by way of a correspondence analysis between the two sets of clusters, that they correspond to coarse-grained and fine-grained structure of the network relationships. The clusters obtained from the minimum spanning tree mapped to various conceptual domains and corresponded to physiological and syndromic states. Hierarchical ordering of these clusters identified six common themes based on interactions with physiological systems and common underlying substrates of age-associated morbidity and disease chronicity, functional disability, and quality of life. These findings provide a starting point for indepth analyses of ageing that incorporate immunologic, metabolomic and proteomic biomarkers, and ultimately offer low-level-based typologies of healthy and unhealthy ageing.

A PSF-based approach to Kepler/K2 data - II. Exoplanet candidates in Praesepe (M 44)

NASA Astrophysics Data System (ADS)

Libralato, M.; Nardiello, D.; Bedin, L. R.; Borsato, L.; Granata, V.; Malavolta, L.; Piotto, G.; Ochner, P.; Cunial, A.; Nascimbeni, V.

2016-12-01

In this work, we keep pushing K2 data to a high photometric precision, close to that of the Kepler main mission, using a point-spread function (PSF)-based, neighbour-subtraction technique, which also overcome the dilution effects in crowded environments. We analyse the open cluster M 44 (NGC 2632), observed during the K2 Campaign 5, and extract light curves of stars imaged on module 14, where most of the cluster lies. We present two candidate exoplanets hosted by cluster members and five by field stars. As a by-product of our investigation, we find 1680 eclipsing binaries and variable stars, 1071 of which are new discoveries. Among them, we report the presence of a heartbeat binary star. Together with this work, we release to the community a catalogue with the variable stars and the candidate exoplanets found, as well as all our raw and detrended light curves.

Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials

PubMed Central

Gomes, Manuel; Ng, Edmond S.-W.; Nixon, Richard; Carpenter, James; Thompson, Simon G.

2012-01-01

Aim. Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Methods. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering—seemingly unrelated regression (SUR) without a robust standard error (SE)—and 4 methods that recognized clustering—SUR and generalized estimating equations (GEEs), both with robust SE, a “2-stage” nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Results. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92–0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. Conclusions. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters. PMID:22016450

Response to "Comparison and Evaluation of Clustering Algorithms for Tandem Mass Spectra".

PubMed

Griss, Johannes; Perez-Riverol, Yasset; The, Matthew; Käll, Lukas; Vizcaíno, Juan Antonio

2018-05-04

In the recent benchmarking article entitled "Comparison and Evaluation of Clustering Algorithms for Tandem Mass Spectra", Rieder et al. compared several different approaches to cluster MS/MS spectra. While we certainly recognize the value of the manuscript, here, we report some shortcomings detected in the original analyses. For most analyses, the authors clustered only single MS/MS runs. In one of the reported analyses, three MS/MS runs were processed together, which already led to computational performance issues in many of the tested approaches. This fact highlights the difficulties of using many of the tested algorithms on the nowadays produced average proteomics data sets. Second, the authors only processed identified spectra when merging MS runs. Thereby, all unidentified spectra that are of lower quality were already removed from the data set and could not influence the clustering results. Next, we found that the authors did not analyze the effect of chimeric spectra on the clustering results. In our analysis, we found that 3% of the spectra in the used data sets were chimeric, and this had marked effects on the behavior of the different clustering algorithms tested. Finally, the authors' choice to evaluate the MS-Cluster and spectra-cluster algorithms using a precursor tolerance of 5 Da for high-resolution Orbitrap data only was, in our opinion, not adequate to assess the performance of MS/MS clustering approaches.

Molecular Clustering Interrelationships and Carbohydrate Conformation in Hull and Seeds Among Barley Cultivars

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

N Liu; P Yu

2011-12-31

The objective of this study was to use molecular spectral analyses with the diffuse reflectance Fourier transform infrared spectroscopy (DRIFT) bioanlytical technique to study carbohydrate conformation features, molecular clustering and interrelationships in hull and seed among six barley cultivars (AC Metcalfe, CDC Dolly, McLeod, CDC Helgason, CDC Trey, CDC Cowboy), which had different degradation kinetics in rumen. The molecular structure spectral analyses in both hull and seed involved the fingerprint regions of ca. 1536-1484 cm{sup -1} (attributed mainly to aromatic lignin semicircle ring stretch), ca. 1293-1212 cm{sup -1} (attributed mainly to cellulosic compounds in the hull), ca. 1269-1217 cm{sup -1}more » (attributed mainly to cellulosic compound in the seeds), and ca. 1180-800 cm{sup -1} (attributed mainly to total CHO C-O stretching vibrations) together with an agglomerative hierarchical cluster (AHCA) and principal component spectral analyses (PCA). The results showed that the DRIFT technique plus AHCA and PCA molecular analyses were able to reveal carbohydrate conformation features and identify carbohydrate molecular structure differences in both hull and seeds among the barley varieties. The carbohydrate molecular spectral analyses at the region of ca. 1185-800 cm{sup -1} together with the AHCA and PCA were able to show that the barley seed inherent structures exhibited distinguishable differences among the barley varieties. CDC Helgason had differences from AC Metcalfe, MeLeod, CDC Cowboy and CDC Dolly in carbohydrate conformation in the seed. Clear molecular cluster classes could be distinguished and identified in AHCA analysis and the separate ellipses could be grouped in PCA analysis. But CDC Helgason had no distinguished differences from CDC Trey in carbohydrate conformation. These carbohydrate conformation/structure difference could partially explain why the varieties were different in digestive behaviors in animals. The molecular spectroscopy technique used in this study could also be used for other plant-based feed and food structure studies.« less

Village-based spatio-temporal cluster analysis of the schistosomiasis risk in the Poyang Lake Region, China.

PubMed

Xia, Congcong; Bergquist, Robert; Lynn, Henry; Hu, Fei; Lin, Dandan; Hao, Yuwan; Li, Shizhu; Hu, Yi; Zhang, Zhijie

2017-03-08

The Poyang Lake Region, one of the major epidemic sites of schistosomiasis in China, remains a severe challenge. To improve our understanding of the current endemic status of schistosomiasis and to better control the transmission of the disease in the Poyang Lake Region, it is important to analyse the clustering pattern of schistosomiasis and detect the hotspots of transmission risk. Based on annual surveillance data, at the village level in this region from 2009 to 2014, spatial and temporal cluster analyses were conducted to assess the pattern of schistosomiasis infection risk among humans through purely spatial (Local Moran's I, Kulldorff and Flexible scan statistic) and space-time scan statistics (Kulldorff). A dramatic decline was found in the infection rate during the study period, which was shown to be maintained at a low level. The number of spatial clusters declined over time and were concentrated in counties around Poyang Lake, including Yugan, Yongxiu, Nanchang, Xingzi, Xinjian, De'an as well as Pengze, situated along the Yangtze River and the most serious area found in this study. Space-time analysis revealed that the clustering time frame appeared between 2009 and 2011 and the most likely cluster with the widest range was particularly concentrated in Pengze County. This study detected areas at high risk for schistosomiasis both in space and time at the village level from 2009 to 2014 in Poyang Lake Region. The high-risk areas are now more concentrated and mainly distributed at the river inflows Poyang Lake and along Yangtze River in Pengze County. It was assumed that the water projects including reservoirs and a recently breached dyke in this area were partly to blame. This study points out that attempts to reduce the negative effects of water projects in China should focus on the Poyang Lake Region.

US forests are showing increased rates of decline in response to a changing climate

Treesearch

Warren B. Cohen; Zhiqiang Yang; David M. Bell; Stephen V. Stehman

2015-01-01

How vulnerable are US forest to a changing climate? We answer this question using Landsat time series data and a unique interpretation approach, TimeSync, a plot-based Landsat visualization and data collection tool. Original analyses were based on a stratified two-stage cluster sample design that included interpretation of 3858 forested plots. From these data, we...

The Effects of Research-Based Curriculum Materials and Curriculum-Based Professional Development on High School Science Achievement: Results of a Cluster-Randomized Trial

ERIC Educational Resources Information Center

Taylor, Joseph; Kowalski, Susan; Getty, Stephen; Wilson, Christopher; Carlson, Janet

2013-01-01

Effective instructional materials can be valuable interventions to improve student interest and achievement in science (National Research Council [NRC], 2007); yet, analyses indicate that many science instructional materials and curricula are fragmented, lack coherence, and are not carefully articulated through a sequence of grade levels (AAAS,…

The association between mood state and chronobiological characteristics in bipolar I disorder: a naturalistic, variable cluster analysis-based study.

PubMed

Gonzalez, Robert; Suppes, Trisha; Zeitzer, Jamie; McClung, Colleen; Tamminga, Carol; Tohen, Mauricio; Forero, Angelica; Dwivedi, Alok; Alvarado, Andres

2018-02-19

Multiple types of chronobiological disturbances have been reported in bipolar disorder, including characteristics associated with general activity levels, sleep, and rhythmicity. Previous studies have focused on examining the individual relationships between affective state and chronobiological characteristics. The aim of this study was to conduct a variable cluster analysis in order to ascertain how mood states are associated with chronobiological traits in bipolar I disorder (BDI). We hypothesized that manic symptomatology would be associated with disturbances of rhythm. Variable cluster analysis identified five chronobiological clusters in 105 BDI subjects. Cluster 1, comprising subjective sleep quality was associated with both mania and depression. Cluster 2, which comprised variables describing the degree of rhythmicity, was associated with mania. Significant associations between mood state and cluster analysis-identified chronobiological variables were noted. Disturbances of mood were associated with subjectively assessed sleep disturbances as opposed to objectively determined, actigraphy-based sleep variables. No associations with general activity variables were noted. Relationships between gender and medication classes in use and cluster analysis-identified chronobiological characteristics were noted. Exploratory analyses noted that medication class had a larger impact on these relationships than the number of psychiatric medications in use. In a BDI sample, variable cluster analysis was able to group related chronobiological variables. The results support our primary hypothesis that mood state, particularly mania, is associated with chronobiological disturbances. Further research is required in order to define these relationships and to determine the directionality of the associations between mood state and chronobiological characteristics.

Identifying optimal threshold statistics for elimination of hookworm using a stochastic simulation model.

PubMed

Truscott, James E; Werkman, Marleen; Wright, James E; Farrell, Sam H; Sarkar, Rajiv; Ásbjörnsdóttir, Kristjana; Anderson, Roy M

2017-06-30

There is an increased focus on whether mass drug administration (MDA) programmes alone can interrupt the transmission of soil-transmitted helminths (STH). Mathematical models can be used to model these interventions and are increasingly being implemented to inform investigators about expected trial outcome and the choice of optimum study design. One key factor is the choice of threshold for detecting elimination. However, there are currently no thresholds defined for STH regarding breaking transmission. We develop a simulation of an elimination study, based on the DeWorm3 project, using an individual-based stochastic disease transmission model in conjunction with models of MDA, sampling, diagnostics and the construction of study clusters. The simulation is then used to analyse the relationship between the study end-point elimination threshold and whether elimination is achieved in the long term within the model. We analyse the quality of a range of statistics in terms of the positive predictive values (PPV) and how they depend on a range of covariates, including threshold values, baseline prevalence, measurement time point and how clusters are constructed. End-point infection prevalence performs well in discriminating between villages that achieve interruption of transmission and those that do not, although the quality of the threshold is sensitive to baseline prevalence and threshold value. Optimal post-treatment prevalence threshold value for determining elimination is in the range 2% or less when the baseline prevalence range is broad. For multiple clusters of communities, both the probability of elimination and the ability of thresholds to detect it are strongly dependent on the size of the cluster and the size distribution of the constituent communities. Number of communities in a cluster is a key indicator of probability of elimination and PPV. Extending the time, post-study endpoint, at which the threshold statistic is measured improves PPV value in discriminating between eliminating clusters and those that bounce back. The probability of elimination and PPV are very sensitive to baseline prevalence for individual communities. However, most studies and programmes are constructed on the basis of clusters. Since elimination occurs within smaller population sub-units, the construction of clusters introduces new sensitivities for elimination threshold values to cluster size and the underlying population structure. Study simulation offers an opportunity to investigate key sources of sensitivity for elimination studies and programme designs in advance and to tailor interventions to prevailing local or national conditions.

Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells.

PubMed

Tait, Luke; Wedgwood, Kyle; Tsaneva-Atanasova, Krasimira; Brown, Jon T; Goodfellow, Marc

2018-07-14

The entorhinal cortex is a crucial component of our memory and spatial navigation systems and is one of the first areas to be affected in dementias featuring tau pathology, such as Alzheimer's disease and frontotemporal dementia. Electrophysiological recordings from principle cells of medial entorhinal cortex (layer II stellate cells, mEC-SCs) demonstrate a number of key identifying properties including subthreshold oscillations in the theta (4-12 Hz) range and clustered action potential firing. These single cell properties are correlated with network activity such as grid firing and coupling between theta and gamma rhythms, suggesting they are important for spatial memory. As such, experimental models of dementia have revealed disruption of organised dorsoventral gradients in clustered action potential firing. To better understand the mechanisms underpinning these different dynamics, we study a conductance based model of mEC-SCs. We demonstrate that the model, driven by extrinsic noise, can capture quantitative differences in clustered action potential firing patterns recorded from experimental models of tau pathology and healthy animals. The differential equation formulation of our model allows us to perform numerical bifurcation analyses in order to uncover the dynamic mechanisms underlying these patterns. We show that clustered dynamics can be understood as subcritical Hopf/homoclinic bursting in a fast-slow system where the slow sub-system is governed by activation of the persistent sodium current and inactivation of the slow A-type potassium current. In the full system, we demonstrate that clustered firing arises via flip bifurcations as conductance parameters are varied. Our model analyses confirm the experimentally suggested hypothesis that the breakdown of clustered dynamics in disease occurs via increases in AHP conductance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A versatile software package for inter-subject correlation based analyses of fMRI.

PubMed

Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

2014-01-01

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/

A versatile software package for inter-subject correlation based analyses of fMRI

PubMed Central

Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

2014-01-01

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/ PMID:24550818

A reanalysis of cluster randomized trials showed interrupted time-series studies were valuable in health system evaluation.

PubMed

Fretheim, Atle; Zhang, Fang; Ross-Degnan, Dennis; Oxman, Andrew D; Cheyne, Helen; Foy, Robbie; Goodacre, Steve; Herrin, Jeph; Kerse, Ngaire; McKinlay, R James; Wright, Adam; Soumerai, Stephen B

2015-03-01

There is often substantial uncertainty about the impacts of health system and policy interventions. Despite that, randomized controlled trials (RCTs) are uncommon in this field, partly because experiments can be difficult to carry out. An alternative method for impact evaluation is the interrupted time-series (ITS) design. Little is known, however, about how results from the two methods compare. Our aim was to explore whether ITS studies yield results that differ from those of randomized trials. We conducted single-arm ITS analyses (segmented regression) based on data from the intervention arm of cluster randomized trials (C-RCTs), that is, discarding control arm data. Secondarily, we included the control group data in the analyses, by subtracting control group data points from intervention group data points, thereby constructing a time series representing the difference between the intervention and control groups. We compared the results from the single-arm and controlled ITS analyses with results based on conventional aggregated analyses of trial data. The findings were largely concordant, yielding effect estimates with overlapping 95% confidence intervals (CI) across different analytical methods. However, our analyses revealed the importance of a concurrent control group and of taking baseline and follow-up trends into account in the analysis of C-RCTs. The ITS design is valuable for evaluation of health systems interventions, both when RCTs are not feasible and in the analysis and interpretation of data from C-RCTs. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Pattern recognition approach to the subsequent event of damaging earthquakes in Italy

NASA Astrophysics Data System (ADS)

Gentili, S.; Di Giovambattista, R.

2017-05-01

In this study, we investigate the occurrence of large aftershocks following the most significant earthquakes that occurred in Italy after 1980. In accordance with previous studies (Vorobieva and Panza, 1993; Vorobieva, 1999), we group clusters associated with mainshocks into two categories: ;type A; if, given a main shock of magnitude M, the subsequent strongest earthquake in the cluster has magnitude ≥M - 1 or type B otherwise. In this paper, we apply a pattern recognition approach using statistical features to foresee the class of the analysed clusters. The classification of the two categories is based on some features of the time, space, and magnitude distribution of the aftershocks. Specifically, we analyse the temporal evolution of the radiated energy at different elapsed times after the mainshock, the spatio-temporal evolution of the aftershocks occurring within a few days, and the probability of a strong earthquake. An attempt is made to classify the studied region into smaller seismic zones with a prevalence of type A and B clusters. We demonstrate that the two types of clusters have distinct preferred geographic locations inside the Italian territory that likely reflected key properties of the deforming regions, different crustal domains and faulting style. We use decision trees as classifiers of single features to characterize the features depending on the cluster type. The performance of the classification is tested by the Leave-One-Out method. The analysis is performed on different time-spans after the mainshock to simulate the dependence of the accuracy on the information available as data increased over a longer period with increasing time after the mainshock.

Single nucleotide polymorphism discovery via genotyping by sequencing to assess population genetic structure and recurrent polyploidization in Andropogon gerardii.

PubMed

McAllister, Christine A; Miller, Allison J

2016-07-01

Autopolyploidy, genome duplication within a single lineage, can result in multiple cytotypes within a species. Geographic distributions of cytotypes may reflect the evolutionary history of autopolyploid formation and subsequent population dynamics including stochastic (drift) and deterministic (differential selection among cytotypes) processes. Here, we used a population genomic approach to investigate whether autopolyploidy occurred once or multiple times in Andropogon gerardii, a widespread, North American grass with two predominant cytotypes. Genotyping by sequencing was used to identify single nucleotide polymorphisms (SNPs) in individuals collected from across the geographic range of A. gerardii. Two independent approaches to SNP calling were used: the reference-free UNEAK pipeline and a reference-guided approach based on the sequenced Sorghum bicolor genome. SNPs generated using these pipelines were analyzed independently with genetic distance and clustering. Analyses of the two SNP data sets showed very similar patterns of population-level clustering of A. gerardii individuals: a cluster of A. gerardii individuals from the southern Plains, a northern Plains cluster, and a western cluster. Groupings of individuals corresponded to geographic localities regardless of cytotype: 6x and 9x individuals from the same geographic area clustered together. SNPs generated using reference-guided and reference-free pipelines in A. gerardii yielded unique subsets of genomic data. Both data sets suggest that the 9x cytotype in A. gerardii likely evolved multiple times from 6x progenitors across the range of the species. Genomic approaches like GBS and diverse bioinformatics pipelines used here facilitate evolutionary analyses of complex systems with multiple ploidy levels. © 2016 Botanical Society of America.

Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services

PubMed Central

Krawczyk, Christopher; Gradziel, Pat; Geraghty, Estella M.

2014-01-01

Objectives. We used a geographic information system and cluster analyses to determine locations in need of enhanced Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program services. Methods. We linked documented births in the 2010 California Birth Statistical Master File with the 2010 data from the WIC Integrated Statewide Information System. Analyses focused on the density of pregnant women who were eligible for but not receiving WIC services in California’s 7049 census tracts. We used incremental spatial autocorrelation and hot spot analyses to identify clusters of WIC-eligible nonparticipants. Results. We detected clusters of census tracts with higher-than-expected densities, compared with the state mean density of WIC-eligible nonparticipants, in 21 of 58 (36.2%) California counties (P < .05). In subsequent county-level analyses, we located neighborhood-level clusters of higher-than-expected densities of eligible nonparticipants in Sacramento, San Francisco, Fresno, and Los Angeles Counties (P < .05). Conclusions. Hot spot analyses provided a rigorous and objective approach to determine the locations of statistically significant clusters of WIC-eligible nonparticipants. Results helped inform WIC program and funding decisions, including the opening of new WIC centers, and offered a novel approach for targeting public health services. PMID:24354821

Defective functional connectivity between posterior hypothalamus and regions of the diencephalic-mesencephalic junction in chronic cluster headache.

PubMed

Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Brivio, Luca; Proietti Cecchini, Alberto; Verri, Mattia; Chiapparini, Luisa; Leone, Massimo

2018-01-01

Objective We tested the hypothesis of a defective functional connectivity between the posterior hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache based on: a) clinical and neuro-endocrinological findings in cluster headache patients; b) neuroimaging findings during cluster headache attacks; c) neuroimaging findings in drug-refractory chronic cluster headache patients improved after successful deep brain stimulation. Methods Resting state functional magnetic resonance imaging, associated with a seed-based approach, was employed to investigate the functional connectivity of the posterior hypothalamus in chronic cluster headache patients (n = 17) compared to age and sex-matched healthy subjects (n = 16). Random-effect analyses were performed to study differences between patients and controls in ipsilateral and contralateral-to-the-pain posterior hypothalamus functional connectivity. Results Cluster headache patients showed an increased functional connectivity between the ipsilateral posterior hypothalamus and a number of diencephalic-mesencephalic structures, comprising ventral tegmental area, dorsal nuclei of raphe, and bilateral substantia nigra, sub-thalamic nucleus, and red nucleus ( p < 0.005 FDR-corrected vs . control group). No difference between patients and controls was found comparing the contralateral hypothalami. Conclusions The observed deranged functional connectivity between the posterior ipsilateral hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache patients mainly involves structures that are part of (i.e. ventral tegmental area, substantia nigra) or modulate (dorsal nuclei of raphe, sub-thalamic nucleus) the midbrain dopaminergic systems. The midbrain dopaminergic systems could play a role in cluster headache pathophysiology and in particular in the chronicization process. Future studies are needed to better clarify if this finding is specific to cluster headache or if it represents an unspecific response to chronic pain.

Development of a model of the tobacco industry's interference with tobacco control programmes

PubMed Central

Trochim, W; Stillman, F; Clark, P; Schmitt, C

2003-01-01

Objective: To construct a conceptual model of tobacco industry tactics to undermine tobacco control programmes for the purposes of: (1) developing measures to evaluate industry tactics, (2) improving tobacco control planning, and (3) supplementing current or future frameworks used to classify and analyse tobacco industry documents. Design: Web based concept mapping was conducted, including expert brainstorming, sorting, and rating of statements describing industry tactics. Statistical analyses used multidimensional scaling and cluster analysis. Interpretation of the resulting maps was accomplished by an expert panel during a face-to-face meeting. Subjects: 34 experts, selected because of their previous encounters with industry resistance or because of their research into industry tactics, took part in some or all phases of the project. Results: Maps with eight non-overlapping clusters in two dimensional space were developed, with importance ratings of the statements and clusters. Cluster and quadrant labels were agreed upon by the experts. Conclusions: The conceptual maps summarise the tactics used by the industry and their relationships to each other, and suggest a possible hierarchy for measures that can be used in statistical modelling of industry tactics and for review of industry documents. Finally, the maps enable hypothesis of a likely progression of industry reactions as public health programmes become more successful, and therefore more threatening to industry profits. PMID:12773723

The ergot alkaloid gene cluster: functional analyses and evolutionary aspects.

PubMed

Lorenz, Nicole; Haarmann, Thomas; Pazoutová, Sylvie; Jung, Manfred; Tudzynski, Paul

2009-01-01

Ergot alkaloids and their derivatives have been traditionally used as therapeutic agents in migraine, blood pressure regulation and help in childbirth and abortion. Their production in submerse culture is a long established biotechnological process. Ergot alkaloids are produced mainly by members of the genus Claviceps, with Claviceps purpurea as best investigated species concerning the biochemistry of ergot alkaloid synthesis (EAS). Genes encoding enzymes involved in EAS have been shown to be clustered; functional analyses of EAS cluster genes have allowed to assign specific functions to several gene products. Various Claviceps species differ with respect to their host specificity and their alkaloid content; comparison of the ergot alkaloid clusters in these species (and of clavine alkaloid clusters in other genera) yields interesting insights into the evolution of cluster structure. This review focuses on recently published and also yet unpublished data on the structure and evolution of the EAS gene cluster and on the function and regulation of cluster genes. These analyses have also significant biotechnological implications: the characterization of non-ribosomal peptide synthetases (NRPS) involved in the synthesis of the peptide moiety of ergopeptines opened interesting perspectives for the synthesis of ergot alkaloids; on the other hand, defined mutants could be generated producing interesting intermediates or only single peptide alkaloids (instead of the alkaloid mixtures usually produced by industrial strains).

Simultaneous Co-Clustering and Classification in Customers Insight

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The adiposity of children is associated with their lifestyle behaviours: a cluster analysis of school-aged children from 12 nations.

PubMed

Dumuid, Dorothea; Olds, T; Lewis, L K; Martin-Fernández, J A; Barreira, T; Broyles, S; Chaput, J-P; Fogelholm, M; Hu, G; Kuriyan, R; Kurpad, A; Lambert, E V; Maia, J; Matsudo, V; Onywera, V O; Sarmiento, O L; Standage, M; Tremblay, M S; Tudor-Locke, C; Zhao, P; Katzmarzyk, P; Gillison, F; Maher, C

2018-02-01

The relationship between children's adiposity and lifestyle behaviour patterns is an area of growing interest. The objectives of this study are to identify clusters of children based on lifestyle behaviours and compare children's adiposity among clusters. Cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment were used. the participants were children (9-11 years) from 12 nations (n = 5710). 24-h accelerometry and self-reported diet and screen time were clustering input variables. Objectively measured adiposity indicators were waist-to-height ratio, percent body fat and body mass index z-scores. sex-stratified analyses were performed on the global sample and repeated on a site-wise basis. Cluster analysis (using isometric log ratios for compositional data) was used to identify common lifestyle behaviour patterns. Site representation and adiposity were compared across clusters using linear models. Four clusters emerged: (1) Junk Food Screenies, (2) Actives, (3) Sitters and (4) All-Rounders. Countries were represented differently among clusters. Chinese children were over-represented in Sitters and Colombian children in Actives. Adiposity varied across clusters, being highest in Sitters and lowest in Actives. Children from different sites clustered into groups of similar lifestyle behaviours. Cluster membership was linked with differing adiposity. Findings support the implementation of activity interventions in all countries, targeting both physical activity and sedentary time. © 2016 World Obesity Federation.

The MUSE-Wide survey: detection of a clustering signal from Lyman α emitters in the range 3 < z < 6

NASA Astrophysics Data System (ADS)

Diener, C.; Wisotzki, L.; Schmidt, K. B.; Herenz, E. C.; Urrutia, T.; Garel, T.; Kerutt, J.; Saust, R. L.; Bacon, R.; Cantalupo, S.; Contini, T.; Guiderdoni, B.; Marino, R. A.; Richard, J.; Schaye, J.; Soucail, G.; Weilbacher, P. M.

2017-11-01

We present a clustering analysis of a sample of 238 Ly α emitters at redshift 3 ≲ z ≲ 6 from the MUSE-Wide survey. This survey mosaics extragalactic legacy fields with 1h MUSE pointings to detect statistically relevant samples of emission line galaxies. We analysed the first year observations from MUSE-Wide making use of the clustering signal in the line-of-sight direction. This method relies on comparing pair-counts at close redshifts for a fixed transverse distance and thus exploits the full potential of the redshift range covered by our sample. A clear clustering signal with a correlation length of r0=2.9^{+1.0}_{-1.1} Mpc (comoving) is detected. Whilst this result is based on only about a quarter of the full survey size, it already shows the immense potential of MUSE for efficiently observing and studying the clustering of Ly α emitters.

Generalising Ward's Method for Use with Manhattan Distances.

PubMed

Strauss, Trudie; von Maltitz, Michael Johan

2017-01-01

The claim that Ward's linkage algorithm in hierarchical clustering is limited to use with Euclidean distances is investigated. In this paper, Ward's clustering algorithm is generalised to use with l1 norm or Manhattan distances. We argue that the generalisation of Ward's linkage method to incorporate Manhattan distances is theoretically sound and provide an example of where this method outperforms the method using Euclidean distances. As an application, we perform statistical analyses on languages using methods normally applied to biology and genetic classification. We aim to quantify differences in character traits between languages and use a statistical language signature based on relative bi-gram (sequence of two letters) frequencies to calculate a distance matrix between 32 Indo-European languages. We then use Ward's method of hierarchical clustering to classify the languages, using the Euclidean distance and the Manhattan distance. Results obtained from using the different distance metrics are compared to show that the Ward's algorithm characteristic of minimising intra-cluster variation and maximising inter-cluster variation is not violated when using the Manhattan metric.

Russian consumers' motives for food choice.

PubMed

Honkanen, Pirjo; Frewer, Lynn

2009-04-01

Knowledge about food choice motives which have potential to influence consumer consumption decisions is important when designing food and health policies, as well as marketing strategies. Russian consumers' food choice motives were studied in a survey (1081 respondents across four cities), with the purpose of identifying consumer segments based on these motives. These segments were then profiled using consumption, attitudinal and demographic variables. Face-to-face interviews were used to sample the data, which were analysed with two-step cluster analysis (SPSS). Three clusters emerged, representing 21.5%, 45.8% and 32.7% of the sample. The clusters were similar in terms of the order of motivations, but differed in motivational level. Sensory factors and availability were the most important motives for food choice in all three clusters, followed by price. This may reflect the turbulence which Russia has recently experienced politically and economically. Cluster profiles differed in relation to socio-demographic factors, consumption patterns and attitudes towards health and healthy food.

Sloshing Gas in the Core of the Most Luminous Galaxy Cluster RXJ1347.5-1145

NASA Technical Reports Server (NTRS)

Johnson, Ryan E.; Zuhone, John; Jones, Christine; Forman, William R.; Markevitvh, Maxim

2011-01-01

We present new constraints on the merger history of the most X-ray luminous cluster of galaxies, RXJ1347.5-1145, based on its unique multiwavelength morphology. Our X-ray analysis confirms the core gas is undergoing "sloshing" resulting from a prior, large scale, gravitational perturbation. In combination with extensive multiwavelength observations, the sloshing gas points to the primary and secondary clusters having had at least two prior strong gravitational interactions. The evidence supports a model in which the secondary subcluster with mass M=4.8+/-2.4x10(exp 14) solar Mass has previously (> or approx.0.6 Gyr ago) passed by the primary cluster, and has now returned for a subsequent crossing where the subcluster's gas has been completely stripped from its dark matter halo. RXJ1347 is a prime example of how core gas sloshing may be used to constrain the merger histories of galaxy clusters through multiwavelength analyses.

Bayesian hierarchical models for cost-effectiveness analyses that use data from cluster randomized trials.

PubMed

Grieve, Richard; Nixon, Richard; Thompson, Simon G

2010-01-01

Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.

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

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H{sub 2}ndc) or 4,4′-(hydroxymethylene)dibenzoic acid (H{sub 2}hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd{sub 2}(2,6-ndc){sub 2}(bpp)(DMF)]·2DMF (1) and [Cd{sub 3}(hmdb){sub 3}(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations inmore » 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process. - Graphical abstract: Compound 1 exhibits a 3D self-penetrating 6-connected framework based on dinuclear cluster, and 2 displays an infinite 3D ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster. The flexible 1,3-bis(4-pyridyl)propane ligand displays different conformations in 1 and 2, which successfully controlled by size-matching mixed ligands during the self-assembly process.« less

Migratory connectivity and effects of winter temperatures on migratory behaviour of the European robin Erithacus rubecula: a continent-wide analysis.

PubMed

Ambrosini, Roberto; Cuervo, José Javier; du Feu, Chris; Fiedler, Wolfgang; Musitelli, Federica; Rubolini, Diego; Sicurella, Beatrice; Spina, Fernando; Saino, Nicola; Møller, Anders Pape

2016-05-01

Many partially migratory species show phenotypically divergent populations in terms of migratory behaviour, with climate hypothesized to be a major driver of such variability through its differential effects on sedentary and migratory individuals. Based on long-term (1947-2011) bird ringing data, we analysed phenotypic differentiation of migratory behaviour among populations of the European robin Erithacus rubecula across Europe. We showed that clusters of populations sharing breeding and wintering ranges varied from partial (British Isles and Western Europe, NW cluster) to completely migratory (Scandinavia and north-eastern Europe, NE cluster). Distance migrated by birds of the NE (but not of the NW) cluster decreased through time because of a north-eastwards shift in the wintering grounds. Moreover, when winter temperatures in the breeding areas were cold, individuals from the NE cluster also migrated longer distances, while those of the NW cluster moved over shorter distances. Climatic conditions may therefore affect migratory behaviour of robins, although large geographical variation in response to climate seems to exist. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut.

PubMed

Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy

2013-11-01

We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

More than one way to be happy: a typology of marital happiness.

PubMed

Rauer, Amy; Volling, Brenda

2013-09-01

This study utilized observational and self-report data from 57 happily married couples to explore assumptions regarding marital happiness. Suggesting that happily married couples are not a homogeneous group, cluster analyses revealed the existence of three types of couples based on their observed behaviors in a problem-solving task: (1) mutually engaged couples (characterized by both spouses' higher negative and positive problem-solving); (2) mutually supportive couples (characterized by both spouses' higher positivity and support); and (3) wife compensation couples (characterized by high wife positivity). Although couples in all three clusters were equally happy with and committed to their marriages, these clusters were differentially associated with spouses' evaluations of their marriage. Spouses in the mutually supportive cluster reported greater intimacy and maintenance and less conflict and ambivalence, although this was more consistently the case in comparison to the wife compensation cluster, as opposed to the mutually engaged cluster. The implications of these typologies are discussed as they pertain to efforts on the part of both practitioners to promote marital happiness and repair marital relations when couples are faced with difficulties. © FPI, Inc.

Students' Preference for Science Careers: International comparisons based on PISA 2006

NASA Astrophysics Data System (ADS)

Kjærnsli, Marit; Lie, Svein

2011-01-01

This article deals with 15-year-old students' tendencies to consider a future science-related career. Two aspects have been the focus of our investigation. The first is based on the construct called 'future science orientation', an affective construct consisting of four Likert scale items that measure students' consideration of being involved in future education and careers in science-related areas. Due to the well-known evidence for Likert scales providing culturally biased estimates, the aim has been to go beyond the comparison of simple country averages. In a series of regression and correlation analyses, we have investigated how well the variance of this construct in each of the participating countries can be accounted for by other Programme for International Student Assessment (PISA) student data. The second aspect is based on a question about students' future jobs. By separating science-related jobs into what we have called 'soft' and 'hard' science-related types of jobs, we have calculated and compared country percentages within each category. In particular, gender differences are discussed, and interesting international patterns have been identified. The results in this article have been reported not only for individual countries, but also for groups of countries. These cluster analyses of countries are based on item-by-item patterns of (residual values of) national average values for the combination of cognitive and affective items. The emerging cluster structure of countries has turned out to contribute to the literature of similarities and differences between countries and the factors behind the country clustering both in science education and more generally.

An imbalance in cluster sizes does not lead to notable loss of power in cross-sectional, stepped-wedge cluster randomised trials with a continuous outcome.

PubMed

Kristunas, Caroline A; Smith, Karen L; Gray, Laura J

2017-03-07

The current methodology for sample size calculations for stepped-wedge cluster randomised trials (SW-CRTs) is based on the assumption of equal cluster sizes. However, as is often the case in cluster randomised trials (CRTs), the clusters in SW-CRTs are likely to vary in size, which in other designs of CRT leads to a reduction in power. The effect of an imbalance in cluster size on the power of SW-CRTs has not previously been reported, nor what an appropriate adjustment to the sample size calculation should be to allow for any imbalance. We aimed to assess the impact of an imbalance in cluster size on the power of a cross-sectional SW-CRT and recommend a method for calculating the sample size of a SW-CRT when there is an imbalance in cluster size. The effect of varying degrees of imbalance in cluster size on the power of SW-CRTs was investigated using simulations. The sample size was calculated using both the standard method and two proposed adjusted design effects (DEs), based on those suggested for CRTs with unequal cluster sizes. The data were analysed using generalised estimating equations with an exchangeable correlation matrix and robust standard errors. An imbalance in cluster size was not found to have a notable effect on the power of SW-CRTs. The two proposed adjusted DEs resulted in trials that were generally considerably over-powered. We recommend that the standard method of sample size calculation for SW-CRTs be used, provided that the assumptions of the method hold. However, it would be beneficial to investigate, through simulation, what effect the maximum likely amount of inequality in cluster sizes would be on the power of the trial and whether any inflation of the sample size would be required.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Evaluating the Diagnostic Validity of a Facet-Based Formative Assessment System

ERIC Educational Resources Information Center

DeBarger, Angela Haydel; DiBello, Louis; Minstrell, Jim; Feng, Mingyu; Stout, William; Pellegrino, James; Haertel, Geneva; Harris, Christopher; Ructinger, Liliana

2011-01-01

This paper describes methods for an alignment study and psychometric analyses of a formative assessment system, Diagnoser Tools for physics. Diagnoser Tools begin with facet clusters as the interpretive framework for designing questions and instructional activities. Thus each question in the diagnostic assessments includes distractors that…

Profiling Learners' Achievement Goals when Completing Academic Essays

ERIC Educational Resources Information Center

Ng, Chi-Hung Clarence

2009-01-01

This study explored adult learners' goal profiles in relation to the completion of a compulsory academic essay. Based on learners' scores on items assessing mastery, performance-approach, and work-avoidance goals, cluster analyses produced three distinct categories of learners: performance-focused, work-avoidant, and multiple-goal learners. These…

Empirically-Derived MCMI-III Personality Profiles of Incarcerated Female Substance Abusers.

ERIC Educational Resources Information Center

Grabarek, Joanna K.; Bourke, Michael L.; Van Hasselt, Vincent B.

2002-01-01

In the present study, the Millon Clinical Multiaxial Inventory- III (MCMI-III) was administered to 210 female inmates in a jail-based substance abuse prevention program. Analyses resulted in the following three cluster profiles: "normal" (no significant elevations), narcissistic, and antisocial. Hypotheses regarding the personality…

Adult Developmental Dyslexia in a Shallow Orthography: Are There Subgroups?

ERIC Educational Resources Information Center

Laasonen, Marja; Service, Elisabet; Lipsanen, Jari; Virsu, Veijo

2012-01-01

The existence and stability of subgroups among adult dyslexic readers of a shallow orthography was explored by comparing three different cluster analyses based on previously suggested combinations of two variables. These were oral reading speed versus accuracy, word versus pseudoword reading speed, and phonological awareness versus rapid naming.…

Effects of the X:IT smoking intervention: a school-based cluster randomized trial.

PubMed

Andersen, Anette; Krølner, Rikker; Bast, Lotus Sofie; Thygesen, Lau Caspar; Due, Pernille

2015-12-01

Uptake of smoking in adolescence is still of major public health concern. Evaluations of school-based programmes for smoking prevention show mixed results. The aim of this study was to examine the effect of X:IT, a multi-component school-based programme to prevent adolescent smoking. Data from a Danish cluster randomized trial included 4041 year-7 students (mean age: 12.5) from 51 intervention and 43 control schools. Outcome measure 'current smoking' was dichotomized into smoking daily, weekly, monthly or more seldom vs do not smoke. Analyses were adjusted for baseline covariates: sex, family socioeconomic position (SEP), best friend's smoking and parental smoking. We performed multilevel, logistic regression analyses of available cases and intention-to-treat (ITT) analyses, replacing missing outcome values by multiple imputation. At baseline, 4.7% and 6.8% of the students at the intervention and the control schools smoked, respectively. After 1 year of the intervention, the prevalence was 7.9% and 10.7%, respectively. At follow-up, 553 students (13.7%) did not answer the question on smoking. Available case analyses: crude odds ratios (OR) for smoking at intervention schools compared with control schools: 0.65 (0.48-0.88) and adjusted: 0.70 (0.47-1.04). ITT analyses: crude OR for smoking at intervention schools compared with control schools: 0.67 (0.50-0.89) and adjusted: 0.61 (0.45-0.82). Students at intervention schools had a lower risk of smoking after a year of intervention in year 7. This multi-component intervention involving educational, parental and context-related intervention components seems to be efficient in lowering or postponing smoking uptake in Danish adolescents. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Transmission clustering among newly diagnosed HIV patients in Chicago, 2008 to 2011: using phylogenetics to expand knowledge of regional HIV transmission patterns

PubMed Central

Lubelchek, Ronald J.; Hoehnen, Sarah C.; Hotton, Anna L.; Kincaid, Stacey L.; Barker, David E.; French, Audrey L.

2014-01-01

Introduction HIV transmission cluster analyses can inform HIV prevention efforts. We describe the first such assessment for transmission clustering among HIV patients in Chicago. Methods We performed transmission cluster analyses using HIV pol sequences from newly diagnosed patients presenting to Chicago’s largest HIV clinic between 2008 and 2011. We compared sequences via progressive pairwise alignment, using neighbor joining to construct an un-rooted phylogenetic tree. We defined clusters as >2 sequences among which each sequence had at least one partner within a genetic distance of ≤ 1.5%. We used multivariable regression to examine factors associated with clustering and used geospatial analysis to assess geographic proximity of phylogenetically clustered patients. Results We compared sequences from 920 patients; median age 35 years; 75% male; 67% Black, 23% Hispanic; 8% had a Rapid Plasma Reagin (RPR) titer ≥ 1:16 concurrent with their HIV diagnosis. We had HIV transmission risk data for 54%; 43% identified as men who have sex with men (MSM). Phylogenetic analysis demonstrated 123 patients (13%) grouped into 26 clusters, the largest having 20 members. In multivariable regression, age < 25, Black race, MSM status, male gender, higher HIV viral load, and RPR ≥ 1:16 associated with clustering. We did not observe geographic grouping of genetically clustered patients. Discussion Our results demonstrate high rates of HIV transmission clustering, without local geographic foci, among young Black MSM in Chicago. Applied prospectively, phylogenetic analyses could guide prevention efforts and help break the cycle of transmission. PMID:25321182

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.

Are There Subtypes of Panic Disorder? An Interpersonal Perspective

PubMed Central

Zilcha-Mano, Sigal; McCarthy, Kevin S.; Dinger, Ulrike; Chambless, Dianne L.; Milrod, Barbara L.; Kunik, Lauren; Barber, Jacques P.

2015-01-01

Objective Panic disorder (PD) is associated with significant personal, social, and economic costs. However, little is known about specific interpersonal dysfunctions that characterize the PD population. The current study systematically examined these interpersonal dysfunctions. Method The present analyses included 194 patients with PD out of a sample of 201 who were randomized to cognitive-behavioral therapy, panic-focused psychodynamic psychotherapy, or applied relaxation training. Interpersonal dysfunction was measured using the Inventory of Interpersonal Problems–Circumplex (Horowitz, Alden, Wiggins, & Pincus, 2000). Results Individuals with PD reported greater levels of interpersonal distress than that of a normative cohort (especially when PD was accompanied by agoraphobia), but lower than that of a cohort of patients with major depression. There was no single interpersonal profile that characterized PD patients. Symptom-based clusters (with versus without agoraphobia) could not be discriminated on core or central interpersonal problems. Rather, as revealed by cluster analysis based on the pathoplasticity framework, there were two empirically derived interpersonal clusters among PD patients which were not accounted for by symptom severity and were opposite in nature: domineering-intrusive and nonassertive. The empirically derived interpersonal clusters appear to be of clinical utility in predicting alliance development throughout treatment: While the domineering-intrusive cluster did not show any changes in the alliance throughout treatment, the non-assertive cluster showed a process of significant strengthening of the alliance. Conclusions Empirically derived interpersonal clusters in PD provide clinically useful and non-redundant information about individuals with PD. PMID:26030762

Detailed analysis of the supermarket task included on the Japanese version of the Rapid Dementia Screening Test.

PubMed

Moriyama, Yasushi; Yoshino, Aihide; Muramatsu, Taro; Mimura, Masaru

2017-05-01

The supermarket task, which is included in the Japanese version of the Rapid Dementia Screening Test, requires the quick (1 min) generation of words for things that can be bought in a supermarket. Cluster size and switches are investigated during this task. We investigated how the severity of dementia related to cluster size and switches on the supermarket task in patients with Alzheimer's disease. We administered the Japanese version of the Rapid Dementia Screening Test to 250 patients with very mild to severe Alzheimer's disease and to 49 healthy volunteers. Patients had Mini-Mental State Examination scores from 12 to 26 and Clinical Dementia Rating scale scores from 0.5 to 3. Patients were divided into four groups based on their Clinical Dementia Rating score (0.5, 1, 2, 3). We performed statistical analyses between the four groups and control subjects based on cluster size and switch scores on the supermarket task. The score for cluster size and switches deteriorated according to the severity of dementia. Moreover, for subjects with a Clinical Dementia Rating score of 0.5, cluster size was impaired, but switches were intact. Our findings indicate that the scores for cluster size and switches on the supermarket task may be useful for detecting the severity of symptoms of dementia in patients with Alzheimer's disease. © 2016 The Authors. Psychogeriatrics © 2016 Japanese Psychogeriatric Society.

Identifying and characterizing hepatitis C virus hotspots in Massachusetts: a spatial epidemiological approach.

PubMed

Stopka, Thomas J; Goulart, Michael A; Meyers, David J; Hutcheson, Marga; Barton, Kerri; Onofrey, Shauna; Church, Daniel; Donahue, Ashley; Chui, Kenneth K H

2017-04-20

Hepatitis C virus (HCV) infections have increased during the past decade but little is known about geographic clustering patterns. We used a unique analytical approach, combining geographic information systems (GIS), spatial epidemiology, and statistical modeling to identify and characterize HCV hotspots, statistically significant clusters of census tracts with elevated HCV counts and rates. We compiled sociodemographic and HCV surveillance data (n = 99,780 cases) for Massachusetts census tracts (n = 1464) from 2002 to 2013. We used a five-step spatial epidemiological approach, calculating incremental spatial autocorrelations and Getis-Ord Gi* statistics to identify clusters. We conducted logistic regression analyses to determine factors associated with the HCV hotspots. We identified nine HCV clusters, with the largest in Boston, New Bedford/Fall River, Worcester, and Springfield (p < 0.05). In multivariable analyses, we found that HCV hotspots were independently and positively associated with the percent of the population that was Hispanic (adjusted odds ratio [AOR]: 1.07; 95% confidence interval [CI]: 1.04, 1.09) and the percent of households receiving food stamps (AOR: 1.83; 95% CI: 1.22, 2.74). HCV hotspots were independently and negatively associated with the percent of the population that were high school graduates or higher (AOR: 0.91; 95% CI: 0.89, 0.93) and the percent of the population in the "other" race/ethnicity category (AOR: 0.88; 95% CI: 0.85, 0.91). We identified locations where HCV clusters were a concern, and where enhanced HCV prevention, treatment, and care can help combat the HCV epidemic in Massachusetts. GIS, spatial epidemiological and statistical analyses provided a rigorous approach to identify hotspot clusters of disease, which can inform public health policy and intervention targeting. Further studies that incorporate spatiotemporal cluster analyses, Bayesian spatial and geostatistical models, spatially weighted regression analyses, and assessment of associations between HCV clustering and the built environment are needed to expand upon our combined spatial epidemiological and statistical methods.

Generalizing MOND to explain the missing mass in galaxy clusters

NASA Astrophysics Data System (ADS)

Hodson, Alistair O.; Zhao, Hongsheng

2017-02-01

Context. MOdified Newtonian Dynamics (MOND) is a gravitational framework designed to explain the astronomical observations in the Universe without the inclusion of particle dark matter. MOND, in its current form, cannot explain the missing mass in galaxy clusters without the inclusion of some extra mass, be it in the form of neutrinos or non-luminous baryonic matter. We investigate whether the MOND framework can be generalized to account for the missing mass in galaxy clusters by boosting gravity in high gravitational potential regions. We examine and review Extended MOND (EMOND), which was designed to increase the MOND scale acceleration in high potential regions, thereby boosting the gravity in clusters. Aims: We seek to investigate galaxy cluster mass profiles in the context of MOND with the primary aim at explaining the missing mass problem fully without the need for dark matter. Methods: Using the assumption that the clusters are in hydrostatic equilibrium, we can compute the dynamical mass of each cluster and compare the result to the predicted mass of the EMOND formalism. Results: We find that EMOND has some success in fitting some clusters, but overall has issues when trying to explain the mass deficit fully. We also investigate an empirical relation to solve the cluster problem, which is found by analysing the cluster data and is based on the MOND paradigm. We discuss the limitations in the text.

