Cluster Analysis of Junior High School Students' Cognitive Structures

ERIC Educational Resources Information Center

Dan, Youngjun; Geng, Leisha; Li, Meng

2017-01-01

This study aimed to explore students' cognitive patterns based on their knowledge and levels. Participants were seventh graders from a junior high school in China. Three relatively distinct groups were specified by Cluster Analysis: high knowledge and low ability, low knowledge and low ability, and high knowledge and high ability. The group of low…

Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

PubMed

Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

2016-05-15

To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Revealing hidden species diversity in closely related species using nuclear SNPs, SSRs and DNA sequences - a case study in the tree genus Milicia.

PubMed

Daïnou, Kasso; Blanc-Jolivet, Céline; Degen, Bernd; Kimani, Priscilla; Ndiade-Bourobou, Dyana; Donkpegan, Armel S L; Tosso, Félicien; Kaymak, Esra; Bourland, Nils; Doucet, Jean-Louis; Hardy, Olivier J

2016-12-01

Species delimitation in closely related plant taxa can be challenging because (i) reproductive barriers are not always congruent with morphological differentiation, (ii) use of plastid sequences might lead to misinterpretation, (iii) rare species might not be sampled. We revisited molecular-based