Beverage consumption patterns of Canadian adults aged 19 to 65 years.

PubMed

Nikpartow, Nooshin; Danyliw, Adrienne D; Whiting, Susan J; Lim, Hyun J; Vatanparast, Hassanali

2012-12-01

To investigate the beverage intake patterns of Canadian adults and explore characteristics of participants in different beverage clusters. Analyses of nationally representative data with cross-sectional complex stratified design. Canadian Community Health Survey, Cycle 2.2 (2004). A total of 14 277 participants aged 19-65 years, in whom dietary intake was assessed using a single 24 h recall, were included in the study. After determining total intake and the contribution of beverages to total energy intake among age/sex groups, cluster analysis (K-means method) was used to classify males and females into distinct clusters based on the dominant pattern of beverage intakes. To test differences across clusters, χ2 tests and 95 % confidence intervals of the mean intakes were used. Six beverage clusters in women and seven beverage clusters in men were identified. 'Sugar-sweetened' beverage clusters - regular soft drinks and fruit drinks - as well as a 'beer' cluster, appeared for both men and women. No 'milk' cluster appeared among women. The mean consumption of the dominant beverage in each cluster was higher among men than women. The 'soft drink' cluster in men had the lowest proportion of the higher levels of education, and in women the highest proportion of inactivity, compared with other beverage clusters. Patterns of beverage intake in Canadian women indicate high consumption of sugar-sweetened beverages particularly fruit drinks, low intake of milk and high intake of beer. These patterns in women have implications for poor bone health, risk of obesity and other morbidities.

Typology of people with first-episode psychosis.

PubMed

Subramaniam, Mythily; Zheng, Huili; Soh, Pauline; Poon, Lye Yin; Vaingankar, Janhavi A; Chong, Siow Ann; Verma, Swapna

2016-08-01

The aim of the current study was to create a typology of patients with first-episode psychosis based on sociodemographic and clinical characteristics, service use and outcomes using cluster analysis. Data from all respondents who were accepted into the Early Psychosis Intervention Programme (EPIP), Singapore from 2007 to 2011 were analysed. A two-step clustering method was carried out to classify the patients into distinct clusters. Two clusters were identified. Cluster 1 comprised largely of younger people with mean age of 25.5 (6.0) years at treatment contact, who were predominantly male (55.3%), single (98.3%) and living with parents (86.3%). Cluster 1 had a higher proportion of people diagnosed with the schizophrenia spectrum disorder (71.4%) and with a positive family history of psychiatric illness. Patients in cluster 2 were generally older with a mean age of 33.6 (4.7) years and the majority were women (74.2%). Cluster 1 had people with higher Positive and Negative Syndrome Scale (PANSS) scores at baseline as compared with cluster 2. After a 1-year follow up, their scores were still poorer than their counterparts in cluster 2, especially for PANSS negative score. The functioning level of people in cluster 1 showed less improvement than the people in cluster 2 after a year of treatment. There is a compelling need to develop new therapies and intensively treat young people presenting with psychosis as this group tends to have poorer outcomes even after 1 year of treatment. © 2014 Wiley Publishing Asia Pty Ltd.

Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

PubMed Central

Villandre, Luc; Günthard, Huldrych F.; Kouyos, Roger; Stadler, Tanja

2016-01-01

Background Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters. Methods The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects’ island membership indices and transmission cluster membership indices with the adjusted Rand index. Results and Conclusion Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network communities correspond to clades in the phylogeny is their main drawback. Understanding the link between transmission clusters and communities in sexual contact networks could help inform policymaking to curb HIV incidence in MSMs. PMID:26863322

Space-Time Analysis of Testicular Cancer Clusters Using Residential Histories: A Case-Control Study in Denmark

PubMed Central

Sloan, Chantel D.; Nordsborg, Rikke B.; Jacquez, Geoffrey M.; Raaschou-Nielsen, Ole; Meliker, Jaymie R.

2015-01-01

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population. PMID:25756204

Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

PubMed

Sloan, Chantel D; Nordsborg, Rikke B; Jacquez, Geoffrey M; Raaschou-Nielsen, Ole; Meliker, Jaymie R

2015-01-01

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population.

Sensitivity and specificity of subacute computerized neurocognitive testing and symptom evaluation in predicting outcomes after sports-related concussion.

PubMed

Lau, Brian C; Collins, Michael W; Lovell, Mark R

2011-06-01

Concussions affect an estimated 136 000 high school athletes yearly. Computerized neurocognitive testing has been shown to be appropriately sensitive and specific in diagnosing concussions, but no studies have assessed its utility to predict length of recovery. Determining prognosis during subacute recovery after sports concussion will help clinicians more confidently address return-to-play and academic decisions. To quantify the prognostic ability of computerized neurocognitive testing in combination with symptoms during the subacute recovery phase from sports-related concussion. Cohort study (prognosis); Level of evidence, 2. In sum, 108 male high school football athletes completed a computer-based neurocognitive test battery within 2.23 days of injury and were followed until returned to play as set by international guidelines. Athletes were grouped into protracted recovery (>14 days; n = 50) or short-recovery (≤14 days; n = 58). Separate discriminant function analyses were performed using total symptom score on Post-Concussion Symptom Scale, symptom clusters (migraine, cognitive, sleep, neuropsychiatric), and Immediate Postconcussion Assessment and Cognitive Testing neurocognitive scores (verbal memory, visual memory, reaction time, processing speed). Multiple discriminant function analyses revealed that the combination of 4 symptom clusters and 4 neurocognitive composite scores had the highest sensitivity (65.22%), specificity (80.36%), positive predictive value (73.17%), and negative predictive value (73.80%) in predicting protracted recovery. Discriminant function analyses of total symptoms on the Post-Concussion Symptom Scale alone had a sensitivity of 40.81%; specificity, 79.31%; positive predictive value, 62.50%; and negative predictive value, 61.33%. The 4 symptom clusters alone discriminant function analyses had a sensitivity of 46.94%; specificity, 77.20%; positive predictive value, 63.90%; and negative predictive value, 62.86%. Discriminant function analyses of the 4 computerized neurocognitive scores alone had a sensitivity of 53.20%; specificity, 75.44%; positive predictive value, 64.10%; and negative predictive value, 66.15%. The use of computerized neurocognitive testing in conjunction with symptom clusters results improves sensitivity, specificity, positive predictive value, and negative predictive value of predicting protracted recovery compared with each used alone. There is also a net increase in sensitivity of 24.41% when using neurocognitive testing and symptom clusters together compared with using total symptoms on Post-Concussion Symptom Scale alone.

Structure and substructure analysis of DAFT/FADA galaxy clusters in the [0.4-0.9] redshift range

NASA Astrophysics Data System (ADS)

Guennou, L.; Adami, C.; Durret, F.; Lima Neto, G. B.; Ulmer, M. P.; Clowe, D.; LeBrun, V.; Martinet, N.; Allam, S.; Annis, J.; Basa, S.; Benoist, C.; Biviano, A.; Cappi, A.; Cypriano, E. S.; Gavazzi, R.; Halliday, C.; Ilbert, O.; Jullo, E.; Just, D.; Limousin, M.; Márquez, I.; Mazure, A.; Murphy, K. J.; Plana, H.; Rostagni, F.; Russeil, D.; Schirmer, M.; Slezak, E.; Tucker, D.; Zaritsky, D.; Ziegler, B.

2014-01-01

Context. The DAFT/FADA survey is based on the study of ~90 rich (masses found in the literature >2 × 1014 M⊙) and moderately distant clusters (redshifts 0.4 < z < 0.9), all with HST imaging data available. This survey has two main objectives: to constrain dark energy (DE) using weak lensing tomography on galaxy clusters and to build a database (deep multi-band imaging allowing photometric redshift estimates, spectroscopic data, X-ray data) of rich distant clusters to study their properties. Aims: We analyse the structures of all the clusters in the DAFT/FADA survey for which XMM-Newton and/or a sufficient number of galaxy redshifts in the cluster range are available, with the aim of detecting substructures and evidence for merging events. These properties are discussed in the framework of standard cold dark matter (ΛCDM) cosmology. Methods: In X-rays, we analysed the XMM-Newton data available, fit a β-model, and subtracted it to identify residuals. We used Chandra data, when available, to identify point sources. In the optical, we applied a Serna & Gerbal (SG) analysis to clusters with at least 15 spectroscopic galaxy redshifts available in the cluster range. We discuss the substructure detection efficiencies of both methods. Results: XMM-Newton data were available for 32 clusters, for which we derive the X-ray luminosity and a global X-ray temperature for 25 of them. For 23 clusters we were able to fit the X-ray emissivity with a β-model and subtract it to detect substructures in the X-ray gas. A dynamical analysis based on the SG method was applied to the clusters having at least 15 spectroscopic galaxy redshifts in the cluster range: 18 X-ray clusters and 11 clusters with no X-ray data. The choice of a minimum number of 15 redshifts implies that only major substructures will be detected. Ten substructures were detected both in X-rays and by the SG method. Most of the substructures detected both in X-rays and with the SG method are probably at their first cluster pericentre approach and are relatively recent infalls. We also find hints of a decreasing X-ray gas density profile core radius with redshift. Conclusions: The percentage of mass included in substructures was found to be roughly constant with redshift values of 5-15%, in agreement both with the general CDM framework and with the results of numerical simulations. Galaxies in substructures show the same general behaviour as regular cluster galaxies; however, in substructures, there is a deficiency of both late type and old stellar population galaxies. Late type galaxies with recent bursts of star formation seem to be missing in the substructures close to the bottom of the host cluster potential well. However, our sample would need to be increased to allow a more robust analysis. Tables 1, 2, 4 and Appendices A-C are available in electronic form at http://www.aanda.org

Brain structure and function correlates of cognitive subtypes in schizophrenia.

PubMed

Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan

2015-10-30

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Business and Marketing Cluster. Task Analyses.

ERIC Educational Resources Information Center

Henrico County Public Schools, Glen Allen, VA. Virginia Vocational Curriculum and Resource Center.

Developed in Virginia, this publication contains task analysis guides to support selected tech prep programs that prepare students for careers in the business and marketing cluster. Guides are included for accounting systems, legal systems administration, office systems technology, and retail marketing. Each task analyses guide has the following…

Comprehensive Genomic Analyses of the OM43 Clade, Including a Novel Species from the Red Sea, Indicate Ecotype Differentiation among Marine Methylotrophs

PubMed Central

Jimenez-Infante, Francy; Ngugi, David Kamanda; Vinu, Manikandan; Alam, Intikhab; Kamau, Allan Anthony; Blom, Jochen; Bajic, Vladimir B.

2015-01-01

The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs that play important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (here designated MBRS-H7) from the ultraoligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species that forms a distinct cluster together with isolate KB13 from Hawaii (Hawaii-Red Sea [H-RS] cluster) that is separate from the cluster represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S-23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low-chlorophyll and/or high-temperature provinces for the H-RS cluster but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of the H-RS cluster include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely, the existence of the NADH:quinone oxidoreductase complex I (NUO) system in the H-RS cluster and the nonhomologous NADH:quinone oxidoreductase (NQR) system in the HTCC2181 cluster, which might have implications for their overall energetic yields. PMID:26655752

Genetic structure and demographic history of the endangered and endemic schizothoracine fish Gymnodiptychus pachycheilus in Qinghai-Tibetan Plateau.

PubMed

Su, Junhu; Ji, Weihong; Wei, Yanming; Zhang, Yanping; Gleeson, Dianne M; Lou, Zhongyu; Ren, Jing

2014-08-01

The endangered schizothoracine fish Gymnodiptychus pachycheilus is endemic to the Qinghai-Tibetan Plateau (QTP), but very little genetic information is available for this species. Here, we accessed the current genetic divergence of G. pachycheilus population to evaluate their distributions modulated by contemporary and historical processes. Population structure and demographic history were assessed by analyzing 1811-base pairs of mitochondrial DNA from 61 individuals across a large proportion of its geographic range. Our results revealed low nucleotide diversity, suggesting severe historical bottleneck events. Analyses of molecular variance and the conventional population statistic FST (0.0435, P = 0.0215) confirmed weak genetic structure. The monophyly of G. pachycheilus was statistically well-supported, while two divergent evolutionary clusters were identified by phylogenetic analyses, suggesting a microgeographic population structure. The consistent scenario of recent population expansion of two clusters was identified based on several complementary analyses of demographic history (0.096 Ma and 0.15 Ma). This genetic divergence and evolutionary process are likely to have resulted from a series of drainage arrangements triggered by the historical tectonic events of the region. The results obtained here provide the first insights into the evolutionary history and genetic status of this little-known fish.

A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

PubMed

Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

2013-12-01

During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Listeria booriae sp. nov. and Listeria newyorkensis sp. nov., from food processing environments in the USA.

PubMed

Weller, Daniel; Andrus, Alexis; Wiedmann, Martin; den Bakker, Henk C

2015-01-01

Sampling of seafood and dairy processing facilities in the north-eastern USA produced 18 isolates of Listeria spp. that could not be identified at the species-level using traditional phenotypic and genotypic identification methods. Results of phenotypic and genotypic analyses suggested that the isolates represent two novel species with an average nucleotide blast identity of less than 92% with previously described species of the genus Listeria. Phylogenetic analyses based on whole genome sequences, 16S rRNA gene and sigB gene sequences confirmed that the isolates represented by type strain FSL M6-0635(T) and FSL A5-0209 cluster phylogenetically with Listeria cornellensis. Phylogenetic analyses also showed that the isolates represented by type strain FSL A5-0281(T) cluster phylogenetically with Listeria riparia. The name Listeria booriae sp. nov. is proposed for the species represented by type strain FSL A5-0281(T) ( =DSM 28860(T) =LMG 28311(T)), and the name Listeria newyorkensis sp. nov. is proposed for the species represented by type strain FSL M6-0635(T) ( =DSM 28861(T) =LMG 28310(T)). Phenotypic and genotypic analyses suggest that neither species is pathogenic. © 2015 IUMS.

Increased Symptom Reporting in Young Athletes Based on History of Previous Concussions.

PubMed

Moser, Rosemarie Scolaro; Schatz, Philip

2017-01-01

Research documents increased symptoms in adolescents with a history of two or more concussions. This study examined baseline evaluations of 2,526 younger athletes, ages 10 to 14. Between-groups analyses examined Post Concussion Symptom Scale symptoms by concussion history group (None, One, Two+) and clusters of Physical, Cognitive, Emotional, and Sleep symptoms. Healthy younger athletes with a concussion history reported greater physical, emotional, and sleep-related symptoms than those with no history of concussion, with a greater endorsement in physical/sleep symptom clusters. Findings suggest younger athletes with a history of multiple concussions may experience residual symptoms.

A singular value decomposition approach for improved taxonomic classification of biological sequences

PubMed Central

2011-01-01

Background Singular value decomposition (SVD) is a powerful technique for information retrieval; it helps uncover relationships between elements that are not prima facie related. SVD was initially developed to reduce the time needed for information retrieval and analysis of very large data sets in the complex internet environment. Since information retrieval from large-scale genome and proteome data sets has a similar level of complexity, SVD-based methods could also facilitate data analysis in this research area. Results We found that SVD applied to amino acid sequences demonstrates relationships and provides a basis for producing clusters and cladograms, demonstrating evolutionary relatedness of species that correlates well with Linnaean taxonomy. The choice of a reasonable number of singular values is crucial for SVD-based studies. We found that fewer singular values are needed to produce biologically significant clusters when SVD is employed. Subsequently, we developed a method to determine the lowest number of singular values and fewest clusters needed to guarantee biological significance; this system was developed and validated by comparison with Linnaean taxonomic classification. Conclusions By using SVD, we can reduce uncertainty concerning the appropriate rank value necessary to perform accurate information retrieval analyses. In tests, clusters that we developed with SVD perfectly matched what was expected based on Linnaean taxonomy. PMID:22369633

Variation in the fumonisin biosynthetic gene cluster in fumonisin-producing and nonproducing black aspergilli.

PubMed

Susca, Antonia; Proctor, Robert H; Butchko, Robert A E; Haidukowski, Miriam; Stea, Gaetano; Logrieco, Antonio; Moretti, Antonio

2014-12-01

The ability to produce fumonisin mycotoxins varies among members of the black aspergilli. Previously, analyses of selected genes in the fumonisin biosynthetic gene (fum) cluster in black aspergilli from California grapes indicated that fumonisin-nonproducing isolates of Aspergillus welwitschiae lack six fum genes, but nonproducing isolates of Aspergillus niger do not. In the current study, analyses of black aspergilli from grapes from the Mediterranean Basin indicate that the genomic context of the fum cluster is the same in isolates of A. niger and A. welwitschiae regardless of fumonisin-production ability and that full-length clusters occur in producing isolates of both species and nonproducing isolates of A. niger. In contrast, the cluster has undergone an eight-gene deletion in fumonisin-nonproducing isolates of A. welwitschiae. Phylogenetic analyses suggest each species consists of a mixed population of fumonisin-producing and nonproducing individuals, and that existence of both production phenotypes may provide a selective advantage to these species. Differences in gene content of fum cluster homologues and phylogenetic relationships of fum genes suggest that the mutation(s) responsible for the nonproduction phenotype differs, and therefore arose independently, in the two species. Partial fum cluster homologues were also identified in genome sequences of four other black Aspergillus species. Gene content of these partial clusters and phylogenetic relationships of fum sequences indicate that non-random partial deletion of the cluster has occurred multiple times among the species. This in turn suggests that an intact cluster and fumonisin production were once more widespread among black aspergilli. Copyright © 2014 Elsevier Inc. All rights reserved.

Inferring Phylogenetic Relationships of Indian Citron (Citrus medica L.) based on rbcL and matK Sequences of Chloroplast DNA.

PubMed

Uchoi, Ajit; Malik, Surendra Kumar; Choudhary, Ravish; Kumar, Susheel; Rohini, M R; Pal, Digvender; Ercisli, Sezai; Chaudhury, Rekha

2016-06-01

Phylogenetic relationships of Indian Citron (Citrus medica L.) with other important Citrus species have been inferred through sequence analyses of rbcL and matK gene region of chloroplast DNA. The study was based on 23 accessions of Citrus genotypes representing 15 taxa of Indian Citrus, collected from wild, semi-wild, and domesticated stocks. The phylogeny was inferred using the maximum parsimony (MP) and neighbor-joining (NJ) methods. Both MP and NJ trees separated all the 23 accessions of Citrus into five distinct clusters. The chloroplast DNA (cpDNA) analysis based on rbcL and matK sequence data carried out in Indian taxa of Citrus was useful in differentiating all the true species and species/varieties of probable hybrid origin in distinct clusters or groups. Sequence analysis based on rbcL and matK gene provided unambiguous identification and disposition of true species like C. maxima, C. medica, C. reticulata, and related hybrids/cultivars. The separation of C. maxima, C. medica, and C. reticulata in distinct clusters or sub-clusters supports their distinctiveness as the basic species of edible Citrus. However, the cpDNA sequence analysis of rbcL and matK gene could not find any clear cut differentiation between subgenera Citrus and Papeda as proposed in Swingle's system of classification.

Improving guideline concordance in multidisciplinary teams: preliminary results of a cluster-randomized trial evaluating the effect of a web-based audit and feedback intervention with outreach visits

PubMed Central

van Engen-Verheul, Mariëtte M.; Gude, Wouter T.; van der Veer, Sabine N.; Kemps, Hareld M.C.; Jaspers, Monique M.W.; de Keizer, Nicolette F.; Peek, Niels

2015-01-01

Despite their widespread use, audit and feedback (A&F) interventions show variable effectiveness on improving professional performance. Based on known facilitators of successful A&F interventions, we developed a web-based A&F intervention with indicator-based performance feedback, benchmark information, action planning and outreach visits. The goal of the intervention was to engage with multidisciplinary teams to overcome barriers to guideline concordance and to improve overall team performance in the field of cardiac rehabilitation (CR). To assess its effectiveness we conducted a cluster-randomized trial in 18 CR clinics (14,847 patients) already working with computerized decision support (CDS). Our preliminary results showed no increase in concordance with guideline recommendations regarding prescription of CR therapies. Future analyses will investigate whether our intervention did improve team performance on other quality indicators. PMID:26958310

[Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

PubMed

Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

2016-09-01

To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire(SGRQ) score, acute exacerbation in the past one year, PEF variability and allergic dermatitis (P<0.05). (2) Four clusters were also identified by two-step cluster analysis as followings, cluster 1, COPD patients with moderate to severe airflow limitation; cluster 2, asthma and COPD patients with heavy smoking, airflow limitation and increased airways reversibility; cluster 3, patients having less smoking and normal pulmonary function with wheezing but no chronic cough; cluster 4, chronic bronchitis patients with normal pulmonary function and chronic cough. Significant differences were revealed regarding gender distribution, respiratory symptoms, pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, MMEF% pred, DLCO/VA% pred, RV% pred, PEF variability, total serum IgE level, cumulative tobacco cigarette consumption (pack-years), and SGRQ score (P<0.05). By different cluster analyses, distinct clinical phenotypes of chronic airway diseases are identified. Thus, individualized treatments may guide doctors to provide based on different phenotypes.

Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses

ERIC Educational Resources Information Center

Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu

2011-01-01

Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…

Analysis of calibrated seafloor backscatter for habitat classification methodology and case study of 158 spots in the Bay of Biscay and Celtic Sea

NASA Astrophysics Data System (ADS)

Fezzani, Ridha; Berger, Laurent

2018-06-01

An automated signal-based method was developed in order to analyse the seafloor backscatter data logged by calibrated multibeam echosounder. The processing consists first in the clustering of each survey sub-area into a small number of homogeneous sediment types, based on the backscatter average level at one or several incidence angles. Second, it uses their local average angular response to extract discriminant descriptors, obtained by fitting the field data to the Generic Seafloor Acoustic Backscatter parametric model. Third, the descriptors are used for seafloor type classification. The method was tested on the multi-year data recorded by a calibrated 90-kHz Simrad ME70 multibeam sonar operated in the Bay of Biscay, France and Celtic Sea, Ireland. It was applied for seafloor-type classification into 12 classes, to a dataset of 158 spots surveyed for demersal and benthic fauna study and monitoring. Qualitative analyses and classified clusters using extracted parameters show a good discriminatory potential, indicating the robustness of this approach.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

The variety of primary healthcare organisations in Australia: a taxonomy.

PubMed

Rodwell, John; Gulyas, Andre

2013-04-08

Healthcare policy appears to treat healthcare organisations as being homogenous, despite evidence that they vary considerably. This study develops a taxonomy of primary health care practices using characteristics associated with the job satisfaction of general medical practitioners (GPs) and the practices. The study used data from 3,662 survey respondents who were GPs in the 2009 wave of the MABEL survey. Cluster analyses were used to determine natural groups of medical practices based on multidimensional characteristics. Seven configurations of primary health care practices emerged from multivariate cluster analyses: optimised team, independent craft, reactive, winding down, classic, practitioner flexible, and scale efficiency. This taxonomy of configurations moves beyond simplistic categorisations such as geographic location and highlights the complexity of primary health care organisations in Australia. Health policy, workforce and procedure interventions informed by taxonomies can engage the diversity of primary health care practices.

Natural-product-derived fragments for fragment-based ligand discovery

NASA Astrophysics Data System (ADS)

Over, Björn; Wetzel, Stefan; Grütter, Christian; Nakai, Yasushi; Renner, Steffen; Rauh, Daniel; Waldmann, Herbert

2013-01-01

Fragment-based ligand and drug discovery predominantly employs sp2-rich compounds covering well-explored regions of chemical space. Despite the ease with which such fragments can be coupled, this focus on flat compounds is widely cited as contributing to the attrition rate of the drug discovery process. In contrast, biologically validated natural products are rich in stereogenic centres and populate areas of chemical space not occupied by average synthetic molecules. Here, we have analysed more than 180,000 natural product structures to arrive at 2,000 clusters of natural-product-derived fragments with high structural diversity, which resemble natural scaffolds and are rich in sp3-configured centres. The structures of the cluster centres differ from previously explored fragment libraries, but for nearly half of the clusters representative members are commercially available. We validate their usefulness for the discovery of novel ligand and inhibitor types by means of protein X-ray crystallography and the identification of novel stabilizers of inactive conformations of p38α MAP kinase and of inhibitors of several phosphatases.

Home-based smoking prevention program Smoke-free Kids on smoking-related cognitions: Secondary outcomes from a cluster randomized controlled trial.

PubMed

Hiemstra, Marieke; Engels, Rutger C M E; van Schayck, Onno C P; Otten, Roy

2016-01-01

The home-based smoking prevention programme 'Smoke-free Kids' did not have an effect on primary outcome smoking initiation. A possible explanation may be that the programme has a delayed effect. The aim of this study was to evaluate the effects on the development of important precursors of smoking: smoking-related cognitions. We used a cluster randomised controlled trial in 9- to 11-year-old children and their mothers. The intervention condition received five activity modules, including a communication sheet for mothers, by mail at four-week intervals. The control condition received a fact-based programme. Secondary outcomes were attitudes, self-efficacy and social norms. Latent growth curves analyses were used to calculate the development of cognitions over time. Subsequently, path modelling was used to estimate the programme effects on the initial level and growth of each cognition. Analyses were performed on 1398 never-smoking children at baseline. Results showed that for children in the intervention condition, perceived maternal norms increased less strongly as compared to the control condition (β = -.10, p = .03). No effects were found for the other cognitions. Based on the limited effects, we do not assume that the programme will have a delayed effect on smoking behaviour later during adolescence.

Star cluster formation history along the minor axis of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Piatti, Andrés E.; Cole, Andrew A.; Emptage, Bryn

2018-01-01

We analysed Washington CMT1 photometry of star clusters located along the minor axis of the Large Magellanic Cloud (LMC), from the LMC optical centre up to ∼39° outwards to the North-West. The data base was exploited in order to search for new star cluster candidates, to produce cluster CMDs cleaned from field star contamination and to derive age estimates for a statistically complete cluster sample. We confirmed that 146 star cluster candidates are genuine physical systems, and concluded that an overall ∼30 per cent of catalogued clusters in the surveyed regions are unlikely to be true physical systems. We did not find any new cluster candidates in the outskirts of the LMC (deprojected distance ≳ 8°). The derived ages of the studied clusters are in the range 7.2 < log(t yr-1) ≤ 9.4, with the sole exception of the globular cluster NGC 1786 (log(t yr-1) = 10.10). We also calculated the cluster frequency for each region, from which we confirmed previously proposed outside-in formation scenarios. In addition, we found that the outer LMC fields show a sudden episode of cluster formation (log(t yr-1) ∼7.8-7.9) which continued until log(t yr-1) ∼7.3 only in the outermost LMC region. We link these features to the first pericentre passage of the LMC to the Milky Way (MW), which could have triggered cluster formation due to ram pressure interaction between the LMC and MW halo.

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

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

Samala, Ravi K., E-mail: rsamala@umich.edu; Chan, Heang-Ping; Lu, Yao

Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was furthermore » improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a sensitivity of 85% was achieved at an FP rate of 2.16 per DBT volume. For case-based detection, a sensitivity of 85% was achieved at an FP rate of 0.85 per DBT volume. JAFROC analysis showed a significant improvement in the performance of the current CADe system compared to that of our previous system (p = 0.003). Conclusions: MBSF regularized SART reconstruction enhances MCs. The enhancement in the signals, in combination with properly designed adaptive threshold criteria, effective MC feature analysis, and false positive reduction techniques, leads to a significant improvement in the detection of clustered MCs in DBT.« less

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

USGS Publications Warehouse

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

Gene duplications in prokaryotes can be associated with environmental adaptation

PubMed Central

2010-01-01

Background Gene duplication is a normal evolutionary process. If there is no selective advantage in keeping the duplicated gene, it is usually reduced to a pseudogene and disappears from the genome. However, some paralogs are retained. These gene products are likely to be beneficial to the organism, e.g. in adaptation to new environmental conditions. The aim of our analysis is to investigate the properties of paralog-forming genes in prokaryotes, and to analyse the role of these retained paralogs by relating gene properties to life style of the corresponding prokaryotes. Results Paralogs were identified in a number of prokaryotes, and these paralogs were compared to singletons of persistent orthologs based on functional classification. This showed that the paralogs were associated with for example energy production, cell motility, ion transport, and defence mechanisms. A statistical overrepresentation analysis of gene and protein annotations was based on paralogs of the 200 prokaryotes with the highest fraction of paralog-forming genes. Biclustering of overrepresented gene ontology terms versus species was used to identify clusters of properties associated with clusters of species. The clusters were classified using similarity scores on properties and species to identify interesting clusters, and a subset of clusters were analysed by comparison to literature data. This analysis showed that paralogs often are associated with properties that are important for survival and proliferation of the specific organisms. This includes processes like ion transport, locomotion, chemotaxis and photosynthesis. However, the analysis also showed that the gene ontology terms sometimes were too general, imprecise or even misleading for automatic analysis. Conclusions Properties described by gene ontology terms identified in the overrepresentation analysis are often consistent with individual prokaryote lifestyles and are likely to give a competitive advantage to the organism. Paralogs and singletons dominate different categories of functional classification, where paralogs in particular seem to be associated with processes involving interaction with the environment. PMID:20961426

Gene duplications in prokaryotes can be associated with environmental adaptation.

PubMed

Bratlie, Marit S; Johansen, Jostein; Sherman, Brad T; Huang, Da Wei; Lempicki, Richard A; Drabløs, Finn

2010-10-20

Gene duplication is a normal evolutionary process. If there is no selective advantage in keeping the duplicated gene, it is usually reduced to a pseudogene and disappears from the genome. However, some paralogs are retained. These gene products are likely to be beneficial to the organism, e.g. in adaptation to new environmental conditions. The aim of our analysis is to investigate the properties of paralog-forming genes in prokaryotes, and to analyse the role of these retained paralogs by relating gene properties to life style of the corresponding prokaryotes. Paralogs were identified in a number of prokaryotes, and these paralogs were compared to singletons of persistent orthologs based on functional classification. This showed that the paralogs were associated with for example energy production, cell motility, ion transport, and defence mechanisms. A statistical overrepresentation analysis of gene and protein annotations was based on paralogs of the 200 prokaryotes with the highest fraction of paralog-forming genes. Biclustering of overrepresented gene ontology terms versus species was used to identify clusters of properties associated with clusters of species. The clusters were classified using similarity scores on properties and species to identify interesting clusters, and a subset of clusters were analysed by comparison to literature data. This analysis showed that paralogs often are associated with properties that are important for survival and proliferation of the specific organisms. This includes processes like ion transport, locomotion, chemotaxis and photosynthesis. However, the analysis also showed that the gene ontology terms sometimes were too general, imprecise or even misleading for automatic analysis. Properties described by gene ontology terms identified in the overrepresentation analysis are often consistent with individual prokaryote lifestyles and are likely to give a competitive advantage to the organism. Paralogs and singletons dominate different categories of functional classification, where paralogs in particular seem to be associated with processes involving interaction with the environment.

Occupational risk factors for Wilms' tumor

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

Bunin, G.; Kramer, S.; Nass, C.

A matched case-control study of Wilms' tumor investigated parental occupational risk factors. Cases diagnosed in 1970-1983 were identified through a population-based tumor registry and hospital registries in the Greater Philadelphia area. Controls were selected by random digit dialing and were matched to cases on race, birth date (+/- 3 years), and the area code and exchange of the case's telephone number at diagnosis. Parents of 100 matched pairs were interviewed by telephone. Parents of patients and controls were generally similar in demographic characteristics, except that mothers differed in religion. Published schemes were used to group jobs into clusters of similarmore » exposures and to determine exposures from industry and job title. Analyses were done for preconception, pregnancy, and postnatal time periods. More case than control fathers had jobs in a cluster that includes machinists and welders (odds ratios (ORs) = 4.0-5.7, p less than or equal to 0.04). Paternal exposures to lead, silver, tin, and iron (some exposures of this cluster) were associated with Wilms' tumor in some analyses, with moderate odds ratios (ORs = 1.5-3.4). In general, the highest odds ratios were found for the preconception period among the genetic (prezygotic) cases. No maternal job clusters or exposures gave significantly elevated odds ratios. These results support a previous finding that lead is a risk factor, but not radiation, hydrocarbon, or boron exposures.« less

Non-negative Matrix Factorization and Co-clustering: A Promising Tool for Multi-tasks Bearing Fault Diagnosis

NASA Astrophysics Data System (ADS)

Shen, Fei; Chen, Chao; Yan, Ruqiang

2017-05-01

Classical bearing fault diagnosis methods, being designed according to one specific task, always pay attention to the effectiveness of extracted features and the final diagnostic performance. However, most of these approaches suffer from inefficiency when multiple tasks exist, especially in a real-time diagnostic scenario. A fault diagnosis method based on Non-negative Matrix Factorization (NMF) and Co-clustering strategy is proposed to overcome this limitation. Firstly, some high-dimensional matrixes are constructed using the Short-Time Fourier Transform (STFT) features, where the dimension of each matrix equals to the number of target tasks. Then, the NMF algorithm is carried out to obtain different components in each dimension direction through optimized matching, such as Euclidean distance and divergence distance. Finally, a Co-clustering technique based on information entropy is utilized to realize classification of each component. To verity the effectiveness of the proposed approach, a series of bearing data sets were analysed in this research. The tests indicated that although the diagnostic performance of single task is comparable to traditional clustering methods such as K-mean algorithm and Guassian Mixture Model, the accuracy and computational efficiency in multi-tasks fault diagnosis are improved.

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

NASA Technical Reports Server (NTRS)

Koslovsky, Matthew; Arellano, John; Schaefer, Caroline; Feiveson, Alan; Young, Millennia; Lee, Stuart

2017-01-01

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Layered clustering multi-fault diagnosis for hydraulic piston pump

NASA Astrophysics Data System (ADS)

Du, Jun; Wang, Shaoping; Zhang, Haiyan

2013-04-01

Efficient diagnosis is very important for improving reliability and performance of aircraft hydraulic piston pump, and it is one of the key technologies in prognostic and health management system. In practice, due to harsh working environment and heavy working loads, multiple faults of an aircraft hydraulic pump may occur simultaneously after long time operations. However, most existing diagnosis methods can only distinguish pump faults that occur individually. Therefore, new method needs to be developed to realize effective diagnosis of simultaneous multiple faults on aircraft hydraulic pump. In this paper, a new method based on the layered clustering algorithm is proposed to diagnose multiple faults of an aircraft hydraulic pump that occur simultaneously. The intensive failure mechanism analyses of the five main types of faults are carried out, and based on these analyses the optimal combination and layout of diagnostic sensors is attained. The three layered diagnosis reasoning engine is designed according to the faults' risk priority number and the characteristics of different fault feature extraction methods. The most serious failures are first distinguished with the individual signal processing. To the desultory faults, i.e., swash plate eccentricity and incremental clearance increases between piston and slipper, the clustering diagnosis algorithm based on the statistical average relative power difference (ARPD) is proposed. By effectively enhancing the fault features of these two faults, the ARPDs calculated from vibration signals are employed to complete the hypothesis testing. The ARPDs of the different faults follow different probability distributions. Compared with the classical fast Fourier transform-based spectrum diagnosis method, the experimental results demonstrate that the proposed algorithm can diagnose the multiple faults, which occur synchronously, with higher precision and reliability.

The old open cluster NGC 2112: updated estimates of fundamental parameters based on a membership analysis†

NASA Astrophysics Data System (ADS)

Carraro, G.; Villanova, S.; Demarque, P.; Moni Bidin, C.; McSwain, M. V.

2008-05-01

We report on a new, wide-field (20 × 20 arcmin2), multicolour (UBVI), photometric campaign in the area of the nearby old open cluster NGC 2112. At the same time, we provide medium-resolution spectroscopy of 35 (and high-resolution of additional 5) red giant and turn-off stars. This material is analysed with the aim to update the fundamental parameters of this traditionally difficult cluster, which is very sparse and suffers from heavy field star contamination. Among the 40 stars with spectra, we identified 21 bona fide radial velocity members which allow us to put more solid constraints on the cluster's metal abundance, long suggested to be as low as the metallicity of globulars. As indicated earlier by us on a purely photometric basis, the cluster [Fe/H] abundance is slightly supersolar ([Fe/H] = 0.16 +/- 0.03) and close to the Hyades value, as inferred from a detailed abundance analysis of three of the five stars with higher resolution spectra. Abundance ratios are also marginally supersolar. Based on this result, we revise the properties of NGC 2112 using stellar models from the Padova and Yale-Yonsei groups. For this metal abundance, we find that the cluster's age, reddening and distance values are 1.8 Gyr, 0.60 mag and 940 pc, respectively. Both the Yale-Yonsei and Padova models predict the same values for the fundamental parameters within the errors. Overall, NGC 2112 is a typical solar neighbourhood, thin-disc star cluster, sharing the same chemical properties of F-G stars and open clusters close to the Sun. This investigation outlines the importance of a detailed membership analysis in the study of disc star clusters. This paper includes data gathered with the 6.5 Magellan Telescopes, located at Las Campanas Observatory, Chile. The data discussed in this paper will be made available at the WEBDA open cluster data base http://www.univie.ac.at/webda, which is maintained by E. Paunzen and J.-C. Mermilliod. ‡ E-mail: gcarraro@eso.org (GC); sandro.villanova@unipd.it (SV); demarque@astro.yale.edu (PD); mbidin@das.uchile.cl (CMB); mcswain@lehigh.edu(MVM)

Spitzer observations of NGC 2264: the nature of the disk population

NASA Astrophysics Data System (ADS)

Teixeira, P. S.; Lada, C. J.; Marengo, M.; Lada, E. A.

2012-04-01

Aims: NGC 2264 is a young cluster with a rich circumstellar disk population which makes it an ideal target for studying the evolution of stellar clusters. Our goal is to study the star formation history of NGC 2264 and to analyse the primordial disk evolution of its members. Methods: The study presented is based on data obtained with the Infrared Array Camera (IRAC) and the Multiband Imaging Photometer for Spitzer (MIPS) on board the Spitzer Space Telescope, combined with deep near-infrared (NIR) ground-based FLAMINGOS imaging and previously published optical data. Results: We build NIR dust extinction maps of the molecular cloud associated with the cluster, and determine it to have a mass of 2.1 × 103 M⊙ above an AV of 7 mag. Using a differential Ks-band luminosity function (KLF) of the cluster, we estimate the size of the population of NGC 2264, within the area observed by FLAMINGOS, to be 1436 ± 242 members. The star formation efficiency is ≥ ~25%. We identify the disk population and divide it into 3 groups based on their spectral energy distribution slopes from 3.6 μm to 8 μm and on the 24 μm excess emission: (i) optically thick inner disks, (ii) anaemic inner disks, and (iii) disks with inner holes, or transition disks. We analyse the spatial distribution of these sources and find that sources with thick disks segregate into sub-clusterings, whereas sources with anaemic disks do not. Furthermore, sources with anaemic disks are found to be unembedded (i.e., with AV < 3 mag), whereas the clustered sources with thick disks are still embedded within the parental cloud. Conclusions: NGC 2264 has undergone more than one star-forming event, where the anaemic and extincted thick disk population appear to have formed in separate episodes: the sources with anaemic disks are more evolved and have had time to disperse and populate a halo of the cluster. We also find tentative evidence of triggered star-formation in the Fox Fur Nebula. In terms of disk evolution, our findings support the emerging disk evolution paradigm of two distinct evolutionary paths for primordial optically thick disks: a homologous one where the disk emission decreases uniformly at NIR and mid-infrared (MIR) wavelengths, and a radially differential one where the emission from the inner region of the disk decreases more rapidly than from the outer region (forming transition disks).

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

PubMed

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

2015-04-14

Elucidation of the molecular mechanisms underlying the human gut microbiota's effects on health and disease has been complicated by difficulties in linking metabolic functions associated with the gut community as a whole to individual microorganisms and activities. Anaerobic microbial choline metabolism, a disease-associated metabolic pathway, exemplifies this challenge, as the specific human gut microorganisms responsible for this transformation have not yet been clearly identified. In this study, we established the link between a bacterial gene cluster, the choline utilization (cut) cluster, and anaerobic choline metabolism in human gut isolates by combining transcriptional, biochemical, bioinformatic, and cultivation-based approaches. Quantitative reverse transcription-PCR analysis and in vitro biochemical characterization of two cut gene products linked the entire cluster to growth on choline and supported a model for this pathway. Analyses of sequenced bacterial genomes revealed that the cut cluster is present in many human gut bacteria, is predictive of choline utilization in sequenced isolates, and is widely but discontinuously distributed across multiple bacterial phyla. Given that bacterial phylogeny is a poor marker for choline utilization, we were prompted to develop a degenerate PCR-based method for detecting the key functional gene choline TMA-lyase (cutC) in genomic and metagenomic DNA. Using this tool, we found that new choline-metabolizing gut isolates universally possessed cutC. We also demonstrated that this gene is widespread in stool metagenomic data sets. Overall, this work represents a crucial step toward understanding anaerobic choline metabolism in the human gut microbiota and underscores the importance of examining this microbial community from a function-oriented perspective. Anaerobic choline utilization is a bacterial metabolic activity that occurs in the human gut and is linked to multiple diseases. While bacterial genes responsible for choline fermentation (the cut gene cluster) have been recently identified, there has been no characterization of these genes in human gut isolates and microbial communities. In this work, we use multiple approaches to demonstrate that the pathway encoded by the cut genes is present and functional in a diverse range of human gut bacteria and is also widespread in stool metagenomes. We also developed a PCR-based strategy to detect a key functional gene (cutC) involved in this pathway and applied it to characterize newly isolated choline-utilizing strains. Both our analyses of the cut gene cluster and this molecular tool will aid efforts to further understand the role of choline metabolism in the human gut microbiota and its link to disease. Copyright © 2015 Martínez-del Campo et al.

Is high-sensitive C-reactive protein a biomarker for functional somatic symptoms? A population-based study.

PubMed

Tak, Lineke M; Bakker, Stephan J L; Slaets, Joris P J; Rosmalen, Judith G M

2009-10-01

Functional somatic symptoms (FSS) are symptoms unexplained in terms of underlying organic pathology. Alterations in the immune system function may be associated with FSS via induction of sickness behavior. We aimed to investigate whether low-grade immune system activation is positively associated with FSS in a population-based cohort of 881 adults (46% male, mean age 53.0, SD 11.4). Participants completed the somatization section of the Composite International Diagnostic Interview surveying the presence of 43 FSS. Innate immune function was assessed by measuring high-sensitive C-reactive protein (hs-CRP). Follow-up measurements of hs-CRP and FSS were performed approximately 2years later. Regression analyses, with adjustments for gender, age, body mass index, anxiety, depression, smoking, alcohol use, and frequency of exercise, did not reveal a cross-sectional association (beta=0.01, t=0.40, p=0.693) or longitudinal association (beta=-0.03, t=-0.93, p=0.352) between hs-CRP and the total number of FSS. When examining different bodily clusters of FSS, hs-CRP was not associated with the gastrointestinal FSS cluster, but the association approached statistical significance for the general FSS cluster (OR 1.08, 95% CI 0.98-1.18) and musculoskeletal FSS cluster (OR 1.08, 95% CI 0.99-1.17). For the latter association, exploratory analyses revealed that mainly the pure musculoskeletal complaints were responsible (OR 1.12, 95% CI 1.03-1.21). We conclude that the level of hs-CRP is not a biomarker for the total number of FSS in the general population. The association between hs-CRP and musculoskeletal and general FSS needs further study.

Phenotyping asthma, rhinitis and eczema in MeDALL population-based birth cohorts: an allergic comorbidity cluster.

PubMed

Garcia-Aymerich, J; Benet, M; Saeys, Y; Pinart, M; Basagaña, X; Smit, H A; Siroux, V; Just, J; Momas, I; Rancière, F; Keil, T; Hohmann, C; Lau, S; Wahn, U; Heinrich, J; Tischer, C G; Fantini, M P; Lenzi, J; Porta, D; Koppelman, G H; Postma, D S; Berdel, D; Koletzko, S; Kerkhof, M; Gehring, U; Wickman, M; Melén, E; Hallberg, J; Bindslev-Jensen, C; Eller, E; Kull, I; Lødrup Carlsen, K C; Carlsen, K-H; Lambrecht, B N; Kogevinas, M; Sunyer, J; Kauffmann, F; Bousquet, J; Antó, J M

2015-08-01

Asthma, rhinitis and eczema often co-occur in children, but their interrelationships at the population level have been poorly addressed. We assessed co-occurrence of childhood asthma, rhinitis and eczema using unsupervised statistical techniques. We included 17 209 children at 4 years and 14 585 at 8 years from seven European population-based birth cohorts (MeDALL project). At each age period, children were grouped, using partitioning cluster analysis, according to the distribution of 23 variables covering symptoms 'ever' and 'in the last 12 months', doctor diagnosis, age of onset and treatments of asthma, rhinitis and eczema; immunoglobulin E sensitization; weight; and height. We tested the sensitivity of our estimates to subject and variable selections, and to different statistical approaches, including latent class analysis and self-organizing maps. Two groups were identified as the optimal way to cluster the data at both age periods and in all sensitivity analyses. The first (reference) group at 4 and 8 years (including 70% and 79% of children, respectively) was characterized by a low prevalence of symptoms and sensitization, whereas the second (symptomatic) group exhibited more frequent symptoms and sensitization. Ninety-nine percentage of children with comorbidities (co-occurrence of asthma, rhinitis and/or eczema) were included in the symptomatic group at both ages. The children's characteristics in both groups were consistent in all sensitivity analyses. At 4 and 8 years, at the population level, asthma, rhinitis and eczema can be classified together as an allergic comorbidity cluster. Future research including time-repeated assessments and biological data will help understanding the interrelationships between these diseases. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Deriving temperature, mass, and age of evolved stars from high-resolution spectra. Application to field stars and the open cluster IC 4651

NASA Astrophysics Data System (ADS)

Biazzo, K.; Pasquini, L.; Girardi, L.; Frasca, A.; da Silva, L.; Setiawan, J.; Marilli, E.; Hatzes, A. P.; Catalano, S.

2007-12-01

Aims:We test our capability of deriving stellar physical parameters of giant stars by analysing a sample of field stars and the well studied open cluster IC 4651 with different spectroscopic methods. Methods: The use of a technique based on line-depth ratios (LDRs) allows us to determine with high precision the effective temperature of the stars and to compare the results with those obtained with a classical LTE abundance analysis. Results: (i) For the field stars we find that the temperatures derived by means of the LDR method are in excellent agreement with those found by the spectral synthesis. This result is extremely encouraging because it shows that spectra can be used to firmly derive population characteristics (e.g., mass and age) of the observed stars. (ii) For the IC 4651 stars we use the determined effective temperature to derive the following results. a) The reddening E(B-V) of the cluster is 0.12±0.02, largely independent of the color-temperature calibration used. b) The age of the cluster is 1.2±0.2 Gyr. c) The typical mass of the analysed giant stars is 2.0±0.2~M⊙. Moreover, we find a systematic difference of about 0.2 dex in log g between spectroscopic and evolutionary values. Conclusions: We conclude that, in spite of known limitations, a classical spectroscopic analysis of giant stars may indeed result in very reliable stellar parameters. We caution that the quality of the agreement, on the other hand, depends on the details of the adopted spectroscopic analysis. Based on observations collected at the ESO telescopes at the Paranal and La Silla Observatories, Chile.

Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects

PubMed Central

Nemmi, Federico; Saint-Aubert, Laure; Adel, Djilali; Salabert, Anne-Sophie; Pariente, Jérémie; Barbeau, Emmanuel; Payoux, Pierre; Péran, Patrice

2014-01-01

Purpose AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer’s disease (AD) but also in healthy population. This binding; thought to be of a non-specific lipophilic nature has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in healthy and pathological populations in white matter. Methods We recruited 24 patients presenting with AD at early stage and 17 matched, healthy subjects. We used an optimized PET-MRI registration method and an approach based on intensity histogram using several indexes. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matters using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed. Results White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms was not decisive to discriminate groups, and indexes based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample in two clusters, showing different uptakes in grey but also in white matter. Conclusion These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using SUVr approach. Although it is not better than standard SUVr to discriminate AD patients from healthy subjects, this information could reveal white matter modifications. PMID:24573658

Newspaper coverage of suicide and initiation of suicide clusters in teenagers in the USA, 1988-96: a retrospective, population-based, case-control study.

PubMed

Gould, Madelyn S; Kleinman, Marjorie H; Lake, Alison M; Forman, Judith; Midle, Jennifer Bassett

2014-06-01

Public health and clinical efforts to prevent suicide clusters are seriously hampered by the unanswered question of why such outbreaks occur. We aimed to establish whether an environmental factor-newspaper reports of suicide-has a role in the emergence of suicide clusters. In this retrospective, population-based, case-control study, we identified suicide clusters in young people aged 13-20 years in the USA from 1988 to 1996 (preceding the advent of social media) using the time-space Scan statistic. For each cluster community, we selected two matched non-cluster control communities in which suicides of similarly aged youth occurred, from non-contiguous counties within the same state as the cluster. We examined newspapers within each cluster community for stories about suicide published in the days between the first and second suicides in the cluster. In non-cluster communities, we examined a matched length of time after the matched control suicide. We used a content-analysis procedure to code the characteristics of each story and compared newspaper stories about suicide published in case and control communities with mixed-effect regression analyses. We identified 53 suicide clusters, of which 48 were included in the media review. For one cluster we could identify only one appropriate control; therefore, 95 matched control communities were included. The mean number of news stories about suicidal individuals published after an index cluster suicide (7·42 [SD 10·02]) was significantly greater than the mean number of suicide stories published after a non-cluster suicide (5·14 [6.00]; p<0·0001). Several story characteristics, including front-page placement, headlines containing the word suicide or a description of the method used, and detailed descriptions of the suicidal individual and act, appeared more often in stories published after the index cluster suicides than after non-cluster suicides. Our identification of an association between newspaper reports about suicide (including specific story characteristics) and the initiation of teenage suicide clusters should provide an empirical basis to support efforts by mental health professionals, community officials, and the media to work together to identify and prevent the onset of suicide clusters. US National Institute of Mental Health and American Foundation for Suicide Prevention. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cosmology with XMM galaxy clusters: the X-CLASS/GROND catalogue and photometric redshifts

NASA Astrophysics Data System (ADS)

Ridl, J.; Clerc, N.; Sadibekova, T.; Faccioli, L.; Pacaud, F.; Greiner, J.; Krühler, T.; Rau, A.; Salvato, M.; Menzel, M.-L.; Steinle, H.; Wiseman, P.; Nandra, K.; Sanders, J.

2017-06-01

The XMM Cluster Archive Super Survey (X-CLASS) is a serendipitously detected X-ray-selected sample of 845 galaxy clusters based on 2774 XMM archival observations and covering an approximately 90 deg2 spread across the high-Galactic latitude (|b| > 20°) sky. The primary goal of this survey is to produce a well-selected sample of galaxy clusters on which cosmological analyses can be performed. This paper presents the photometric redshift follow-up of a high signal-to-noise ratio subset of 265 of these clusters with declination δ < +20° with Gamma-Ray Burst Optical and Near-Infrared Detector (GROND), a 7-channel (grizJHK) simultaneous imager on the MPG 2.2-m telescope at the ESO La Silla Observatory. We use a newly developed technique based on the red sequence colour-redshift relation, enhanced with information coming from the X-ray detection to provide photometric redshifts for this sample. We determine photometric redshifts for 232 clusters, finding a median redshift of z = 0.39 with an accuracy of Δz = 0.02(1 + z) when compared to a sample of 76 spectroscopically confirmed clusters. We also compute X-ray luminosities for the entire sample and find a median bolometric luminosity of 7.2 × 1043 erg s-1 and a median temperature of 2.9 keV. We compare our results to those of the XMM-XCS and XMM-XXL surveys, finding good agreement in both samples. The X-CLASS catalogue is available online at http://xmm-lss.in2p3.fr:8080/l4sdb/.

Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2014-12-30

Understanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice. An automatic unsupervised spike sorting method is proposed in this paper. The method uses features extracted by the locality preserving projection (LPP) algorithm. These features afterwards serve as inputs for the landmark-based spectral clustering (LSC) method. Gap statistics (GS) is employed to evaluate the number of clusters before the LSC can be performed. The proposed LPP-LSC is highly accurate and computationally inexpensive spike sorting approach. LPP spike features are very discriminative; thereby boost the performance of clustering methods. Furthermore, the LSC method exhibits its efficiency when integrated with the cluster evaluator GS. The proposed method's accuracy is approximately 13% superior to that of the benchmark combination between wavelet transformation and superparamagnetic clustering (WT-SPC). Additionally, LPP-LSC computing time is six times less than that of the WT-SPC. LPP-LSC obviously demonstrates a win-win spike sorting solution meeting both accuracy and computational cost criteria. LPP and LSC are linear algorithms that help reduce computational burden and thus their combination can be applied into real-time spike analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Planck 2015 results. XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Weller, J.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing of background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. Improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.

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.

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

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

Ade, P. A. R.; Aghanim, N.; Arnaud, M.

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

New Insights into the Diversity of the Genus Faecalibacterium.

PubMed

Benevides, Leandro; Burman, Sriti; Martin, Rebeca; Robert, Véronique; Thomas, Muriel; Miquel, Sylvie; Chain, Florian; Sokol, Harry; Bermudez-Humaran, Luis G; Morrison, Mark; Langella, Philippe; Azevedo, Vasco A; Chatel, Jean-Marc; Soares, Siomar

2017-01-01

Faecalibacterium prausnitzii is a commensal bacterium, ubiquitous in the gastrointestinal tracts of animals and humans. This species is a functionally important member of the microbiota and studies suggest it has an impact on the physiology and health of the host. F. prausnitzii is the only identified species in the genus Faecalibacterium , but a recent study clustered strains of this species in two different phylogroups. Here, we propose the existence of distinct species in this genus through the use of comparative genomics. Briefly, we performed analyses of 16S rRNA gene phylogeny, phylogenomics, whole genome Multi-Locus Sequence Typing (wgMLST), Average Nucleotide Identity (ANI), gene synteny, and pangenome to better elucidate the phylogenetic relationships among strains of Faecalibacterium . For this, we used 12 newly sequenced, assembled, and curated genomes of F. prausnitzii , which were isolated from feces of healthy volunteers from France and Australia, and combined these with published data from 5 strains downloaded from public databases. The phylogenetic analysis of the 16S rRNA sequences, together with the wgMLST profiles and a phylogenomic tree based on comparisons of genome similarity, all supported the clustering of Faecalibacterium strains in different genospecies. Additionally, the global analysis of gene synteny among all strains showed a highly fragmented profile, whereas the intra-cluster analyses revealed larger and more conserved collinear blocks. Finally, ANI analysis substantiated the presence of three distinct clusters-A, B, and C-composed of five, four, and four strains, respectively. The pangenome analysis of each cluster corroborated the classification of these clusters into three distinct species, each containing less variability than that found within the global pangenome of all strains. Here, we propose that comparison of pangenome subsets and their associated α values may be used as an alternative approach, together with ANI, in the in silico classification of new species. Altogether, our results provide evidence not only for the reconsideration of the phylogenetic and genomic relatedness among strains currently assigned to F. prausnitzii , but also the need for lineage (strain-based) differentiation of this taxon to better define how specific members might be associated with positive or negative host interactions.

Relationship between Procedural Tactical Knowledge and Specific Motor Skills in Young Soccer Players

PubMed Central

Aquino, Rodrigo; Marques, Renato Francisco R.; Petiot, Grégory Hallé; Gonçalves, Luiz Guilherme C.; Moraes, Camila; Santiago, Paulo Roberto P.; Puggina, Enrico Fuini

2016-01-01

The purpose of this study was to investigate the association between offensive tactical knowledge and the soccer-specific motor skills performance. Fifteen participants were submitted to two evaluation tests, one to assess their technical and tactical analysis. The motor skills performance was measured through four tests of technical soccer skills: ball control, shooting, passing and dribbling. The tactical performance was based on a tactical assessment system called FUT-SAT (Analyses of Procedural Tactical Knowledge in Soccer). Afterwards, technical and tactical evaluation scores were ranked with and without the use of the cluster method. A positive, weak correlation was perceived in both analyses (rho = 0.39, not significant p = 0.14 (with cluster analysis); and rho = 0.35; not significant p = 0.20 (without cluster analysis)). We can conclude that there was a weak association between the technical and the offensive tactical knowledge. This shows the need to reflect on the use of such tests to assess technical skills in team sports since they do not take into account the variability and unpredictability of game actions and disregard the inherent needs to assess such skill performance in the game. PMID:29910300

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Effect of wheat flour characteristics on sponge cake quality.

PubMed

Moiraghi, Malena; de la Hera, Esther; Pérez, Gabriela T; Gómez, Manuel

2013-02-01

To select the flour parameters that relate strongly to cake-making performance, in this study the relationship between sponge cake quality, solvent retention capacity (SRC) profile and flour physicochemical characteristics was investigated using 38 soft wheat samples of different origins. Particle size average, protein, damaged starch, water-soluble pentosans, total pentosans, SRC and pasting properties were analysed. Sponge cake volume and crumb texture were measured to evaluate cake quality. Cluster analysis was applied to assess differences in flour quality parameters among wheat lines based on the SRC profile. Cluster 1 showed significantly higher sponge cake volume and crumb softness, finer particle size and lower SRC sucrose, SRC carbonate, SRC water, damaged starch and protein content. Particle size, damaged starch, protein, thickening capacity and SRC parameters correlated negatively with sponge cake volume, while total pentosans and pasting temperature showed the opposite effect. The negative correlations between cake volume and SRC parameters along with the cluster analysis results indicated that flours with smaller particle size, lower absorption capacity and higher pasting temperature had better cake-making performance. Some simple analyses, such as SRC, particle size distribution and pasting properties, may help to choose flours suitable for cake making. Copyright © 2012 Society of Chemical Industry.

Defect Clustering and Nano-phase Structure Characterization of Multicomponent Rare Earth-Oxide-Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

2004-01-01

Advanced thermal barrier coatings (TBCs) have been developed by incorporating multicomponent rare earth oxide dopants into zirconia-based thermal barrier coatings to promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nanophases within the coating systems. In this paper, the defect clusters, induced by Nd, Gd, and Yb rare earth dopants in the zirconia-yttria thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The TEM lattice imaging, selected area diffraction (SAD), and electron energy-loss spectroscopy (EELS) analyses demonstrated that the extensive nanoscale rare earth dopant segregation exists in the plasma-sprayed and electron-physical-vapor-deposited (EB PVD) thermal barrier coatings. The nanoscale concentration heterogeneity and the resulting large lattice distortion promoted the formation of parallel and rotational defective lattice clusters in the coating systems. The presence of the 5-to 100-nm-sized defect clusters and nanophases is believed to be responsible for the significant reduction of thermal conductivity, improved sintering resistance, and long-term high temperature stability of the advanced thermal barrier coating systems.

Genetic diversity and population structure of the tsetse fly Glossina fuscipes fuscipes (Diptera: Glossinidae) in Northern Uganda: Implications for vector control

PubMed Central

Echodu, Richard; Opiyo, Elizabeth A.; Dion, Kirstin; Halyard, Alexis; Dunn, Augustine W.; Aksoy, Serap; Caccone, Adalgisa

2017-01-01

Uganda is the only country where the chronic and acute forms of human African Trypanosomiasis (HAT) or sleeping sickness both occur and are separated by < 100 km in areas north of Lake Kyoga. In Uganda, Glossina fuscipes fuscipes is the main vector of the Trypanosoma parasites responsible for these diseases as well for the animal African Trypanosomiasis (AAT), or Nagana. We used highly polymorphic microsatellite loci and a mitochondrial DNA (mtDNA) marker to provide fine scale spatial resolution of genetic structure of G. f. fuscipes from 42 sampling sites from the northern region of Uganda where a merger of the two disease belts is feared. Based on microsatellite analyses, we found that G. f. fuscipes in northern Uganda are structured into three distinct genetic clusters with varying degrees of interconnectivity among them. Based on genetic assignment and spatial location, we grouped the sampling sites into four genetic units corresponding to northwestern Uganda in the Albert Nile drainage, northeastern Uganda in the Lake Kyoga drainage, western Uganda in the Victoria Nile drainage, and a transition zone between the two northern genetic clusters characterized by high level of genetic admixture. An analysis using HYBRIDLAB supported a hybrid swarm model as most consistent with tsetse genotypes in these admixed samples. Results of mtDNA analyses revealed the presence of 30 haplotypes representing three main haplogroups, whose location broadly overlaps with the microsatellite defined clusters. Migration analyses based on microsatellites point to moderate migration among the northern units located in the Albert Nile, Achwa River, Okole River, and Lake Kyoga drainages, but not between the northern units and the Victoria Nile drainage in the west. Effective population size estimates were variable with low to moderate sizes in most populations and with evidence of recent population bottlenecks, especially in the northeast unit of the Lake Kyoga drainage. Our microsatellite and mtDNA based analyses indicate that G. f. fuscipes movement along the Achwa and Okole rivers may facilitate northwest expansion of the Rhodesiense disease belt in Uganda. We identified tsetse migration corridors and recommend a rolling carpet approach from south of Lake Kyoga northward to minimize disease dispersal and prevent vector re-colonization. Additionally, our findings highlight the need for continuing tsetse monitoring efforts during and after control. PMID:28453513

A Locus Encoding Variable Defense Systems against Invading DNA Identified in Streptococcus suis

PubMed Central

Okura, Masatoshi; Nozawa, Takashi; Watanabe, Takayasu; Murase, Kazunori; Nakagawa, Ichiro; Takamatsu, Daisuke; Osaki, Makoto; Sekizaki, Tsutomu; Gottschalk, Marcelo; Hamada, Shigeyuki

2017-01-01

Streptococcus suis, an important zoonotic pathogen, is known to have an open pan-genome and to develop a competent state. In S. suis, limited genetic lineages are suggested to be associated with zoonosis. However, little is known about the evolution of diversified lineages and their respective phenotypic or ecological characteristics. In this study, we performed comparative genome analyses of S. suis, with a focus on the competence genes, mobile genetic elements, and genetic elements related to various defense systems against exogenous DNAs (defense elements) that are associated with gene gain/loss/exchange mediated by horizontal DNA movements and their restrictions. Our genome analyses revealed a conserved competence-inducing peptide type (pherotype) of the competence system and large-scale genome rearrangements in certain clusters based on the genome phylogeny of 58 S. suis strains. Moreover, the profiles of the defense elements were similar or identical to each other among the strains belonging to the same genomic clusters. Our findings suggest that these genetic characteristics of each cluster might exert specific effects on the phenotypic or ecological differences between the clusters. We also found certain loci that shift several types of defense elements in S. suis. Of note, one of these loci is a previously unrecognized variable region in bacteria, at which strains of distinct clusters code for different and various defense elements. This locus might represent a novel defense mechanism that has evolved through an arms race between bacteria and invading DNAs, mediated by mobile genetic elements and genetic competence. PMID:28379509

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.

Permutation Tests of Hierarchical Cluster Analyses of Carrion Communities and Their Potential Use in Forensic Entomology.

PubMed

van der Ham, Joris L

2016-05-19

Forensic entomologists can use carrion communities' ecological succession data to estimate the postmortem interval (PMI). Permutation tests of hierarchical cluster analyses of these data provide a conceptual method to estimate part of the PMI, the post-colonization interval (post-CI). This multivariate approach produces a baseline of statistically distinct clusters that reflect changes in the carrion community composition during the decomposition process. Carrion community samples of unknown post-CIs are compared with these baseline clusters to estimate the post-CI. In this short communication, I use data from previously published studies to demonstrate the conceptual feasibility of this multivariate approach. Analyses of these data produce series of significantly distinct clusters, which represent carrion communities during 1- to 20-day periods of the decomposition process. For 33 carrion community samples, collected over an 11-day period, this approach correctly estimated the post-CI within an average range of 3.1 days. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cluster Analysis Identifies 3 Phenotypes within Allergic Asthma.

PubMed

Sendín-Hernández, María Paz; Ávila-Zarza, Carmelo; Sanz, Catalina; García-Sánchez, Asunción; Marcos-Vadillo, Elena; Muñoz-Bellido, Francisco J; Laffond, Elena; Domingo, Christian; Isidoro-García, María; Dávila, Ignacio

Asthma is a heterogeneous chronic disease with different clinical expressions and responses to treatment. In recent years, several unbiased approaches based on clinical, physiological, and molecular features have described several phenotypes of asthma. Some phenotypes are allergic, but little is known about whether these phenotypes can be further subdivided. We aimed to phenotype patients with allergic asthma using an unbiased approach based on multivariate classification techniques (unsupervised hierarchical cluster analysis). From a total of 54 variables of 225 patients with well-characterized allergic asthma diagnosed following American Thoracic Society (ATS) recommendation, positive skin prick test to aeroallergens, and concordant symptoms, we finally selected 19 variables by multiple correspondence analyses. Then a cluster analysis was performed. Three groups were identified. Cluster 1 was constituted by patients with intermittent or mild persistent asthma, without family antecedents of atopy, asthma, or rhinitis. This group showed the lowest total IgE levels. Cluster 2 was constituted by patients with mild asthma with a family history of atopy, asthma, or rhinitis. Total IgE levels were intermediate. Cluster 3 included patients with moderate or severe persistent asthma that needed treatment with corticosteroids and long-acting β-agonists. This group showed the highest total IgE levels. We identified 3 phenotypes of allergic asthma in our population. Furthermore, we described 2 phenotypes of mild atopic asthma mainly differentiated by a family history of allergy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Definition of run-off-road crash clusters-For safety benefit estimation and driver assistance development.

PubMed

Nilsson, Daniel; Lindman, Magdalena; Victor, Trent; Dozza, Marco

2018-04-01

Single-vehicle run-off-road crashes are a major traffic safety concern, as they are associated with a high proportion of fatal outcomes. In addressing run-off-road crashes, the development and evaluation of advanced driver assistance systems requires test scenarios that are representative of the variability found in real-world crashes. We apply hierarchical agglomerative cluster analysis to define similarities in a set of crash data variables, these clusters can then be used as the basis in test scenario development. Out of 13 clusters, nine test scenarios are derived, corresponding to crashes characterised by: drivers drifting off the road in daytime and night-time, high speed departures, high-angle departures on narrow roads, highways, snowy roads, loss-of-control on wet roadways, sharp curves, and high speeds on roads with severe road surface conditions. In addition, each cluster was analysed with respect to crash variables related to the crash cause and reason for the unintended lane departure. The study shows that cluster analysis of representative data provides a statistically based method to identify relevant properties for run-off-road test scenarios. This was done to support development of vehicle-based run-off-road countermeasures and driver behaviour models used in virtual testing. Future studies should use driver behaviour from naturalistic driving data to further define how test-scenarios and behavioural causation mechanisms should be included. Copyright © 2018 Elsevier Ltd. All rights reserved.

Associations between Functional Milestones and Psychiatric Admissions in an Urban Area: Utility of a Cluster-Analytical Approach.

PubMed

Montemagni, Cristiana; Frieri, Tiziana; Villari, Vincenzo; Rocca, Paola

2018-06-01

The purpose of the study was to identify homogenous subgroups, based upon achievement of two functional milestones (marriage and employment) and Global Assessment of Functioning (GAF) score in a sample of 848 acute patients admitted to the Psychiatric Emergency Service (PES) of the Città della Salute e della Scienza di Torino, during a 24-months period. A two-step cluster-analysis, using GAF total score and the achievements in the two milestones as input data was performed. In order to examine whether the identified subgroups differed in external variables that were not included in the clustering process, and consequently to validate the found functional profiles, chi-square tests for categorical variables and analyses of variance (ANOVA) for continuous variables were performed. Five clusters were found. Employed patients (Clusters 4 and 5) had more years of education, less illness chronicity (shorter duration of illness and lower proportion of previous voluntary hospitalizations), lower use of mental health resources in the last year yet higher treatment adherence, larger network size, and higher ordinary discharge. Married inpatients (Clusters 3 and 5) had lower frequencies of substance abuse. The remarkably high rate of unemployment in this inpatients' sample, and the evidence of associations between unemployment and poorer functioning, argue for further research and development of evidence-based supported employment programs, that put forth diligent effort in helping people obtain work quickly and sustain; they may also help to reduce health care service use among that clientele.

Low Divergence of Clonorchis sinensis in China Based on Multilocus Analysis

PubMed Central

Sun, Jiufeng; Huang, Yan; Huang, Huaiqiu; Liang, Pei; Wang, Xiaoyun; Mao, Qiang; Men, Jingtao; Chen, Wenjun; Deng, Chuanhuan; Zhou, Chenhui; Lv, Xiaoli; Zhou, Juanjuan; Zhang, Fan; Li, Ran; Tian, Yanli; Lei, Huali; Liang, Chi; Hu, Xuchu; Xu, Jin; Li, Xuerong; XinbingYu

2013-01-01

Clonorchis sinensis, an ancient parasite that infects a number of piscivorous mammals, attracts significant public health interest due to zoonotic exposure risks in Asia. The available studies are insufficient to reflect the prevalence, geographic distribution, and intraspecific genetic diversity of C. sinensis in endemic areas. Here, a multilocus analysis based on eight genes (ITS1, act, tub, ef-1a, cox1, cox3, nad4 and nad5 [4.986 kb]) was employed to explore the intra-species genetic construction of C. sinensis in China. Two hundred and fifty-six C. sinensis isolates were obtained from environmental reservoirs from 17 provinces of China. A total of 254 recognized Multilocus Types (MSTs) showed high diversity among these isolates using multilocus analysis. The comparison analysis of nuclear and mitochondrial phylogeny supports separate clusters in a nuclear dendrogram. Genetic differentiation analysis of three clusters (A, B, and C) showed low divergence within populations. Most isolates from clusters B and C are geographically limited to central China, while cluster A is extraordinarily genetically diverse. Further genetic analyses between different geographic distributions, water bodies and hosts support the low population divergence. The latter haplotype analyses were consistent with the phylogenetic and genetic differentiation results. A recombination network based on concatenated sequences showed a concentrated linkage recombination population in cox1, cox3, nad4 and nad5, with spatial structuring in ITS1. Coupled with the history record and archaeological evidence of C. sinensis infection in mummified desiccated feces, these data point to an ancient origin of C. sinensis in China. In conclusion, we present a likely phylogenetic structure of the C. sinensis population in mainland China, highlighting its possible tendency for biogeographic expansion. Meanwhile, ITS1 was found to be an effective marker for tracking C. sinensis infection worldwide. Thus, the present study improves our understanding of the global epidemiology and evolution of C. sinensis. PMID:23825605

ADHD latent class clusters: DSM-IV subtypes and comorbidity

PubMed Central

Elia, Josephine; Arcos-Burgos, Mauricio; Bolton, Kelly L.; Ambrosini, Paul J.; Berrettini, Wade; Muenke, Maximilian

2014-01-01

ADHD (Attention Deficit Hyperactivity Disorder) has a complex, heterogeneous phenotype only partially captured by Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. In this report, latent class analyses (LCA) are used to identify ADHD phenotypes using K-SADS-IVR (Schedule for Affective Disorders & Schizophrenia for School Age Children-IV-Revised) symptoms and symptom severity data from a clinical sample of 500 ADHD subjects, ages 6–18, participating in an ADHD genetic study. Results show that LCA identified six separate ADHD clusters, some corresponding to specific DSM-IV subtypes while others included several subtypes. DSM-IV comorbid anxiety and mood disorders were generally similar across all clusters, and subjects without comorbidity did not aggregate within any one cluster. Age and gender composition also varied. These results support findings from population-based LCA studies. The six clusters provide additional homogenous groups that can be used to define ADHD phenotypes in genetic association studies. The limited age ranges aggregating in the different clusters may prove to be a particular advantage in genetic studies where candidate gene expression may vary during developmental phases. DSM-IV comorbid mood and anxiety disorders also do not appear to increase cluster heterogeneity; however, longitudinal studies that cover period of risk are needed to support this finding. PMID:19900717

Detecting Genomic Clustering of Risk Variants from Sequence Data: Cases vs. Controls

PubMed Central

Schaid, Daniel J.; Sinnwell, Jason P.; McDonnell, Shannon K.; Thibodeau, Stephen N.

2013-01-01

As the ability to measure dense genetic markers approaches the limit of the DNA sequence itself, taking advantage of possible clustering of genetic variants in, and around, a gene would benefit genetic association analyses, and likely provide biological insights. The greatest benefit might be realized when multiple rare variants cluster in a functional region. Several statistical tests have been developed, one of which is based on the popular Kulldorff scan statistic for spatial clustering of disease. We extended another popular spatial clustering method – Tango’s statistic – to genomic sequence data. An advantage of Tango’s method is that it is rapid to compute, and when single test statistic is computed, its distribution is well approximated by a scaled chi-square distribution, making computation of p-values very rapid. We compared the Type-I error rates and power of several clustering statistics, as well as the omnibus sequence kernel association test (SKAT). Although our version of Tango’s statistic, which we call “Kernel Distance” statistic, took approximately half the time to compute than the Kulldorff scan statistic, it had slightly less power than the scan statistic. Our results showed that the Ionita-Laza version of Kulldorff’s scan statistic had the greatest power over a range of clustering scenarios. PMID:23842950

densityCut: an efficient and versatile topological approach for automatic clustering of biological data

PubMed Central

Ding, Jiarui; Shah, Sohrab; Condon, Anne

2016-01-01

Motivation: Many biological data processing problems can be formalized as clustering problems to partition data points into sensible and biologically interpretable groups. Results: This article introduces densityCut, a novel density-based clustering algorithm, which is both time- and space-efficient and proceeds as follows: densityCut first roughly estimates the densities of data points from a K-nearest neighbour graph and then refines the densities via a random walk. A cluster consists of points falling into the basin of attraction of an estimated mode of the underlining density function. A post-processing step merges clusters and generates a hierarchical cluster tree. The number of clusters is selected from the most stable clustering in the hierarchical cluster tree. Experimental results on ten synthetic benchmark datasets and two microarray gene expression datasets demonstrate that densityCut performs better than state-of-the-art algorithms for clustering biological datasets. For applications, we focus on the recent cancer mutation clustering and single cell data analyses, namely to cluster variant allele frequencies of somatic mutations to reveal clonal architectures of individual tumours, to cluster single-cell gene expression data to uncover cell population compositions, and to cluster single-cell mass cytometry data to detect communities of cells of the same functional states or types. densityCut performs better than competing algorithms and is scalable to large datasets. Availability and Implementation: Data and the densityCut R package is available from https://bitbucket.org/jerry00/densitycut_dev. Contact: condon@cs.ubc.ca or sshah@bccrc.ca or jiaruid@cs.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153661

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.

Diverse characteristics of the urinary excretion of amino acids in humans and the use of amino acid supplementation to reduce fatigue and sub-health in adults.

PubMed

Dunstan, R H; Sparkes, D L; Macdonald, M M; De Jonge, X Janse; Dascombe, B J; Gottfries, J; Gottfries, C-G; Roberts, T K

2017-03-23

The excretion of amino acids in urine represents an important avenue for the loss of key nutrients. Some amino acids such as glycine and histidine are lost in higher abundance than others. These two amino acids perform important physiological functions and are required for the synthesis of key proteins such as haemoglobin and collagen. Stage 1 of this study involved healthy subjects (n = 151) who provided first of the morning urine samples and completed symptom questionnaires. Urine was analysed for amino acid composition by gas chromatography. Stage 2 involved a subset of the initial cohort (n = 37) who completed a 30 day trial of an amino acid supplement and subsequent symptom profile evaluation. Analyses of urinary amino acid profiles revealed that three groups could be objectively defined from the 151 participants using k-means clustering. The amino acid profiles were significantly different between each of the clusters (Wilks' Lambda = 0.13, p < 0.0001). Cluster 1 had the highest loss of amino acids with histidine being the most abundant component. Cluster 2 had glycine present as the most abundant urinary amino acid and cluster 3 had equivalent abundances of glycine and histidine. Strong associations were observed between urinary proline concentrations and fatigue/pain scores (r = .56 to .83) for females in cluster 1, with several other differential sets of associations observed for the other clusters. Different phenotypic subsets exist in the population based on amino acid excretion characteristics found in urine. Provision of the supplement resulted in significant improvements in reported fatigue and sleep for 81% of the trial cohort with all females reporting improvements in fatigue. The study was registered on the 18th April 2011 with the Australian New Zealand Clinical Trials Registry ( ACTRN12611000403932 ).

Tardigrade workbench: comparing stress-related proteins, sequence-similar and functional protein clusters as well as RNA elements in tardigrades

PubMed Central

2009-01-01

Background Tardigrades represent an animal phylum with extraordinary resistance to environmental stress. Results To gain insights into their stress-specific adaptation potential, major clusters of related and similar proteins are identified, as well as specific functional clusters delineated comparing all tardigrades and individual species (Milnesium tardigradum, Hypsibius dujardini, Echiniscus testudo, Tulinus stephaniae, Richtersius coronifer) and functional elements in tardigrade mRNAs are analysed. We find that 39.3% of the total sequences clustered in 58 clusters of more than 20 proteins. Among these are ten tardigrade specific as well as a number of stress-specific protein clusters. Tardigrade-specific functional adaptations include strong protein, DNA- and redox protection, maintenance and protein recycling. Specific regulatory elements regulate tardigrade mRNA stability such as lox P DICE elements whereas 14 other RNA elements of higher eukaryotes are not found. Further features of tardigrade specific adaption are rapidly identified by sequence and/or pattern search on the web-tool tardigrade analyzer http://waterbear.bioapps.biozentrum.uni-wuerzburg.de. The work-bench offers nucleotide pattern analysis for promotor and regulatory element detection (tardigrade specific; nrdb) as well as rapid COG search for function assignments including species-specific repositories of all analysed data. Conclusion Different protein clusters and regulatory elements implicated in tardigrade stress adaptations are analysed including unpublished tardigrade sequences. PMID:19821996

Tardigrade workbench: comparing stress-related proteins, sequence-similar and functional protein clusters as well as RNA elements in tardigrades.

PubMed

Förster, Frank; Liang, Chunguang; Shkumatov, Alexander; Beisser, Daniela; Engelmann, Julia C; Schnölzer, Martina; Frohme, Marcus; Müller, Tobias; Schill, Ralph O; Dandekar, Thomas

2009-10-12

Tardigrades represent an animal phylum with extraordinary resistance to environmental stress. To gain insights into their stress-specific adaptation potential, major clusters of related and similar proteins are identified, as well as specific functional clusters delineated comparing all tardigrades and individual species (Milnesium tardigradum, Hypsibius dujardini, Echiniscus testudo, Tulinus stephaniae, Richtersius coronifer) and functional elements in tardigrade mRNAs are analysed. We find that 39.3% of the total sequences clustered in 58 clusters of more than 20 proteins. Among these are ten tardigrade specific as well as a number of stress-specific protein clusters. Tardigrade-specific functional adaptations include strong protein, DNA- and redox protection, maintenance and protein recycling. Specific regulatory elements regulate tardigrade mRNA stability such as lox P DICE elements whereas 14 other RNA elements of higher eukaryotes are not found. Further features of tardigrade specific adaption are rapidly identified by sequence and/or pattern search on the web-tool tardigrade analyzer http://waterbear.bioapps.biozentrum.uni-wuerzburg.de. The work-bench offers nucleotide pattern analysis for promotor and regulatory element detection (tardigrade specific; nrdb) as well as rapid COG search for function assignments including species-specific repositories of all analysed data. Different protein clusters and regulatory elements implicated in tardigrade stress adaptations are analysed including unpublished tardigrade sequences.

The Impact of Multilocus Variable-Number Tandem-Repeat Analysis on PulseNet Canada Escherichia coli O157:H7 Laboratory Surveillance and Outbreak Support, 2008-2012.

PubMed

Rumore, Jillian Leigh; Tschetter, Lorelee; Nadon, Celine

2016-05-01

The lack of pattern diversity among pulsed-field gel electrophoresis (PFGE) profiles for Escherichia coli O157:H7 in Canada does not consistently provide optimal discrimination, and therefore, differentiating temporally and/or geographically associated sporadic cases from potential outbreak cases can at times impede investigations. To address this limitation, DNA sequence-based methods such as multilocus variable-number tandem-repeat analysis (MLVA) have been explored. To assess the performance of MLVA as a supplemental method to PFGE from the Canadian perspective, a retrospective analysis of all E. coli O157:H7 isolated in Canada from January 2008 to December 2012 (inclusive) was conducted. A total of 2285 E. coli O157:H7 isolates and 63 clusters of cases (by PFGE) were selected for the study. Based on the qualitative analysis, the addition of MLVA improved the categorization of cases for 60% of clusters and no change was observed for ∼40% of clusters investigated. In such situations, MLVA serves to confirm PFGE results, but may not add further information per se. The findings of this study demonstrate that MLVA data, when used in combination with PFGE-based analyses, provide additional resolution to the detection of clusters lacking PFGE diversity as well as demonstrate good epidemiological concordance. In addition, MLVA is able to identify cluster-associated isolates with variant PFGE pattern combinations that may have been previously missed by PFGE alone. Optimal laboratory surveillance in Canada is achieved with the application of PFGE and MLVA in tandem for routine surveillance, cluster detection, and outbreak response.

Unravelling the Intrinsic Functional Organization of the Human Striatum: A Parcellation and Connectivity Study Based on Resting-State fMRI

PubMed Central

Jung, Wi Hoon; Jang, Joon Hwan; Park, Jin Woo; Kim, Euitae; Goo, Eun-Hoe; Im, Oh-Soo; Kwon, Jun Soo

2014-01-01

As the main input hub of the basal ganglia, the striatum receives projections from the cerebral cortex. Many studies have provided evidence for multiple parallel corticostriatal loops based on the structural and functional connectivity profiles of the human striatum. A recent resting-state fMRI study revealed the topography of striatum by assigning each voxel in the striatum to its most strongly correlated cortical network among the cognitive, affective, and motor networks. However, it remains unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. Thus, we applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions without any anatomically or functionally defined cortical targets. Functional connectivity maps of striatal subdivisions, identified through clustering analyses, were also computed. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity. For example, we found functional connections between dorsal and ventral striatal clusters and the areas involved in cognitive and affective processes, respectively, and between rostral and caudal putamen clusters and the areas involved in cognitive and motor processes, respectively. This study confirms prior findings, showing similar striatal parcellation patterns between the present and prior studies. Given such striking similarity, it is suggested that striatal subregions are functionally linked to cortical networks involving specific functions rather than discrete portions of cortical regions. Our findings also demonstrate that the clustering of functional connectivity patterns is a reliable feature in parcellating the striatum into anatomically and functionally meaningful subdivisions. The striatal subdivisions identified here may have important implications for understanding the relationship between corticostriatal dysfunction and various neurodegenerative and psychiatric disorders. PMID:25203441

Students' Perceptions of Motivational Climate and Enjoyment in Finnish Physical Education: A Latent Profile Analysis.

PubMed

Jaakkola, Timo; Wang, C K John; Soini, Markus; Liukkonen, Jarmo

2015-09-01

The purpose of this study was to identify student clusters with homogenous profiles in perceptions of task- and ego-involving, autonomy, and social relatedness supporting motivational climate in school physical education. Additionally, we investigated whether different motivational climate groups differed in their enjoyment in PE. Participants of the study were 2 594 girls and 1 803 boys, aged 14-15 years. Students responded to questionnaires assessing their perception of motivational climate and enjoyment in physical education. Latent profile analyses produced a five-cluster solution labeled 1) 'low autonomy, relatedness, task, and moderate ego climate' group', 2) 'low autonomy, relatedness, and high task and ego climate, 3) 'moderate autonomy, relatedness, task and ego climate' group 4) 'high autonomy, relatedness, task, and moderate ego climate' group, and 5) 'high relatedness and task but moderate autonomy and ego climate' group. Analyses of variance showed that students in clusters 4 and 5 perceived the highest level of enjoyment whereas students in cluster 1 experienced the lowest level of enjoyment. The results showed that the students' perceptions of various motivational climates created differential levels of enjoyment in PE classes. Key pointsLatent profile analyses produced a five-cluster solution labeled 1) 'low autonomy, relatedness, task, and moderate ego climate' group', 2) 'low autonomy, relatedness, and high task and ego climate, 3) 'moderate autonomy, relatedness, task and ego climate' group 4) 'high autonomy, relatedness, task, and moderate ego climate' group, and 5) 'high relatedness and task but moderate autonomy and ego climate' group.Analyses of variance showed that clusters 4 and 5 perceived the highest level of enjoyment whereas cluster 1 experienced the lowest level of enjoyment. The results showed that the students' perceptions of motivational climate create differential levels of enjoyment in PE classes.

The Genome of Tolypocladium inflatum: Evolution, Organization, and Expression of the Cyclosporin Biosynthetic Gene Cluster

PubMed Central

Bushley, Kathryn E.; Raja, Rajani; Jaiswal, Pankaj; Cumbie, Jason S.; Nonogaki, Mariko; Boyd, Alexander E.; Owensby, C. Alisha; Knaus, Brian J.; Elser, Justin; Miller, Daniel; Di, Yanming; McPhail, Kerry L.; Spatafora, Joseph W.

2013-01-01

The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role of secondary metabolite gene clusters and their metabolites in fungal biology. PMID:23818858

Re-evaluation of the taxonomy of the Mitis group of the genus Streptococcus based on whole genome phylogenetic analyses, and proposed reclassification of Streptococcus dentisani as Streptococcus oralis subsp. dentisani comb. nov., Streptococcus tigurinus as Streptococcus oralis subsp. tigurinus comb. nov., and Streptococcus oligofermentans as a later synonym of Streptococcus cristatus.

PubMed

Jensen, Anders; Scholz, Christian F P; Kilian, Mogens

2016-11-01

The Mitis group of the genus Streptococcus currently comprises 20 species with validly published names, including the pathogen S. pneumoniae. They have been the subject of much taxonomic confusion, due to phenotypic overlap and genetic heterogeneity, which has hampered a full appreciation of their clinical significance. The purpose of this study was to critically re-examine the taxonomy of the Mitis group using 195 publicly available genomes, including designated type strains for phylogenetic analyses based on core genomes, multilocus sequences and 16S rRNA gene sequences, combined with estimates of average nucleotide identity (ANI) and in silico and in vitro analyses of specific phenotypic characteristics. Our core genomic phylogenetic analyses revealed distinct clades that, to some extent, and from the clustering of type strains represent known species. However, many of the genomes have been incorrectly identified adding to the current confusion. Furthermore, our data show that 16S rRNA gene sequences and ANI are unsuitable for identifying and circumscribing new species of the Mitis group of the genus Streptococci. Based on the clustering patterns resulting from core genome phylogenetic analysis, we conclude that S. oligofermentans is a later synonym of S. cristatus. The recently described strains of the species Streptococcus dentisani includes one previously referred to as 'S. mitis biovar 2'. Together with S. oralis, S. dentisani and S. tigurinus form subclusters within a coherent phylogenetic clade. We propose that the species S. oralis consists of three subspecies: S. oralis subsp. oralis subsp. nov., S. oralis subsp. tigurinus comb. nov., and S. oralis subsp. dentisani comb. nov.

A systematic review of cluster randomised trials in residential facilities for older people suggests how to improve quality.

PubMed

Diaz-Ordaz, Karla; Froud, Robert; Sheehan, Bart; Eldridge, Sandra

2013-10-22

Previous reviews of cluster randomised trials have been critical of the quality of the trials reviewed, but none has explored determinants of the quality of these trials in a specific field over an extended period of time. Recent work suggests that correct conduct and reporting of these trials may require more than published guidelines. In this review, our aim was to assess the quality of cluster randomised trials conducted in residential facilities for older people, and to determine whether (1) statistician involvement in the trial and (2) strength of journal endorsement of the Consolidated Standards of Reporting Trials (CONSORT) statement influence quality. We systematically identified trials randomising residential facilities for older people, or parts thereof, without language restrictions, up to the end of 2010, using National Library of Medicine (Medline) via PubMed and hand-searching. We based quality assessment criteria largely on the extended CONSORT statement for cluster randomised trials. We assessed statistician involvement based on statistician co-authorship, and strength of journal endorsement of the CONSORT statement from journal websites. 73 trials met our inclusion criteria. Of these, 20 (27%) reported accounting for clustering in sample size calculations and 54 (74%) in the analyses. In 29 trials (40%), methods used to identify/recruit participants were judged by us to have potentially caused bias or reporting was unclear to reach a conclusion. Some elements of quality improved over time but this appeared not to be related to the publication of the extended CONSORT statement for these trials. Trials with statistician/epidemiologist co-authors were more likely to account for clustering in sample size calculations (unadjusted odds ratio 5.4, 95% confidence interval 1.1 to 26.0) and analyses (unadjusted OR 3.2, 1.2 to 8.5). Journal endorsement of the CONSORT statement was not associated with trial quality. Despite international attempts to improve methods in cluster randomised trials, important quality limitations remain amongst these trials in residential facilities. Statistician involvement on trial teams may be more effective in promoting quality than further journal endorsement of the CONSORT statement. Funding bodies and journals should promote statistician involvement and co-authorship in addition to adherence to CONSORT guidelines.

Effectiveness of a multifaceted implementation strategy on physicians' referral behavior to an evidence-based psychosocial intervention in dementia: a cluster randomized controlled trial.

PubMed

Döpp, Carola M E; Graff, Maud J L; Teerenstra, Steven; Nijhuis-van der Sanden, Maria W G; Olde Rikkert, Marcel G M; Vernooij-Dassen, Myrra J F J

2013-05-30

To evaluate the effectiveness of a multifaceted implementation strategy on physicians' referral rate to and knowledge on the community occupational therapy in dementia program (COTiD program). A cluster randomized controlled trial with 28 experimental and 17 control clusters was conducted. Cluster included a minimum of one physician, one manager, and two occupational therapists. In the control group physicians and managers received no interventions and occupational therapists received a postgraduate course. In the experimental group physicians and managers had access to a website, received newsletters, and were approached by telephone. In addition, physicians were offered one outreach visit. In the experimental group occupational therapists received the postgraduate course, training days, outreach visits, regional meetings, and access to a reporting system. Main outcome measure was the number of COTiD referrals received by each cluster which was assessed at 6 and 12 months after the start of the intervention. Referrals were included from both participating physicians (enrolled in the study and received either the control or experimental intervention) and non-participating physicians (not enrolled but of whom referrals were received by participating occupational therapists). Mixed model analyses were used to analyze the data. All analyses were based on the principle of intention-to-treat. At 12 months experimental clusters received significantly more referrals with an average of 5,24 referrals (SD 5,75) to the COTiD program compared to 2,07 referrals in the control group (SD 5,14). The effect size at 12 months was 0.58. Although no difference in referral rate was found for the physicians participating in the study, the number of referrals from non-participating physicians (t -2,55 / 43 / 0,02) differed significantly at 12 months. Passive dissemination strategies are less likely to result in changes in professional behavior. The amount of physicians exposed to active strategies was limited. In spite of this we found a significant difference in the number of referrals which was accounted for by more referrals of non-participating physicians in the experimental clusters. We hypothesize that the increase in referrals was caused by an increase in occupational therapists' efforts to promote their services within their network. NCT01117285.

Classifying Autism Spectrum Disorders by ADI-R: Subtypes or Severity Gradient?

ERIC Educational Resources Information Center

Cholemkery, Hannah; Medda, Juliane; Lempp, Thomas; Freitag, Christine M.

2016-01-01

To reduce phenotypic heterogeneity of Autism spectrum disorders (ASD) and add to the current diagnostic discussion this study aimed at identifying clinically meaningful ASD subgroups. Cluster analyses were used to describe empirically derived groups based on the Autism Diagnostic Interview-revised (ADI-R) in a large sample of n = 463 individuals…

Relationship between Attitudes and Indicators of Obesity for Midlife Women

ERIC Educational Resources Information Center

Sudo, Noriko; Degeneffe, Dennis; Vue, Houa; Merkle, Emily; Kinsey, Jean; Ghosh, Koel; Reicks, Marla

2009-01-01

This study uses segmentation analyses to identify five distinct subgroups of U.S. midlife women (n = 200) based on their prevailing attitudes toward food and its preparation and consumption. Mean age of the women is 46 years and they are mostly White (86%), highly educated, and employed. Attitude segments (clusters of women sharing similar…

A Critical Mapping of Practice-Based Research as Evidenced by Swedish Architectural Theses

ERIC Educational Resources Information Center

Buchler, Daniela; Biggs, Michael A. R.; Stahl, Lars-Henrik

2011-01-01

This article presents an investigation that was funded by the Swedish Institute into the role of creative practice in architectural research as evidenced in Swedish doctoral theses. The sample was mapped and analysed in terms of clusters of interest, approaches, cultures of knowledge and uses of creative practice. This allowed the identification…

Applying Concept Mapping Methodology to Identify the Perceptions of Risk and Protective Factors for Childhood Obesity among Southeast Asian Refugees.

PubMed

Keita, Akilah Dulin; Whittaker, Shannon; Wynter, Jamila; Kidanu, Tamnnet Woldemichael; Chhay, Channavy; Cardel, Michelle; Gans, Kim M

2016-01-01

This study identifies Southeast Asian refugee parents' and grandparents' perceptions of the risk and protective factors for childhood obesity. We used a mixed methods approach (concept mapping) for data collection and analyses. Fifty-nine participants engaged in modified nominal group meetings where they generated statements about children's weight status and structuring meetings where they sorted statements into piles based on similarity and rated statements on relative importance. Concept Systems® software generated clusters of ideas, cluster ratings, and pattern matches. Eleven clusters emerged. Participants rated "Healthy Food Changes Made within the School" and "Parent-related Physical Activity Factors" as most important, whereas "Neighborhood Built Features" was rated as the least important. Cambodian and Hmong participants agreed the most on cluster ratings of relative importance (r = 0.62). The study findings may be used to inform the development of culturally appropriate obesity prevention interventions for Southeast Asian refugee communities.

Parallel and Scalable Clustering and Classification for Big Data in Geosciences

NASA Astrophysics Data System (ADS)

Riedel, M.

2015-12-01

Machine learning, data mining, and statistical computing are common techniques to perform analysis in earth sciences. This contribution will focus on two concrete and widely used data analytics methods suitable to analyse 'big data' in the context of geoscience use cases: clustering and classification. From the broad class of available clustering methods we focus on the density-based spatial clustering of appliactions with noise (DBSCAN) algorithm that enables the identification of outliers or interesting anomalies. A new open source parallel and scalable DBSCAN implementation will be discussed in the light of a scientific use case that detects water mixing events in the Koljoefjords. The second technique we cover is classification, with a focus set on the support vector machines algorithm (SVMs), as one of the best out-of-the-box classification algorithm. A parallel and scalable SVM implementation will be discussed in the light of a scientific use case in the field of remote sensing with 52 different classes of land cover types.

Including foreshocks and aftershocks in time-independent probabilistic seismic hazard analyses

USGS Publications Warehouse

Boyd, Oliver S.

2012-01-01

Time‐independent probabilistic seismic‐hazard analysis treats each source as being temporally and spatially independent; hence foreshocks and aftershocks, which are both spatially and temporally dependent on the mainshock, are removed from earthquake catalogs. Yet, intuitively, these earthquakes should be considered part of the seismic hazard, capable of producing damaging ground motions. In this study, I consider the mainshock and its dependents as a time‐independent cluster, each cluster being temporally and spatially independent from any other. The cluster has a recurrence time of the mainshock; and, by considering the earthquakes in the cluster as a union of events, dependent events have an opportunity to contribute to seismic ground motions and hazard. Based on the methods of the U.S. Geological Survey for a high‐hazard site, the inclusion of dependent events causes ground motions that are exceeded at probability levels of engineering interest to increase by about 10% but could be as high as 20% if variations in aftershock productivity can be accounted for reliably.

Ecological tolerances of Miocene larger benthic foraminifera from Indonesia

NASA Astrophysics Data System (ADS)

Novak, Vibor; Renema, Willem

2018-01-01

To provide a comprehensive palaeoenvironmental reconstruction based on larger benthic foraminifera (LBF), a quantitative analysis of their assemblage composition is needed. Besides microfacies analysis which includes environmental preferences of foraminiferal taxa, statistical analyses should also be employed. Therefore, detrended correspondence analysis and cluster analysis were performed on relative abundance data of identified LBF assemblages deposited in mixed carbonate-siliciclastic (MCS) systems and blue-water (BW) settings. Studied MCS system localities include ten sections from the central part of the Kutai Basin in East Kalimantan, ranging from late Burdigalian to Serravallian age. The BW samples were collected from eleven sections of the Bulu Formation on Central Java, dated as Serravallian. Results from detrended correspondence analysis reveal significant differences between these two environmental settings. Cluster analysis produced five clusters of samples; clusters 1 and 2 comprise dominantly MCS samples, clusters 3 and 4 with dominance of BW samples, and cluster 5 showing a mixed composition with both MCS and BW samples. The results of cluster analysis were afterwards subjected to indicator species analysis resulting in the interpretation that generated three groups among LBF taxa: typical assemblage indicators, regularly occurring taxa and rare taxa. By interpreting the results of detrended correspondence analysis, cluster analysis and indicator species analysis, along with environmental preferences of identified LBF taxa, a palaeoenvironmental model is proposed for the distribution of LBF in Miocene MCS systems and adjacent BW settings of Indonesia.

Infrared spectroscopy of phenol-(H2O)(n>10): structural strains in hydrogen bond networks of neutral water clusters.

PubMed

Mizuse, Kenta; Hamashima, Toru; Fujii, Asuka

2009-11-05

To investigate hydrogen bond network structures of tens of water molecules, we report infrared spectra of moderately size (n)-selected phenol-(H2O)n (approximately 10 < or = n < or = approximately 50), which have essentially the same network structures as (H2O)(n+1). The phenyl group in phenol-(H2O)(n) allows us to apply photoionization-based size selection and infrared-ultraviolet double resonance spectroscopy. The spectra show a clear low-frequency shift of the free OH stretching band with increasing n. Detailed analyses with density functional theory calculations indicate that this shift is accounted for by the hydrogen bond network development from highly strained ones in the small (n < approximately 10) clusters to more relaxed ones in the larger clusters, in addition to the cooperativity of hydrogen bonds.

Clusterentwicklung als regionale Verantwortung:. Volkswagen in Wolfsburg

NASA Astrophysics Data System (ADS)

Kiese, Matthias

2016-03-01

This contribution analyses the role of corporate regional responsibility (CRR) in cluster development, using the case of Volkswagen and its headquarter city Wolfsburg for illustration. The conceptual discussion of CRR and cluster development shows obvious synergies, as both the firm and the region benefit from the firm-led upgrading of the business environment. Recognising that their fate is mutually linked, Volkswagen started making strategic investment in its headquarter location in the late 1990s, based on a cluster concept. Despite apparent achievements in attracting suppliers and increasing the attractiveness and dynamism of the location, the company town's dependence on its dominant firm remains obvious. Wolfsburg thus provides a showcase for the congruence of interests between firm and city as a precondition for successful CRR, but its transferability appears confined to company towns dominated by a single employer.

WebStruct and VisualStruct: Web interfaces and visualization for Structure software implemented in a cluster environment.

PubMed

Jayashree, B; Rajgopal, S; Hoisington, D; Prasanth, V P; Chandra, S

2008-09-24

Structure, is a widely used software tool to investigate population genetic structure with multi-locus genotyping data. The software uses an iterative algorithm to group individuals into "K" clusters, representing possibly K genetically distinct subpopulations. The serial implementation of this programme is processor-intensive even with small datasets. We describe an implementation of the program within a parallel framework. Speedup was achieved by running different replicates and values of K on each node of the cluster. A web-based user-oriented GUI has been implemented in PHP, through which the user can specify input parameters for the programme. The number of processors to be used can be specified in the background command. A web-based visualization tool "Visualstruct", written in PHP (HTML and Java script embedded), allows for the graphical display of population clusters output from Structure, where each individual may be visualized as a line segment with K colors defining its possible genomic composition with respect to the K genetic sub-populations. The advantage over available programs is in the increased number of individuals that can be visualized. The analyses of real datasets indicate a speedup of up to four, when comparing the speed of execution on clusters of eight processors with the speed of execution on one desktop. The software package is freely available to interested users upon request.

A new physical performance classification system for elite handball players: cluster analysis

PubMed Central

Chirosa, Ignacio J.; Robinson, Joseph E.; van der Tillaar, Roland; Chirosa, Luis J.; Martín, Isidoro Martínez

2016-01-01

Abstract The aim of the present study was to identify different cluster groups of handball players according to their physical performance level assessed in a series of physical assessments, which could then be used to design a training program based on individual strengths and weaknesses, and to determine which of these variables best identified elite performance in a group of under-19 [U19] national level handball players. Players of the U19 National Handball team (n=16) performed a set of tests to determine: 10 m (ST10) and 20 m (ST20) sprint time, ball release velocity (BRv), countermovement jump (CMJ) height and squat jump (SJ) height. All players also performed an incremental-load bench press test to determine the 1 repetition maximum (1RMest), the load corresponding to maximum mean power (LoadMP), the mean propulsive phase power at LoadMP (PMPPMP) and the peak power at LoadMP (PPEAKMP). Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST20, 1RMest, PPEAKMP and PMPPMP. These variables could help coaches identify talent or monitor the physical performance of athletes in their team. Each cluster of players has a particular weakness related to physical performance and therefore, the cluster results can be applied to a specific training programmed based on individual needs. PMID:28149376

Cyclic Nanostructures of Tungsten Oxide (WO3) n   (n = 2-6) as NO x Gas Sensor: A Theoretical Study.

PubMed

Izadyar, Mohammad; Jamsaz, Azam

2014-01-01

Today's WO3-based gas sensors have received a lot of attention, because of important role as a sensitive layer for detection of the small quantities of  NO x . In this research, a theoretical study has been done on the sensing properties of different cyclic nanoclusters of (WO3) n   (n = 2-6) for NO x   (x = 1,2) gases. Based on the calculated adsorption energies by B3LYP and X3LYP functionals, from the different orientations of  NO x molecule on the tungsten oxide clusters, O-N⋯W was preferred. Different sizes of the mentioned clusters have been analyzed and W2O6 cluster was chosen as the best candidate for NO x detection from the energy viewpoint. Using the concepts of the chemical hardness and electronic charge transfer, some correlations between the energy of adsorption and interaction energy have been established. These analyses confirmed that the adsorption energy will be boosted with charge transfer enhancement. However, the chemical hardness relationship is reversed. Finally, obtained results from the natural bond orbital and electronic density of states analysis confirmed the electronic charge transfer from the adsorbates to WO3 clusters and Fermi level shifting after adsorption, respectively. The last parameter confirms that the cyclic clusters of tungsten oxide can be used as NO x gas sensors.

Cyclic Nanostructures of Tungsten Oxide (WO3)n  (n = 2–6) as NOx Gas Sensor: A Theoretical Study

PubMed Central

Izadyar, Mohammad; Jamsaz, Azam

2014-01-01

Today's WO3-based gas sensors have received a lot of attention, because of important role as a sensitive layer for detection of the small quantities of  NOx. In this research, a theoretical study has been done on the sensing properties of different cyclic nanoclusters of (WO3)n  (n = 2–6) for NOx  (x = 1,2) gases. Based on the calculated adsorption energies by B3LYP and X3LYP functionals, from the different orientations of  NOx molecule on the tungsten oxide clusters, O–N⋯W was preferred. Different sizes of the mentioned clusters have been analyzed and W2O6 cluster was chosen as the best candidate for NOx detection from the energy viewpoint. Using the concepts of the chemical hardness and electronic charge transfer, some correlations between the energy of adsorption and interaction energy have been established. These analyses confirmed that the adsorption energy will be boosted with charge transfer enhancement. However, the chemical hardness relationship is reversed. Finally, obtained results from the natural bond orbital and electronic density of states analysis confirmed the electronic charge transfer from the adsorbates to WO3 clusters and Fermi level shifting after adsorption, respectively. The last parameter confirms that the cyclic clusters of tungsten oxide can be used as NOx gas sensors. PMID:25544841

Whole-genome sequencing of Aspergillus tubingensis G131 and overview of its secondary metabolism potential.

PubMed

Choque, Elodie; Klopp, Christophe; Valiere, Sophie; Raynal, José; Mathieu, Florence

2018-03-15

Black Aspergilli represent one of the most important fungal resources of primary and secondary metabolites for biotechnological industry. Having several black Aspergilli sequenced genomes should allow targeting the production of certain metabolites with bioactive properties. In this study, we report the draft genome of a black Aspergilli, A. tubingensis G131, isolated from a French Mediterranean vineyard. This 35 Mb genome includes 10,994 predicted genes. A genomic-based discovery identifies 80 secondary metabolites biosynthetic gene clusters. Genomic sequences of these clusters were blasted on 3 chosen black Aspergilli genomes: A. tubingensis CBS 134.48, A. niger CBS 513.88 and A. kawachii IFO 4308. This comparison highlights different levels of clusters conservation between the four strains. It also allows identifying seven unique clusters in A. tubingensis G131. Moreover, the putative secondary metabolites clusters for asperazine and naphtho-gamma-pyrones production were proposed based on this genomic analysis. Key biosynthetic genes required for the production of 2 mycotoxins, ochratoxin A and fumonisin, are absent from this draft genome. Even if intergenic sequences of these mycotoxins biosynthetic pathways are present, this could not lead to the production of those mycotoxins by A. tubingensis G131. Functional and bioinformatics analyses of A. tubingensis G131 genome highlight its potential for metabolites production in particular for TAN-1612, asperazine and naphtho-gamma-pyrones presenting antioxidant, anticancer or antibiotic properties.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Patterns of breast cancer mortality trends in Europe.

PubMed

Amaro, Joana; Severo, Milton; Vilela, Sofia; Fonseca, Sérgio; Fontes, Filipa; La Vecchia, Carlo; Lunet, Nuno

2013-06-01

To identify patterns of variation in breast cancer mortality in Europe (1980-2010), using a model-based approach. Mortality data were obtained from the World Health Organization database and mixed models were used to describe the time trends in the age-standardized mortality rates (ASMR). Model-based clustering was used to identify clusters of countries with homogeneous variation in ASMR. Three patterns were identified. Patterns 1 and 2 are characterized by stable or slightly increasing trends in ASMR in the first half of the period analysed, and a clear decline is observed thereafter; in pattern 1 the median of the ASMR is higher, and the highest rates were achieved sooner. Pattern 3 is characterised by a rapid increase in mortality until 1999, declining slowly thereafter. This study provides a general model for the description and interpretation of the variation in breast cancer mortality in Europe, based in three main patterns. Copyright © 2013 Elsevier Ltd. All rights reserved.

A comprehensive HST BVI catalogue of star clusters in five Hickson compact groups of galaxies

NASA Astrophysics Data System (ADS)

Fedotov, K.; Gallagher, S. C.; Durrell, P. R.; Bastian, N.; Konstantopoulos, I. S.; Charlton, J.; Johnson, K. E.; Chandar, R.

2015-05-01

We present a photometric catalogue of star cluster candidates in Hickson compact groups (HCGs) 7, 31, 42, 59, and 92, based on observations with the Advanced Camera for Surveys and the Wide Field Camera 3 on the Hubble Space Telescope. The catalogue contains precise cluster positions (right ascension and declination), magnitudes, and colours in the BVI filters. The number of detected sources ranges from 2200 to 5600 per group, from which we construct the high-confidence sample by applying a number of criteria designed to reduce foreground and background contaminants. Furthermore, the high-confidence cluster candidates for each of the 16 galaxies in our sample are split into two subpopulations: one that may contain young star clusters and one that is dominated by globular older clusters. The ratio of young star cluster to globular cluster candidates varies from group to group, from equal numbers to the extreme of HCG 31 which has a ratio of 8 to 1, due to a recent starburst induced by interactions in the group. We find that the number of blue clusters with MV < -9 correlates well with the current star formation rate in an individual galaxy, while the number of globular cluster candidates with MV < -7.8 correlates well (though with large scatter) with the stellar mass. Analyses of the high-confidence sample presented in this paper show that star clusters can be successfully used to infer the gross star formation history of the host groups and therefore determine their placement in a proposed evolutionary sequence for compact galaxy groups.

Social network-based recruitment successfully reveals HIV-1 transmission networks among high-risk individuals in El Salvador.

PubMed

Dennis, Ann M; Murillo, Wendy; de Maria Hernandez, Flor; Guardado, Maria Elena; Nieto, Ana Isabel; Lorenzana de Rivera, Ivette; Eron, Joseph J; Paz-Bailey, Gabriela

2013-05-01

HIV in Central America is concentrated among certain groups such as men who have sex with men (MSM) and female sex workers (FSWs). We compared social recruitment chains and HIV transmission clusters from 699 MSM and 787 FSWs to better understand factors contributing to ongoing HIV transmission in El Salvador. Phylogenies were reconstructed using pol sequences from 119 HIV-positive individuals recruited by respondent-driven sampling (RDS) and compared with RDS chains in 3 cities in El Salvador. Transmission clusters with a mean pairwise genetic distance ≤ 0.015 and Bayesian posterior probabilities =1 were identified. Factors associated with cluster membership were evaluated among MSM. Sequences from 34 (43%) MSM and 4 (10%) FSW grouped in 14 transmission clusters. Clusters were defined by risk group (12 MSM clusters) and geographic residence (only 1 spanned separate cities). In 4 MSM clusters (all n = 2), individuals were also members of the same RDS chain, but only 2 had members directly linked through recruitment. All large clusters (n ≥ 3) spanned >1 RDS chain. Among MSM, factors independently associated with cluster membership included recent infection by BED assay (P = 0.02), sex with stable male partners (P = 0.02), and sex with ≥ 3 male partners in the past year (P = 0.04). We found few HIV transmissions corresponding directly with the social recruitment. However, we identified clustering in nearly one-half of MSM suggesting that RDS recruitment was indirectly but successfully uncovering transmission networks, particularly among recent infections. Interrogating RDS chains with phylogenetic analyses may help refine methods for identifying transmission clusters.

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.

The molecular epidemiology of HIV-1 in the Comunidad Valenciana (Spain): analysis of transmission clusters.

PubMed

Patiño-Galindo, Juan Ángel; Torres-Puente, Manoli; Bracho, María Alma; Alastrué, Ignacio; Juan, Amparo; Navarro, David; Galindo, María José; Ocete, Dolores; Ortega, Enrique; Gimeno, Concepción; Belda, Josefina; Domínguez, Victoria; Moreno, Rosario; González-Candelas, Fernando

2017-09-14

HIV infections are still a very serious concern for public heath worldwide. We have applied molecular evolution methods to study the HIV-1 epidemics in the Comunidad Valenciana (CV, Spain) from a public health surveillance perspective. For this, we analysed 1804 HIV-1 sequences comprising protease and reverse transcriptase (PR/RT) coding regions, sampled between 2004 and 2014. These sequences were subtyped and subjected to phylogenetic analyses in order to detect transmission clusters. In addition, univariate and multinomial comparisons were performed to detect epidemiological differences between HIV-1 subtypes, and risk groups. The HIV epidemic in the CV is dominated by subtype B infections among local men who have sex with men (MSM). 270 transmission clusters were identified (>57% of the dataset), 12 of which included ≥10 patients; 11 of subtype B (9 affecting MSMs) and one (n = 21) of CRF14, affecting predominately intravenous drug users (IDUs). Dated phylogenies revealed these large clusters to have originated from the mid-80s to the early 00 s. Subtype B is more likely to form transmission clusters than non-B variants and MSMs to cluster than other risk groups. Multinomial analyses revealed an association between non-B variants, which are not established in the local population yet, and different foreign groups.

Accounting for Multiple Births in Neonatal and Perinatal Trials: Systematic Review and Case Study

PubMed Central

Hibbs, Anna Maria; Black, Dennis; Palermo, Lisa; Cnaan, Avital; Luan, Xianqun; Truog, William E; Walsh, Michele C; Ballard, Roberta A

2010-01-01

Objectives To determine the prevalence in the neonatal literature of statistical approaches accounting for the unique clustering patterns of multiple births. To explore the sensitivity of an actual trial to several analytic approaches to multiples. Methods A systematic review of recent perinatal trials assessed the prevalence of studies accounting for clustering of multiples. The NO CLD trial served as a case study of the sensitivity of the outcome to several statistical strategies. We calculated odds ratios using non-clustered (logistic regression) and clustered (generalized estimating equations, multiple outputation) analyses. Results In the systematic review, most studies did not describe the randomization of twins and did not account for clustering. Of those studies that did, exclusion of multiples and generalized estimating equations were the most common strategies. The NO CLD study included 84 infants with a sibling enrolled in the study. Multiples were more likely than singletons to be white and were born to older mothers (p<0.01). Analyses that accounted for clustering were statistically significant; analyses assuming independence were not. Conclusions The statistical approach to multiples can influence the odds ratio and width of confidence intervals, thereby affecting the interpretation of a study outcome. A minority of perinatal studies address this issue. PMID:19969305

The cosmological analysis of X-ray cluster surveys. IV. Testing ASpiX with template-based cosmological simulations

NASA Astrophysics Data System (ADS)

Valotti, A.; Pierre, M.; Farahi, A.; Evrard, A.; Faccioli, L.; Sauvageot, J.-L.; Clerc, N.; Pacaud, F.

2018-06-01

Context. This paper is the fourth of a series evaluating the ASpiX cosmological method, based on X-ray diagrams, which are constructed from simple cluster observable quantities, namely: count rate (CR), hardness ratio (HR), core radius (rc), and redshift. Aims: Following extensive tests on analytical toy catalogues (Paper III), we present the results of a more realistic study over a 711 deg2 template-based maps derived from a cosmological simulation. Methods: Dark matter haloes from the Aardvark simulation have been ascribed luminosities, temperatures, and core radii, using local scaling relations and assuming self-similar evolution. The predicted X-ray sky-maps were converted into XMM event lists, using a detailed instrumental simulator. The XXL pipeline runs on the resulting sky images, produces an observed cluster catalogue over which the tests have been performed. This allowed us to investigate the relative power of various combinations of the CR, HR, rc, and redshift information. Two fitting methods were used: a traditional Markov chain Monte Carlo (MCMC) approach and a simple minimisation procedure (Amoeba) whose mean uncertainties are a posteriori evaluated by means of synthetic catalogues. The results were analysed and compared to the predictions from the Fisher analysis (FA). Results: For this particular catalogue realisation, assuming that the scaling relations are perfectly known, the CR-HR combination gives σ8 and Ωm at the 10% level, while CR-HR-rc-z improves this to ≤3%. Adding a second HR improves the results from the CR-HR1-rc combination, but to a lesser extent than when adding the redshift information. When all coefficients of the mass-temperature relation (M-T, including scatter) are also fitted, the cosmological parameters are constrained to within 5-10% and larger for the M-T coefficients (up to a factor of two for the scatter). The errors returned by the MCMC, those by Amoeba and the FA predictions are in most cases in excellent agreement and always within a factor of two. We also study the impact of the scatter of the mass-size relation (M-Rc) on the number of detected clusters: for the cluster typical sizes usually assumed, the larger the scatter, the lower the number of detected objects. Conclusions: The present study confirms and extends the trends outlined in our previous analyses, namely the power of X-ray observable diagrams to successfully and easily fit at the same time, the cosmological parameters, cluster physics, and the survey selection, by involving all detected clusters. The accuracy levels quoted should not be considered as definitive. A number of simplifying hypotheses were made for the testing purpose, but this should affect any method in the same way. The next publication will consider in greater detail the impact of cluster shapes (selection and measurements) and of cluster physics on the final error budget by means of hydrodynamical simulations.

Group sequential designs for stepped-wedge cluster randomised trials

PubMed Central

Grayling, Michael J; Wason, James MS; Mander, Adrian P

2017-01-01

Background/Aims: The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Methods: Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. Results: We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial’s type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. Conclusion: The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into stepped-wedge cluster randomised trials according to the needs of the particular trial. PMID:28653550

Group sequential designs for stepped-wedge cluster randomised trials.

PubMed

Grayling, Michael J; Wason, James Ms; Mander, Adrian P

2017-10-01

The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial's type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into stepped-wedge cluster randomised trials according to the needs of the particular trial.

Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Ulbrich, Sven; Karremann, Melanie K.; Stephenson, David B.; Economou, Theodoros; Shaffrey, Len C.

2016-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area in winter. Given appropriate large-scale conditions, the occurrence of such series (clusters) of storms may lead to large socio-economic impacts and cumulative losses. Recent studies analyzing Reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. This study explores the sensitivity of serial clustering to the choice of tracking method. With this aim, the IMILAST cyclone track database based on ERA-interim data is analysed. Clustering is estimated by the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid point over the Euro-Atlantic area. Results indicate that while the general pattern of clustering is identified for all methods, there are considerable differences in detail. This can primarily be attributed to the differences in the variance of cyclone counts between the methods, which range up to one order of magnitude. Nevertheless, clustering over the Eastern North Atlantic and Western Europe can be identified for all methods and can thus be generally considered as a robust feature. The statistical links between large-scale patterns like the NAO and clustering are obtained for all methods, though with different magnitudes. We conclude that the occurrence of cyclone clustering over the Eastern North Atlantic and Western Europe is largely independent from the choice of tracking method and hence from the definition of a cyclone.

A redshift survey of the strong-lensing cluster ABELL 383

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

Geller, Margaret J.; Hwang, Ho Seong; Kurtz, Michael J.

2014-03-01

Abell 383 is a famous rich cluster (z = 0.1887) imaged extensively as a basis for intensive strong- and weak-lensing studies. Nonetheless, there are few spectroscopic observations. We enable dynamical analyses by measuring 2360 new redshifts for galaxies with r {sub Petro} ≤ 20.5 and within 50' of the Brightest Cluster Galaxy (BCG; R.A.{sub 2000} = 42.°014125, decl.{sub 2000} = –03.°529228). We apply the caustic technique to identify 275 cluster members within 7 h {sup –1} Mpc of the hierarchical cluster center. The BCG lies within –11 ± 110 km s{sup –1} and 21 ± 56 h {sup –1} kpcmore » of the hierarchical cluster center; the velocity dispersion profile of the BCG appears to be an extension of the velocity dispersion profile based on cluster members. The distribution of cluster members on the sky corresponds impressively with the weak-lensing contours of Okabe et al. especially when the impact of foreground and background structure is included. The values of R {sub 200} = 1.22 ± 0.01 h {sup –1} Mpc and M {sub 200} = (5.07 ± 0.09) × 10{sup 14} h {sup –1} M {sub ☉} obtained by application of the caustic technique agree well with recent completely independent lensing measures. The caustic estimate extends direct measurement of the cluster mass profile to a radius of ∼5 h {sup –1} Mpc.« less

Identifying sighting clusters of endangered taxa with historical records.

PubMed

Duffy, Karl J

2011-04-01

The probability and time of extinction of taxa is often inferred from statistical analyses of historical records. Many of these analyses require the exclusion of multiple records within a unit of time (i.e., a month or a year). Nevertheless, spatially explicit, temporally aggregated data may be useful for identifying clusters of sightings (i.e., sighting clusters) in space and time. Identification of sighting clusters highlights changes in the historical recording of endangered taxa. I used two methods to identify sighting clusters in historical records: the Ederer-Myers-Mantel (EMM) test and the space-time permutation scan (STPS). I applied these methods to the spatially explicit sighting records of three species of orchids that are listed as endangered in the Republic of Ireland under the Wildlife Act (1976): Cephalanthera longifolia, Hammarbya paludosa, and Pseudorchis albida. Results with the EMM test were strongly affected by the choice of the time interval, and thus the number of temporal samples, used to examine the records. For example, sightings of P. albida clustered when the records were partitioned into 20-year temporal samples, but not when they were partitioned into 22-year temporal samples. Because the statistical power of EMM was low, it will not be useful when data are sparse. Nevertheless, the STPS identified regions that contained sighting clusters because it uses a flexible scanning window (defined by cylinders of varying size that move over the study area and evaluate the likelihood of clustering) to detect them, and it identified regions with high and regions with low rates of orchid sightings. The STPS analyses can be used to detect sighting clusters of endangered species that may be related to regions of extirpation and may assist in the categorization of threat status. ©2010 Society for Conservation Biology.

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

PubMed

Reynolds, Hannah T; Slot, Jason C; Divon, Hege H; Lysøe, Erik; Proctor, Robert H; Brown, Daren W

2017-08-01

In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6-10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

Evidence of new species for malaria vector Anopheles nuneztovari sensu lato in the Brazilian Amazon region.

PubMed

Scarpassa, Vera Margarete; Cunha-Machado, Antonio Saulo; Saraiva, José Ferreira

2016-04-12

Anopheles nuneztovari sensu lato comprises cryptic species in northern South America, and the Brazilian populations encompass distinct genetic lineages within the Brazilian Amazon region. This study investigated, based on two molecular markers, whether these lineages might actually deserve species status. Specimens were collected in five localities of the Brazilian Amazon, including Manaus, Careiro Castanho and Autazes, in the State of Amazonas; Tucuruí, in the State of Pará; and Abacate da Pedreira, in the State of Amapá, and analysed for the COI gene (Barcode region) and 12 microsatellite loci. Phylogenetic analyses were performed using the maximum likelihood (ML) approach. Intra and inter samples genetic diversity were estimated using population genetics analyses, and the genetic groups were identified by means of the ML, Bayesian and factorial correspondence analyses and the Bayesian analysis of population structure. The Barcode region dataset (N = 103) generated 27 haplotypes. The haplotype network suggested three lineages. The ML tree retrieved five monophyletic groups. Group I clustered all specimens from Manaus and Careiro Castanho, the majority of Autazes and a few from Abacate da Pedreira. Group II clustered most of the specimens from Abacate da Pedreira and a few from Autazes and Tucuruí. Group III clustered only specimens from Tucuruí (lineage III), strongly supported (97 %). Groups IV and V clustered specimens of A. nuneztovari s.s. and A. dunhami, strongly (98 %) and weakly (70 %) supported, respectively. In the second phylogenetic analysis, the sequences from GenBank, identified as A. goeldii, clustered to groups I and II, but not to group III. Genetic distances (Kimura-2 parameters) among the groups ranged from 1.60 % (between I and II) to 2.32 % (between I and III). Microsatellite data revealed very high intra-population genetic variability. Genetic distances showed the highest and significant values (P = 0.005) between Tucuruí and all the other samples, and between Abacate da Pedreira and all the other samples. Genetic distances, Bayesian (Structure and BAPS) analyses and FCA suggested three distinct biological groups, supporting the barcode region results. The two markers revealed three genetic lineages for A. nuneztovari s.l. in the Brazilian Amazon region. Lineages I and II may represent genetically distinct groups or species within A. goeldii. Lineage III may represent a new species, distinct from the A. goeldii group, and may be the most ancestral in the Brazilian Amazon. They may have differences in Plasmodium susceptibility and should therefore be investigated further.

Space-time cluster analysis of sea lice infestation (Caligus clemensi and Lepeophtheirus salmonis) on wild juvenile Pacific salmon in the Broughton Archipelago of Canada.

PubMed

Patanasatienkul, Thitiwan; Sanchez, Javier; Rees, Erin E; Pfeiffer, Dirk; Revie, Crawford W

2015-06-15

Sea lice infestation levels on wild chum and pink salmon in the Broughton Archipelago region are known to vary spatially and temporally; however, the locations of areas associated with a high infestation level had not been investigated yet. In the present study, the multivariate spatial scan statistic based on a Poisson model was used to assess spatial clustering of elevated sea lice (Caligus clemensi and Lepeophtheirus salmonis) infestation levels on wild chum and pink salmon sampled between March and July of 2004 to 2012 in the Broughton Archipelago and Knight Inlet regions of British Columbia, Canada. Three covariates, seine type (beach and purse seining), fish size, and year effect, were used to provide adjustment within the analyses. The analyses were carried out across the five months/datasets and between two fish species to assess the consistency of the identified clusters. Sea lice stages were explored separately for the early life stages (non-motile) and the late life stages of sea lice (motile). Spatial patterns in fish migration were also explored using monthly plots showing the average number of each fish species captured per sampling site. The results revealed three clusters for non-motile C. clemensi, two clusters for non-motile L. salmonis, and one cluster for the motile stage in each of the sea lice species. In general, the location and timing of clusters detected for both fish species were similar. Early in the season, the clusters of elevated sea lice infestation levels on wild fish are detected in areas closer to the rivers, with decreasing relative risks as the season progresses. Clusters were detected further from the estuaries later in the season, accompanied by increasing relative risks. In addition, the plots for fish migration exhibit similar patterns for both fish species in that, as expected, the juveniles move from the rivers toward the open ocean as the season progresses The identification of space-time clustering of infestation on wild fish from this study can help in targeting investigations of factors associated with these infestations and thereby support the development of more effective sea lice control measures. Copyright © 2015 Elsevier B.V. All rights reserved.

Analyses of amplified fragment length polymorphisms (AFLP) indicate rapid radiation of Diospyros species (Ebenaceae) endemic to New Caledonia

PubMed Central

2013-01-01

Background Radiation in some plant groups has occurred on islands and due to the characteristic rapid pace of phenotypic evolution, standard molecular markers often provide insufficient variation for phylogenetic reconstruction. To resolve relationships within a clade of 21 closely related New Caledonian Diospyros species and evaluate species boundaries we analysed genome-wide DNA variation via amplified fragment length polymorphisms (AFLP). Results A neighbour-joining (NJ) dendrogram based on Dice distances shows all species except D. minimifolia, D. parviflora and D. vieillardii to form unique clusters of genetically similar accessions. However, there was little variation between these species clusters, resulting in unresolved species relationships and a star-like general NJ topology. Correspondingly, analyses of molecular variance showed more variation within species than between them. A Bayesian analysis with BEAST produced a similar result. Another Bayesian method, this time a clustering method, Structure, demonstrated the presence of two groups, highly congruent with those observed in a principal coordinate analysis (PCO). Molecular divergence between the two groups is low and does not correspond to any hypothesised taxonomic, ecological or geographical patterns. Conclusions We hypothesise that such a pattern could have been produced by rapid and complex evolution involving a widespread progenitor for which an initial split into two groups was followed by subsequent fragmentation into many diverging populations, which was followed by range expansion of then divergent entities. Overall, this process resulted in an opportunistic pattern of phenotypic diversification. The time since divergence was probably insufficient for some species to become genetically well-differentiated, resulting in progenitor/derivative relationships being exhibited in a few cases. In other cases, our analyses may have revealed evidence for the existence of cryptic species, for which more study of morphology and ecology are now required. PMID:24330478

Genome-Wide Analysis of Type VI System Clusters and Effectors in Burkholderia Species.

PubMed

Nguyen, Thao Thi; Lee, Hyun-Hee; Park, Inmyoung; Seo, Young-Su

2018-02-01

Type VI secretion system (T6SS) has been discovered in a variety of gram-negative bacteria as a versatile weapon to stimulate the killing of eukaryotic cells or prokaryotic competitors. Type VI secretion effectors (T6SEs) are well known as key virulence factors for important pathogenic bacteria. In many Burkholderia species, T6SS has evolved as the most complicated secretion pathway with distinguished types to translocate diverse T6SEs, suggesting their essential roles in this genus. Here we attempted to detect and characterize T6SSs and potential T6SEs in target genomes of plant-associated and environmental Burkholderia species based on computational analyses. In total, 66 potential functional T6SS clusters were found in 30 target Burkholderia bacterial genomes, of which 33% possess three or four clusters. The core proteins in each cluster were specified and phylogenetic trees of three components (i.e., TssC, TssD, TssL) were constructed to elucidate the relationship among the identified T6SS clusters. Next, we identified 322 potential T6SEs in the target genomes based on homology searches and explored the important domains conserved in effector candidates. In addition, using the screening approach based on the profile hidden Markov model (pHMM) of T6SEs that possess markers for type VI effectors (MIX motif) (MIX T6SEs), 57 revealed proteins that were not included in training datasets were recognized as novel MIX T6SE candidates from the Burkholderia species. This approach could be useful to identify potential T6SEs from other bacterial genomes.

Cluster stability in the analysis of mass cytometry data.

PubMed

Melchiotti, Rossella; Gracio, Filipe; Kordasti, Shahram; Todd, Alan K; de Rinaldis, Emanuele

2017-01-01

Manual gating has been traditionally applied to cytometry data sets to identify cells based on protein expression. The advent of mass cytometry allows for a higher number of proteins to be simultaneously measured on cells, therefore providing a means to define cell clusters in a high dimensional expression space. This enhancement, whilst opening unprecedented opportunities for single cell-level analyses, makes the incremental replacement of manual gating with automated clustering a compelling need. To this aim many methods have been implemented and their successful applications demonstrated in different settings. However, the reproducibility of automatically generated clusters is proving challenging and an analytical framework to distinguish spurious clusters from more stable entities, and presumably more biologically relevant ones, is still missing. One way to estimate cell clusters' stability is the evaluation of their consistent re-occurrence within- and between-algorithms, a metric that is commonly used to evaluate results from gene expression. Herein we report the usage and importance of cluster stability evaluations, when applied to results generated from three popular clustering algorithms - SPADE, FLOCK and PhenoGraph - run on four different data sets. These algorithms were shown to generate clusters with various degrees of statistical stability, many of them being unstable. By comparing the results of automated clustering with manually gated populations, we illustrate how information on cluster stability can assist towards a more rigorous and informed interpretation of clustering results. We also explore the relationships between statistical stability and other properties such as clusters' compactness and isolation, demonstrating that whilst cluster stability is linked to other properties it cannot be reliably predicted by any of them. Our study proposes the introduction of cluster stability as a necessary checkpoint for cluster interpretation and contributes to the construction of a more systematic and standardized analytical framework for the assessment of cytometry clustering results. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Cortical thickness and prosocial behavior in school-age children: A population-based MRI study.

PubMed

Thijssen, Sandra; Wildeboer, Andrea; Muetzel, Ryan L; Bakermans-Kranenburg, Marian J; El Marroun, Hanan; Hofman, Albert; Jaddoe, Vincent W V; van der Lugt, Aad; Verhulst, Frank C; Tiemeier, Henning; van IJzendoorn, Marinus H; White, Tonya

2015-01-01

Prosocial behavior plays an important role in establishing and maintaining relationships with others and thus may have important developmental implications. This study examines the association between cortical thickness and prosocial behavior in a population-based sample of 6- to 9-year-old children. The present study was embedded within the Generation R Study. Magnetic resonance scans were acquired from 464 children whose parents had completed the prosocial scale of the Strengths and Difficulties Questionnaire. To study the association between cortical thickness and prosocial behavior, we performed whole-brain surface-based analyses. Prosocial behavior was related to a thicker cortex in a cluster that covers part of the left superior frontal and rostral middle frontal cortex (p < .001). Gender moderated the association between prosocial behavior and cortical thickness in a cluster including the right rostral middle frontal and superior frontal cortex (p < .001) as well as in a cluster covering the right superior parietal cortex, cuneus, and precuneus (p < .001). Our results suggest that prosocial behavior is associated with cortical thickness in regions related to theory of mind (superior frontal cortex, rostral middle frontal cortex cuneus, and precuneus) and inhibitory control (superior frontal and rostral middle frontal cortex).

Rapid identification and classification of bacteria by 16S rDNA restriction fragment melting curve analyses (RFMCA).

PubMed

Rudi, Knut; Kleiberg, Gro H; Heiberg, Ragnhild; Rosnes, Jan T

2007-08-01

The aim of this work was to evaluate restriction fragment melting curve analyses (RFMCA) as a novel approach for rapid classification of bacteria during food production. RFMCA was evaluated for bacteria isolated from sous vide food products, and raw materials used for sous vide production. We identified four major bacterial groups in the material analysed (cluster I-Streptococcus, cluster II-Carnobacterium/Bacillus, cluster III-Staphylococcus and cluster IV-Actinomycetales). The accuracy of RFMCA was evaluated by comparison with 16S rDNA sequencing. The strains satisfying the RFMCA quality filtering criteria (73%, n=57), with both 16S rDNA sequence information and RFMCA data (n=45) gave identical group assignments with the two methods. RFMCA enabled rapid and accurate classification of bacteria that is database compatible. Potential application of RFMCA in the food or pharmaceutical industry will include development of classification models for the bacteria expected in a given product, and then to build an RFMCA database as a part of the product quality control.

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.

Structural and electronic properties of Aun-xPtx (n = 2-14; x ⩽ n) clusters: The density functional theory investigation

NASA Astrophysics Data System (ADS)

Yuan, H. K.; Kuang, A. L.; Tian, C. L.; Chen, H.

2014-03-01

The structural evolutions and electronic properties of bimetallic Aun-xPtx (n = 2-14; x ⩽ n) clusters are investigated by using the density functional theory (DFT) with the generalized gradient approximation (GGA). The monatomic doping Aun-1Pt clusters are emphasized and compared with the corresponding pristine Aun clusters. The results reveal that the planar configurations are favored for both Aun-1Pt and Aun clusters with size up to n = 13, and the former often employ the substitution patterns based on the structures of the latter. The most stable clusters are Au6 and Au6Pt, which adopt regular planar triangle (D3h) and hexagon-ring (D6h) structures and can be regarded as the preferential building units in designing large clusters. For Pt-rich bimetallic clusters, their structures can be obtained from the substitution of Pt atoms by Au atoms from the Ptn structures, where Pt atoms assemble together and occupy the center yet Au atoms prefer the apex positions showing a segregation effect. With respect to pristine Au clusters, AunPt clusters exhibit somewhat weaker and less pronounced odd-even oscillations in the highest occupied and lowest unoccupied molecular-orbital gaps (HOMO-LUMO gap), electron affinity (EA), and ionization potential (IP) due to the partially released electron pairing effect. The analyses of electronic structure indicate that Pt atoms in AuPt clusters would delocalize their one 6s and one 5d electrons to contribute the electronic shell closure. The sp-d hybridizations as well as the d-d interactions between the host Au and dopant Pt atoms result in the enhanced stabilities of AuPt clusters.

The real population of star clusters in the bar of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Piatti, Andrés E.

2017-09-01

We report results on star clusters located in the south-eastern half of the Large Magellanic (LMC) bar from Washington CT1 photometry. Using appropriate kernel density estimators, we detected 73 star cluster candidates, three of which do not show any detectable trace of star cluster sequences in their colour-magnitude diagrams (CMDs). We did not detect the other 38 previously catalogued clusters, which could not be recognized when visually inspecting the C and T1 images either; the distribution of stars in their respective fields do not resemble that of a stellar aggregate. They represent 33 per cent of all catalogued objects located within the analysed LMC bar field. From matching theoretical isochrones to the cluster CMDs cleaned from field star contamination, we derived ages in the range 7.2 < log(t yr-1) < 10.1. As far as we are aware, this is the first time that homogeneous age estimates based on resolved stellar photometry are obtained for most of the studied clusters. We built the cluster frequency (CF) for the surveyed area, and found that the main star cluster formation activity has taken place during the period log(t yr-1) 8.0-9.0. Since 100 Myr ago, clusters have been formed during a few bursting formation episodes. When comparing the observed CF to that recovered from the star formation rate, we found noticeable differences, which suggests that field star and star cluster formation histories could have been significantly different. Photometric catalogues of the studied star clusters are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/606/A21

Spatio-temporal analysis of wildfire ignitions in the St. Johns River Water Management District, Florida

Treesearch

Marc G. Genton; David T. Butry; Marcia L. Gumpertz; Jeffrey P. Prestemon

2006-01-01

We analyse the spatio-temporal structure of wildfire ignitions in the St. Johns River Water Management District in north-eastern Florida. We show, using tools to analyse point patterns (e.g. the L-function), that wildfire events occur in clusters. Clustering of these events correlates with irregular distribution of fire ignitions, including lightning...

Symptoms and Symptom Clusters Identified by Adolescents and Young Adults With Cancer Using a Symptom Heuristics App.

PubMed

Ameringer, Suzanne; Erickson, Jeanne M; Macpherson, Catherine Fiona; Stegenga, Kristin; Linder, Lauri A

2015-12-01

Adolescents and young adults (AYAs) with cancer experience multiple distressing symptoms during treatment. Because the typical approach to symptom assessment does not easily reflect the symptom experience of individuals, alternative approaches to enhancing communication between the patient and provider are needed. We developed an iPad-based application that uses a heuristic approach to explore AYAs' cancer symptom experiences. In this mixed-methods descriptive study, 72 AYAs (13-29 years old) with cancer receiving myelosuppressive chemotherapy used the Computerized Symptom Capture Tool (C-SCAT) to create images of the symptoms and symptom clusters they experienced from a list of 30 symptoms. They answered open-ended questions within the C-SCAT about the causes of their symptoms and symptom clusters. The images generated through the C-SCAT and accompanying free-text data were analyzed using descriptive, content, and visual analyses. Most participants (n = 70) reported multiple symptoms (M = 8.14). The most frequently reported symptoms were nausea (65.3%), feeling drowsy (55.6%), lack of appetite (55.6%), and lack of energy (55.6%). Forty-six grouped their symptoms into one or more clusters. The most common symptom cluster was nausea/eating problems/appetite problems. Nausea was most frequently named as the priority symptom in a cluster and as a cause of other symptoms. Although common threads were present in the symptoms experienced by AYAs, the graphic images revealed unique perspectives and a range of complexity of symptom relationships, clusters, and causes. Results highlight the need for a tailored approach to symptom management based on how the AYA with cancer perceives his or her symptom experience. © 2015 Wiley Periodicals, Inc.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

ERIC Educational Resources Information Center

DiStefano, Christine; Kamphaus, R. W.

2006-01-01

Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…

Is Technology-Mediated Parental Monitoring Related to Adolescent Substance Use?

PubMed

Rudi, Jessie; Dworkin, Jodi

2018-01-03

Prevention researchers have identified parental monitoring leading to parental knowledge to be a protective factor against adolescent substance use. In today's digital society, parental monitoring can occur using technology-mediated communication methods, such as text messaging, email, and social networking sites. The current study aimed to identify patterns, or clusters, of in-person and technology-mediated monitoring behaviors, and examine differences between the patterns (clusters) in adolescent substance use. Cross-sectional survey data were collected from 289 parents of adolescents using Facebook and Amazon Mechanical Turk (MTurk). Cluster analyses were computed to identify patterns of in-person and technology-mediated monitoring behaviors, and chi-square analyses were computed to examine differences in substance use between the identified clusters. Three monitoring clusters were identified: a moderate in-person and moderate technology-mediated monitoring cluster (moderate-moderate), a high in-person and high technology-mediated monitoring cluster (high-high), and a high in-person and low technology-mediated monitoring cluster (high-low). Higher frequency of technology-mediated parental monitoring was not associated with lower levels of substance use. Results show that higher levels of technology-mediated parental monitoring may not be associated with adolescent substance use.

Spectrum syntheses of high-resolution integrated light spectra of Galactic globular clusters

NASA Astrophysics Data System (ADS)

Sakari, Charli M.; Shetrone, Matthew; Venn, Kim; McWilliam, Andrew; Dotter, Aaron

2013-09-01

Spectrum syntheses for three elements (Mg, Na and Eu) in high-resolution integrated light spectra of the Galactic globular clusters 47 Tuc, M3, M13, NGC 7006 and M15 are presented, along with calibration syntheses of the solar and Arcturus spectra. Iron abundances in the target clusters are also derived from integrated light equivalent width analyses. Line profiles in the spectra of these five globular clusters are well fitted after careful consideration of the atomic and molecular spectral features, providing levels of precision that are better than equivalent width analyses of the same integrated light spectra, and that are comparable to the precision in individual stellar analyses. The integrated light abundances from the 5528 and 5711 Å Mg I lines, the 6154 and 6160 Å Na I lines, and the 6645 Å Eu II line fall within the observed ranges from individual stars; however, these integrated light abundances do not always agree with the average literature abundances. Tests with the second parameter clusters M3, M13 and NGC 7006 show that assuming an incorrect horizontal branch morphology is likely to have only a small ( ≲ 0.06 dex) effect on these Mg, Na and Eu abundances. These tests therefore show that integrated light spectrum syntheses can be applied to unresolved globular clusters over a wide range of metallicities and horizontal branch morphologies. Such high precision in integrated light spectrum syntheses is valuable for interpreting the chemical abundances of globular cluster systems around other galaxies.

Spatial Autocorrelation of Cancer Incidence in Saudi Arabia

PubMed Central

Al-Ahmadi, Khalid; Al-Zahrani, Ali

2013-01-01

Little is known about the geographic distribution of common cancers in Saudi Arabia. We explored the spatial incidence patterns of common cancers in Saudi Arabia using spatial autocorrelation analyses, employing the global Moran’s I and Anselin’s local Moran’s I statistics to detect nonrandom incidence patterns. Global ordinary least squares (OLS) regression and local geographically-weighted regression (GWR) were applied to examine the spatial correlation of cancer incidences at the city level. Population-based records of cancers diagnosed between 1998 and 2004 were used. Male lung cancer and female breast cancer exhibited positive statistically significant global Moran’s I index values, indicating a tendency toward clustering. The Anselin’s local Moran’s I analyses revealed small significant clusters of lung cancer, prostate cancer and Hodgkin’s disease among males in the Eastern region and significant clusters of thyroid cancers in females in the Eastern and Riyadh regions. Additionally, both regression methods found significant associations among various cancers. For example, OLS and GWR revealed significant spatial associations among NHL, leukemia and Hodgkin’s disease (r² = 0.49–0.67 using OLS and r² = 0.52–0.68 using GWR) and between breast and prostate cancer (r² = 0.53 OLS and 0.57 GWR) in Saudi Arabian cities. These findings may help to generate etiologic hypotheses of cancer causation and identify spatial anomalies in cancer incidence in Saudi Arabia. Our findings should stimulate further research on the possible causes underlying these clusters and associations. PMID:24351742

Cluster analyses of association of weather, daily factors and emergent medical conditions.

PubMed

Malkić, Jasmin; Sarajlić, Nermin; Smrke, Barbara U R; Smrke, Dragica

2013-03-01

The goal of this study was to evaluate associations between the meteorological conditions and the number of emergency cases for five distinctive causes of dispatch groups reported to SOS dispatch centre in Uppsala, Sweden. Center's responsibility include alerting to 17 ambulances in whole Uppsala County, area of 8,209 km2 with around 320,000 inhabitants representing the target patient group. Source of the medical data for this study is the database of dispatch data for the year of 2009, while the metrological data have been provided from Uppsala University Department of Earth Sciences yearly weather report. Medical and meteorological data were summoned into the unified data space where each point represents a day with its weather parameters and dispatch cause group cardinality. DBSCAN data mining algorithm was implemented to five distinctive groups of dispatch causes after the data spaces have gone through the variance adjustment and the principal component analyses. As the result, several point clusters were discovered in each of the examined data spaces indicating the distinctive conditions regarding the weather and daily cardinality of the dispatch cause, as well as the associations between these two. Most interesting finding is that specific type of winter weather formed a cluster only around the days with the high count of breathing difficulties, while one of the summer weather clusters made similar association with the days with low number of cases. Findings were confirmed by confidence level estimation based on signal to noise ratio for the observed data points.

Hierarchical structure of the Sicilian goats revealed by Bayesian analyses of microsatellite information.

PubMed

Siwek, M; Finocchiaro, R; Curik, I; Portolano, B

2011-02-01

Genetic structure and relationship amongst the main goat populations in Sicily (Girgentana, Derivata di Siria, Maltese and Messinese) were analysed using information from 19 microsatellite markers genotyped on 173 individuals. A posterior Bayesian approach implemented in the program STRUCTURE revealed a hierarchical structure with two clusters at the first level (Girgentana vs. Messinese, Derivata di Siria and Maltese), explaining 4.8% of variation (amovaФ(ST) estimate). Seven clusters nested within these first two clusters (further differentiations of Girgentana, Derivata di Siria and Maltese), explaining 8.5% of variation (amovaФ(SC) estimate). The analyses and methods applied in this study indicate their power to detect subtle population structure. © 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.

A Multivariate Model and Analysis of Competitive Strategy in the U.S. Hardwood Lumber Industry

Treesearch

Robert J. Bush; Steven A. Sinclair

1991-01-01

Business-level competitive strategy in the hardwood lumber industry was modeled through the identification of strategic groups among large U.S. hardwood lumber producers. Strategy was operationalized using a measure based on the variables developed by Dess and Davis (1984). Factor and cluster analyses were used to define strategic groups along the dimensions of cost...

Frequency and Proximity Clustering Analyses for Georeferencing Toponyms and Points-of-Interest Names from a Travel Journal

ERIC Educational Resources Information Center

McDermott, Scott D.

2017-01-01

This research study uses geographic information retrieval (GIR) to georeference toponyms and points-of-interest (POI) names from a travel journal. Travel journals are an ideal data source with which to conduct this study because they are significant accounts specific to the author's experience, and contain geographic instances based on the…

The Lung Microbiome in Moderate and Severe Chronic Obstructive Pulmonary Disease

PubMed Central

Pragman, Alexa A.; Kim, Hyeun Bum; Reilly, Cavan S.; Wendt, Christine; Isaacson, Richard E.

2012-01-01

Chronic obstructive pulmonary disease (COPD) is an inflammatory disorder characterized by incompletely reversible airflow obstruction. Bacterial infection of the lower respiratory tract contributes to approximately 50% of COPD exacerbations. Even during periods of stable lung function, the lung harbors a community of bacteria, termed the microbiome. The role of the lung microbiome in the pathogenesis of COPD remains unknown. The COPD lung microbiome, like the healthy lung microbiome, appears to reflect microaspiration of oral microflora. Here we describe the COPD lung microbiome of 22 patients with Moderate or Severe COPD compared to 10 healthy control patients. The composition of the lung microbiomes was determined using 454 pyrosequencing of 16S rDNA found in bronchoalveolar lavage fluid. Sequences were analyzed using mothur, Ribosomal Database Project, Fast UniFrac, and Metastats. Our results showed a significant increase in microbial diversity with the development of COPD. The main phyla in all samples were Actinobacteria, Firmicutes, and Proteobacteria. Principal coordinate analyses demonstrated separation of control and COPD samples, but samples did not cluster based on disease severity. However, samples did cluster based on the use of inhaled corticosteroids and inhaled bronchodilators. Metastats analyses demonstrated an increased abundance of several oral bacteria in COPD samples. PMID:23071781

The Xenon Test Chamber Q-SUN® for testing realistic tolerances of fungi exposed to simulated full spectrum solar radiation.

PubMed

Dias, Luciana P; Araújo, Claudinéia A S; Pupin, Breno; Ferreira, Paulo C; Braga, Gilberto Ú L; Rangel, Drauzio E N

2018-06-01

The low survival of insect-pathogenic fungi when used for insect control in agriculture is mainly due to the deleterious effects of ultraviolet radiation and heat from solar irradiation. In this study, conidia of 15 species of entomopathogenic fungi were exposed to simulated full-spectrum solar radiation emitted by a Xenon Test Chamber Q-SUN XE-3-HC 340S (Q-LAB ® Corporation, Westlake, OH, USA), which very closely simulates full-spectrum solar radiation. A dendrogram obtained from cluster analyses, based on lethal time 50 % and 90 % calculated by Probit analyses, separated the fungi into three clusters: cluster 3 contains species with highest tolerance to simulated full-spectrum solar radiation, included Metarhizium acridum, Cladosporium herbarum, and Trichothecium roseum with LT 50  > 200 min irradiation. Cluster 2 contains eight species with moderate UV tolerance: Aschersonia aleyrodis, Isaria fumosorosea, Mariannaea pruinosa, Metarhizium anisopliae, Metarhizium brunneum, Metarhizium robertsii, Simplicillium lanosoniveum, and Torrubiella homopterorum with LT 50 between 120 and 150 min irradiation. The four species in cluster 1 had the lowest UV tolerance: Lecanicillium aphanocladii, Beauveria bassiana, Tolypocladium cylindrosporum, and Tolypocladium inflatum with LT 50  < 120 min irradiation. The QSUN Xenon Test Chamber XE3 is often used by the pharmaceutical and automotive industry to test light stability and weathering, respectively, but it was never used to evaluate fungal tolerance to full-spectrum solar radiation before. We conclude that the equipment provided an excellent tool for testing realistic tolerances of fungi to full-spectrum solar radiation of microbial agents for insect biological control in agriculture. Copyright © 2018 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

A model-based cluster analysis of social experiences in clinically anxious youth: links to emotional functioning.

PubMed

Suveg, Cynthia; Jacob, Marni L; Whitehead, Monica; Jones, Anna; Kingery, Julie Newman

2014-01-01

Social difficulties are commonly associated with anxiety disorders in youth, yet are not well specified in the literature. The aim of this study was to identify patterns of social experiences in clinically anxious children and examine the associations with indices of emotional functioning. A model-based cluster analysis was conducted on parent-, teacher-, and child-reports of social experiences with 64 children, ages 7-12 years (M = 8.86 years, SD = 1.59 years; 60.3% boys; 85.7% Caucasian) with a primary diagnosis of separation anxiety disorder, social phobia, and/or generalized anxiety disorder. Follow-up analyses examined cluster differences on indices of emotional functioning. Findings yielded three clusters of social experiences that were unrelated to diagnosis: (1) Unaware Children (elevated scores on parent- and teacher-reports of social difficulties but relatively low scores on child-reports, n = 12), (2) Average Functioning (relatively average scores across all informants, n = 44), and (3) Victimized and Lonely (elevated child-reports of overt and relational victimization and loneliness and relatively low scores on parent- and teacher-reports of social difficulties, n = 8). Youth in the Unaware Children cluster were rated as more emotionally dysregulated by teachers and had a greater number of diagnoses than youth in the Average Functioning group. In contrast, the Victimized and Lonely group self-reported greater frequency of negative affect and reluctance to share emotional experiences than the Average Functioning cluster. Overall, this study demonstrates that social maladjustment in clinically anxious children can manifest in a variety of ways and assessment should include multiple informants and methods.

Neuropsychological phenotypes among men with and without HIV disease in the multicenter AIDS cohort study.

PubMed

Molsberry, Samantha A; Cheng, Yu; Kingsley, Lawrence; Jacobson, Lisa; Levine, Andrew J; Martin, Eileen; Miller, Eric N; Munro, Cynthia A; Ragin, Ann; Sacktor, Ned; Becker, James T

2018-05-11

Mild forms of HIV-associated neurocognitive disorder (HAND) remain prevalent in the combination anti-retroviral therapy (cART) era. This study's objective was to identify neuropsychological subgroups within the Multicenter AIDS Cohort Study (MACS) based on the participant-based latent structure of cognitive function and to identify factors associated with subgroups. The MACS is a four-site longitudinal study of the natural and treated history of HIV disease among gay and bisexual men. Using neuropsychological domain scores we used a cluster variable selection algorithm to identify the optimal subset of domains with cluster information. Latent profile analysis was applied using scores from identified domains. Exploratory and post-hoc analyses were conducted to identify factors associated with cluster membership and the drivers of the observed associations. Cluster variable selection identified all domains as containing cluster information except for Working Memory. A three-profile solution produced the best fit for the data. Profile 1 performed below average on all domains, Profile 2 performed average on executive functioning, motor, and speed and below average on learning and memory, Profile 3 performed at or above average across all domains. Several demographic, cognitive, and social factors were associated with profile membership; these associations were driven by differences between Profile 1 and the other profiles. There is an identifiable pattern of neuropsychological performance among MACS members determined by all domains except Working Memory. Neither HIV nor HIV-related biomarkers were related with cluster membership, consistent with other findings that cognitive performance patterns do not map directly onto HIV serostatus.

Acculturation and School Adjustment of Immigrant Youth in Six European Countries: Findings from the Programme for International Student Assessment (PISA).

PubMed

Schachner, Maja K; He, Jia; Heizmann, Boris; Van de Vijver, Fons J R

2017-01-01

School adjustment determines long-term adjustment in society. Yet, immigrant youth do better in some countries than in others. Drawing on acculturation research (Berry, 1997; Ward, 2001) and self-determination theory (Ryan and Deci, 2000), we investigated indirect effects of adolescent immigrants' acculturation orientations on school adjustment (school-related attitudes, truancy, and mathematics achievement) through school belonging. Analyses were based on data from the Programme for International Student Assessment from six European countries, which were combined into three clusters based on their migrant integration and multicultural policies: Those with the most supportive policies (Belgium and Finland), those with moderately supportive policies (Italy and Portugal), and those with the most unsupportive policies (Denmark and Slovenia). In a multigroup path model, we confirmed most associations. As expected, mainstream orientation predicted higher belonging and better outcomes in all clusters, whereas the added value of students' ethnic orientation was only observed in some clusters. Results are discussed in terms of differences in acculturative climate and policies between countries of settlement.

Electric bistability induced by incorporating self-assembled monolayers/aggregated clusters of azobenzene derivatives in pentacene-based thin-film transistors.

PubMed

Tseng, Chiao-Wei; Huang, Ding-Chi; Tao, Yu-Tai

2012-10-24

Composite films of pentacene and a series of azobenzene derivatives are prepared and used as the active channel material in top-contact, bottom-gate field-effect transistors. The transistors exhibit high field-effect mobility as well as large I-V hysteresis as a function of the gate bias history. The azobenzene moieties, incorporated either in the form of self-assembled monolayer or discrete multilayer clusters at the dielectric surface, result in electric bistability of the pentacene-based transistor either by photoexcitation or gate biasing. The direction of threshold voltage shifts, size of hysteresis, response time, and retention characteristics all strongly depend on the substituent on the benzene ring. The results show that introducing a monolayer of azobenzene moieties results in formation of charge carrier traps responsible for slower switching between the bistable states and longer retention time. With clusters of azobenzene moieties as the trap sites, the switching is faster but the retention is shorter. Detailed film structure analyses and correlation with the transistor/memory properties of these devices are provided.

Phenetic Comparison of Prokaryotic Genomes Using k-mers

PubMed Central

Déraspe, Maxime; Raymond, Frédéric; Boisvert, Sébastien; Culley, Alexander; Roy, Paul H.; Laviolette, François; Corbeil, Jacques

2017-01-01

Abstract Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets. PMID:28957508

Gender differences in psychiatric disorders and clusters of self-esteem among detained adolescents.

PubMed

Van Damme, Lore; Colins, Olivier F; Vanderplasschen, Wouter

2014-12-30

Detained minors display substantial mental health needs. This study focused on two features (psychopathology and self-esteem) that have received considerable attention in the literature and clinical work, but have rarely been studied simultaneously in detained youths. The aims of this study were to examine gender differences in psychiatric disorders and clusters of self-esteem, and to test the hypothesis that the cluster of adolescents with lower (versus higher) levels of self-esteem have higher rates of psychiatric disorders. The prevalence of psychiatric disorders was assessed in 440 Belgian, detained adolescents using the Diagnostic Interview Schedule for Children-IV. Self-esteem was assessed using the Self-perception Profile for Adolescents. Model-based cluster analyses were performed to identify youths with lower and/or higher levels of self-esteem across several domains. Girls have higher rates for most psychiatric disorders and lower levels of self-esteem than boys. A higher number of clusters was identified in boys (four) than girls (three). Generally, the cluster of adolescents with lower (versus higher) levels of self-esteem had a higher prevalence of psychiatric disorders. These results suggest that the detection of low levels of self-esteem in adolescents, especially girls, might help clinicians to identify a subgroup of detained adolescents with the highest prevalence of psychopathology.

A guide to enterotypes across the human body: meta-analysis of microbial community structures in human microbiome datasets.

PubMed

Koren, Omry; Knights, Dan; Gonzalez, Antonio; Waldron, Levi; Segata, Nicola; Knight, Rob; Huttenhower, Curtis; Ley, Ruth E

2013-01-01

Recent analyses of human-associated bacterial diversity have categorized individuals into 'enterotypes' or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes.

A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets

PubMed Central

Waldron, Levi; Segata, Nicola; Knight, Rob; Huttenhower, Curtis; Ley, Ruth E.

2013-01-01

Recent analyses of human-associated bacterial diversity have categorized individuals into ‘enterotypes’ or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes. PMID:23326225

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.

Critical thinking in higher education: The influence of teaching styles and peer collaboration on science and math learning

NASA Astrophysics Data System (ADS)

Quitadamo, Ian Joseph

Many higher education faculty perceive a deficiency in students' ability to reason, evaluate, and make informed judgments, skills that are deemed necessary for academic and job success in science and math. These skills, often collected within a domain called critical thinking (CT), have been studied and are thought to be influenced by teaching styles (the combination of beliefs, behavior, and attitudes used when teaching) and small group collaborative learning (SGCL). However, no existing studies show teaching styles and SGCL cause changes in student CT performance. This study determined how combinations of teaching styles called clusters and peer-facilitated SGCL (a specific form of SGCL) affect changes in undergraduate student CT performance using a quasi-experimental pre-test/post-test research design and valid and reliable CT performance indicators. Quantitative analyses of three teaching style cluster models (Grasha's cluster model, a weighted cluster model, and a student-centered/teacher-centered cluster model) and peer-facilitated SGCL were performed to evaluate their ability to cause measurable changes in student CT skills. Based on results that indicated weighted teaching style clusters and peer-facilitated SGCL are associated with significant changes in student CT, we conclude that teaching styles and peer-facilitated SGCL influence the development of undergraduate CT in higher education science and math.

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

PubMed Central

2013-01-01

Background There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage. PMID:24314148

Modifiable lifestyle behavior patterns, sedentary time and physical activity contexts: a cluster analysis among middle school boys and girls in the SALTA study.

PubMed

Marques, Elisa A; Pizarro, Andreia N; Figueiredo, Pedro; Mota, Jorge; Santos, Maria P

2013-06-01

To analyze how modifiable health-related variables are clustered and associated with children's participation in play, active travel and structured exercise and sport among boys and girls. Data were collected from 9 middle-schools in Porto (Portugal) area. A total of 636 children in the 6th grade (340 girls and 296 boys) with a mean age of 11.64 years old participated in the study. Cluster analyses were used to identify patterns of lifestyle and healthy/unhealthy behaviors. Multinomial logistic regression analysis was used to estimate associations between cluster allocation, sedentary time and participation in three different physical activity (PA) contexts: play, active travel, and structured exercise/sport. Four distinct clusters were identified based on four lifestyle risk factors. The most disadvantaged cluster was characterized by high body mass index, low high-density lipoprotein cholesterol and cardiorespiratory fitness and a moderate level of moderate to vigorous PA. Everyday outdoor play (OR=1.85, 95%CI 0.318-0.915) and structured exercise/sport (OR=1.85, 95%CI 0.291-0.990) were associated with healthier lifestyle patterns. There were no significant associations between health patterns and sedentary time or travel mode. Outdoor play and sport/exercise participation seem more important than active travel from school in influencing children's healthy cluster profiles. Copyright © 2013 Elsevier Inc. All rights reserved.

Cognitive Clusters in Specific Learning Disorder.

PubMed

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.

Computational nano-material design of exotic luminescent materials based upon europium doped gallium nitrides

NASA Astrophysics Data System (ADS)

Masago, Akira; Fukushima, Tetsuya; Sato, Kazunori; Katayama-Yoshida, Hiroshi

2015-03-01

Eu-doped GaN has attracted much attention, because the red light luminescence ability provides us with expectations to realize monolithic full-color LEDs, which work on seamless conditions such as substrates, electrodes, and operating bias voltages. Toward implementation of multifunctional activity into the luminescent materials using the spinodal nano-structures, we investigate atomic configurations and magnetic structures of the GaN crystal codoped with Eu, Mg, Si, O, and/or the vacancies using the density functional method (DFT) calculations. Our calculations show that the impurity clusterized distributions are energetically favorable more than the homogeneous distribution. Moreover, analyses of the formation energy and binding energy suggest that the clusterized distributions are spontaneously formed by the nano-spinodal decomposition. Though the host matrix has no magnetic moments, the cluster has finite magnetic moments, where Zener's p-f exchange interaction works between the Eu f-state and the nearby N p-states.

Do peritraumatic emotions differentially predict PTSD symptom clusters? Initial evidence for emotion specificity.

PubMed

Dewey, Daniel; Schuldberg, David; Madathil, Renee

2014-08-01

This study investigated whether specific peritraumatic emotions differentially predict PTSD symptom clusters in individuals who have experienced stressful life events. Hypotheses were developed based on the SPAARS model of PTSD. It was predicted that the peritraumatic emotions of anger, disgust, guilt, and fear would significantly predict re-experiencing and avoidance symptoms, while only fear would predict hyperarousal. Undergraduate students (N = 144) participated in this study by completing a packet of self-report questionnaires. Multiple regression analyses were conducted with PCL-S symptom cluster scores as dependent variables and peritraumatic fear, guilt, anger, shame, and disgust as predictor variables. As hypothesized, peritraumatic anger, guilt, and fear all significantly predicted re-experiencing. However, only fear predicted avoidance, and anger significantly predicted hyperarousal. Results are discussed in relation to the theoretical role of emotions in the etiology of PTSD following the experience of a stressful life event.

Turbulent Reconnection Rates from Cluster Observations in the Magnetosheath

NASA Technical Reports Server (NTRS)

Wendel, Deirdre

2011-01-01

The role of turbulence in producing fast reconnection rates is an important unresolved question. Scant in situ analyses exist. We apply multiple spacecraft techniques to a case of nonlinear turbulent reconnection in the magnetosheath to test various theoretical results for turbulent reconnection rates. To date, in situ estimates of the contribution of turbulence to reconnection rates have been calculated from an effective electric field derived through linear wave theory. However, estimates of reconnection rates based on fully nonlinear turbulence theories and simulations exist that are amenable to multiple spacecraft analyses. Here we present the linear and nonlinear theories and apply some of the nonlinear rates to Cluster observations of reconnecting, turbulent current sheets in the magnetosheath. We compare the results to the net reconnection rate found from the inflow speed. Ultimately, we intend to test and compare linear and nonlinear estimates of the turbulent contribution to reconnection rates and to measure the relative contributions of turbulence and the Hall effect.

Turbulent Reconnection Rates from Cluster Observations in the Magneto sheath

NASA Technical Reports Server (NTRS)

Wendel, Deirdre

2011-01-01

The role of turbulence in producing fast reconnection rates is an important unresolved question. Scant in situ analyses exist. We apply multiple spacecraft techniques to a case of nonlinear turbulent reconnection in the magnetosheath to test various theoretical results for turbulent reconnection rates. To date, in situ estimates of the contribution of turbulence to reconnection rates have been calculated from an effective electric field derived through linear wave theory. However, estimates of reconnection rates based on fully nonlinear turbulence theories and simulations exist that are amenable to multiple spacecraft analyses. Here we present the linear and nonlinear theories and apply some of the nonlinear rates to Cluster observations of reconnecting, turbulent current sheets in the magnetos heath. We compare the results to the net reconnection rate found from the inflow speed. Ultimately, we intend to test and compare linear and nonlinear estimates of the turbulent contribution to reconnection rates and to measure the relative contributions of turbulence and the Hall effect.

On the question of fractal packing structure in metallic glasses

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

Ding, Jun; Asta, Mark; Ritchie, Robert O.

2017-07-25

This work addresses the long-standing debate over fractal models of packing structure in metallic glasses (MGs). Through detailed fractal and percolation analyses of MG structures, derived from simulations spanning a range of compositions and quenching rates, we conclude that there is no fractal atomic-level structure associated with the packing of all atoms or solute-centered clusters. The results are in contradiction with conclusions derived from previous studies based on analyses of shifts in radial distribution function and structure factor peaks associated with volume changes induced by pressure and compositional variations. Here in this paper, the interpretation of such shifts is shownmore » to be challenged by the heterogeneous nature of MG structure and deformation at the atomic scale. Moreover, our analysis in the present work illustrates clearly the percolation theory applied to MGs, for example, the percolation threshold and characteristics of percolation clusters formed by subsets of atoms, which can have important consequences for structure–property relationships in these amorphous materials.« less

Quark cluster model for deep-inelastic lepton-deuteron scattering

NASA Astrophysics Data System (ADS)

Yen, G.; Vary, J. P.; Harindranath, A.; Pirner, H. J.

1990-10-01

We evaluate the contribution of quasifree nucleon knockout and of inelastic lepton-nucleon scattering in inclusive electron-deuteron reactions at large momentum transfer. We examine the degree of quantitative agreement with deuteron wave functions from the Reid soft-core and Bonn realistic nucleon-nucleon interactions. For the range of data available there is strong sensitivity to the tensor correlations which are distinctively different in these two deuteron models. At this stage of the analyses the Reid soft-core wave function provides a reasonable description of the data while the Bonn wave function does not. We then include a six-quark cluster component whose relative contribution is based on an overlap criterion and obtain a good description of all the data with both interactions. The critical separation at which overlap occurs (formation of six-quark clusters) is taken to be 1.0 fm and the six-quark cluster probability is 4.7% for Reid and 5.4% for Bonn. As a consequence the quark cluster model with either Reid or Bonn wave function describe the SLAC inclusive electron-deuteron scattering data equally well. We then show how additional data would be decisive in resolving which model is ultimately more correct.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

A simple algorithm for the identification of clinical COPD phenotypes.

PubMed

Burgel, Pierre-Régis; Paillasseur, Jean-Louis; Janssens, Wim; Piquet, Jacques; Ter Riet, Gerben; Garcia-Aymerich, Judith; Cosio, Borja; Bakke, Per; Puhan, Milo A; Langhammer, Arnulf; Alfageme, Inmaculada; Almagro, Pere; Ancochea, Julio; Celli, Bartolome R; Casanova, Ciro; de-Torres, Juan P; Decramer, Marc; Echazarreta, Andrés; Esteban, Cristobal; Gomez Punter, Rosa Mar; Han, MeiLan K; Johannessen, Ane; Kaiser, Bernhard; Lamprecht, Bernd; Lange, Peter; Leivseth, Linda; Marin, Jose M; Martin, Francis; Martinez-Camblor, Pablo; Miravitlles, Marc; Oga, Toru; Sofia Ramírez, Ana; Sin, Don D; Sobradillo, Patricia; Soler-Cataluña, Juan J; Turner, Alice M; Verdu Rivera, Francisco Javier; Soriano, Joan B; Roche, Nicolas

2017-11-01

This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative.Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV 1 , dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV 1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years).A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes. Copyright ©ERS 2017.

How to engage occupational physicians in recruitment of research participants: a mixed-methods study of challenges and opportunities.

PubMed

Arends, Iris; Bültmann, Ute; Shaw, William S; van Rhenen, Willem; Roelen, Corné; Nielsen, Karina; van der Klink, Jac J L

2014-03-01

To investigate barriers and facilitators for research participant recruitment by occupational physicians (OPs). A mixed-methods approach was used. Focus groups and interviews were conducted with OPs to explore perceived barriers and facilitators for recruitment. Based on data of a cluster-randomised controlled trial (cluster-RCT), univariate and multivariate analyses were conducted to investigate associations between OPs' personal and work characteristics and the number of recruited participants for the cluster-RCT per OP. Perceived barriers and facilitators for recruitment were categorised into: study characteristics (e.g. concise inclusion criteria); study population characteristics; OP's attention; OP's workload; context (e.g. working at different locations); and OP's characteristics (e.g. motivated to help). Important facilitators were encouragement by colleagues and reminders by information technology tools. Multivariate analyses showed that the number of OPs within the clinical unit who recruited participants was positively associated with the number of recruited participants per OP [rate ratio of 1.43, 95 % confidence interval 1.24-1.64]. When mobilising OPs for participant recruitment, researchers need to engage entire clinical units rather than approach OPs on an individual basis. OPs consider regular communication, especially face-to-face contact and information technology tools serving as reminders, as helpful.

Carrying the pain of abuse: gender-specific findings on the relationship between childhood physical abuse and obesity in adulthood.

PubMed

Fuller-Thomson, Esme; Sinclair, Deborah A; Brennenstuhl, Sarah

2013-01-01

Childhood abuse has been associated with negative adult health outcomes, including obesity. This study sought to investigate the association between childhood physical abuse and adult obesity, while controlling for five clusters of potentially confounding factors: childhood stressors, socioeconomic indicators, marital status, health behaviors, and mental health. Representative data from the 2005 Canadian Community Health Survey were selected. The response rate was approximately 84%. Gender-specific logistic regression analyses determined the association between abuse and obesity, while controlling for age and race and five clusters of potentially confounding factors. Of the 12,590 respondents with complete data, 2,787 were obese and 976 reported physical abuse as a child or adolescent by someone close to them. Among women with childhood physical abuse compared to no abuse, the odds of obesity were 35% higher, even when controlling for age, race, and the five clusters of factors (odds ratio (OR) = 1.35; 95% confidence interval (CI) = 1.09, 1.67). Childhood physical abuse was not associated with adult obesity among men (OR = 1.12; 95% CI = 0.82, 1.53). This study provides one of the first population-based, gender-specific analyses of the association between childhood physical abuse and obesity controlling for a wide range of factors. The gender-specific findings require further exploration.

Clusters of midlife women by physical activity and their racial/ethnic differences.

PubMed

Im, Eun-Ok; Ko, Young; Chee, Eunice; Chee, Wonshik; Mao, Jun James

2017-04-01

The purpose of this study was to identify clusters of midlife women by physical activity and to determine racial/ethnic differences in physical activities in each cluster. This was a secondary analysis of the data from 542 women (157 non-Hispanic [NH] Whites, 127 Hispanics, 135 NH African Americans, and 123 NH Asian) in a larger Internet study on midlife women's attitudes toward physical activity. The instruments included the Barriers to Health Activities Scale, the Physical Activity Assessment Inventory, the Questions on Attitudes toward Physical Activity, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention, and the Kaiser Physical Activity Survey. The data were analyzed using hierarchical cluster analyses, analysis of variance, and multinominal logistic analyses. A three-cluster solution was adopted: cluster 1 (high active living and sports/exercise activity group; 48%), cluster 2 (high household/caregiving and occupational activity group; 27%), and cluster 3 (low active living and sports/exercise activity group; 26%). There were significant racial/ethnic differences in occupational activities of clusters 1 and 3 (all P < 0.01). Compared with cluster 1, cluster 2 tended to have lower family income, less access to health care, higher unemployment, higher perceived barriers scores, and lower social influences scores (all P < 0.01). Compared with cluster 1, cluster 3 tended to have greater obesity, less access to health care, higher perceived barriers scores, more negative attitudes toward physical activity, and lower self-efficacy scores (all P < 0.01). Midlife women's unique patterns of physical activity and their associated factors need to be considered in future intervention development.

Clusters of Midlife Women by Physical Activity and Their Racial/Ethnic Differences

PubMed Central

Im, Eun-Ok; Ko, Young; Chee, Eunice; Chee, Wonshik; Mao, Jun James

2016-01-01

Objective The purpose of this study was to identify clusters of midlife women by physical activity and to determine racial/ethnic differences in physical activities in each cluster. Methods This was a secondary analysis of the data from 542 women (157 Non-Hispanic [NH] Whites, 127 Hispanics, 135 NH African Americans, and 123 NH Asian) in a larger Internet study on midlife women’s attitudes toward physical activity. The instruments included the Barriers to Health Activities Scale, the Physical Activity Assessment Inventory, the Questions on Attitudes toward Physical Activity, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention, and the Kaiser Physical Activity Survey. The data were analyzed using hierarchical cluster analyses, ANOVA, and multinominal logistic analyses. Results A three cluster solution was adopted: Cluster 1 (high active living and sports/exercise activity group; 48%), Cluster 2 (high household/caregiving and occupational activity group; 27%), and Cluster 3 (low active living and sports/exercise activity group; 26%). There were significant racial/ethnic differences in occupational activities of Clusters 1 and 3 (all p<.01). Compared with Cluster 1, Cluster 2 tended to have lower family income, less access to health care, higher unemployment, higher perceived barriers scores, and lower social influences scores (all p<.01). Compared with Cluster 1, Cluster 3 tended to have greater obesity, less access to health care, higher perceived barriers scores, more negative attutides toward physical activity, and lower self-efficacy scores (all p<.01). Conclusions Midlife women’s unique patterns of physical activity and their associated factors need to be considered in future intervention development. PMID:27846052

Automated recognition of microcalcification clusters in mammograms

NASA Astrophysics Data System (ADS)

Bankman, Isaac N.; Christens-Barry, William A.; Kim, Dong W.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-07-01

The widespread and increasing use of mammographic screening for early breast cancer detection is placing a significant strain on clinical radiologists. Large numbers of radiographic films have to be visually interpreted in fine detail to determine the subtle hallmarks of cancer that may be present. We developed an algorithm for detecting microcalcification clusters, the most common and useful signs of early, potentially curable breast cancer. We describe this algorithm, which utilizes contour map representations of digitized mammographic films, and discuss its benefits in overcoming difficulties often encountered in algorithmic approaches to radiographic image processing. We present experimental analyses of mammographic films employing this contour-based algorithm and discuss practical issues relevant to its use in an automated film interpretation instrument.

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

PubMed

Robertson, A Gordon; Kim, Jaegil; Al-Ahmadie, Hikmat; Bellmunt, Joaquim; Guo, Guangwu; Cherniack, Andrew D; Hinoue, Toshinori; Laird, Peter W; Hoadley, Katherine A; Akbani, Rehan; Castro, Mauro A A; Gibb, Ewan A; Kanchi, Rupa S; Gordenin, Dmitry A; Shukla, Sachet A; Sanchez-Vega, Francisco; Hansel, Donna E; Czerniak, Bogdan A; Reuter, Victor E; Su, Xiaoping; de Sa Carvalho, Benilton; Chagas, Vinicius S; Mungall, Karen L; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Lu, Yiling; Klimczak, Leszek J; Zhang, Jiexin; Choo, Caleb; Ojesina, Akinyemi I; Bullman, Susan; Leraas, Kristen M; Lichtenberg, Tara M; Wu, Catherine J; Schultz, Nicholaus; Getz, Gad; Meyerson, Matthew; Mills, Gordon B; McConkey, David J; Weinstein, John N; Kwiatkowski, David J; Lerner, Seth P

2017-10-19

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments. Copyright © 2017 Elsevier Inc. All rights reserved.

Analyses of genetic diversity of bacterial blight pathogen, Xanthomonas oryzae pv. oryzae using IS1112 in Bangladesh.

PubMed

Islam, Md Rashidul; Alam, Md Samiul; Khan, Ashik Iqbal; Hossain, Ismail; Adam, Lorne R; Daayf, Fouad

2016-01-01

Bacterial blight (BB) is caused by Xanthomonas oryzae pv. oryzae (Xoo), a most destructive disease of rice, mostly in Asia, including Bangladesh. Altogether 96 isolates of Xoo were collected from 19 rice-growing districts of Bangladesh in both the rain-fed and irrigated seasons of 2014 to assess their pathotypic and genetic variation. Pathotypic analyses were carried out on a set of 12 Near Isogenic Lines (NILs) of rice containing a single resistance gene and two check varieties IR24 and TN1 by the leaf clipping inoculation method. A total of 24 pathotypes were identified based on their virulence patterns on the NILs tested. Among these, pathotypes VII, XII and XIV, considered as major, containing a maximum number of isolates (9.38% each), are frequently distributed in seven northern to mid-eastern districts of Bangladesh. The most virulent pathotype I was recorded in the Habiganj and Brahmanbaria districts. The molecular analysis of variability among the isolates was carried out through PCR analysis using multi-locus primers Jel1 and Jel2 (based on the repetitive element IS1112 in the Xoo genome). Using the genotypic data, a dendrogram was constructed with 17 clusters along with 17 molecular haplotypes at the 65% similarity index. Cluster I was composed of 46 isolates considered as major, whereas clusters X, XI, XII and XVII were represented by a single isolate. A phenogram was constructed based on virulence to interpret the relationship between the pathotypes and the molecular haplotypes. At the 50% similarity level, among 10 clusters, cluster I, considered as major, consisted of a maximum of 10 pathotypes out of 24. In case of haplotypes, a maximum of 7 haplotypes were obtained from pathotype XII, whereas pathotypes IX, X, XV, XXII and XXIV were represented by a single haplotype. However, the present study revealed that different isolates belonging to the same pathotypes belonged to different haplotypes. Conversely, genetically similar haplotypes were also detected from different pathotypes collected from separate districts. This relationship appeared due to a high degree of DNA polymorphism among strains within many pathotypes existing in Bangladesh. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Spatial event cluster detection using an approximate normal distribution.

PubMed

Torabi, Mahmoud; Rosychuk, Rhonda J

2008-12-12

In geographic surveillance of disease, areas with large numbers of disease cases are to be identified so that investigations of the causes of high disease rates can be pursued. Areas with high rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. Typically cluster detection tests are applied to incident or prevalent cases of disease, but surveillance of disease-related events, where an individual may have multiple events, may also be of interest. Previously, a compound Poisson approach that detects clusters of events by testing individual areas that may be combined with their neighbours has been proposed. However, the relevant probabilities from the compound Poisson distribution are obtained from a recursion relation that can be cumbersome if the number of events are large or analyses by strata are performed. We propose a simpler approach that uses an approximate normal distribution. This method is very easy to implement and is applicable to situations where the population sizes are large and the population distribution by important strata may differ by area. We demonstrate the approach on pediatric self-inflicted injury presentations to emergency departments and compare the results for probabilities based on the recursion and the normal approach. We also implement a Monte Carlo simulation to study the performance of the proposed approach. In a self-inflicted injury data example, the normal approach identifies twelve out of thirteen of the same clusters as the compound Poisson approach, noting that the compound Poisson method detects twelve significant clusters in total. Through simulation studies, the normal approach well approximates the compound Poisson approach for a variety of different population sizes and case and event thresholds. A drawback of the compound Poisson approach is that the relevant probabilities must be determined through a recursion relation and such calculations can be computationally intensive if the cluster size is relatively large or if analyses are conducted with strata variables. On the other hand, the normal approach is very flexible, easily implemented, and hence, more appealing for users. Moreover, the concepts may be more easily conveyed to non-statisticians interested in understanding the methodology associated with cluster detection test results.

A new Self-Adaptive disPatching System for local clusters

NASA Astrophysics Data System (ADS)

Kan, Bowen; Shi, Jingyan; Lei, Xiaofeng

2015-12-01

The scheduler is one of the most important components of a high performance cluster. This paper introduces a self-adaptive dispatching system (SAPS) based on Torque[1] and Maui[2]. It promotes cluster resource utilization and improves the overall speed of tasks. It provides some extra functions for administrators and users. First of all, in order to allow the scheduling of GPUs, a GPU scheduling module based on Torque and Maui has been developed. Second, SAPS analyses the relationship between the number of queueing jobs and the idle job slots, and then tunes the priority of users’ jobs dynamically. This means more jobs run and fewer job slots are idle. Third, integrating with the monitoring function, SAPS excludes nodes in error states as detected by the monitor, and returns them to the cluster after the nodes have recovered. In addition, SAPS provides a series of function modules including a batch monitoring management module, a comprehensive scheduling accounting module and a real-time alarm module. The aim of SAPS is to enhance the reliability and stability of Torque and Maui. Currently, SAPS has been running stably on a local cluster at IHEP (Institute of High Energy Physics, Chinese Academy of Sciences), with more than 12,000 cpu cores and 50,000 jobs running each day. Monitoring has shown that resource utilization has been improved by more than 26%, and the management work for both administrator and users has been reduced greatly.

Detecting space-time cancer clusters using residential histories

NASA Astrophysics Data System (ADS)

Jacquez, Geoffrey M.; Meliker, Jaymie R.

2007-04-01

Methods for analyzing geographic clusters of disease typically ignore the space-time variability inherent in epidemiologic datasets, do not adequately account for known risk factors (e.g., smoking and education) or covariates (e.g., age, gender, and race), and do not permit investigation of the latency window between exposure and disease. Our research group recently developed Q-statistics for evaluating space-time clustering in cancer case-control studies with residential histories. This technique relies on time-dependent nearest neighbor relationships to examine clustering at any moment in the life-course of the residential histories of cases relative to that of controls. In addition, in place of the widely used null hypothesis of spatial randomness, each individual's probability of being a case is instead based on his/her risk factors and covariates. Case-control clusters will be presented using residential histories of 220 bladder cancer cases and 440 controls in Michigan. In preliminary analyses of this dataset, smoking, age, gender, race and education were sufficient to explain the majority of the clustering of residential histories of the cases. Clusters of unexplained risk, however, were identified surrounding the business address histories of 10 industries that emit known or suspected bladder cancer carcinogens. The clustering of 5 of these industries began in the 1970's and persisted through the 1990's. This systematic approach for evaluating space-time clustering has the potential to generate novel hypotheses about environmental risk factors. These methods may be extended to detect differences in space-time patterns of any two groups of people, making them valuable for security intelligence and surveillance operations.

The use of hierarchical clustering for the design of optimized monitoring networks

NASA Astrophysics Data System (ADS)

Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

2018-05-01

Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different sampling methodologies as well as outliers (stations' time series which are markedly different from all others in a given dataset).

Frequency and Proximity Clustering Analyses for Georeferencing Toponyms and Points-of-Interest Names from a Travel Journal

NASA Astrophysics Data System (ADS)

McDermott, Scott D.

This research study uses geographic information retrieval (GIR) to georeference toponyms and points-of-interest (POI) names from a travel journal. Travel journals are an ideal data source with which to conduct this study because they are significant accounts specific to the author's experience, and contain geographic instances based on the experiences made at a specific time and location along a traversed route of a trip. Using a travel journal, toponyms and POI names are georeferenced to locate where the author visited or what the author observed along a travel path. GIR relies on algorithms to maximize the georeferencing of spatially sensitive data while minimizing issues related to semantic ambiguities, which can incorrectly place geographic content due to shared names by other geographic or non-geographic contents. Frequency analysis and proximity clustering are used to minimize semantic ambiguities and georeference the toponyms and POI names to their correct locations. Frequency analysis identifies the primary and adjacent state names for each chapter of the travel journal, which act as containers for the subsequent toponyms and POI names. Proximity clustering groups the toponyms and POI names based on the distance to the cluster group's centroid. A cluster group with a significant number of toponyms and POI names contains the placenames that are more relevant to the travel journal. The use of frequency and proximity clustering analyses narrows the geographic scope to select states and identify the toponyms and POI names that exist along the travel path. The reliability measurements for this dissertation yield a precision rate of 88 percent and a recall rate of 30 percent. The precision rate is comparable to similar peer-reviewed studies and shows that this dissertation can assist in the GIR process. Obstacles and issues in this research study include name matching errors between the travel journal, geoparser, and gazetteers; temporal disassociations between the time the journal was written and the time this dissertation was conducted; omissions of POI names from the gazetteers; and incorrect tagging by the geoparser. Future studies are needed to provide better name matching between the travel journal, geoparser, and gazetteers and on managing POI names to become integral to the GIR process.

Genomic and Transcriptomic Analyses to Identify Pathways Involved in Nanoparticle Generation in the Ubiquitous Marine Bacterium Alteromonas macleodii Under Elevated Copper Conditions

NASA Astrophysics Data System (ADS)

Cusick, K. D.; Dale, J.; Little, B.; Cockrell, A.; Biffinger, J.

2016-02-01

Alteromonas macleodii is a ubiquitous marine bacterium that clusters by molecular analyses into two ecotypes: surface and deep-water. Our group isolated a marine bacterium from copper coupons that generates nanoparticles (NPs) at elevated copper concentrations. Sequencing of the 16S rRNA gene identified it as an A. macleodii strain. In phylogenetic analyses based on the gyrB gene, it clustered with other surface isolates; however, it formed a unique cluster separate from that of other surface isolates based on rpoB gene sequences. Copper is commonly employed as an antifouling agent on the hulls of ships, and so copper tolerance and NP generation is under investigation in this strain. The overall goals of this study were: (1) to determine if copper tolerance is the result of changes at the genetic or transcriptional level and (2) to identify the genes involved in NP formation. Sub-cultures were established from the initial isolate in which copper concentrations were increased in .25 mM increments through multiple generations. These sub-cultures were assayed for NP formation in seawater medium supplemented with 3-4 mM copper. Scanning electron microscopy revealed large aggregates of NPs on the exterior surface of all sub-cultures. Additionally, a portion of the cells in all sub-cultures displayed an elongated morphology in comparison to the wild-type. No NPs were observed in wild-type controls grown without the addition of increased copper. Metagenomic sequencing of natural populations of A. macleodii revealed extreme divergence in several large genomic regions whose content includes genes coding for exopolysaccharide production and metal resistance. High-throughput sequencing is being used to determine whether copper tolerance and NP generation is the result of genetic or transcriptional changes. These results will be extended to natural communities to gain insights into the role of bacterial NPs during conditions of elevated metal concentrations in coastal systems.

Clustering of attitudes towards obesity: a mixed methods study of Australian parents and children

PubMed Central

2013-01-01

Background Current population-based anti-obesity campaigns often target individuals based on either weight or socio-demographic characteristics, and give a ‘mass’ message about personal responsibility. There is a recognition that attempts to influence attitudes and opinions may be more effective if they resonate with the beliefs that different groups have about the causes of, and solutions for, obesity. Limited research has explored how attitudinal factors may inform the development of both upstream and downstream social marketing initiatives. Methods Computer-assisted face-to-face interviews were conducted with 159 parents and 184 of their children (aged 9–18 years old) in two Australian states. A mixed methods approach was used to assess attitudes towards obesity, and elucidate why different groups held various attitudes towards obesity. Participants were quantitatively assessed on eight dimensions relating to the severity and extent, causes and responsibility, possible remedies, and messaging strategies. Cluster analysis was used to determine attitudinal clusters. Participants were also able to qualify each answer. Qualitative responses were analysed both within and across attitudinal clusters using a constant comparative method. Results Three clusters were identified. Concerned Internalisers (27% of the sample) judged that obesity was a serious health problem, that Australia had among the highest levels of obesity in the world and that prevalence was rapidly increasing. They situated the causes and remedies for the obesity crisis in individual choices. Concerned Externalisers (38% of the sample) held similar views about the severity and extent of the obesity crisis. However, they saw responsibility and remedies as a societal rather than an individual issue. The final cluster, the Moderates, which contained significantly more children and males, believed that obesity was not such an important public health issue, and judged the extent of obesity to be less extreme than the other clusters. Conclusion Attitudinal clusters provide new information and insights which may be useful in tailoring anti-obesity social marketing initiatives. PMID:24119724

Clustering of attitudes towards obesity: a mixed methods study of Australian parents and children.

PubMed

Olds, Tim; Thomas, Samantha; Lewis, Sophie; Petkov, John

2013-10-12

Current population-based anti-obesity campaigns often target individuals based on either weight or socio-demographic characteristics, and give a 'mass' message about personal responsibility. There is a recognition that attempts to influence attitudes and opinions may be more effective if they resonate with the beliefs that different groups have about the causes of, and solutions for, obesity. Limited research has explored how attitudinal factors may inform the development of both upstream and downstream social marketing initiatives. Computer-assisted face-to-face interviews were conducted with 159 parents and 184 of their children (aged 9-18 years old) in two Australian states. A mixed methods approach was used to assess attitudes towards obesity, and elucidate why different groups held various attitudes towards obesity. Participants were quantitatively assessed on eight dimensions relating to the severity and extent, causes and responsibility, possible remedies, and messaging strategies. Cluster analysis was used to determine attitudinal clusters. Participants were also able to qualify each answer. Qualitative responses were analysed both within and across attitudinal clusters using a constant comparative method. Three clusters were identified. Concerned Internalisers (27% of the sample) judged that obesity was a serious health problem, that Australia had among the highest levels of obesity in the world and that prevalence was rapidly increasing. They situated the causes and remedies for the obesity crisis in individual choices. Concerned Externalisers (38% of the sample) held similar views about the severity and extent of the obesity crisis. However, they saw responsibility and remedies as a societal rather than an individual issue. The final cluster, the Moderates, which contained significantly more children and males, believed that obesity was not such an important public health issue, and judged the extent of obesity to be less extreme than the other clusters. Attitudinal clusters provide new information and insights which may be useful in tailoring anti-obesity social marketing initiatives.

The shape of galaxy dark matter halos in massive galaxy clusters: Insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-04-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and VLT/MUSE spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z=0.397, M(R < 200 kpc)=1.6×1014M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar halos are allowed, the model improves by 35%. This technique may provide a new way to investigate the processes and timescales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

Molecular epidemiology demonstrated three emerging clusters of human immunodeficiency virus type 1 subtype B infection in Hong Kong.

PubMed

Leung, Tommy W C; Mak, Darwin; Wong, K H; Wang, Y; Song, Y H; Tsang, D N C; Wong, C; Shao, Y M; Lim, W L

2008-07-01

We conducted a molecular epidemiological study on newly diagnosed human immunodeficiency virus type 1 (HIV-1)-infected patients in Hong Kong to identify the epidemiological linkage of HIV-1 infection in the locality. Reverse transcription polymerase chain reaction (RT-PCR) for HIV-1 was performed on newly diagnosed HIV-1-positive sera collected from January 2002 to December 2006. PCR products correspond to the env C2V3V4 region and gag p17/p24 junction of the HIV-1 genome were nucleotide sequenced. Phylogenetic analyses performed on the acquired nucleotide sequences revealed that CRF01_AE and subtype B were the two dominant HIV-1 subtypes. Analyses also demonstrated the presence of three emerging HIV-1 clusters among the subtype B sequences in Hong Kong. Individual cluster possesses a unique cluster-specific amino acid signature for identification. Data show that one of the clusters (Cluster I) is rapidly expanding. In addition to the unique cluster-specific amino acid signature, the majority of sequences in Cluster I harbor a 6-amino acid insertion at the gag p17/p24 junction in a region that is thought to be closely associated with HIV-1 infectivity.

The shape of galaxy dark matter haloes in massive galaxy clusters: insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-07-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and Very Large Telescope/Multi Unit Spectroscopic Explorer spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z = 0.397, M(R < 200 kpc) = 1.6 × 1014 M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar haloes are allowed, the model improves by 35 per cent. This technique may provide a new way to investigate the processes and time-scales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

Resolving Recent Plant Radiations: Power and Robustness of Genotyping-by-Sequencing.

PubMed

Fernández-Mazuecos, Mario; Mellers, Greg; Vigalondo, Beatriz; Sáez, Llorenç; Vargas, Pablo; Glover, Beverley J

2018-03-01

Disentangling species boundaries and phylogenetic relationships within recent evolutionary radiations is a challenge due to the poor morphological differentiation and low genetic divergence between species, frequently accompanied by phenotypic convergence, interspecific gene flow and incomplete lineage sorting. Here we employed a genotyping-by-sequencing (GBS) approach, in combination with morphometric analyses, to investigate a small western Mediterranean clade in the flowering plant genus Linaria that radiated in the Quaternary. After confirming the morphological and genetic distinctness of eight species, we evaluated the relative performances of concatenation and coalescent methods to resolve phylogenetic relationships. Specifically, we focused on assessing the robustness of both approaches to variations in the parameter used to estimate sequence homology (clustering threshold). Concatenation analyses suffered from strong systematic bias, as revealed by the high statistical support for multiple alternative topologies depending on clustering threshold values. By contrast, topologies produced by two coalescent-based methods (NJ$_{\\mathrm{st}}$, SVDquartets) were robust to variations in the clustering threshold. Reticulate evolution may partly explain incongruences between NJ$_{\\mathrm{st}}$, SVDquartets and concatenated trees. Integration of morphometric and coalescent-based phylogenetic results revealed (i) extensive morphological divergence associated with recent splits between geographically close or sympatric sister species and (ii) morphological convergence in geographically disjunct species. These patterns are particularly true for floral traits related to pollinator specialization, including nectar spur length, tube width and corolla color, suggesting pollinator-driven diversification. Given its relatively simple and inexpensive implementation, GBS is a promising technique for the phylogenetic and systematic study of recent radiations, but care must be taken to evaluate the robustness of results to variation of data assembly parameters.

Computational solution of spike overlapping using data-based subtraction algorithms to resolve synchronous sympathetic nerve discharge

PubMed Central

Su, Chun-Kuei; Chiang, Chia-Hsun; Lee, Chia-Ming; Fan, Yu-Pei; Ho, Chiu-Ming; Shyu, Liang-Yu

2013-01-01

Sympathetic nerves conveying central commands to regulate visceral functions often display activities in synchronous bursts. To understand how individual fibers fire synchronously, we establish “oligofiber recording techniques” to record “several” nerve fiber activities simultaneously, using in vitro splanchnic sympathetic nerve–thoracic spinal cord preparations of neonatal rats as experimental models. While distinct spike potentials were easily recorded from collagenase-dissociated sympathetic fibers, a problem arising from synchronous nerve discharges is a higher incidence of complex waveforms resulted from spike overlapping. Because commercial softwares do not provide an explicit solution for spike overlapping, a series of custom-made LabVIEW programs incorporated with MATLAB scripts was therefore written for spike sorting. Spikes were represented as data points after waveform feature extraction and automatically grouped by k-means clustering followed by principal component analysis (PCA) to verify their waveform homogeneity. For dissimilar waveforms with exceeding Hotelling's T2 distances from the cluster centroids, a unique data-based subtraction algorithm (SA) was used to determine if they were the complex waveforms resulted from superimposing a spike pattern close to the cluster centroid with the other signals that could be observed in original recordings. In comparisons with commercial software, higher accuracy was achieved by analyses using our algorithms for the synthetic data that contained synchronous spiking and complex waveforms. Moreover, both T2-selected and SA-retrieved spikes were combined as unit activities. Quantitative analyses were performed to evaluate if unit activities truly originated from single fibers. We conclude that applications of our programs can help to resolve synchronous sympathetic nerve discharges (SND). PMID:24198782

Members of Microvirga and Bradyrhizobium genera are native endosymbiotic bacteria nodulating Lupinus luteus in Northern Tunisian soils.

PubMed

Msaddak, Abdelhakim; Rejili, Mokhtar; Durán, David; Rey, Luis; Imperial, Juan; Palacios, Jose Manuel; Ruiz-Argüeso, Tomas; Mars, Mohamed

2017-06-01

The genetic diversity of bacterial populations nodulating Lupinus luteus (yellow lupine) in Northern Tunisia was examined. Phylogenetic analyses of 43 isolates based on recA and gyrB partial sequences grouped them in three clusters, two of which belong to genus Bradyrhizobium (41 isolates) and one, remarkably, to Microvirga (2 isolates), a genus never previously described as microsymbiont of this lupine species. Representatives of the three clusters were analysed in-depth by multilocus sequence analysis of five housekeeping genes (rrs, recA, glnII, gyrB and dnaK). Surprisingly, the Bradyrhizobium cluster with the two isolates LluI4 and LluTb2 may constitute a new species defined by a separate position between Bradyrhizobium manausense and B. denitrificans. A nodC-based phylogeny identified only two groups: one formed by Bradyrhizobium strains included in the symbiovar genistearum and the other by the Microvirga strains. Symbiotic behaviour of representative isolates was tested, and among the seven legumes inoculated only a difference was observed i.e. the Bradyrhizobium strains nodulated Ornithopus compressus unlike the two strains of Microvirga. On the basis of these data, we conclude that L. luteus root nodule symbionts in Northern Tunisia are mostly strains within the B. canariense/B. lupini lineages, and the remaining strains belong to two groups not previously identified as L. luteus endosymbionts: one corresponding to a new clade of Bradyrhizobium and the other to the genus Microvirga. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identifying consumer segments in health services markets: an application of conjoint and cluster analyses to the ambulatory care pharmacy market.

PubMed

Carrol, N V; Gagon, J P

1983-01-01

Because of increasing competition, it is becoming more important that health care providers pursue consumer-based market segmentation strategies. This paper presents a methodology for identifying and describing consumer segments in health service markets, and demonstrates the use of the methodology by presenting a study of consumer segments in the ambulatory care pharmacy market.

Does Enjoying Friendship Help or Impede Academic Achievement? Academic and Social Intrinsic Value Profiles Predict Academic Achievement

ERIC Educational Resources Information Center

Seo, Eunjin; Lee, You-kyung

2018-01-01

We examine the intrinsic value students placed on schoolwork (i.e. academic intrinsic value) and social relationships (i.e. social intrinsic value). We then look at how these values predict middle and high school achievement. To do this, we came up with four profiles based on cluster analyses of 6,562 South Korean middle school students. The four…

WIYN OPEN CLUSTER STUDY. XXXVI. SPECTROSCOPIC BINARY ORBITS IN NGC 188

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

Geller, Aaron M.; Mathieu, Robert D.; Harris, Hugh C.

2009-04-15

We present 98 spectroscopic binary orbits resulting from our ongoing radial velocity survey of the old (7 Gyr) open cluster NGC 188. All but 13 are high-probability cluster members based on both radial velocity and proper motion membership analyses. Fifteen of these member binaries are double lined. Our stellar sample spans a magnitude range of 10.8 {<=}V{<=} 16.5 (1.14-0.92 M {sub sun}) and extends spatially to 17 pc ({approx}13 core radii). All of our binary orbits have periods ranging from a few days to on the order of 10{sup 3} days, and thus are hard binaries that dynamically power themore » cluster. For each binary, we present the orbital solutions and place constraints on the component masses. Additionally, we discuss a few binaries of note from our sample, identifying a likely blue straggler-blue straggler binary system (7782), a double-lined binary with a secondary star which is underluminous for its mass (5080), two potential eclipsing binaries (4705 and 5762), and two binaries which are likely members of a quadruple system (5015a and 5015b)« less

Copper chalcogenide clusters stabilized with ferrocene-based diphosphine ligands.

PubMed

Khadka, Chhatra B; Najafabadi, Bahareh Khalili; Hesari, Mahdi; Workentin, Mark S; Corrigan, John F

2013-06-17

The redox-active diphosphine ligand 1,1'-bis(diphenylphosphino)ferrocene (dppf) has been used to stabilize the copper(I) chalcogenide clusters [Cu12(μ4-S)6(μ-dppf)4] (1), [Cu8(μ4-Se)4(μ-dppf)3] (2), [Cu4(μ4-Te)(μ4-η(2)-Te2)(μ-dppf)2] (3), and [Cu12(μ5-Te)4(μ8-η(2)-Te2)2(μ-dppf)4] (4), prepared by the reaction of the copper(I) acetate coordination complex (dppf)CuOAc (5) with 0.5 equiv of E(SiMe3)2 (E = S, Se, Te). Single-crystal X-ray analyses of complexes 1-4 confirm the presence of {Cu(2x)E(x)} cores stabilized by dppf ligands on their surfaces, where the bidentate ligands adopt bridging coordination modes. The redox chemistry of cluster 1 was examined using cyclic voltammetry and compared to the electrochemistry of the free ligand dppf and the corresponding copper(I) acetate coordination complex 5. Cluster 1 shows the expected consecutive oxidations of the ferrocene moieties, Cu(I) centers, and phosphine of the dppf ligand.

ETE: a python Environment for Tree Exploration.

PubMed

Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni

2010-01-13

Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.

ETE: a python Environment for Tree Exploration

PubMed Central

2010-01-01

Background Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Results Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. Conclusions ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org. PMID:20070885

MUSE crowded field 3D spectroscopy of over 12 000 stars in the globular cluster NGC 6397. I. The first comprehensive HRD of a globular cluster

NASA Astrophysics Data System (ADS)

Husser, Tim-Oliver; Kamann, Sebastian; Dreizler, Stefan; Wendt, Martin; Wulff, Nina; Bacon, Roland; Wisotzki, Lutz; Brinchmann, Jarle; Weilbacher, Peter M.; Roth, Martin M.; Monreal-Ibero, Ana

2016-04-01

Aims: We demonstrate the high multiplex advantage of crowded field 3D spectroscopy with the new integral field spectrograph MUSE by means of a spectroscopic analysis of more than 12 000 individual stars in the globular cluster NGC 6397. Methods: The stars are deblended with a point spread function fitting technique, using a photometric reference catalogue from HST as prior, including relative positions and brightnesses. This catalogue is also used for a first analysis of the extracted spectra, followed by an automatic in-depth analysis via a full-spectrum fitting method based on a large grid of PHOENIX spectra. Results: We analysed the largest sample so far available for a single globular cluster of 18 932 spectra from 12 307 stars in NGC 6397. We derived a mean radial velocity of vrad = 17.84 ± 0.07 km s-1 and a mean metallicity of [Fe/H] = -2.120 ± 0.002, with the latter seemingly varying with temperature for stars on the red giant branch (RGB). We determine Teff and [Fe/H] from the spectra, and log g from HST photometry. This is the first very comprehensive Hertzsprung-Russell diagram (HRD) for a globular cluster based on the analysis of several thousands of stellar spectra, ranging from the main sequence to the tip of the RGB. Furthermore, two interesting objects were identified; one is a post-AGB star and the other is a possible millisecond-pulsar companion. Data products are available at http://muse-vlt.eu/scienceBased on observations obtained at the Very Large Telescope (VLT) of the European Southern Observatory, Paranal, Chile (ESO Programme ID 60.A-9100(C)).

Multivariate Statistical Analysis of Cigarette Design Feature Influence on ISO TNCO Yields.

PubMed

Agnew-Heard, Kimberly A; Lancaster, Vicki A; Bravo, Roberto; Watson, Clifford; Walters, Matthew J; Holman, Matthew R

2016-06-20

The aim of this study is to explore how differences in cigarette physical design parameters influence tar, nicotine, and carbon monoxide (TNCO) yields in mainstream smoke (MSS) using the International Organization of Standardization (ISO) smoking regimen. Standardized smoking methods were used to evaluate 50 U.S. domestic brand cigarettes and a reference cigarette representing a range of TNCO yields in MSS collected from linear smoking machines using a nonintense smoking regimen. Multivariate statistical methods were used to form clusters of cigarettes based on their ISO TNCO yields and then to explore the relationship between the ISO generated TNCO yields and the nine cigarette physical design parameters between and within each cluster simultaneously. The ISO generated TNCO yields in MSS are 1.1-17.0 mg tar/cigarette, 0.1-2.2 mg nicotine/cigarette, and 1.6-17.3 mg CO/cigarette. Cluster analysis divided the 51 cigarettes into five discrete clusters based on their ISO TNCO yields. No one physical parameter dominated across all clusters. Predicting ISO machine generated TNCO yields based on these nine physical design parameters is complex due to the correlation among and between the nine physical design parameters and TNCO yields. From these analyses, it is estimated that approximately 20% of the variability in the ISO generated TNCO yields comes from other parameters (e.g., filter material, filter type, inclusion of expanded or reconstituted tobacco, and tobacco blend composition, along with differences in tobacco leaf origin and stalk positions and added ingredients). A future article will examine the influence of these physical design parameters on TNCO yields under a Canadian Intense (CI) smoking regimen. Together, these papers will provide a more robust picture of the design features that contribute to TNCO exposure across the range of real world smoking patterns.

Non-targeted analyses of animal plasma: betaine and choline represent the nutritional and metabolic status.

PubMed

Katayama, K; Sato, T; Arai, T; Amao, H; Ohta, Y; Ozawa, T; Kenyon, P R; Hickson, R E; Tazaki, H

2013-02-01

Simple liquid chromatography-mass spectrometry (LC-MS) was applied to non-targeted metabolic analyses to discover new metabolic markers in animal plasma. Principle component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) were used to analyse LC-MS multivariate data. PCA clearly generated two separate clusters for artificially induced diabetic mice and healthy control mice. PLS-DA of time-course changes in plasma metabolites of chicks after feeding generated three clusters (pre- and immediately after feeding, 0.5-3 h after feeding and 4 h after feeding). Two separate clusters were also generated for plasma metabolites of pregnant Angus heifers with differing live-weight change profiles (gaining or losing). The accompanying PLS-DA loading plot detailed the metabolites that contribute the most to the cluster separation. In each case, the same highly hydrophilic metabolite was strongly correlated to the group separation. The metabolite was identified as betaine by LC-MS/MS. This result indicates that betaine and its metabolic precursor, choline, may be useful biomarkers to evaluate the nutritional and metabolic status of animals. © 2011 Blackwell Verlag GmbH.

Accounting for multiple births in neonatal and perinatal trials: systematic review and case study.

PubMed

Hibbs, Anna Maria; Black, Dennis; Palermo, Lisa; Cnaan, Avital; Luan, Xianqun; Truog, William E; Walsh, Michele C; Ballard, Roberta A

2010-02-01

To determine the prevalence in the neonatal literature of statistical approaches accounting for the unique clustering patterns of multiple births and to explore the sensitivity of an actual trial to several analytic approaches to multiples. A systematic review of recent perinatal trials assessed the prevalence of studies accounting for clustering of multiples. The Nitric Oxide to Prevent Chronic Lung Disease (NO CLD) trial served as a case study of the sensitivity of the outcome to several statistical strategies. We calculated odds ratios using nonclustered (logistic regression) and clustered (generalized estimating equations, multiple outputation) analyses. In the systematic review, most studies did not describe the random assignment of twins and did not account for clustering. Of those studies that did, exclusion of multiples and generalized estimating equations were the most common strategies. The NO CLD study included 84 infants with a sibling enrolled in the study. Multiples were more likely than singletons to be white and were born to older mothers (P < .01). Analyses that accounted for clustering were statistically significant; analyses assuming independence were not. The statistical approach to multiples can influence the odds ratio and width of confidence intervals, thereby affecting the interpretation of a study outcome. A minority of perinatal studies address this issue. Copyright 2010 Mosby, Inc. All rights reserved.

The insignificant evolution of the richness-mass relation of galaxy clusters

NASA Astrophysics Data System (ADS)

Andreon, S.; Congdon, P.

2014-08-01

We analysed the richness-mass scaling of 23 very massive clusters at 0.15 < z < 0.55 with homogenously measured weak-lensing masses and richnesses within a fixed aperture of 0.5 Mpc radius. We found that the richness-mass scaling is very tight (the scatter is <0.09 dex with 90% probability) and independent of cluster evolutionary status and morphology. This implies a close association between infall and evolution of dark matter and galaxies in the central region of clusters. We also found that the evolution of the richness-mass intercept is minor at most, and, given the minor mass evolution across the studied redshift range, the richness evolution of individual massive clusters also turns out to be very small. Finally, it was paramount to account for the cluster mass function and the selection function. Ignoring them would lead to larger biases than the (otherwise quoted) errors. Our study benefits from: a) weak-lensing masses instead of proxy-based masses thereby removing the ambiguity between a real trend and one induced by an accounted evolution of the used mass proxy; b) the use of projected masses that simplify the statistical analysis thereby not requiring consideration of the unknown covariance induced by the cluster orientation/triaxiality; c) the use of aperture masses as they are free of the pseudo-evolution of mass definitions anchored to the evolving density of the Universe; d) a proper accounting of the sample selection function and of the Malmquist-like effect induced by the cluster mass function; e) cosmological simulations for the computation of the cluster mass function, its evolution, and the mass growth of each individual cluster.

The biological characteristics of predominant strains of HIV-1 genotype: modeling of HIV-1 infection among men who have sex with men.

PubMed

Dai, Di; Shang, Hong; Han, Xiao-Xu; Zhao, Bin; Liu, Jing; Ding, Hai-Bo; Xu, Jun-Jie; Chu, Zhen-Xing

2015-04-01

To investigate the molecular subtypes of prevalent HIV-1 strains and characterize the genetics of dominant strains among men who have sex with men. Molecular epidemiology surveys in this study concentrated on the prevalent HIV-1 strains in Liaoning province by year. 229 adult patients infected with HIV-1 and part of a high-risk group of men who have sex with men were recruited. Reverse transcription and nested PCR amplification were performed. Sequencing reactions were conducted and edited, followed by codon-based alignment. NJ phylogenetic tree analyses detected two distinct CRF01_AE phylogenetic clusters, designated clusters 1 and 2. Clusters 1 and 2 accounted for 12.8% and 84.2% of sequences in the pol gene and 17.6% and 73.1% of sequences in the env gene, respectively. Another six samples were distributed on other phylogenetic clusters. Cluster 1 increased significantly from 5.6% to 20.0%, but cluster 2 decreased from 87.5% to 80.0%. Genetic distance analysis indicated that CRF01_AE cluster 1 in Liaoning was homologous to epidemic CRF01_AE strains, but CRF01_AE cluster 2 was different from other scattered strains. Additionally, significant differences were found in tetra-peptide motifs at the tip of V3 loop between cluster 1 and 2; however, differences in coreceptor usage were not detected. This study shows that subtype CRF01_AE strain may be the most prevalent epidemic strain in the men who have sex with men. Genetic characteristics of the subtype CRF01_AE cluster strain in Liaoning showed homology to the prevalent strains of men who have sex with men in other parts of China. © 2015 Wiley Periodicals, Inc.

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

PubMed

Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

2011-11-01

Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

Assessing different measures of population-level vaccine protection using a case-control study.

PubMed

Ali, Mohammad; You, Young Ae; Kanungo, Suman; Manna, Byomkesh; Deen, Jacqueline L; Lopez, Anna Lena; Wierzba, Thomas F; Bhattacharya, Sujit K; Sur, Dipika; Clemens, John D

2015-11-27

Case-control studies have not been examined for their utility in assessing population-level vaccine protection in individually randomized trials. We used the data of a randomized, placebo-controlled trial of a cholera vaccine to compare the results of case-control analyses with those of cohort analyses. Cases of cholera were selected from the trial population followed for three years following dosing. For each case, we selected 4 age-matched controls who had not developed cholera. For each case and control, GIS was used to calculate vaccine coverage of individuals in a surrounding "virtual" cluster. Specific selection strategies were used to evaluate the vaccine protective effects. 66,900 out of 108,389 individuals received two doses of the assigned regimen. For direct protection among subjects in low vaccine coverage clusters, we observed 78% (95% CI: 47-91%) protection in a cohort analysis and 84% (95% CI: 60-94%) in case-control analysis after adjusting for confounding factors. Using our GIS-based approach, estimated indirect protection was 52% (95% CI: 10-74%) in cohort and 76% (95% CI: 47-89%) in case control analysis. Estimates of total and overall effectiveness were similar for cohort and case-control analyses. The findings show that case-control analyses of individually randomized vaccine trials may be used to evaluate direct as well as population-level vaccine protection. Copyright © 2015. Published by Elsevier Ltd.

Analysis of Genetic Diversity and Structure Pattern of Indigofera Pseudotinctoria in Karst Habitats of the Wushan Mountains Using AFLP Markers.

PubMed

Fan, Yan; Zhang, Chenglin; Wu, Wendan; He, Wei; Zhang, Li; Ma, Xiao

2017-10-16

Indigofera pseudotinctoria Mats is an agronomically and economically important perennial legume shrub with a high forage yield, protein content and strong adaptability, which is subject to natural habitat fragmentation and serious human disturbance. Until now, our knowledge of the genetic relationships and intraspecific genetic diversity for its wild collections is still poor, especially at small spatial scales. Here amplified fragment length polymorphism (AFLP) technology was employed for analysis of genetic diversity, differentiation, and structure of 364 genotypes of I. pseudotinctoria from 15 natural locations in Wushan Montain, a highly structured mountain with typical karst landforms in Southwest China. We also tested whether eco-climate factors has affected genetic structure by correlating genetic diversity with habitat features. A total of 515 distinctly scoreable bands were generated, and 324 of them were polymorphic. The polymorphic information content (PIC) ranged from 0.694 to 0.890 with an average of 0.789 per primer pair. On species level, Nei's gene diversity ( H j ), the Bayesian genetic diversity index ( H B ) and the Shannon information index ( I ) were 0.2465, 0.2363 and 0.3772, respectively. The high differentiation among all sampling sites was detected ( F ST = 0.2217, G ST = 0.1746, G' ST = 0.2060, θ B = 0.1844), and instead, gene flow among accessions ( N m = 1.1819) was restricted. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. This structure pattern may indicate joint effects by the neutral evolution and natural selection. Restricted N m was observed across all accessions, and genetic barriers were detected between adjacent accessions due to specifically geographical landform.

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

The anatomy of a cluster IDP. Part 1: Carbon abundance, bulk chemistry, and mineralogy of fragments from L2008#5

NASA Technical Reports Server (NTRS)

Thomas, K. L.; Keller, L. P.; Klock, W.; Warren, J.; Blanford, G. E.; Mckay, David S.

1994-01-01

The objective of this study was to determine whether or not cluster particles are sufficiently homogeneous to enable observations from one fragment of the cluster to be extrapolated to the entire cluster. We report on the results of a consortium study of the fragments of a large cluster particle. Multiple fragments from one large cluster were distributed to several research groups and were subjected to a variety of mineralogical and chemical analyses including: SEM, TEM, ion probe, SXRF, noble gas measurements, and microprobe laser mass spectrometry of individual fragments.

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.

Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants.

PubMed

Sauzet, Odile; Peacock, Janet L

2017-07-20

The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins) and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

Finding Semirigid Domains in Biomolecules by Clustering Pair-Distance Variations

PubMed Central

Schreiner, Wolfgang

2014-01-01

Dynamic variations in the distances between pairs of atoms are used for clustering subdomains of biomolecules. We draw on a well-known target function for clustering and first show mathematically that the assignment of atoms to clusters has to be crisp, not fuzzy, as hitherto assumed. This reduces the computational load of clustering drastically, and we demonstrate results for several biomolecules relevant in immunoinformatics. Results are evaluated regarding the number of clusters, cluster size, cluster stability, and the evolution of clusters over time. Crisp clustering lends itself as an efficient tool to locate semirigid domains in the simulation of biomolecules. Such domains seem crucial for an optimum performance of subsequent statistical analyses, aiming at detecting minute motional patterns related to antigen recognition and signal transduction. PMID:24959586

Neighborhood deprivation and maternal psychological distress during pregnancy: a multilevel analysis.

PubMed

Yang, Seungmi; Kestens, Yan; Dahhou, Mourad; Daniel, Mark; Kramer, Michael S

2015-05-01

Maternal psychosocial distress is conceptualized as an important factor underlying the association between neighborhood deprivation and pregnancy outcomes. However, empirical studies to examine effects of neighborhood deprivation on psychosocial distress during pregnancy are scant. Based on a large multicenter cohort of pregnant women in Montreal, we examined (1) the extent to which psychosocial distress is clustered at the neighborhood-level, (2) the extent to which the clustering is explained by neighborhood material or social deprivation, and (3) whether associations between neighborhood deprivation and psychosocial distress persist after accounting for neighborhood composition (individual-level characteristics) using multilevel analyses. For 5,218 women residing in 740 neighborhoods, a prenatal interview at 24-26 gestational weeks measured both general and pregnancy-related psychological distress using well-validated scales: perceived stress, social support, depressive symptoms, optimism, commitment to the pregnancy, pregnancy-related anxiety, and maternal locus-of-control. Neighborhood deprivation indices were linked to study participants by their residential postal code. Neighborhood-level clustering (intraclass correlation) ranged from 1 to 2 % for perceived stress (lowest), optimism, pregnancy-related anxiety, and commitment to pregnancy to 4-6 % for perceived social support, depressive symptoms, and maternal locus of control (highest). Neighborhood material deprivation explained far more of the clustering (23-75 %) than did social deprivation (no more than 4 %). Although both material and social deprivation were associated with psychological distress in unadjusted analyses, the associations disappeared after accounting for individual-level socioeconomic characteristics. Our results highlight the importance of accounting for individual-level socioeconomic characteristics in studies of potential neighborhood effects on maternal mental health.

Timing of sea ice retreat can alter phytoplankton community structure in the western Arctic Ocean

NASA Astrophysics Data System (ADS)

Fujiwara, A.; Hirawake, T.; Suzuki, K.; Imai, I.; Saitoh, S.-I.

2014-04-01

This study assesses the response of phytoplankton assemblages to recent climate change, especially with regard to the shrinking of sea ice in the northern Chukchi Sea of the western Arctic Ocean. Distribution patterns of phytoplankton groups in the late summers of 2008-2010 were analysed based on HPLC pigment signatures and, the following four major algal groups were inferred via multiple regression and cluster analyses: prasinophytes, diatoms, haptophytes and dinoflagellates. A remarkable interannual difference in the distribution pattern of the groups was found in the northern basin area. Haptophytes dominated and dispersed widely in warm surface waters in 2008, whereas prasinophytes dominated in cold water in 2009 and 2010. A difference in the onset date of sea ice retreat was evident among years-the sea ice retreat in 2008 was 1-2 months earlier than in 2009 and 2010. The spatial distribution of early sea ice retreat matched the areas in which a shift in algal community composition was observed. Steel-Dwass's multiple comparison tests were used to assess the physical, chemical and biological parameters of the four clusters. We found a statistically significant difference in temperature between the haptophyte-dominated cluster and the other clusters, suggesting that the change in the phytoplankton communities was related to the earlier sea ice retreat in 2008 and the corollary increase in sea surface temperatures. Longer periods of open water during the summer, which are expected in the future, may affect food webs and biogeochemical cycles in the western Arctic due to shifts in phytoplankton community structure.

Effects of physical activity on schoolchildren's academic performance: The Active Smarter Kids (ASK) cluster-randomized controlled trial.

PubMed

Resaland, Geir K; Aadland, Eivind; Moe, Vegard Fusche; Aadland, Katrine N; Skrede, Turid; Stavnsbo, Mette; Suominen, Laura; Steene-Johannessen, Jostein; Glosvik, Øyvind; Andersen, John R; Kvalheim, Olav M; Engelsrud, Gunn; Andersen, Lars B; Holme, Ingar M; Ommundsen, Yngvar; Kriemler, Susi; van Mechelen, Willem; McKay, Heather A; Ekelund, Ulf; Anderssen, Sigmund A

2016-10-01

To investigate the effect of a seven-month, school-based cluster-randomized controlled trial on academic performance in 10-year-old children. In total, 1129 fifth-grade children from 57 elementary schools in Sogn og Fjordane County, Norway, were cluster-randomized by school either to the intervention group or to the control group. The children in the 28 intervention schools participated in a physical activity intervention between November 2014 and June 2015 consisting of three components: 1) 90min/week of physically active educational lessons mainly carried out in the school playground; 2) 5min/day of physical activity breaks during classroom lessons; 3) 10min/day physical activity homework. Academic performance in numeracy, reading and English was measured using standardized Norwegian national tests. Physical activity was measured objectively by accelerometry. We found no effect of the intervention on academic performance in primary analyses (standardized difference 0.01-0.06, p>0.358). Subgroup analyses, however, revealed a favorable intervention effect for those who performed the poorest at baseline (lowest tertile) for numeracy (p=0.005 for the subgroup∗group interaction), compared to controls (standardized difference 0.62, 95% CI 0.19-1.07). This large, rigorously conducted cluster RCT in 10-year-old children supports the notion that there is still inadequate evidence to conclude that increased physical activity in school enhances academic achievement in all children. Still, combining physical activity and learning seems a viable model to stimulate learning in those academically weakest schoolchildren. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Conformational diversity of flexible ligand in metal-organic frameworks controlled by size-matching mixed ligands

NASA Astrophysics Data System (ADS)

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi; Yu, Lei; Xie, Yi-Xin; Han, Lei

2015-12-01

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H2ndc) or 4,4‧-(hydroxymethylene)dibenzoic acid (H2hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd2(2,6-ndc)2(bpp)(DMF)]·2DMF (1) and [Cd3(hmdb)3(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional 'Lucky Clover' shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations in 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process.

Functional video-based analysis of 3D cardiac structures generated from human embryonic stem cells.

PubMed

Nitsch, Scarlett; Braun, Florian; Ritter, Sylvia; Scholz, Michael; Schroeder, Insa S

2018-05-01

Human embryonic stem cells (hESCs) differentiated into cardiomyocytes (CM) often develop into complex 3D structures that are composed of various cardiac cell types. Conventional methods to study the electrophysiology of cardiac cells are patch clamp and microelectrode array (MEAs) analyses. However, these methods are not suitable to investigate the contractile features of 3D cardiac clusters that detach from the surface of the culture dishes during differentiation. To overcome this problem, we developed a video-based motion detection software relying on the optical flow by Farnebäck that we call cBRA (cardiac beat rate analyzer). The beating characteristics of the differentiated cardiac clusters were calculated based on the local displacement between two subsequent images. Two differentiation protocols, which profoundly differ in the morphology of cardiac clusters generated and in the expression of cardiac markers, were used and the resulting CM were characterized. Despite these differences, beat rates and beating variabilities could be reliably determined using cBRA. Likewise, stimulation of β-adrenoreceptors by isoproterenol could easily be identified in the hESC-derived CM. Since even subtle changes in the beating features are detectable, this method is suitable for high throughput cardiotoxicity screenings. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Molecular genetic variation and structure of Southeast Asian crocodile (Tomistoma schlegelii): Comparative potentials of SSRs versus ISSRs.

PubMed

Shafiei-Astani, Behnam; Ong, Alan Han Kiat; Valdiani, Alireza; Tan, Soon Guan; Yien, Christina Yong Seok; Ahmady, Fatemeh; Alitheen, Noorjahan Banu; Ng, Wei Lun; Kuar, Taranjeet

2015-10-15

Tomistoma schlegelii, also referred to as the "false gharial", is one of the most exclusive and least known of the world's fresh water crocodilians, limited to Southeast Asia. Indeed, lack of economic value for its skin has led to neglect the biodiversity of the species. The current study aimed to investigate the mentioned case using 40 simple sequence repeat (SSR) primer pairs and 45 inter-simple sequence repeat (ISSR) primers. DNA analysis of 17 T. schlegelii samples using the SSR and ISSR markers resulted in producing a total of 49 and 108 polymorphic bands, respectively. Furthermore, the SSR- and ISSR-based cluster analyses both generated two main clusters. However, the SSR based results were found to be more in line with the geographical distributions of the crocodile samples collected across the country as compared with the ISSR-based results. The observed heterozygosity (HO) and expected heterozygosity (HE) of the polymorphic SSRs ranged between 0.588-1 and 0.470-0.891, respectively. The present results suggest that the Malaysian T. schlegelii populations had originated from a core population of crocodiles. In cooperation with the SSR markers, the ISSRs showed high potential for studying the genetic variation of T. schlegelii, and these markers are suitable to be employed in conservation genetic programs of this endangered species. Both SSR- and ISSR-based STRUCTURE analyses suggested that all the individuals of T. schlegelii are genetically similar with each other. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Subtyping of Children with Developmental Dyslexia via Bootstrap Aggregated Clustering and the Gap Statistic: Comparison with the Double-Deficit Hypothesis

ERIC Educational Resources Information Center

King, Wayne M.; Giess, Sally A.; Lombardino, Linda J.

2007-01-01

Background: The marked degree of heterogeneity in persons with developmental dyslexia has motivated the investigation of possible subtypes. Attempts have proceeded both from theoretical models of reading and the application of unsupervised learning (clustering) methods. Previous cluster analyses of data obtained from persons with reading…

Investigations in Science Education, Vol. 3, No. 3. Expanded Abstracts and Critical Analyses of Recent Research.

ERIC Educational Resources Information Center

Helgeson, Stanley L., Ed.; Blosser, Patricia E., Ed.

This issue contains expanded abstracts of research reports grouped into two clusters and a section of individual studies. The first cluster contains abstracts of two research reports dealing with trait-treatment interaction studies. The second cluster deals with examination items categorized according to Bloom's Taxonomy. The final section,…

Geographic Variation of Amyotrophic Lateral Sclerosis Incidence in New Jersey, 2009–2011

PubMed Central

Henry, Kevin A.; Fagliano, Jerald; Jordan, Heather M.; Rechtman, Lindsay; Kaye, Wendy E.

2015-01-01

Few analyses in the United States have examined geographic variation and socioeconomic disparities in amyotrophic lateral sclerosis (ALS) incidence, because of lack of population-based incidence data. In this analysis, we used population-based ALS data to identify whether ALS incidence clusters geographically and to determine whether ALS risk varies by area-based socioeconomic status (SES). This study included 493 incident ALS cases diagnosed (via El Escorial criteria) in New Jersey between 2009 and 2011. Geographic variation and clustering of ALS incidence was assessed using a spatial scan statistic and Bayesian geoadditive models. Poisson regression was used to estimate the associations between ALS risk and SES based on census-tract median income while controlling for age, sex, and race. ALS incidence varied across and within counties, but there were no statistically significant geographic clusters. SES was associated with ALS incidence. After adjustment for age, sex, and race, the relative risk of ALS was significantly higher (relative risk (RR) = 1.37, 95% confidence interval (CI): 1.02, 1.82) in the highest income quartile than in the lowest. The relative risk of ALS was significantly lower among blacks (RR = 0.57, 95% CI: 0.39, 0.83) and Asians (RR = 0.63, 95% CI: 0.41, 0.97) than among whites. Our findings suggest that ALS incidence in New Jersey appears to be associated with SES and race. PMID:26041711

Developmental trajectories of children's symbolic numerical magnitude processing skills and associated cognitive competencies.

PubMed

Vanbinst, Kiran; Ceulemans, Eva; Peters, Lien; Ghesquière, Pol; De Smedt, Bert

2018-02-01

Although symbolic numerical magnitude processing skills are key for learning arithmetic, their developmental trajectories remain unknown. Therefore, we delineated during the first 3years of primary education (5-8years of age) groups with distinguishable developmental trajectories of symbolic numerical magnitude processing skills using a model-based clustering approach. Three clusters were identified and were labeled as inaccurate, accurate but slow, and accurate and fast. The clusters did not differ in age, sex, socioeconomic status, or IQ. We also tested whether these clusters differed in domain-specific (nonsymbolic magnitude processing and digit identification) and domain-general (visuospatial short-term memory, verbal working memory, and processing speed) cognitive competencies that might contribute to children's ability to (efficiently) process the numerical meaning of Arabic numerical symbols. We observed minor differences between clusters in these cognitive competencies except for verbal working memory for which no differences were observed. Follow-up analyses further revealed that the above-mentioned cognitive competencies did not merely account for the cluster differences in children's development of symbolic numerical magnitude processing skills, suggesting that other factors account for these individual differences. On the other hand, the three trajectories of symbolic numerical magnitude processing revealed remarkable and stable differences in children's arithmetic fact retrieval, which stresses the importance of symbolic numerical magnitude processing for learning arithmetic. Copyright © 2017 Elsevier Inc. All rights reserved.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-07-17

The explosion of biological data has largely influenced the focus of today’s biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-06-01

The explosion of biological data has largely influenced the focus of today's biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Spatial dynamics of invasion: the geometry of introduced species.

PubMed

Korniss, Gyorgy; Caraco, Thomas

2005-03-07

Many exotic species combine low probability of establishment at each introduction with rapid population growth once introduction does succeed. To analyse this phenomenon, we note that invaders often cluster spatially when rare, and consequently an introduced exotic's population dynamics should depend on locally structured interactions. Ecological theory for spatially structured invasion relies on deterministic approximations, and determinism does not address the observed uncertainty of the exotic-introduction process. We take a new approach to the population dynamics of invasion and, by extension, to the general question of invasibility in any spatial ecology. We apply the physical theory for nucleation of spatial systems to a lattice-based model of competition between plant species, a resident and an invader, and the analysis reaches conclusions that differ qualitatively from the standard ecological theories. Nucleation theory distinguishes between dynamics of single- and multi-cluster invasion. Low introduction rates and small system size produce single-cluster dynamics, where success or failure of introduction is inherently stochastic. Single-cluster invasion occurs only if the cluster reaches a critical size, typically preceded by a number of failed attempts. For this case, we identify the functional form of the probability distribution of time elapsing until invasion succeeds. Although multi-cluster invasion for sufficiently large systems exhibits spatial averaging and almost-deterministic dynamics of the global densities, an analytical approximation from nucleation theory, known as Avrami's law, describes our simulation results far better than standard ecological approximations.

WINGS-SPE. III. Equivalent width measurements, spectral properties, and evolution of local cluster galaxies

NASA Astrophysics Data System (ADS)

Fritz, J.; Poggianti, B. M.; Cava, A.; Moretti, A.; Varela, J.; Bettoni, D.; Couch, W. J.; D'Onofrio D'Onofrio, M.; Dressler, A.; Fasano, G.; Kjærgaard, P.; Marziani, P.; Moles, M.; Omizzolo, A.

2014-06-01

Context. Cluster galaxies are the ideal sites to look at when studying the influence of the environment on the various aspects of the evolution of galaxies, such as the changes in their stellar content and morphological transformations. In the framework of wings, the WIde-field Nearby Galaxy-cluster Survey, we have obtained optical spectra for ~6000 galaxies selected in fields centred on 48 local (0.04 < z < 0.07) X-ray selected clusters to tackle these issues. Aims: By classifying the spectra based on given spectral lines, we investigate the frequency of the various spectral types as a function of both the clusters' properties and the galaxies' characteristics. In this way, using the same classification criteria adopted for studies at higher redshift, we can consistently compare the properties of the local cluster population to those of their more distant counterparts. Methods: We describe a method that we have developed to automatically measure the equivalent width of spectral lines in a robust way, even in spectra with a non optimal signal-to-noise ratio. This way, we can derive a spectral classification reflecting the stellar content, based on the presence and strength of the [Oii] and Hδ lines. Results: After a quality check, we are able to measure 4381 of the ~6000 originally observed spectra in the fields of 48 clusters, of which 2744 are spectroscopically confirmed cluster members. The spectral classification is then analysed as a function of galaxies' luminosity, stellar mass, morphology, local density, and host cluster's global properties and compared to higher redshift samples (MORPHS and EDisCS). The vast majority of galaxies in the local clusters population are passive objects, being also the most luminous and massive. At a magnitude limit of MV < -18, galaxies in a post-starburst phase represent only ~11% of the cluster population, and this fraction is reduced to ~5% at MV < -19.5, which compares to the 18% at the same magnitude limit for high-z clusters. "Normal" star-forming galaxies (e(c)) are proportionally more common in local clusters. Conclusions: The relative occurrence of post-starbursts suggests a very similar quenching efficiency in clusters at redshifts in the 0 to ~1 range. Furthermore, more important than the global environment, the local density seems to be the main driver of galaxy evolution in local clusters at least with respect to their stellar populations content. Based on observations taken at the Anglo Australian Telescope (3.9 m- AAT) and at the William Herschel Telescope (4.2 m-WHT).Full Table A.1 is available in electronic form at both the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/566/A32 and by querying the wings database at http://web.oapd.inaf.it/wings/new/index.htmlAppendices are available in electronic form at http://www.aanda.org

Electron attachment to molecules in a cluster environment: suppression and enhancement effects

NASA Astrophysics Data System (ADS)

Fabrikant, Ilya I.

2018-05-01

Cluster environments can strongly influence dissociative electron attachment (DEA) processes. These effects are important in many applications, particularly for surface chemistry, radiation damage, and atmospheric physics. We review several mechanisms for DEA suppression and enhancement due to cluster environments, particularly due to microhydration. Long-range electron-molecule and electron-cluster interactions play often a significant role in these effects and can be analysed by using theoretical models. Nevertheless many observations remain unexplained due to complexity of the physics and chemistry of interaction of DEA fragments with the cluster environment.

PlantTribes: a gene and gene family resource for comparative genomics in plants

PubMed Central

Wall, P. Kerr; Leebens-Mack, Jim; Müller, Kai F.; Field, Dawn; Altman, Naomi S.; dePamphilis, Claude W.

2008-01-01

The PlantTribes database (http://fgp.huck.psu.edu/tribe.html) is a plant gene family database based on the inferred proteomes of five sequenced plant species: Arabidopsis thaliana, Carica papaya, Medicago truncatula, Oryza sativa and Populus trichocarpa. We used the graph-based clustering algorithm MCL [Van Dongen (Technical Report INS-R0010 2000) and Enright et al. (Nucleic Acids Res. 2002; 30: 1575–1584)] to classify all of these species’ protein-coding genes into putative gene families, called tribes, using three clustering stringencies (low, medium and high). For all tribes, we have generated protein and DNA alignments and maximum-likelihood phylogenetic trees. A parallel database of microarray experimental results is linked to the genes, which lets researchers identify groups of related genes and their expression patterns. Unified nomenclatures were developed, and tribes can be related to traditional gene families and conserved domain identifiers. SuperTribes, constructed through a second iteration of MCL clustering, connect distant, but potentially related gene clusters. The global classification of nearly 200 000 plant proteins was used as a scaffold for sorting ∼4 million additional cDNA sequences from over 200 plant species. All data and analyses are accessible through a flexible interface allowing users to explore the classification, to place query sequences within the classification, and to download results for further study. PMID:18073194

Plasmasphere-Ring Current-Radiation Belts Interactions: Review of 16 Years of Cluster Observations

NASA Astrophysics Data System (ADS)

Dandouras, I. S.

2016-12-01

The Cluster mission is based on four identical spacecraft launched in 2000 on similar elliptical polar orbits with an initial perigee at about 4 RE and an apogee at 19.6 RE. This allows Cluster to cross the outer plasmasphere, the ring current region and the radiation belts, from south to north, during every perigee pass and to obtain their latitudinal profile following almost the same flux tube. Due to various perturbations the perigee geocentric distance decreased during 2007-2010 to about 2 RE, whereas actually it is again up to about 5 RE, allowing in this way to study, during the mission, the inner magnetosphere populations and their interactions at a wide range of L-shells and under different solar activity conditions. The CIS experiment, on board these spacecraft, provides the ion distribution functions from 1 eV (plasmasphere populations) up to 40 keV (ring current), whereas the MeV penetrating particles allow to monitor the position and dynamics of the radiation belts. The FGM experiment on board these four spacecraft allowed for the first time an instantaneous calculation of the magnetic field gradients and thus a direct measurement of the local current density using the curlometer technique. Earlier and more recent results, based on Cluster data acquired during the passes in inner magnetosphere, will be reviewed and analysed.

Artificial neural networks for efficient clustering of conformational ensembles and their potential for medicinal chemistry.

PubMed

Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura

2013-01-01

The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.

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

Integrated light chemical tagging analyses of seven M31 outer halo globular clusters from the Pan-Andromeda Archaeological Survey

NASA Astrophysics Data System (ADS)

Sakari, Charli M.; Venn, Kim A.; Mackey, Dougal; Shetrone, Matthew D.; Dotter, Aaron; Ferguson, Annette M. N.; Huxor, Avon

2015-04-01

Detailed chemical abundances are presented for seven M31 outer halo globular clusters (with projected distances from M31 greater than 30 kpc), as derived from high-resolution integrated light spectra taken with the Hobby-Eberly Telescope. Five of these clusters were recently discovered in the Pan-Andromeda Archaeological Survey (PAndAS) - this paper presents the first determinations of integrated Fe, Na, Mg, Ca, Ti, Ni, Ba, and Eu abundances for these clusters. Four of the target clusters (PA06, PA53, PA54, and PA56) are metal poor ([Fe/H] < -1.5), α-enhanced (though they are possibly less α-enhanced than Milky Way stars at the 1σ level), and show signs of star-to-star Na and Mg variations. The other three globular clusters (H10, H23, and PA17) are more metal rich, with metallicities ranging from [Fe/H] = -1.4 to -0.9. While H23 is chemically similar to Milky Way field stars, Milky Way globular clusters, and other M31 clusters, H10 and PA17, have moderately low [Ca/Fe], compared to Milky Way field stars and clusters. Additionally, PA17's high [Mg/Ca] and [Ba/Eu] ratios are distinct from Milky Way stars, and are in better agreement with the stars and clusters in the Large Magellanic Cloud. None of the clusters studied here can be conclusively linked to any of the identified streams from PAndAS; however, based on their locations, kinematics, metallicities, and detailed abundances, the most metal-rich PAndAS clusters H23 and PA17 may be associated with the progenitor of the Giant Stellar Stream, H10 may be associated with the SW cloud, and PA53 and PA56 may be associated with the eastern cloud.

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.

A Novel Coordination Polymer Based on Trinuclear Cobalt Building Blocks Cluster: Synthesis, Crystal Structure, and Properties

NASA Astrophysics Data System (ADS)

Lu, J. F.; Tang, Z. H.; Shi, J.; Ge, H. G.; Jiang, M.; Song, J.; Jin, L. X.

2017-12-01

The title compound {[Co3(μ3-OH)(μ2-H2O)2(H2O)5(BTC)2] · 6H2O} n (H3BTC is a 1,3,5-benzenetricarboxylic acid) was prepared and characterized by single crystal and powder X-ray diffraction, Fourier transform infrared spectroscopy, thermogravimetric and elemental analyses. The single crystal X-ray diffraction reveals that the title compound consists of 1D infinite zigzag chains which were constructed by trinuclear cobalt cluster and BTC3- ligand. Neighbouring above-mentioned 1D infinite zigzag chains are further linked by intermolecular hydrogen bonding to form a 3D supermolecular structure. In addition, the luminescent properties of the title compound were investigated.

The cluster Abell 780: an optical view

NASA Astrophysics Data System (ADS)

Durret, F.; Slezak, E.; Adami, C.

2009-11-01

Context: The Abell 780 cluster, better known as the Hydra A cluster, has been thouroughly analyzed in X-rays. However, little is known about its optical properties. Aims: We propose to derive the galaxy luminosity function (GLF) in this apparently relaxed cluster and to search for possible environmental effects by comparing the GLFs in various regions and by looking at the galaxy distribution at large scale around Abell 780. Methods: Our study is based on optical images obtained with the ESO 2.2m telescope and WFI camera in the B and R bands, covering a total region of 67.22 × 32.94 arcmin^2, or 4.235 × 2.075 Mpc2 for a cluster redshift of 0.0539. Results: In a region of 500 kpc radius around the cluster center, the GLF in the R band shows a double structure, with a broad and flat bright part and a flat faint end that can be fit by a power law with an index α ~ - 0.85 ± 0.12 in the 20.25 ≤ R ≤ 21.75 interval. If we divide this 500 kpc radius region in north+south or east+west halves, we find no clear difference between the GLFs in these smaller regions. No obvious large-scale structure is apparent within 5 Mpc from the cluster, based on galaxy redshifts and magnitudes collected from the NED database in a much larger region than that covered by our data, suggesting that there is no major infall of material in any preferential direction. However, the Serna-Gerbal method reveals a gravitationally bound structure of 27 galaxies, which includes the cD, and of a more strongly gravitationally bound structure of 14 galaxies. Conclusions: These optical results agree with the overall relaxed structure of Abell 780 previously derived from X-ray analyses. Based on observations obtained at the European Southern Observatory, program ESO 68.A-0084(A), P. I. E. Slezak. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Impact of a social-emotional and character development program on school-level indicators of academic achievement, absenteeism, and disciplinary outcomes: A matched-pair, cluster randomized, controlled trial.

PubMed

Snyder, Frank; Flay, Brian; Vuchinich, Samuel; Acock, Alan; Washburn, Isaac; Beets, Michael; Li, Kin-Kit

2010-01-01

This paper reports the effects of a comprehensive elementary school-based social-emotional and character education program on school-level achievement, absenteeism, and disciplinary outcomes utilizing a matched-pair, cluster randomized, controlled design. The Positive Action Hawai'i trial included 20 racially/ethnically diverse schools (mean enrollment = 544) and was conducted from the 2002-03 through the 2005-06 academic years. Using school-level archival data, analyses comparing change from baseline (2002) to one-year post trial (2007) revealed that intervention schools scored 9.8% better on the TerraNova (2 nd ed.) test for reading and 8.8% on math; 20.7% better in Hawai'i Content and Performance Standards scores for reading and 51.4% better in math; and that intervention schools reported 15.2% lower absenteeism and fewer suspensions (72.6%) and retentions (72.7%). Overall, effect sizes were moderate to large (range 0.5-1.1) for all of the examined outcomes. Sensitivity analyses using permutation models and random-intercept growth curve models substantiated results. The results provide evidence that a comprehensive school-based program, specifically developed to target student behavior and character, can positively influence school-level achievement, attendance, and disciplinary outcomes concurrently.

Phylogenomic and Molecular Demarcation of the Core Members of the Polyphyletic Pasteurellaceae Genera Actinobacillus, Haemophilus, and Pasteurella

PubMed Central

Naushad, Sohail; Adeolu, Mobolaji; Goel, Nisha; Khadka, Bijendra; Al-Dahwi, Aqeel; Gupta, Radhey S.

2015-01-01

The genera Actinobacillus, Haemophilus, and Pasteurella exhibit extensive polyphyletic branching in phylogenetic trees and do not represent coherent clusters of species. In this study, we have utilized molecular signatures identified through comparative genomic analyses in conjunction with genome based and multilocus sequence based phylogenetic analyses to clarify the phylogenetic and taxonomic boundary of these genera. We have identified large clusters of Actinobacillus, Haemophilus, and Pasteurella species which represent the “sensu stricto” members of these genera. We have identified 3, 7, and 6 conserved signature indels (CSIs), which are specifically shared by sensu stricto members of Actinobacillus, Haemophilus, and Pasteurella, respectively. We have also identified two different sets of CSIs that are unique characteristics of the pathogen containing genera Aggregatibacter and Mannheimia, respectively. It is now possible to demarcate the genera Actinobacillus sensu stricto, Haemophilus sensu stricto, and Pasteurella sensu stricto on the basis of discrete molecular signatures. The other members of the genera Actinobacillus, Haemophilus, and Pasteurella that do not fall within the “sensu stricto” clades and do not contain these molecular signatures should be reclassified as other genera. The CSIs identified here also provide useful diagnostic targets for the identification of current and novel members of the indicated genera. PMID:25821780

Brain Volume Differences Associated With Hearing Impairment in Adults

PubMed Central

Vriend, Chris; Heslenfeld, Dirk J.; Versfeld, Niek J.; Kramer, Sophia E.

2018-01-01

Speech comprehension depends on the successful operation of a network of brain regions. Processing of degraded speech is associated with different patterns of brain activity in comparison with that of high-quality speech. In this exploratory study, we studied whether processing degraded auditory input in daily life because of hearing impairment is associated with differences in brain volume. We compared T1-weighted structural magnetic resonance images of 17 hearing-impaired (HI) adults with those of 17 normal-hearing (NH) controls using a voxel-based morphometry analysis. HI adults were individually matched with NH adults based on age and educational level. Gray and white matter brain volumes were compared between the groups by region-of-interest analyses in structures associated with speech processing, and by whole-brain analyses. The results suggest increased gray matter volume in the right angular gyrus and decreased white matter volume in the left fusiform gyrus in HI listeners as compared with NH ones. In the HI group, there was a significant correlation between hearing acuity and cluster volume of the gray matter cluster in the right angular gyrus. This correlation supports the link between partial hearing loss and altered brain volume. The alterations in volume may reflect the operation of compensatory mechanisms that are related to decoding meaning from degraded auditory input. PMID:29557274

Proteogenomics connects somatic mutations to signalling in breast cancer.

PubMed

Mertins, Philipp; Mani, D R; Ruggles, Kelly V; Gillette, Michael A; Clauser, Karl R; Wang, Pei; Wang, Xianlong; Qiao, Jana W; Cao, Song; Petralia, Francesca; Kawaler, Emily; Mundt, Filip; Krug, Karsten; Tu, Zhidong; Lei, Jonathan T; Gatza, Michael L; Wilkerson, Matthew; Perou, Charles M; Yellapantula, Venkata; Huang, Kuan-lin; Lin, Chenwei; McLellan, Michael D; Yan, Ping; Davies, Sherri R; Townsend, R Reid; Skates, Steven J; Wang, Jing; Zhang, Bing; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Ding, Li; Paulovich, Amanda G; Fenyö, David; Ellis, Matthew J; Carr, Steven A

2016-06-02

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Further psychometric evaluation and revision of the Mayo-Portland Adaptability Inventory in a national sample.

PubMed

Malec, James F; Kragness, Miriam; Evans, Randall W; Finlay, Karen L; Kent, Ann; Lezak, Muriel D

2003-01-01

To evaluate the internal consistency of the Mayo-Portland Adaptability Inventory (MPAI), further refine the instrument, and provide reference data based on a large, geographically diverse sample of persons with acquired brain injury (ABI). 386 persons, most with moderate to severe ABI. Outpatient, community-based, and residential rehabilitation facilities for persons with ABI located in the United States: West, Midwest, and Southeast. Rasch, item cluster, principal components, and traditional psychometric analyses for internal consistency of MPAI data and subscales. With rescoring of rating scales for 4 items, a 29-item version of the MPAI showed satisfactory internal consistency by Rasch (Person Reliability=.88; Item Reliability=.99) and traditional psychometric indicators (Cronbach's alpha=.89). Three rationally derived subscales for Ability, Activity, and Participation demonstrated psychometric properties that were equivalent to subscales derived empirically through item cluster and factor analyses. For the 3 subscales, Person Reliability ranged from.78 to.79; Item Reliability, from.98 to.99; and Cronbach's alpha, from.76 to.83. Subscales correlated moderately (Pearson r =.49-.65) with each other and strongly with the overall scale (Pearson r=.82-.86). Outcome after ABI is represented by the unitary dimension described by the MPAI. MPAI subscales further define regions of this dimension that may be useful for evaluation of clinical cases and program evaluation.

XMM-Newton X-ray and HST weak gravitational lensing study of the extremely X-ray luminous galaxy cluster Cl J120958.9+495352 ( z = 0.902)

DOE PAGES

Tholken, Sophia; Schrabback, Tim; Reiprich, Thomas H.; ...

2018-03-05

Here, observations of relaxed, massive, and distant clusters can provide important tests of standard cosmological models, for example by using the gas mass fraction. To perform this test, the dynamical state of the cluster and its gas properties have to be investigated. X-ray analyses provide one of the best opportunities to access this information and to determine important properties such as temperature profiles, gas mass, and the total X-ray hydrostatic mass. For the last of these, weak gravitational lensing analyses are complementary independent probes that are essential in order to test whether X-ray masses could be biased.

XMM-Newton X-ray and HST weak gravitational lensing study of the extremely X-ray luminous galaxy cluster Cl J120958.9+495352 ( z = 0.902)

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

Tholken, Sophia; Schrabback, Tim; Reiprich, Thomas H.

Here, observations of relaxed, massive, and distant clusters can provide important tests of standard cosmological models, for example by using the gas mass fraction. To perform this test, the dynamical state of the cluster and its gas properties have to be investigated. X-ray analyses provide one of the best opportunities to access this information and to determine important properties such as temperature profiles, gas mass, and the total X-ray hydrostatic mass. For the last of these, weak gravitational lensing analyses are complementary independent probes that are essential in order to test whether X-ray masses could be biased.

Percolation analyses of observed and simulated galaxy clustering

NASA Astrophysics Data System (ADS)

Bhavsar, S. P.; Barrow, J. D.

1983-11-01

A percolation cluster analysis is performed on equivalent regions of the CFA redshift survey of galaxies and the 4000 body simulations of gravitational clustering made by Aarseth, Gott and Turner (1979). The observed and simulated percolation properties are compared and, unlike correlation and multiplicity function analyses, favour high density (Omega = 1) models with n = - 1 initial data. The present results show that the three-dimensional data are consistent with the degree of filamentary structure present in isothermal models of galaxy formation at the level of percolation analysis. It is also found that the percolation structure of the CFA data is a function of depth. Percolation structure does not appear to be a sensitive probe of intrinsic filamentary structure.

Spatial Analysis of HIV Positive Injection Drug Users in San Francisco, 1987 to 2005

PubMed Central

Martinez, Alexis N.; Mobley, Lee R.; Lorvick, Jennifer; Novak, Scott P.; Lopez, Andrea M.; Kral, Alex H.

2014-01-01

Spatial analyses of HIV/AIDS related outcomes are growing in popularity as a tool to understand geographic changes in the epidemic and inform the effectiveness of community-based prevention and treatment programs. The Urban Health Study was a serial, cross-sectional epidemiological study of injection drug users (IDUs) in San Francisco between 1987 and 2005 (N = 29,914). HIV testing was conducted for every participant. Participant residence was geocoded to the level of the United States Census tract for every observation in dataset. Local indicator of spatial autocorrelation (LISA) tests were used to identify univariate and bivariate Census tract clusters of HIV positive IDUs in two time periods. We further compared three tract level characteristics (% poverty, % African Americans, and % unemployment) across areas of clustered and non-clustered tracts. We identified significant spatial clustering of high numbers of HIV positive IDUs in the early period (1987–1995) and late period (1996–2005). We found significant bivariate clusters of Census tracts where HIV positive IDUs and tract level poverty were above average compared to the surrounding areas. Our data suggest that poverty, rather than race, was an important neighborhood characteristic associated with the spatial distribution of HIV in SF and its spatial diffusion over time. PMID:24722543

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Implicit Priors in Galaxy Cluster Mass and Scaling Relation Determinations

NASA Technical Reports Server (NTRS)

Mantz, A.; Allen, S. W.

2011-01-01

Deriving the total masses of galaxy clusters from observations of the intracluster medium (ICM) generally requires some prior information, in addition to the assumptions of hydrostatic equilibrium and spherical symmetry. Often, this information takes the form of particular parametrized functions used to describe the cluster gas density and temperature profiles. In this paper, we investigate the implicit priors on hydrostatic masses that result from this fully parametric approach, and the implications of such priors for scaling relations formed from those masses. We show that the application of such fully parametric models of the ICM naturally imposes a prior on the slopes of the derived scaling relations, favoring the self-similar model, and argue that this prior may be influential in practice. In contrast, this bias does not exist for techniques which adopt an explicit prior on the form of the mass profile but describe the ICM non-parametrically. Constraints on the slope of the cluster mass-temperature relation in the literature show a separation based the approach employed, with the results from fully parametric ICM modeling clustering nearer the self-similar value. Given that a primary goal of scaling relation analyses is to test the self-similar model, the application of methods subject to strong, implicit priors should be avoided. Alternative methods and best practices are discussed.

An integrative model for in-silico clinical-genomics discovery science.

PubMed

Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

2002-01-01

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Large-Scale Cooperative Dissemination of Governmental Information in Emergency — An Experiment and Future Strategies

NASA Astrophysics Data System (ADS)

Horiba, Katsuhiro; Okawa, Keiko; Murai, Jun

On the 11th of March, 2011, a massive earthquake hit the northeast region of Japan. The government of Japan needed to publish information regarding the earthquake and its influences. However, their capacity of Web services overflowed. They called the industry and academia for help for providing stable information service to the people. Industry and academia formed a team to answer the call and named themselves the “EQ project”. This paper describes how the EQ Project was organized and operated, and gives analyses of the statistics. An academic organization took the lead in the EQ Project. Ten organizations which consisted of commercial IT industry and academics specialized in Internet technology, were participating in the EQ Project and they structured the three clusters based on their relationships and technological approach. In WIDE Cluster, one of three clusters in the structure of EQ, the peak number of file accesses per day was over 90 thousand, the mobile browsers was 3.4% and foreign languages (translated contents) were referred 35%. We have also discussed the future information distribution strategies in emergency situation based on the experiences of the EQ Project, and proposed nine suggestions to the MEXT as a future strategy.

Examining the structural evolution of bicarbonate–water clusters: insights from photoelectron spectroscopy, basin-hopping structural search, and comparison with available IR spectral studies

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

Wen, Hui; Hou, Gao-Lei; Liu, Yi-Rong

2016-05-31

Bicarbonate serves a crucial biochemical role in the physiological pH buffering system and also has important atmospheric implications. In the current study, HCO 3 $-$(H 2O) n (n = 0-13) clusters were successfully produced via electrospray ionization of corresponding bulk salt solution, and were characterized by combining negative ion photoelectron spectroscopy and theoretical calculations. The photoelectron spectra reveal that the electron binding energy monotonically increases with the cluster size up to n = 10 and remains largely the same after n > 10. The photo-detaching feature of the solute HCO3$-$itself, which dominates in the small clusters, diminishes with increase ofmore » water coverage. Based on the charge distribution and molecular orbital analyses, the universal high electron binding energy tail that dominates in the larger clusters can be attributed to ionization of water. Thus, the transition of ionization from solute to solvent at the size larger than n=10 has been observed. Extensive theoretical structural search based on the Basin-Hopping unbiased method was carried out, and a plethora of low energy isomers have been obtained for each medium and large size. By comparing the simulated photoelectron spectra and calculated electron binding energies with the experiments, as well as by comparing the simulated infrared spectra with previously reported IR spectra, the probable global minima and the structural evolutionary routes are presented. The nature of bicarbonate-water interactions are mainly electrostatic as implied by the electron localization function (ELF) analysis.« less

A structured approach to the study of metabolic control principles in intact and impaired mitochondria.

PubMed

Huber, Heinrich J; Connolly, Niamh M C; Dussmann, Heiko; Prehn, Jochen H M

2012-03-01

We devised an approach to extract control principles of cellular bioenergetics for intact and impaired mitochondria from ODE-based models and applied it to a recently established bioenergetic model of cancer cells. The approach used two methods for varying ODE model parameters to determine those model components that, either alone or in combination with other components, most decisively regulated bioenergetic state variables. We found that, while polarisation of the mitochondrial membrane potential (ΔΨ(m)) and, therefore, the protomotive force were critically determined by respiratory complex I activity in healthy mitochondria, complex III activity was dominant for ΔΨ(m) during conditions of cytochrome-c deficiency. As a further important result, cellular bioenergetics in healthy, ATP-producing mitochondria was regulated by three parameter clusters that describe (1) mitochondrial respiration, (2) ATP production and consumption and (3) coupling of ATP-production and respiration. These parameter clusters resembled metabolic blocks and their intermediaries from top-down control analyses. However, parameter clusters changed significantly when cells changed from low to high ATP levels or when mitochondria were considered to be impaired by loss of cytochrome-c. This change suggests that the assumption of static metabolic blocks by conventional top-down control analyses is not valid under these conditions. Our approach is complementary to both ODE and top-down control analysis approaches and allows a better insight into cellular bioenergetics and its pathological alterations.

Integrating Gene Transcription-Based Biomarkers to Understand Desert Tortoise and Ecosystem Health.

PubMed

Bowen, Lizabeth; Miles, A Keith; Drake, K Kristina; Waters, Shannon C; Esque, Todd C; Nussear, Kenneth E

2015-09-01

Tortoises are susceptible to a wide variety of environmental stressors, and the influence of human disturbances on health and survival of tortoises is difficult to detect. As an addition to current diagnostic methods for desert tortoises, we have developed the first leukocyte gene transcription biomarker panel for the desert tortoise (Gopherus agassizii), enhancing the ability to identify specific environmental conditions potentially linked to declining animal health. Blood leukocyte transcript profiles have the potential to identify physiologically stressed animals in lieu of clinical signs. For desert tortoises, the gene transcript profile included a combination of immune or detoxification response genes with the potential to be modified by biological or physical injury and consequently provide information on the type and magnitude of stressors present in the animal's habitat. Blood from 64 wild adult tortoises at three sites in Clark County, NV, and San Bernardino, CA, and from 19 captive tortoises in Clark County, NV, was collected and evaluated for genes indicative of physiological status. Statistical analysis using a priori groupings indicated significant differences among groups for several genes, while multidimensional scaling and cluster analyses of transcription C T values indicated strong differentiation of a large cluster and multiple outlying individual tortoises or small clusters in multidimensional space. These analyses highlight the effectiveness of the gene panel at detecting environmental perturbations as well as providing guidance in determining the health of the desert tortoise.

Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing.

PubMed

Massana, Ramon; Gobet, Angélique; Audic, Stéphane; Bass, David; Bittner, Lucie; Boutte, Christophe; Chambouvet, Aurélie; Christen, Richard; Claverie, Jean-Michel; Decelle, Johan; Dolan, John R; Dunthorn, Micah; Edvardsen, Bente; Forn, Irene; Forster, Dominik; Guillou, Laure; Jaillon, Olivier; Kooistra, Wiebe H C F; Logares, Ramiro; Mahé, Frédéric; Not, Fabrice; Ogata, Hiroyuki; Pawlowski, Jan; Pernice, Massimo C; Probert, Ian; Romac, Sarah; Richards, Thomas; Santini, Sébastien; Shalchian-Tabrizi, Kamran; Siano, Raffaele; Simon, Nathalie; Stoeck, Thorsten; Vaulot, Daniel; Zingone, Adriana; de Vargas, Colomban

2015-10-01

Although protists are critical components of marine ecosystems, they are still poorly characterized. Here we analysed the taxonomic diversity of planktonic and benthic protist communities collected in six distant European coastal sites. Environmental deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from three size fractions (pico-, nano- and micro/mesoplankton), as well as from dissolved DNA and surface sediments were used as templates for tag pyrosequencing of the V4 region of the 18S ribosomal DNA. Beta-diversity analyses split the protist community structure into three main clusters: picoplankton-nanoplankton-dissolved DNA, micro/mesoplankton and sediments. Within each cluster, protist communities from the same site and time clustered together, while communities from the same site but different seasons were unrelated. Both DNA and RNA-based surveys provided similar relative abundances for most class-level taxonomic groups. Yet, particular groups were overrepresented in one of the two templates, such as marine alveolates (MALV)-I and MALV-II that were much more abundant in DNA surveys. Overall, the groups displaying the highest relative contribution were Dinophyceae, Diatomea, Ciliophora and Acantharia. Also, well represented were Mamiellophyceae, Cryptomonadales, marine alveolates and marine stramenopiles in the picoplankton, and Monadofilosa and basal Fungi in sediments. Our extensive and systematic sequencing of geographically separated sites provides the most comprehensive molecular description of coastal marine protist diversity to date. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Integrating gene transcription-based biomarkers to understand desert tortoise and ecosystem health

USGS Publications Warehouse

Bowen, Lizabeth; Miles, A. Keith; Drake, Karla K.; Waters, Shannon C.; Esque, Todd C.; Nussear, Kenneth E.

2015-01-01

Tortoises are susceptible to a wide variety of environmental stressors, and the influence of human disturbances on health and survival of tortoises is difficult to detect. As an addition to current diagnostic methods for desert tortoises, we have developed the first leukocyte gene transcription biomarker panel for the desert tortoise (Gopherus agassizii), enhancing the ability to identify specific environmental conditions potentially linked to declining animal health. Blood leukocyte transcript profiles have the potential to identify physiologically stressed animals in lieu of clinical signs. For desert tortoises, the gene transcript profile included a combination of immune or detoxification response genes with the potential to be modified by biological or physical injury and consequently provide information on the type and magnitude of stressors present in the animal’s habitat. Blood from 64 wild adult tortoises at three sites in Clark County, NV, and San Bernardino, CA, and from 19 captive tortoises in Clark County, NV, was collected and evaluated for genes indicative of physiological status. Statistical analysis using a priori groupings indicated significant differences among groups for several genes, while multidimensional scaling and cluster analyses of transcriptionC T values indicated strong differentiation of a large cluster and multiple outlying individual tortoises or small clusters in multidimensional space. These analyses highlight the effectiveness of the gene panel at detecting environmental perturbations as well as providing guidance in determining the health of the desert tortoise.

Analyses of Mitogenome Sequences Revealed that Asian Citrus Psyllids (Diaphorina citri) from California Were Related to Those from Florida.

PubMed

Wu, Fengnian; Kumagai, Luci; Cen, Yijing; Chen, Jianchi; Wallis, Christopher M; Polek, MaryLou; Jiang, Hongyan; Zheng, Zheng; Liang, Guangwen; Deng, Xiaoling

2017-08-31

Asian citrus psyllid (ACP, Diaphorina citri Kuwayama) transmits "Candidatus Liberibacter asiaticus" (CLas), an unculturable alpha-proteobacterium associated with citrus Huanglongbing (HLB). CLas has recently been found in California. Understanding ACP population diversity is necessary for HLB regulatory practices aimed at reducing CLas spread. In this study, two circular ACP mitogenome sequences from California (mt-CApsy, ~15,027 bp) and Florida (mt-FLpsy, ~15,012 bp), USA, were acquired. Each mitogenome contained 13 protein coding genes, 2 ribosomal RNA and 22 transfer RNA genes, and a control region varying in sizes. The Californian mt-CApsy was identical to the Floridian mt-FLpsy, but different from the mitogenome (mt-GDpsy) of Guangdong, China, in 50 single nucleotide polymorphisms (SNPs). Further analyses were performed on sequences in cox1 and trnAsn regions with 100 ACPs, SNPs in nad1-nad4-nad5 locus through PCR with 252 ACP samples. All results showed the presence of a Chinese ACP cluster (CAC) and an American ACP cluster (AAC). We proposed that ACP in California was likely not introduced from China based on our current ACP collection but somewhere in America. However, more studies with ACP samples from around the world are needed. ACP mitogenome sequence analyses will facilitate ACP population research.

Identification among morphologically similar Argyreia (Convolvulaceae) based on leaf anatomy and phenetic analyses.

PubMed

Traiperm, Paweena; Chow, Janene; Nopun, Possathorn; Staples, G; Swangpol, Sasivimon C

2017-12-01

The genus Argyreia Lour. is one of the species-rich Asian genera in the family Convolvulaceae. Several species complexes were recognized in which taxon delimitation was imprecise, especially when examining herbarium materials without fully developed open flowers. The main goal of this study is to investigate and describe leaf anatomy for some morphologically similar Argyreia using epidermal peeling, leaf and petiole transverse sections, and scanning electron microscopy. Phenetic analyses including cluster analysis and principal component analysis were used to investigate the similarity of these morpho-types. Anatomical differences observed between the morpho-types include epidermal cell walls and the trichome types on the leaf epidermis. Additional differences in the leaf and petiole transverse sections include the epidermal cell shape of the adaxial leaf blade, the leaf margins, and the petiole transverse sectional outline. The phenogram from cluster analysis using the UPGMA method represented four groups with an R value of 0.87. Moreover, the important quantitative and qualitative leaf anatomical traits of the four groups were confirmed by the principal component analysis of the first two components. The results from phenetic analyses confirmed the anatomical differentiation between the morpho-types. Leaf anatomical features regarded as particularly informative for morpho-type differentiation can be used to supplement macro morphological identification.

Implementation of novel statistical procedures and other advanced approaches to improve analysis of CASA data.

PubMed

Ramón, M; Martínez-Pastor, F

2018-04-23

Computer-aided sperm analysis (CASA) produces a wealth of data that is frequently ignored. The use of multiparametric statistical methods can help explore these datasets, unveiling the subpopulation structure of sperm samples. In this review we analyse the significance of the internal heterogeneity of sperm samples and its relevance. We also provide a brief description of the statistical tools used for extracting sperm subpopulations from the datasets, namely unsupervised clustering (with non-hierarchical, hierarchical and two-step methods) and the most advanced supervised methods, based on machine learning. The former method has allowed exploration of subpopulation patterns in many species, whereas the latter offering further possibilities, especially considering functional studies and the practical use of subpopulation analysis. We also consider novel approaches, such as the use of geometric morphometrics or imaging flow cytometry. Finally, although the data provided by CASA systems provides valuable information on sperm samples by applying clustering analyses, there are several caveats. Protocols for capturing and analysing motility or morphometry should be standardised and adapted to each experiment, and the algorithms should be open in order to allow comparison of results between laboratories. Moreover, we must be aware of new technology that could change the paradigm for studying sperm motility and morphology.

A comparative study of cold- and warm-adapted Endonucleases A using sequence analyses and molecular dynamics simulations.

PubMed

Michetti, Davide; Brandsdal, Bjørn Olav; Bon, Davide; Isaksen, Geir Villy; Tiberti, Matteo; Papaleo, Elena

2017-01-01

The psychrophilic and mesophilic endonucleases A (EndA) from Aliivibrio salmonicida (VsEndA) and Vibrio cholera (VcEndA) have been studied experimentally in terms of the biophysical properties related to thermal adaptation. The analyses of their static X-ray structures was no sufficient to rationalize the determinants of their adaptive traits at the molecular level. Thus, we used Molecular Dynamics (MD) simulations to compare the two proteins and unveil their structural and dynamical differences. Our simulations did not show a substantial increase in flexibility in the cold-adapted variant on the nanosecond time scale. The only exception is a more rigid C-terminal region in VcEndA, which is ascribable to a cluster of electrostatic interactions and hydrogen bonds, as also supported by MD simulations of the VsEndA mutant variant where the cluster of interactions was introduced. Moreover, we identified three additional amino acidic substitutions through multiple sequence alignment and the analyses of MD-based protein structure networks. In particular, T120V occurs in the proximity of the catalytic residue H80 and alters the interaction with the residue Y43, which belongs to the second coordination sphere of the Mg2+ ion. This makes T120V an amenable candidate for future experimental mutagenesis.

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

PubMed

Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

Atmospheric effects on cluster analyses. [for remote sensing application

NASA Technical Reports Server (NTRS)

Kiang, R. K.

1979-01-01

Ground reflected radiance, from which information is extracted through techniques of cluster analyses for remote sensing application, is altered by the atmosphere when it reaches the satellite. Therefore it is essential to understand the effects of the atmosphere on Landsat measurements, cluster characteristics and analysis accuracy. A doubling model is employed to compute the effective reflectivity, observed from the satellite, as a function of ground reflectivity, solar zenith angle and aerosol optical thickness for standard atmosphere. The relation between the effective reflectivity and ground reflectivity is approximately linear. It is shown that for a horizontally homogeneous atmosphere, the classification statistics from a maximum likelihood classifier remains unchanged under these transforms. If inhomogeneity is present, the divergence between clusters is reduced, and correlation between spectral bands increases. Radiance reflected by the background area surrounding the target may also reach the satellite. The influence of background reflectivity on effective reflectivity is discussed.

Bias correction of satellite-based rainfall data

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Solomatine, Dimitri

2015-04-01

Limitation in hydro-meteorological data availability in many catchments limits the possibility of reliable hydrological analyses especially for near-real-time predictions. However, the variety of satellite based and meteorological model products for rainfall provides new opportunities. Often times the accuracy of these rainfall products, when compared to rain gauge measurements, is not impressive. The systematic differences of these rainfall products from gauge observations can be partially compensated by adopting a bias (error) correction. Many of such methods correct the satellite based rainfall data by comparing their mean value to the mean value of rain gauge data. Refined approaches may also first find out a suitable time scale at which different data products are better comparable and then employ a bias correction at that time scale. More elegant methods use quantile-to-quantile bias correction, which however, assumes that the available (often limited) sample size can be useful in comparing probabilities of different rainfall products. Analysis of rainfall data and understanding of the process of its generation reveals that the bias in different rainfall data varies in space and time. The time aspect is sometimes taken into account by considering the seasonality. In this research we have adopted a bias correction approach that takes into account the variation of rainfall in space and time. A clustering based approach is employed in which every new data point (e.g. of Tropical Rainfall Measuring Mission (TRMM)) is first assigned to a specific cluster of that data product and then, by identifying the corresponding cluster of gauge data, the bias correction specific to that cluster is adopted. The presented approach considers the space-time variation of rainfall and as a result the corrected data is more realistic. Keywords: bias correction, rainfall, TRMM, satellite rainfall

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches.

PubMed

Bolin, Jocelyn H; Edwards, Julianne M; Finch, W Holmes; Cassady, Jerrell C

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches

PubMed Central

Bolin, Jocelyn H.; Edwards, Julianne M.; Finch, W. Holmes; Cassady, Jerrell C.

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering. PMID:24795683

The Grism Lens-amplified Survey from Space (Glass). IX. The Dual Origin of Low-mass Cluster Galaxies as Revealed by New Structural Analyses

NASA Astrophysics Data System (ADS)

Morishita, Takahiro; Abramson, Louis E.; Treu, Tommaso; Vulcani, Benedetta; Schmidt, Kasper B.; Dressler, Alan; Poggianti, Bianca M.; Malkan, Matthew A.; Wang, Xin; Huang, Kuang-Han; Trenti, Michele; Bradač, Maruša; Hoag, Austin

2017-02-01

Using deep Hubble Frontier Fields imaging and slitless spectroscopy from the Grism Survey from Space, we study 2200 cluster and 1748 field galaxies at 0.2≤slant z≤slant 0.7 to determine the impact of environment on galaxy size and structure at stellar masses {log}{M}* /{M}⊙ > 7.8, an unprecedented limit at these redshifts. Based on simple assumptions—{r}e=f({M}* )—we find no significant differences in half-light radii (re) between equal-mass cluster or field systems. More complex analyses—{r}e=f({M}* ,U-V,n,z,{{Σ }})—reveal local density (Σ) to induce only a 7% ± 3% (95% confidence) reduction in re beyond what can be accounted for by U - V color, Sérsic index (n), and redshift (z) effects. Almost any size difference between galaxies in high- and low-density regions is thus attributable to their different distributions in properties other than environment. Indeed, we find a clear color-re correlation in low-mass passive cluster galaxies ({log}{M}* /{M}⊙ < 9.8) such that bluer systems have larger radii, with the bluest having sizes consistent with equal-mass star-forming galaxies. We take this as evidence that large-re low-mass passive cluster galaxies are recently acquired systems that have been environmentally quenched without significant structural transformation (e.g., by ram pressure stripping or starvation). Conversely, ˜20% of small-re low-mass passive cluster galaxies appear to have been in place since z≳ 3. Given the consistency of the small-re galaxies’ stellar surface densities (and even colors) with those of systems more than ten times as massive, our findings suggest that clusters mark places where galaxy evolution is accelerated for an ancient base population spanning most masses, with late-time additions quenched by environment-specific mechanisms mainly restricted to the lowest masses.

Blastodinium spp. infect copepods in the ultra-oligotrophic marine waters of the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Alves-de-Souza, C.; Cornet, C.; Nowaczyk, A.; Gasparini, S.; Skovgaard, A.; Guillou, L.

2011-08-01

Blastodinium are chloroplast-containing dinoflagellates which infect a wide range of copepods. They develop inside the gut of their host, where they produce successive generations of sporocytes that are eventually expelled through the anus of the copepod. Here, we report on copepod infections in the oligotrophic to ultra-oligotrophic waters of the Mediterranean Sea sampled during the BOUM cruise. Based on a DNA-stain screening of gut contents, 16 % of copepods were possibly infected in samples from the Eastern Mediterranean infected, with up to 51 % of Corycaeidae, 33 % of Calanoida, but less than 2 % of Oithonidae and Oncaeidae. Parasites were classified into distinct morphotypes, with some tentatively assigned to species B. mangini, B. contortum, and B. cf. spinulosum. Based upon the SSU rDNA gene sequence analyses of 15 individuals, the genus Blastodinium was found to be polyphyletic, containing at least three independent clusters. The first cluster grouped all sequences retrieved from parasites of Corycaeidae and Oncaeidae during this study, and included sequences of Blastodinium mangini (the "mangini" cluster). Sequences from cells infecting Calanoida belonged to two different clusters, one including B. contortum (the "contortum" cluster), and the other uniting all B. spinulosum-like morphotypes (the "spinulosum" cluster). Cluster-specific oligonucleotidic probes were designed and tested by fluorescence in situ hybridization (FISH) in order to assess the distribution of dinospores, the Blastodinium dispersal and infecting stage. Probe-positive cells were all small thecate dinoflagellates, with lengths ranging from 7 to 18 μm. Maximal abundances of Blastodinium dinospores were detected at the Deep Chlorophyll Maximum (DCM) or slightly below. This was in contrast to distributions of autotrophic pico- and nanoplankton, microplanktonic dinoflagellates, and nauplii which showed maximal concentrations above the DCM. The distinct distribution of dinospores and nauplii argues against infection during the naupliar stage. Dinospores, described as autotrophic in the literature, may escape the severe nutrient limitation of ultra-oligotrophic ecosystems by living inside copepods.

Blastodinium spp. infect copepods in the ultra-oligotrophic marine waters of the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Alves-de-Souza, C.; Cornet, C.; Nowaczyk, A.; Gasparini, S.; Skovgaard, A.; Guillou, L.

2011-03-01

Blastodinium are chloroplast-containing dinoflagellates which infect a wide range of copepods. They develop inside the gut of their host, where they produce successive generations of sporocytes that are eventually expelled through the anus of the copepod. Here, we report on copepod infections in the oligotrophic to ultra-oligotrophic waters of the Mediterranean Sea sampled during the BOUM cruise. Based on a DNA-stain screening of gut contents, 16% of copepods were possibly infected in samples from the Eastern Mediterranean, with up to 51% of Corycaeidae, 33% of Calanoida, but less than 2% of Oithonidae and Oncaeidae. Parasites were classified into distinct morphotypes, with some tentatively assigned to species B. mangini, B. contortum, and B. cf. spinulosum. Based upon the SSU rDNA gene sequence analyses of 15 individuals, the genus Blastodinium was found to be polyphyletic, containing at least three independent clusters. The first cluster grouped all sequences retrieved from parasites of Corycaeidae and Oncaeidae during this study, and included sequences of Blastodinium mangini (the "mangini" cluster). Sequences from cells infecting Calanoida belonged to two different clusters, one including B. contortum (the "contortum" cluster), and the other uniting all B. spinulosum-like morphotypes (the "spinulosum" cluster). Cluster-specific oligonucleotidic probes were designed and tested by FISH in order to assess the distribution of dinospores, the Blastodinium dispersal and infecting stage. Probe-positive cells were all small thecate dinoflagellates, with lengths ranging from 7 to 18 μm. Maximal abundances of Blastodinium dinospores were detected at the Deep Chlorophyll Maximum (DCM) or slightly below. This was in contrast to distributions of autotrophic pico- and nanoplankton, microplanktonic dinoflagellates, and nauplii which showed maximal concentrations above the DCM. The distinct distributions of dinospores and nauplii argues against infection during the naupliar stage. Blastodinium, described as autotrophic in the literature, may escape the severe nutrient limitation of ultra-oligotrophic ecosystems by living inside copepods.

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

PubMed Central

Yin, Wenwu; Yu, Hongjie; Si, Yali; Li, Jianhui; Zhou, Yuanchun; Zhou, Xiaoyan; Magalhães, Ricardo J. Soares.

2013-01-01

Background Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China. Methods We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread. Findings Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease. Conclusion Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program. PMID:23991098

Detecting Subgroups in Children Diagnosed with Pervasive Developmental Disorder--Not Otherwise Specified

ERIC Educational Resources Information Center

Brennan, Laura; Barton, Marianne; Chen, Chi-Ming; Green, James; Fein, Deborah

2015-01-01

Hierarchical cluster analyses were used to detect three subgroups in a sample of children with pervasive developmental disorder--not otherwise specified (PDD-NOS) evaluated at ages 2 and 4. At age 2, Cluster 1 demonstrated few autism symptoms and high cognitive scores; 60% no longer met criteria for PDD at 4. Cluster 2 exhibited more autism…

Plasmaspheric Plumes Observed by the CLUSTER and IMAGE Spacecraft

NASA Technical Reports Server (NTRS)

Fung, S. F.; Benson, R. F.; Garcia, L. N.; Adrian, M. L.; Sandel, B.; Goldstein, M. L.

2008-01-01

Global IMAGE/EUV observations have revealed complex changes in plasmaspheric structures as the plasmasphere responds to geomagnetic activity while remaining under varying degrees of influence by co-rotation, depending on the radial distance. The complex plasmaspheric dynamics, with different scales of variability, is clearly far from being well understood. There is now renewed interest in the plasmasphere due to its apparent connections with the development of the ring current and radiation belt, and loss of ionospheric plasmas. Early in the mission, the Cluster spacecraft only crossed the plasmapause (L - 4) occasionally and made measurements of the outer plasmasphere and plasmaspheric drainage plumes. The study by Darrouzet et al. [2006] provided detailed analyses of in situ Cluster observations and IMAGE EUV observations of three plasmaspheric plumes detected in April-June, 2002. Within the next couple of years, Cluster orbit will change, causing perigee to migrate to lower altitudes, and thus providing excellent opportunities to obtain more detailed measurements of the plasmasphere. In this paper, we report our analyses of the earlier Cluster-IMAGE events by incorporating the different perspectives provided by the IMAGE Radio Plasma Imager (RPI) observations. We will discuss our new understanding of the structure and dynamics of the Cluster-IMAGE events.

Investigating the internal structure of galaxies and clusters through strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jigish Gandhi, Pratik; Grillo, Claudio; Bonamigo, Mario

2018-01-01

Gravitational lensing studies have radically improved our understanding of the internal structure of galaxies and cluster-scale systems. In particular, the combination of strong lensing and stellar dynamics or stellar population synthesis models have made it possible to characterize numerous fundamental properties of the galaxies as well as dark matter halos and subhalos with unprecedented robustness and accuracy. Here we demonstrate the usefulness and accuracy of strong lensing as a probe for characterising the properties of cluster members as well as dark matter halos, to show that such characterisation carried out via lensing analyses alone is as viable as those carried out through a combination of spectroscopy and lensing analyses.Our study uses focuses on the early-type galaxy cluster MACS J1149.5+2223 at redshift 0.54 in the Hubble Frontier Fields (HFF) program, where the first magnified and spatially resolved multiple images of supernova (SN) “Refsdal” and its late-type host galaxy at redshift 1.489 were detected. The Refsdal system is unique in being the first ever multiply-imaged supernova, with it’s first four images appearing in an Einstein Cross configuration around one of the cluster members in 2015. In our lensing analyses we use HST data of the multiply-imaged SN Refsdal to constrain the dynamical masses, velocity dispersions, and virial radii of individual galaxies and dark matter halos in the MACS J1149.5+2223 cluster. For our lensing models we select a sample of 300 cluster members within approximately 500 kpc from the BCG, and a set of reliable multiple images associated with 18 distinct knots in the SN host spiral galaxy, as well as multiple images of the supernova itself. Our results provide accurate measurements of the masses, velocity dispersions, and radii of the cluster’s dark matter halo as well as three chosen members galaxies, in strong agreement with those obtained by Grillo et al 2015, demonstrating the usefulness of strong lensing in characterising the properties of cluster-scale systems.

Cluster Randomised Trials in Cochrane Reviews: Evaluation of Methodological and Reporting Practice.

PubMed

Richardson, Marty; Garner, Paul; Donegan, Sarah

2016-01-01

Systematic reviews can include cluster-randomised controlled trials (C-RCTs), which require different analysis compared with standard individual-randomised controlled trials. However, it is not known whether review authors follow the methodological and reporting guidance when including these trials. The aim of this study was to assess the methodological and reporting practice of Cochrane reviews that included C-RCTs against criteria developed from existing guidance. Criteria were developed, based on methodological literature and personal experience supervising review production and quality. Criteria were grouped into four themes: identifying, reporting, assessing risk of bias, and analysing C-RCTs. The Cochrane Database of Systematic Reviews was searched (2nd December 2013), and the 50 most recent reviews that included C-RCTs were retrieved. Each review was then assessed using the criteria. The 50 reviews we identified were published by 26 Cochrane Review Groups between June 2013 and November 2013. For identifying C-RCTs, only 56% identified that C-RCTs were eligible for inclusion in the review in the eligibility criteria. For reporting C-RCTs, only eight (24%) of the 33 reviews reported the method of cluster adjustment for their included C-RCTs. For assessing risk of bias, only one review assessed all five C-RCT-specific risk-of-bias criteria. For analysing C-RCTs, of the 27 reviews that presented unadjusted data, only nine (33%) provided a warning that confidence intervals may be artificially narrow. Of the 34 reviews that reported data from unadjusted C-RCTs, only 13 (38%) excluded the unadjusted results from the meta-analyses. The methodological and reporting practices in Cochrane reviews incorporating C-RCTs could be greatly improved, particularly with regard to analyses. Criteria developed as part of the current study could be used by review authors or editors to identify errors and improve the quality of published systematic reviews incorporating C-RCTs.

[A method for the analysis of overlapped peaks in the high performance liquid chromatogram based on spectrum analysis].

PubMed

Liu, Bao; Fan, Xiaoming; Huo, Shengnan; Zhou, Lili; Wang, Jun; Zhang, Hui; Hu, Mei; Zhu, Jianhua

2011-12-01

A method was established to analyse the overlapped chromatographic peaks based on the chromatographic-spectra data detected by the diode-array ultraviolet detector. In the method, the three-dimensional data were de-noised and normalized firstly; secondly the differences and clustering analysis of the spectra at different time points were calculated; then the purity of the whole chromatographic peak were analysed and the region were sought out in which the spectra of different time points were stable. The feature spectra were extracted from the spectrum-stable region as the basic foundation. The nonnegative least-square method was chosen to separate the overlapped peaks and get the flow curve which was based on the feature spectrum. The three-dimensional divided chromatographic-spectrum peak could be gained by the matrix operations of the feature spectra with the flow curve. The results displayed that this method could separate the overlapped peaks.

Diary Data Subjected to Cluster Analysis of Intake/Output/Void Habits with Resulting Clusters Compared by Continence Status, Age, Race

PubMed Central

Miller, Janis M; Guo, Ying; Rodseth, Sarah Becker

2011-01-01

Background Data that incorporate the full complexity of healthy beverage intake and voiding frequency do not exist; therefore, clinicians reviewing bladder habits or voiding diaries for continence care must rely on expert opinion recommendations. Objective To use data-driven cluster analyses to reduce complex voiding diary variables into discrete patterns or data cluster profiles, descriptively name the clusters, and perform validity testing. Method Participants were 352 community women who filled out a 3-day voiding diary. Six variables (void frequency during daytime hours, void frequency during nighttime hours, modal output, total output, total intake, and body mass index) were entered into cluster analyses. The clusters were analyzed for differences by continence status, age, race (Black women, n = 196 White women, n = 156), and for those who were incontinent, by leakage episode severity. Results Three clusters emerged, labeled descriptively as Conventional, Benchmark, and Superplus. The Conventional cluster (68% of the sample) demonstrated mean daily intake of 45 ±13 ounces; mean daily output of 37 ± 15 ounces, mean daily voids 5 ± 2 times, mean modal daytime output 10±0.5 ounces, and mean nighttime voids 1±1 times. The Superplus cluster (7% of the sample) showed double or triple these values across the 5 variables, and the Benchmark cluster (25%) showed values consistent with current popular recommendations on intake and output (e.g., meeting or exceeding the 8 × 8 fluid intake rule of thumb). The clusters differed significantly (p < .05) by age, race, amount of irritating beverages consumed, and incontinence status. Discussion Identification of three discrete clusters provides for a potential parsimonious but data-driven means of classifying individuals for additional epidemiological or clinical study. The clinical utility rests with potential for intervening to move an individual from a high risk to low risk cluster with regards to incontinence. PMID:21317828

Strategy-based reasoning training modulates cortical thickness and resting-state functional connectivity in adults with chronic traumatic brain injury.

PubMed

Han, Kihwan; Davis, Rebecca A; Chapman, Sandra B; Krawczyk, Daniel C

2017-05-01

Prior studies have demonstrated training-induced changes in the healthy adult brain. Yet, it remains unclear how the injured brain responds to cognitive training months-to-years after injury. Sixty individuals with chronic traumatic brain injury (TBI) were randomized into either strategy-based ( N  = 31) or knowledge-based ( N  = 29) training for 8 weeks. We measured cortical thickness and resting-state functional connectivity (rsFC) before training, immediately posttraining, and 3 months posttraining. Relative to the knowledge-based training group, the cortical thickness of the strategy-based training group showed diverse temporal patterns of changes over multiple brain regions ( p vertex  < .05, p cluster  < .05): (1) increases followed by decreases, (2) monotonic increases, and (3) monotonic decreases. However, network-based statistics (NBS) analysis of rsFC among these regions revealed that the strategy-based training group induced only monotonic increases in connectivity, relative to the knowledge-based training group (| Z | > 1.96, p NBS  < 0.05). Complementing the rsFC results, the strategy-based training group yielded monotonic improvement in scores for the trail-making test ( p  <   .05). Analyses of brain-behavior relationships revealed that improvement in trail-making scores were associated with training-induced changes in cortical thickness ( p vertex  < .05, p cluster  < .05) and rsFC ( p vertex  < .05, p cluster  < .005) within the strategy-based training group. These findings suggest that training-induced brain plasticity continues through chronic phases of TBI and that brain connectivity and cortical thickness may serve as markers of plasticity.

Media exposure and dimensions of anxiety sensitivity: differential associations with PTSD symptom clusters.

PubMed

Collimore, Kelsey C; McCabe, Randi E; Carleton, R Nicholas; Asmundson, Gordon J G

2008-08-01

The present investigation examined the impact of anxiety sensitivity (AS) and media exposure on posttraumatic stress disorder (PTSD) symptoms. Reactions from 143 undergraduate students in Hamilton, Ontario were assessed in the Fall of 2003 to gather information on anxiety, media coverage, and PTSD symptoms related to exposure to a remote traumatic event (September 11th). Regression analyses revealed that the Anxiety Sensitivity Index (ASI; [Peterson, R. A., & Reiss, S. (1992). Anxiety Sensitivity Index manual, 2nd ed. Worthington, Ohio: International Diagnostic Systems]) and State-Trait Anxiety Inventory trait form (STAI-T; [Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970). State-trait anxiety inventory. Palo Alto, California: Consulting Psychologists Press]) total scores were significant predictors of PTSD symptoms in general. The ASI total score was also a significant predictor of hyperarousal and avoidance symptoms. Subsequent analyses further demonstrated differential relationships based on subscales and symptom clusters. Specifically, media exposure and trait anxiety predicted hyperarousal and re-experiencing symptoms, whereas the ASI fear of somatic sensations subscale significantly predicted avoidance and overall PTSD symptoms. Implications and directions for future research are discussed.

Associations Across Caregiver and Care Recipient Symptoms: Self-Organizing Map and Meta-analysis.

PubMed

Voutilainen, Ari; Ruokostenpohja, Nora; Välimäki, Tarja

2018-03-19

The main objective of this study was to reveal generalizable associations across caregiver burden (CGB), caregiver depression (CGD), care recipient cognitive ability (CRCA), and care recipient behavioral and psychological symptoms of dementia (BPSD). Studies published between 2004 and 2014 and reporting CGB and/or CGD together with CRCA and/or BPSD were included. Only 95 out of 1,955 studies provided enough data for data clustering with the Self-Organizing Map (SOM) and 27 of them for meta-analyses based on correlation coefficients. Caregiver and care recipient symptoms were not tightly associated with each other, except for the CGB-BPSD interaction at the individual level. SOM emphasized the cluster comprising studies reporting low CGB, low CGD, high CRCA, and few BPSD. Meta-analyses indicated high heterogeneity between the original studies. Relationships between caregiver and care recipient symptoms should be treated as situation-specific phenomena, at least when the symptoms are moderate at most. Dementia caregiving per se should not be understood as a source of stress and mental health problems. More systematic and coherent use of measures is necessary to enable a comprehensive analysis of caregiving.

Descriptive epidemiology of typhoid fever during an epidemic in Harare, Zimbabwe, 2012.

PubMed

Polonsky, Jonathan A; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J

2014-01-01

Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range.

Descriptive Epidemiology of Typhoid Fever during an Epidemic in Harare, Zimbabwe, 2012

PubMed Central

Polonsky, Jonathan A.; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J.

2014-01-01

Background Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. Methods A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. Principal Findings We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. Conclusions This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range. PMID:25486292

The faces of pain: a cluster analysis of individual differences in facial activity patterns of pain.

PubMed

Kunz, M; Lautenbacher, S

2014-07-01

There is general agreement that facial activity during pain conveys pain-specific information but is nevertheless characterized by substantial inter-individual differences. With the present study we aim to investigate whether these differences represent idiosyncratic variations or whether they can be clustered into distinct facial activity patterns. Facial actions during heat pain were assessed in two samples of pain-free individuals (n = 128; n = 112) and were later analysed using the Facial Action Coding System. Hierarchical cluster analyses were used to look for combinations of single facial actions in episodes of pain. The stability/replicability of facial activity patterns was determined across samples as well as across different basic social situations. Cluster analyses revealed four distinct activity patterns during pain, which stably occurred across samples and situations: (I) narrowed eyes with furrowed brows and wrinkled nose; (II) opened mouth with narrowed eyes; (III) raised eyebrows; and (IV) furrowed brows with narrowed eyes. In addition, a considerable number of participants were facially completely unresponsive during pain induction (stoic cluster). These activity patterns seem to be reaction stereotypies in the majority of individuals (in nearly two-thirds), whereas a minority displayed varying clusters across situations. These findings suggest that there is no uniform set of facial actions but instead there are at least four different facial activity patterns occurring during pain that are composed of different configurations of facial actions. Raising awareness about these different 'faces of pain' might hold the potential of improving the detection and, thereby, the communication of pain. © 2013 European Pain Federation - EFIC®

SOTXTSTREAM: Density-based self-organizing clustering of text streams.

PubMed

Bryant, Avory C; Cios, Krzysztof J

2017-01-01

A streaming data clustering algorithm is presented building upon the density-based self-organizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

WAIS-III index score profiles in the Canadian standardization sample.

PubMed

Lange, Rael T

2007-01-01

Representative index score profiles were examined in the Canadian standardization sample of the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III). The identification of profile patterns was based on the methodology proposed by Lange, Iverson, Senior, and Chelune (2002) that aims to maximize the influence of profile shape and minimize the influence of profile magnitude on the cluster solution. A two-step cluster analysis procedure was used (i.e., hierarchical and k-means analyses). Cluster analysis of the four index scores (i.e., Verbal Comprehension [VCI], Perceptual Organization [POI], Working Memory [WMI], Processing Speed [PSI]) identified six profiles in this sample. Profiles were differentiated by pattern of performance and were primarily characterized as (a) high VCI/POI, low WMI/PSI, (b) low VCI/POI, high WMI/PSI, (c) high PSI, (d) low PSI, (e) high VCI/WMI, low POI/PSI, and (f) low VCI, high POI. These profiles are potentially useful for determining whether a patient's WAIS-III performance is unusual in a normal population.

A Fine-Scale Functional Logic to Convergence from Retina to Thalamus.

PubMed

Liang, Liang; Fratzl, Alex; Goldey, Glenn; Ramesh, Rohan N; Sugden, Arthur U; Morgan, Josh L; Chen, Chinfei; Andermann, Mark L

2018-05-31

Numerous well-defined classes of retinal ganglion cells innervate the thalamus to guide image-forming vision, yet the rules governing their convergence and divergence remain unknown. Using two-photon calcium imaging in awake mouse thalamus, we observed a functional arrangement of retinal ganglion cell axonal boutons in which coarse-scale retinotopic ordering gives way to fine-scale organization based on shared preferences for other visual features. Specifically, at the ∼6 μm scale, clusters of boutons from different axons often showed similar preferences for either one or multiple features, including axis and direction of motion, spatial frequency, and changes in luminance. Conversely, individual axons could "de-multiplex" information channels by participating in multiple, functionally distinct bouton clusters. Finally, ultrastructural analyses demonstrated that retinal axonal boutons in a local cluster often target the same dendritic domain. These data suggest that functionally specific convergence and divergence of retinal axons may impart diverse, robust, and often novel feature selectivity to visual thalamus. Copyright © 2018 Elsevier Inc. All rights reserved.

Evidence of sibling species in the brown planthopper complex (Nilaparvata lugens) detected from short and long primer random amplified polymorphic DNA fingerprints.

PubMed

Latif, M A; Soon Guan, Tan; Mohd Yusoh, Omar; Siraj, Siti Shapor

2008-08-01

The inheritance of 31 amplicons from short and long primer RAPD was tested for segregating ratios in two families of the brown planthopper, Nilaparvata lugens, and they were found to be inherited in a simple Mendelian fashion. These markers could now be used in population genetics studies of N. lugens. Ten populations of N. lugens were collected from five locations in Malaysia. Each location had two sympatric populations. Cluster and principal coordinate analyses based on genetic distance along with AMOVA revealed that the rice-infesting populations (with high esterase activity) at five localities clustered together as a group, and Leersia-infesting populations (with low esterase activity) at the same localities formed another distinct cluster. Two amplicons from primers OPD03 (0.65 kb) and peh#6 (1.0 kb) could be considered diagnostic bands, which were fixed in the Leersia-infesting populations. These results represent evidence of a sibling species in the N. lugens complex.

Effects of different preservation methods on inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) molecular markers in botanic samples.

PubMed

Wang, Xiaolong; Li, Lin; Zhao, Jiaxin; Li, Fangliang; Guo, Wei; Chen, Xia

2017-04-01

To evaluate the effects of different preservation methods (stored in a -20°C ice chest, preserved in liquid nitrogen and dried in silica gel) on inter simple sequence repeat (ISSR) or random amplified polymorphic DNA (RAPD) analyses in various botanical specimens (including broad-leaved plants, needle-leaved plants and succulent plants) for different times (three weeks and three years), we used a statistical analysis based on the number of bands, genetic index and cluster analysis. The results demonstrate that methods used to preserve samples can provide sufficient amounts of genomic DNA for ISSR and RAPD analyses; however, the effect of different preservation methods on these analyses vary significantly, and the preservation time has little effect on these analyses. Our results provide a reference for researchers to select the most suitable preservation method depending on their study subject for the analysis of molecular markers based on genomic DNA. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Analyses on the geometrical structure of magnetic field in the current sheet based on cluster measurements

NASA Astrophysics Data System (ADS)

Shen, C.; Li, X.; Dunlop, M.; Liu, Z. X.; Balogh, A.; Baker, D. N.; Hapgood, M.; Wang, X.

2003-05-01

The geometrical structure of the magnetic field is a critical character in the magnetospheric dynamics. Using the magnetic field data measured by the Cluster constellation satellites, the geometrical structure including the curvature radius, directions of curvature, and normal of the osculating planes of the magnetic field lines within the current sheet/neutral sheet have been investigated. The results are (1) Inside of the tail neutral sheet (NS), the curvature of magnetic field lines points towards Earth, the normal of the osculating plane points duskward, and the characteristic half width (or the minimum curvature radius) of the neutral sheet is generally less than 2 RE, for many cases less than 1600 km. (2) Outside of the neutral sheet, the curvature of magnetic field lines pointed northward (southward) at the north (south) side of NS, the normal of the osculating plane points dawnward, and the curvature radius is about 5 RE ˜ 10 RE. (3) Thin NS, where the magnetic field lines have the minimum of the curvature radius less than 0.25 RE, may appear at all the local time between LT 20 hours and 4 hours, but thin NS occurs more frequently near to midnight than that at the dawnside and duskside. (4) The size of the NS is dependent on substorm phases. Generally, the NS is thin during the growth and expansion phases and grows thick during the recovery phase. (5) For the one-dimensional NS, the half thickness and flapping velocity of the NS could be quantitatively determined. Therefore the differential geometry analyses based on Cluster 4-point magnetic measurements open a window for visioning the three-dimensional static and dynamic magnetic field structure of geomagnetosphere.

Frequent gene flow blurred taxonomic boundaries of sections in Lilium L. (Liliaceae)

PubMed Central

Liu, Shih-Hui; Chiang, Tzen-Yuh

2017-01-01

Gene flow between species may last a long time in plants. Reticulation inevitably causes difficulties in phylogenetic reconstruction. In this study, we looked into the genetic divergence and phylogeny of 20 Lilium species based on multilocus analyses of 8 genes of chloroplast DNA (cpDNA), the internally transcribed nuclear ribosomal DNA (nrITS) spacer and 20 loci extracted from the expressed sequence tag (EST) libraries of L. longiflorum Thunb. and L. formosanum Wallace. The phylogeny based on the combined data of the maternally inherited cpDNA and nrITS was largely consistent with the taxonomy of Lilium sections. This phylogeny was deemed the hypothetical species tree and uncovered three groups, i.e., Cluster A consisting of 4 taxa from the sections Pseudolirium and Liriotypus, Cluster B consisting of the 4 taxa from the sections Leucolirion, Archelirion and Daurolirion, and Cluster C comprising 10 taxa mostly from the sections Martagon and Sinomartagon. In contrast, systematic inconsistency occurred across the EST loci, with up to 19 genes (95%) displaying tree topologies deviating from the hypothetical species tree. The phylogenetic incongruence was likely attributable to the frequent genetic exchanges between species/sections, as indicated by the high levels of genetic recombination and the IMa analyses with the EST loci. Nevertheless, multilocus analysis could provide complementary information among the loci on the species split and the extent of gene flow between the species. In conclusion, this study not only detected frequent gene flow among Lilium sections that resulted in phylogenetic incongruence but also reconstructed a hypothetical species tree that gave insights into the nature of the complex relationships among Lilium species. PMID:28841664

Dynamics and Biodiversity of Populations of Lactic Acid Bacteria and Acetic Acid Bacteria Involved in Spontaneous Heap Fermentation of Cocoa Beans in Ghana▿

PubMed Central

Camu, Nicholas; De Winter, Tom; Verbrugghe, Kristof; Cleenwerck, Ilse; Vandamme, Peter; Takrama, Jemmy S.; Vancanneyt, Marc; De Vuyst, Luc

2007-01-01

The Ghanaian cocoa bean heap fermentation process was studied through a multiphasic approach, encompassing both microbiological and metabolite target analyses. A culture-dependent (plating and incubation, followed by repetitive-sequence-based PCR analyses of picked-up colonies) and culture-independent (denaturing gradient gel electrophoresis [DGGE] of 16S rRNA gene amplicons, PCR-DGGE) approach revealed a limited biodiversity and targeted population dynamics of both lactic acid bacteria (LAB) and acetic acid bacteria (AAB) during fermentation. Four main clusters were identified among the LAB isolated: Lactobacillus plantarum, Lactobacillus fermentum, Leuconostoc pseudomesenteroides, and Enterococcus casseliflavus. Other taxa encompassed, for instance, Weissella. Only four clusters were found among the AAB identified: Acetobacter pasteurianus, Acetobacter syzygii-like bacteria, and two small clusters of Acetobacter tropicalis-like bacteria. Particular strains of L. plantarum, L. fermentum, and A. pasteurianus, originating from the environment, were well adapted to the environmental conditions prevailing during Ghanaian cocoa bean heap fermentation and apparently played a significant role in the cocoa bean fermentation process. Yeasts produced ethanol from sugars, and LAB produced lactic acid, acetic acid, ethanol, and mannitol from sugars and/or citrate. Whereas L. plantarum strains were abundant in the beginning of the fermentation, L. fermentum strains converted fructose into mannitol upon prolonged fermentation. A. pasteurianus grew on ethanol, mannitol, and lactate and converted ethanol into acetic acid. A newly proposed Weissella sp., referred to as “Weissella ghanaensis,” was detected through PCR-DGGE analysis in some of the fermentations and was only occasionally picked up through culture-based isolation. Two new species of Acetobacter were found as well, namely, the species tentatively named “Acetobacter senegalensis” (A. tropicalis-like) and “Acetobacter ghanaensis” (A. syzygii-like). PMID:17277227

XMM-Newton X-ray and HST weak gravitational lensing study of the extremely X-ray luminous galaxy cluster Cl J120958.9+495352 (z = 0.902)

NASA Astrophysics Data System (ADS)

Thölken, Sophia; Schrabback, Tim; Reiprich, Thomas H.; Lovisari, Lorenzo; Allen, Steven W.; Hoekstra, Henk; Applegate, Douglas; Buddendiek, Axel; Hicks, Amalia

2018-03-01

Context. Observations of relaxed, massive, and distant clusters can provide important tests of standard cosmological models, for example by using the gas mass fraction. To perform this test, the dynamical state of the cluster and its gas properties have to be investigated. X-ray analyses provide one of the best opportunities to access this information and to determine important properties such as temperature profiles, gas mass, and the total X-ray hydrostatic mass. For the last of these, weak gravitational lensing analyses are complementary independent probes that are essential in order to test whether X-ray masses could be biased. Aims: We study the very luminous, high redshift (z = 0.902) galaxy cluster Cl J120958.9+495352 using XMM-Newton data. We measure global cluster properties and study the temperature profile and the cooling time to investigate the dynamical status with respect to the presence of a cool core. We use Hubble Space Telescope (HST) weak lensing data to estimate its total mass and determine the gas mass fraction. Methods: We perform a spectral analysis using an XMM-Newton observation of 15 ks cleaned exposure time. As the treatment of the background is crucial, we use two different approaches to account for the background emission to verify our results. We account for point spread function effects and deproject our results to estimate the gas mass fraction of the cluster. We measure weak lensing galaxy shapes from mosaic HST imaging and select background galaxies photometrically in combination with imaging data from the William Herschel Telescope. Results: The X-ray luminosity of Cl J120958.9+495352 in the 0.1-2.4 keV band estimated from our XMM-Newton data is LX = (13.4+1.2-1.0) × 1044 erg/s and thus it is one of the most X-ray luminous clusters known at similarly high redshift. We find clear indications for the presence of a cool core from the temperature profile and the central cooling time, which is very rare at such high redshifts. Based on the weak lensing analysis, we estimate a cluster mass of M500/1014 M⊙ = 4.4+2.2-2.0 (stat.) + 0.6 (sys.) and a gas mass fraction of fgas,2500 = 0.11-0.03+0.06 in good agreement with previous findings for high redshift and local clusters.

Solid state and aqueous behavior of uranyl peroxide cage clusters

NASA Astrophysics Data System (ADS)

Pellegrini, Kristi Lynn

Uranyl peroxide cage clusters include a large family of more than 50 published clusters of a variety of sizes, which can incorporate various ligands including pyrophosphate and oxalate. Previous studies have reported that uranyl clusters can be used as a method to separate uranium from a solid matrix, with potential applications in reprocessing of irradiated nuclear fuel. Because of the potential applications of these novel structures in an advanced nuclear fuel cycle and their likely presence in areas of contamination, it is important to understand their behavior in both solid state and aqueous systems, including complex environments where other ions are present. In this thesis, I examine the aqueous behavior of U24Pp 12, as well as aqueous cluster systems with added mono-, di-, and trivalent cations. The resulting solutions were analyzed using dynamic light scattering and ultra-small angle X-ray scattering to evaluate the species in solution. Precipitates of these systems were analyzed using powder X-ray diffraction, X-ray fluorescence spectrometry, and Raman spectroscopy. The results of these analyses demonstrate the importance of cation size, charge, and concentration of added cations on the aqueous behavior of uranium macroions. Specifically, aggregates of various sizes and shapes form rapidly upon addition of cations, and in some cases these aggregates appear to precipitate into an X-ray amorphous material that still contains U24Pp12 clusters. In addition, I probe aggregation of U24Pp12 and U60, another uranyl peroxide cage cluster, in mixed solvent water-alcohol systems. The aggregation of uranyl clusters in water-alcohol systems is a result of hydrogen bonding with polar organic molecules and the reduction of the dielectric constant of the system. Studies of aggregation of uranyl clusters also allow for comparison between the newer uranyl polyoxometalate family and century-old transition metal polyoxometalates. To complement the solution studies of uranyl cage clusters, solid state analyses of U24Pp12 are presented, including single crystal X-ray diffraction and preliminary single crystal neutron diffraction. Solid state analyses are used to probe the complicated bonding environments between U24Pp12 and crystallized counterions, giving further insight into the importance of cluster protonation and counterions in uranyl cluster systems. The combination of solid state and solution techniques provides information about the complicated nature of uranyl peroxide nanoclusters, and insight towards future applications of clusters in the advanced nuclear fuel cycle and the environment.

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

Atmospheric Methane Enhancements Related with Natural Gas Usage in the Greater Houston Area

NASA Astrophysics Data System (ADS)

Sanchez, N. P.; Zheng, C.; Ye, W.; Czader, B.; Cohan, D. S.; Tittel, F. K.; Griffin, R. J.

2017-12-01

Natural gas (NG) usage as a replacement of oil and coal has increased significantly in the U.S in recent years. Despite the benefits associated with this fuel, leakage from NG distribution systems and in-use uncombusted NG (e.g., compressed natural gas vehicles) can be relevant sources of methane (CH4) emissions in urban centers. Methane, the main constituent of NG, is a potent greenhouse gas impacting the chemistry of the atmosphere, whose emission might outweigh the potential environmental advantages of NG use. Although the Greater Houston area (GHA) is the fifth-largest metropolitan area in the U.S, no studies on the potential impact of NG usage on atmospheric CH4 levels have been published in the scientific literature to date. In this work, a mobile-based study of CH4 and ethane (C2H6) concentration levels in eight residential zones with different expected probability of NG leakage in the GHA was conducted in the summer of 2016. A novel laser-based sensor system for simultaneous detection of CH4 and C2H6 was developed and deployed in a mid-sized vehicle, and monitoring of these gas species was conducted for over 14 days covering 250 road miles. Both linear discriminant and cluster analyses were performed to assess the spatial variability of atmospheric CH4 concentrations in the GHA. These analyses showed clear differences in the CH4 mixing ratios in an inter- and intra-neighborhood level and indicated the presence of high CH4 concentration clusters mainly located in the central and west central parts of the GHA. Source discrimination analyses based on orthogonal regression analysis and a Keeling-like plot method were conducted to establish the predominant origin of CH4 in the identified high concentration clusters and in over 30 CH4 concentration peaks observed during the field campaign. Results of these analyses indicate that thermogenic sources of CH4 (e.g., NG) were predominant in short-duration concentration spikes (lasting less than 10 minutes), while CH4 with a biogenic origin was mainly related with large-area concentration events (duration above 10 minutes). The content of C2H6 in the thermogenic-related peak events (2.7-5.9%) agreed with the composition of the NG distributed in the GHA, indicating the potential relevance of NG usage on CH4 enhancements observed in the Houston atmosphere.

Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review.

PubMed

Groppe, David M; Urbach, Thomas P; Kutas, Marta

2011-12-01

Event-related potentials (ERPs) and magnetic fields (ERFs) are typically analyzed via ANOVAs on mean activity in a priori windows. Advances in computing power and statistics have produced an alternative, mass univariate analyses consisting of thousands of statistical tests and powerful corrections for multiple comparisons. Such analyses are most useful when one has little a priori knowledge of effect locations or latencies, and for delineating effect boundaries. Mass univariate analyses complement and, at times, obviate traditional analyses. Here we review this approach as applied to ERP/ERF data and four methods for multiple comparison correction: strong control of the familywise error rate (FWER) via permutation tests, weak control of FWER via cluster-based permutation tests, false discovery rate control, and control of the generalized FWER. We end with recommendations for their use and introduce free MATLAB software for their implementation. Copyright © 2011 Society for Psychophysiological Research.

Evolution of specifier proteins in glucosinolate-containing plants

PubMed Central

2012-01-01

Background The glucosinolate-myrosinase system is an activated chemical defense system found in plants of the Brassicales order. Glucosinolates are stored separately from their hydrolytic enzymes, the myrosinases, in plant tissues. Upon tissue damage, e.g. by herbivory, glucosinolates and myrosinases get mixed and glucosinolates are broken down to an array of biologically active compounds of which isothiocyanates are toxic to a wide range of organisms. Specifier proteins occur in some, but not all glucosinolate-containing plants and promote the formation of biologically active non-isothiocyanate products upon myrosinase-catalyzed glucosinolate breakdown. Results Based on a phytochemical screening among representatives of the Brassicales order, we selected candidate species for identification of specifier protein cDNAs. We identified ten specifier proteins from a range of species of the Brassicaceae and assigned each of them to one of the three specifier protein types (NSP, nitrile-specifier protein, ESP, epithiospecifier protein, TFP, thiocyanate-forming protein) after heterologous expression in Escherichia coli. Together with nine known specifier proteins and three putative specifier proteins found in databases, we subjected the newly identified specifier proteins to phylogenetic analyses. Specifier proteins formed three major clusters, named AtNSP5-cluster, AtNSP1-cluster, and ESP/TFP cluster. Within the ESP/TFP cluster, specifier proteins grouped according to the Brassicaceae lineage they were identified from. Non-synonymous vs. synonymous substitution rate ratios suggested purifying selection to act on specifier protein genes. Conclusions Among specifier proteins, NSPs represent the ancestral activity. The data support a monophyletic origin of ESPs from NSPs. The split between NSPs and ESPs/TFPs happened before the radiation of the core Brassicaceae. Future analyses have to show if TFP activity evolved from ESPs at least twice independently in different Brassicaceae lineages as suggested by the phylogeny. The ability to form non-isothiocyanate products by specifier protein activity may provide plants with a selective advantage. The evolution of specifier proteins in the Brassicaceae demonstrates the plasticity of secondary metabolism within an activated plant defense system. PMID:22839361

Spatial Analysis of the Human Immunodeficiency Virus Epidemic among Men Who Have Sex with Men in China, 2006-2015.

PubMed

Qin, Qianqian; Guo, Wei; Tang, Weiming; Mahapatra, Tanmay; Wang, Liyan; Zhang, Nanci; Ding, Zhengwei; Cai, Chang; Cui, Yan; Sun, Jiangping

2017-04-01

Studies have shown a recent upsurge in human immunodeficiency virus (HIV) burden among men who have sex with men (MSM) in China, especially in urban areas. For intervention planning and resource allocation, spatial analyses of HIV/AIDS case-clusters were required to identify epidemic foci and trends among MSM in China. Information regarding MSM recorded as HIV/AIDS cases during 2006-2015 were extracted from the National Case Reporting System. Demographic trends were determined through Cochran-Armitage trend tests. Distribution of case-clusters was examined using spatial autocorrelation. Spatial-temporal scan was used to detect disease clustering. Spatial correlations between cases and socioenvironmental factors were determined by spatial regression. Between 2006 and 2015, in China, 120 371 HIV/AIDS cases were identified among MSM. Newly identified HIV/AIDS cases among self-reported MSM increased from 487 cases in 2006 to >30 000 cases in 2015. Among those HIV/AIDS cases recorded during 2006-2015, 47.0% were 20-29 years old and 24.9% were aged 30-39 years. Based on clusters of HIV/AIDS cases identified through spatial analysis, the epidemic was concentrated among MSM in large cities. Spatial-temporal clusters contained municipalities, provincial capitals, and main cities such as Beijing, Shanghai, Chongqing, Chengdu, and Guangzhou. Spatial regression analysis showed that sociodemographic indicators such as population density, per capita gross domestic product, and number of county-level medical institutions had statistically significant positive correlations with HIV/AIDS among MSM. Assorted spatial analyses revealed an increasingly concentrated HIV epidemic among young MSM in Chinese cities, calling for targeted health education and intensive interventions at an early age. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Data for Known Geothermal Resource Areas (KGRA) and Identified Hydrothermal Resource Areas (IHRA) in Southern Idaho and Southeastern Oregon

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

Neupane, Ghanashyam; McLing, Travis; Mattson, Earl

The presented database includes water chemistry data and structural rating values for various geothermal features used for performing principal component (PC) and cluster analyses work to identify promising KGRAs and IHRAs in southern Idaho and southeastern Oregon. A brief note on various KGRAs/IHRAs is also included herewith. Results of PC and cluster analyses are presented as a separate paper (Lindsey et al., 2017) that is, as of the time of this submission, in 'revision' status.

Tripartite efficacy profiles: a cluster analytic investigation of athletes' perceptions of their relationship with their coach.

PubMed

Jackson, Ben; Gucciardi, Daniel F; Dimmock, James A

2011-06-01

Recent studies of coach-athlete interaction have explored the bivariate relationships between each of the tripartite efficacy constructs (self-efficacy; other-efficacy; relation-inferred self-efficacy, or RISE) and various indicators of relationship quality. This investigation adopted an alternative approach by using cluster analyses to identify tripartite efficacy profiles within a sample of 377 individual sport athletes (Mage = 20.25, SD = 2.12), and examined how individuals in each cluster group differed in their perceptions about their relationship with their coach (i.e., commitment, satisfaction, conflict). Four clusters emerged: High (n = 128), Moderate (n = 95), and Low (n = 78) profiles, in which athletes reported relatively high, moderate, or low scores across all tripartite perceptions, respectively, as well as an Unfulfilled profile (n = 76) in which athletes held relatively high self-efficacy, but perceived lower levels of other-efficacy and RISE. Multivariate analyses revealed differences between the clusters on all relationship variables that were in line with theory. These results underscore the utility of considering synergistic issues in the examination of the tripartite efficacy framework.

A method of alignment masking for refining the phylogenetic signal of multiple sequence alignments.

PubMed

Rajan, Vaibhav

2013-03-01

Inaccurate inference of positional homologies in multiple sequence alignments and systematic errors introduced by alignment heuristics obfuscate phylogenetic inference. Alignment masking, the elimination of phylogenetically uninformative or misleading sites from an alignment before phylogenetic analysis, is a common practice in phylogenetic analysis. Although masking is often done manually, automated methods are necessary to handle the much larger data sets being prepared today. In this study, we introduce the concept of subsplits and demonstrate their use in extracting phylogenetic signal from alignments. We design a clustering approach for alignment masking where each cluster contains similar columns-similarity being defined on the basis of compatible subsplits; our approach then identifies noisy clusters and eliminates them. Trees inferred from the columns in the retained clusters are found to be topologically closer to the reference trees. We test our method on numerous standard benchmarks (both synthetic and biological data sets) and compare its performance with other methods of alignment masking. We find that our method can eliminate sites more accurately than other methods, particularly on divergent data, and can improve the topologies of the inferred trees in likelihood-based analyses. Software available upon request from the author.

Application of diffusion maps to identify human factors of self-reported anomalies in aviation.

PubMed

Andrzejczak, Chris; Karwowski, Waldemar; Mikusinski, Piotr

2012-01-01

A study investigating what factors are present leading to pilots submitting voluntary anomaly reports regarding their flight performance was conducted. Diffusion Maps (DM) were selected as the method of choice for performing dimensionality reduction on text records for this study. Diffusion Maps have seen successful use in other domains such as image classification and pattern recognition. High-dimensionality data in the form of narrative text reports from the NASA Aviation Safety Reporting System (ASRS) were clustered and categorized by way of dimensionality reduction. Supervised analyses were performed to create a baseline document clustering system. Dimensionality reduction techniques identified concepts or keywords within records, and allowed the creation of a framework for an unsupervised document classification system. Results from the unsupervised clustering algorithm performed similarly to the supervised methods outlined in the study. The dimensionality reduction was performed on 100 of the most commonly occurring words within 126,000 text records describing commercial aviation incidents. This study demonstrates that unsupervised machine clustering and organization of incident reports is possible based on unbiased inputs. Findings from this study reinforced traditional views on what factors contribute to civil aviation anomalies, however, new associations between previously unrelated factors and conditions were also found.

Patterns of work-related intimate partner violence and job performance among abusive men.

PubMed

Mankowski, Eric S; Galvez, Gino; Perrin, Nancy A; Hanson, Ginger C; Glass, Nancy

2013-10-01

This study assesses different types of work-related intimate partner violence (IPV) perpetration and their relationship to perpetrators' work performance and employment. We determine if groups of abusive men with similar patterns of work-related IPV exist and then examine whether the patterns are related to their characteristics, job performance, and employment outcomes. Participants were 198 adult men (60% Latino, 40% non-Latino) from batterer intervention programs (BIPs) who self-reported their lifetime work-related IPV and job outcomes. Five distinct clusters were identified and named based on the pattern (predominance or absence) of different work-related abusive behaviors reported: (a) low-level tactics, (b) job interference, (c) job interference with threatened or actual violence, (d) extreme abuse without jealousy and (e) extreme abuse. Analyses revealed significant differences between the clusters on ethnicity, parental status, partner's employment status, income, education, and (among Latinos only) acculturation. The probability of men's work-related IPV substantially impacting their own job performance was nearly 4 times greater among those in the extreme abuse cluster than those in the low-level tactics cluster. These data inform the development of employee training programs and workplace policies for reducing IPV that affects the workplace.

Fingerprints of resistant Escherichia coli O157:H7 from vegetables and environmental samples.

PubMed

Abakpa, Grace Onyukwo; Umoh, Veronica J; Kamaruzaman, Sijam; Ibekwe, Mark

2018-01-01

Some routes of transmission of Escherichia coli O157:H7 to fresh produce include contaminated irrigation water and manure polluted soils. The aim of the present study was to determine the genetic relationships of E. coli O157:H7 isolated from some produce growing region in Nigeria using enterobacterial repetitive intergenic consensus (ERIC) DNA fingerprinting analysis. A total of 440 samples comprising leafy greens, irrigation water, manure and soil were obtained from vegetable producing regions in Kano and Plateau States, Nigeria. Genes coding for the quinolone resistance-determinant (gyrA) and plasmid (pCT) coding for multidrug resistance (MDR) were determined using polymerase chain reaction (PCR) in 16 isolates that showed MDR. Cluster analysis of the ERIC-PCR profiles based on band sizes revealed six main clusters from the sixteen isolates analysed. The largest cluster (cluster 3) grouped isolates from vegetables and manure at a similarity coefficient of 0.72. The present study provides data that support the potential transmission of resistant strains of E. coli O157:H7 from vegetables and environmental sources to humans with potential public health implications, especially in developing countries. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

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

Cluster Analysis of Atmospheric Dynamics and Pollution Transport in a Coastal Area

NASA Astrophysics Data System (ADS)

Sokolov, Anton; Dmitriev, Egor; Maksimovich, Elena; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmentin, Marc; Locoge, Nadine

2016-11-01

Summertime atmospheric dynamics in the coastal zone of the industrialized Dunkerque agglomeration in northern France was characterized by a cluster analysis of back trajectories in the context of pollution transport. The MESO-NH atmospheric model was used to simulate the local dynamics at multiple scales with horizontal resolution down to 500 m, and for the online calculation of the Lagrangian backward trajectories with 30-min temporal resolution. Airmass transport was performed along six principal pathways obtained by the weighted k-means clustering technique. Four of these centroids corresponded to a range of wind speeds over the English Channel: two for wind directions from the north-east and two from the south-west. Another pathway corresponded to a south-westerly continental transport. The backward trajectories of the largest and most dispersed sixth cluster contained low wind speeds, including sea-breeze circulations. Based on analyses of meteorological data and pollution measurements, the principal atmospheric pathways were related to local air-contamination events. Continuous air quality and meteorological data were collected during the Benzene-Toluene-Ethylbenzene-Xylene 2006 campaign. The sites of the pollution measurements served as the endpoints for the backward trajectories. Pollutant transport pathways corresponding to the highest air contamination were defined.

Diversity of bacteria and glycosyl hydrolase family 48 genes in cellulolytic consortia enriched from thermophilic biocompost.

PubMed

Izquierdo, Javier A; Sizova, Maria V; Lynd, Lee R

2010-06-01

The enrichment from nature of novel microbial communities with high cellulolytic activity is useful in the identification of novel organisms and novel functions that enhance the fundamental understanding of microbial cellulose degradation. In this work we identify predominant organisms in three cellulolytic enrichment cultures with thermophilic compost as an inoculum. Community structure based on 16S rRNA gene clone libraries featured extensive representation of clostridia from cluster III, with minor representation of clostridial clusters I and XIV and a novel Lutispora species cluster. Our studies reveal different levels of 16S rRNA gene diversity, ranging from 3 to 18 operational taxonomic units (OTUs), as well as variability in community membership across the three enrichment cultures. By comparison, glycosyl hydrolase family 48 (GHF48) diversity analyses revealed a narrower breadth of novel clostridial genes associated with cultured and uncultured cellulose degraders. The novel GHF48 genes identified in this study were related to the novel clostridia Clostridium straminisolvens and Clostridium clariflavum, with one cluster sharing as little as 73% sequence similarity with the closest known relative. In all, 14 new GHF48 gene sequences were added to the known diversity of 35 genes from cultured species.

Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia

NASA Astrophysics Data System (ADS)

Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.

2017-12-01

Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.

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.

RCSLenS: The Red Cluster Sequence Lensing Survey

NASA Astrophysics Data System (ADS)

Hildebrandt, H.; Choi, A.; Heymans, C.; Blake, C.; Erben, T.; Miller, L.; Nakajima, R.; van Waerbeke, L.; Viola, M.; Buddendiek, A.; Harnois-Déraps, J.; Hojjati, A.; Joachimi, B.; Joudaki, S.; Kitching, T. D.; Wolf, C.; Gwyn, S.; Johnson, N.; Kuijken, K.; Sheikhbahaee, Z.; Tudorica, A.; Yee, H. K. C.

2016-11-01

We present the Red Cluster Sequence Lensing Survey (RCSLenS), an application of the methods developed for the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) to the ˜785 deg2, multi-band imaging data of the Red-sequence Cluster Survey 2. This project represents the largest public, sub-arcsecond seeing, multi-band survey to date that is suited for weak gravitational lensing measurements. With a careful assessment of systematic errors in shape measurements and photometric redshifts, we extend the use of this data set to allow cross-correlation analyses between weak lensing observables and other data sets. We describe the imaging data, the data reduction, masking, multi-colour photometry, photometric redshifts, shape measurements, tests for systematic errors, and a blinding scheme to allow for more objective measurements. In total, we analyse 761 pointings with r-band coverage, which constitutes our lensing sample. Residual large-scale B-mode systematics prevent the use of this shear catalogue for cosmic shear science. The effective number density of lensing sources over an unmasked area of 571.7 deg2 and down to a magnitude limit of r ˜ 24.5 is 8.1 galaxies per arcmin2 (weighted: 5.5 arcmin-2) distributed over 14 patches on the sky. Photometric redshifts based on four-band griz data are available for 513 pointings covering an unmasked area of 383.5 deg2. We present weak lensing mass reconstructions of some example clusters as well as the full survey representing the largest areas that have been mapped in this way. All our data products are publicly available through Canadian Astronomy Data Centre at http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/en/community/rcslens/query.html in a format very similar to the CFHTLenS data release.

Genomic Epidemiology of Clostridium botulinum Isolates from Temporally Related Cases of Infant Botulism in New South Wales, Australia

PubMed Central

Gray, Timothy J.; Wang, Qinning; Ng, Jimmy; Hicks, Leanne; Nguyen, Trang; Yuen, Marion; Hill-Cawthorne, Grant A.; Sintchenko, Vitali

2015-01-01

Infant botulism is a potentially life-threatening paralytic disease that can be associated with prolonged morbidity if not rapidly diagnosed and treated. Four infants were diagnosed and treated for infant botulism in NSW, Australia, between May 2011 and August 2013. Despite the temporal relationship between the cases, there was no close geographical clustering or other epidemiological links. Clostridium botulinum isolates, three of which produced botulism neurotoxin serotype A (BoNT/A) and one BoNT serotype B (BoNT/B), were characterized using whole-genome sequencing (WGS). In silico multilocus sequence typing (MLST) found that two of the BoNT/A-producing isolates shared an identical novel sequence type, ST84. The other two isolates were single-locus variants of this sequence type (ST85 and ST86). All BoNT/A-producing isolates contained the same chromosomally integrated BoNT/A2 neurotoxin gene cluster. The BoNT/B-producing isolate carried a single plasmid-borne bont/B gene cluster, encoding BoNT subtype B6. Single nucleotide polymorphism (SNP)-based typing results corresponded well with MLST; however, the extra resolution provided by the whole-genome SNP comparisons showed that the isolates differed from each other by >3,500 SNPs. WGS analyses indicated that the four infant botulism cases were caused by genomically distinct strains of C. botulinum that were unlikely to have originated from a common environmental source. The isolates did, however, cluster together, compared with international isolates, suggesting that C. botulinum from environmental reservoirs throughout NSW have descended from a common ancestor. Analyses showed that the high resolution of WGS provided important phylogenetic information that would not be captured by standard seven-loci MLST. PMID:26109442

Genomic Epidemiology of Clostridium botulinum Isolates from Temporally Related Cases of Infant Botulism in New South Wales, Australia.

PubMed

McCallum, Nadine; Gray, Timothy J; Wang, Qinning; Ng, Jimmy; Hicks, Leanne; Nguyen, Trang; Yuen, Marion; Hill-Cawthorne, Grant A; Sintchenko, Vitali

2015-09-01

Infant botulism is a potentially life-threatening paralytic disease that can be associated with prolonged morbidity if not rapidly diagnosed and treated. Four infants were diagnosed and treated for infant botulism in NSW, Australia, between May 2011 and August 2013. Despite the temporal relationship between the cases, there was no close geographical clustering or other epidemiological links. Clostridium botulinum isolates, three of which produced botulism neurotoxin serotype A (BoNT/A) and one BoNT serotype B (BoNT/B), were characterized using whole-genome sequencing (WGS). In silico multilocus sequence typing (MLST) found that two of the BoNT/A-producing isolates shared an identical novel sequence type, ST84. The other two isolates were single-locus variants of this sequence type (ST85 and ST86). All BoNT/A-producing isolates contained the same chromosomally integrated BoNT/A2 neurotoxin gene cluster. The BoNT/B-producing isolate carried a single plasmid-borne bont/B gene cluster, encoding BoNT subtype B6. Single nucleotide polymorphism (SNP)-based typing results corresponded well with MLST; however, the extra resolution provided by the whole-genome SNP comparisons showed that the isolates differed from each other by >3,500 SNPs. WGS analyses indicated that the four infant botulism cases were caused by genomically distinct strains of C. botulinum that were unlikely to have originated from a common environmental source. The isolates did, however, cluster together, compared with international isolates, suggesting that C. botulinum from environmental reservoirs throughout NSW have descended from a common ancestor. Analyses showed that the high resolution of WGS provided important phylogenetic information that would not be captured by standard seven-loci MLST. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Phytochemical, phylogenetic, and anti-inflammatory evaluation of 43 Urtica accessions (stinging nettle) based on UPLC-Q-TOF-MS metabolomic profiles.

PubMed

Farag, Mohamed A; Weigend, Maximilian; Luebert, Federico; Brokamp, Grischa; Wessjohann, Ludger A

2013-12-01

Several species of the genus Urtica (especially Urtica dioica, Urticaceae), are used medicinally to treat a variety of ailments. To better understand the chemical diversity of the genus and to compare different accessions and different taxa of Urtica, 63 leaf samples representing a broad geographical, taxonomical and morphological diversity were evaluated under controlled conditions. A molecular phylogeny for all taxa investigated was prepared to compare phytochemical similarity with phylogenetic relatedness. Metabolites were analyzed via UPLC-PDA-MS and multivariate data analyses. In total, 43 metabolites were identified, with phenolic compounds and hydroxy fatty acids as the dominant substance groups. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) provides a first structured chemotaxonomy of the genus. The molecular data present a highly resolved phylogeny with well-supported clades and subclades. U. dioica is retrieved as both para- and polyphyletic. European members of the U. dioica group and the North American subspecies share a rather similar metabolite profile and were largely retrieved as one, nearly exclusive cluster by metabolite data. This latter cluster also includes - remotely related - Urtica urens, which is pharmaceutically used in the same way as U. dioica. However, most highly supported phylogenetic clades were not retrieved in the metabolite cluster analyses. Overall, metabolite profiles indicate considerable phytochemical diversity in the genus, which largely falls into a group characterized by high contents of hydroxy fatty acids (e.g., most Andean-American taxa) and another group characterized by high contents of phenolic acids (especially the U. dioica-clade). Anti-inflammatory in vitro COX1 enzyme inhibition assays suggest that bioactivity may be predicted by gross metabolic profiling in Urtica. Copyright © 2013. Published by Elsevier Ltd.

Seismotectonics of the Taiwan Shoal region in the northeastern South China Sea: Insights from the crustal structure

NASA Astrophysics Data System (ADS)

Wan, Kuiyuan; Sun, Jinlong; Xu, Huilong; Xie, Xiaoling; Xia, Shaohong; Zhang, Xiang; Cao, Jinghe; Zhao, Fang; Fan, Chaoyan

2018-02-01

A cluster of earthquakes occurred in the Taiwan Shoal region on the outer rise of the Manila Trench. Although most were of small to medium magnitudes, one strong earthquake occurred on September 16, 1994. Several previous studies have provided important information to progress our understanding of this single earthquake. However, little is currently known about the earthquake cluster, and it is necessary to investigate the deep crustal structure of the Taiwan Shoal region to understand the mechanisms involved in controlling and generating it. This study presents a two-dimensional seismic tomographic image of the crustal structure along the OBS2012 profile based on ocean-bottom seismograph (OBS) data, which exhibits a high-velocity anomaly flanked by low-velocity anomalies in the upper crust beneath the Taiwan Shoal. In this study, 765 earthquakes (Richter magnitude ML > 1.5) occurring between 1991 and 2015 were studied and analyses of earthquake epicenters, regional faults, and the crustal structure provides an improved understanding of the nature of active tectonics in this region. Results of analyses indicate firstly that the high-velocity area represents major asperities that correspond to the location of the earthquake cluster and where stress is concentrated. It is also depicted that the earthquake cluster was influenced by fault interactions. However, the September 1994 earthquake occurred independently of these seismic activities and was associated with reactivation of a preexisting fault. It is also determined that slab pull is resisted by the exposed precollision accretionary prism, and the resistive force is causing accumulation of inplane compressive-stress. This may trigger a future damaging earthquake in the Taiwan Shoal region.

Theria-Specific Homeodomain and cis-Regulatory Element Evolution of the Dlx3–4 Bigene Cluster in 12 Different Mammalian Species

PubMed Central

SUMIYAMA, KENTA; MIYAKE, TSUTOMU; GRIMWOOD, JANE; STUART, ANDREW; DICKSON, MARK; SCHMUTZ, JEREMY; RUDDLE, FRANK H.; MYERS, RICHARD M.; AMEMIYA, CHRIS T.

2013-01-01

The mammalian Dlx3 and Dlx4 genes are configured as a bigene cluster, and their respective expression patterns are controlled temporally and spatially by cis-elements that largely reside within the intergenic region of the cluster. Previous work revealed that there are conspicuously conserved elements within the intergenic region of the Dlx3–4 bigene clusters of mouse and human. In this paper we have extended these analyses to include 12 additional mammalian taxa (including a marsupial and a monotreme) in order to better define the nature and molecular evolutionary trends of the coding and non-coding functional elements among morphologically divergent mammals. Dlx3–4 regions were fully sequenced from 12 divergent taxa of interest. We identified three theria-specific amino acid replacements in homeodomain of Dlx4 gene that functions in placenta. Sequence analyses of constrained nucleotide sites in the intergenic non-coding region showed that many of the intergenic conserved elements are highly conserved and have evolved slowly within the mammals. In contrast, a branchial arch/craniofacial enhancer I37-2 exhibited accelerated evolution at the branch between the monotreme and therian common ancestor despite being highly conserved among therian species. Functional analysis of I37-2 in transgenic mice has shown that the equivalent region of the platypus fails to drive transcriptional activity in branchial arches. These observations, taken together with our molecular evolutionary data, suggest that theria-specific episodic changes in the I37-2 element may have contributed to craniofacial innovation at the base of the mammalian lineage. PMID:22951979

Process evaluation of a cluster-randomised trial testing a pressure ulcer prevention care bundle: a mixed-methods study.

PubMed

Roberts, Shelley; McInnes, Elizabeth; Bucknall, Tracey; Wallis, Marianne; Banks, Merrilyn; Chaboyer, Wendy

2017-02-13

As pressure ulcers contribute to significant patient burden and increased health care costs, their prevention is a clinical priority. Our team developed and tested a complex intervention, a pressure ulcer prevention care bundle promoting patient participation in care, in a cluster-randomised trial. The UK Medical Research Council recommends process evaluation of complex interventions to provide insight into why they work or fail and how they might be improved. This study aimed to evaluate processes underpinning implementation of the intervention and explore end-users' perceptions of it, in order to give a deeper understanding of its effects. A pre-specified, mixed-methods process evaluation was conducted as an adjunct to the main trial, guided by a framework for process evaluation of cluster-randomised trials. Data was collected across eight Australian hospitals but mainly focused on the four intervention hospitals. Quantitative and qualitative data were collected across the evaluation domains: recruitment, reach, intervention delivery and response to intervention, at both cluster and individual patient level. Quantitative data were analysed using descriptive and inferential statistics. Qualitative data were analysed using thematic analysis. In the context of the main trial, which found a 42% reduction in risk of pressure ulcer with the intervention that was not significant after adjusting for clustering and covariates, this process evaluation provides important insights. Recruitment and reach among clusters and individuals was high, indicating that patients, nurses and hospitals are willing to engage with a pressure ulcer prevention care bundle. Of 799 intervention patients in the trial, 96.7% received the intervention, which took under 10 min to deliver. Patients and nurses accepted the care bundle, recognising benefits to it and describing how it enabled participation in pressure ulcer prevention (PUP) care. This process evaluation found no major failures relating to implementation of the intervention. The care bundle was found to be easy to understand and deliver, and it reached a large proportion of the target population and was found to be acceptable to patients and nurses; therefore, it may be an effective way of engaging patients in their pressure ulcer prevention care and promoting evidence-based practise.

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment (Kartchner Caverns, AZ, USA)

PubMed Central

Zhang, Lin; Vranckx, Katleen; Janssens, Koen; Sandrin, Todd R.

2015-01-01

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level. PMID:25590854

Use of MALDI-TOF mass spectrometry and a custom database to characterize bacteria indigenous to a unique cave environment (Kartchner Caverns, AZ, USA).

PubMed

Zhang, Lin; Vranckx, Katleen; Janssens, Koen; Sandrin, Todd R

2015-01-02

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.

Range overlap and individual movements during breeding season influence genetic relationships of caribou herds in south-central Alaska

USGS Publications Warehouse

Roffler, Gretchen H.; Adams, Layne G.; Talbot, Sandra L.; Sage, George K.; Dale, Bruce W.

2012-01-01

North American caribou (Rangifer tarandus) herds commonly exhibit little nuclear genetic differentiation among adjacent herds, although available evidence supports strong demographic separation, even for herds with seasonal range overlap. During 1997–2003, we studied the Mentasta and Nelchina caribou herds in south-central Alaska using radiotelemetry to determine individual movements and range overlap during the breeding season, and nuclear and mitochondrial DNA (mtDNA) markers to assess levels of genetic differentiation. Although the herds were considered discrete because females calved in separate regions, individual movements and breeding-range overlap in some years provided opportunity for male-mediated gene flow, even without demographic interchange. Telemetry results revealed strong female philopatry, and little evidence of female emigration despite overlapping seasonal distributions. Analyses of 13 microsatellites indicated the Mentasta and Nelchina herds were not significantly differentiated using both traditional population-based analyses and individual-based Bayesian clustering analyses. However, we observed mtDNA differentiation between the 2 herds (FSTM = 0.041, P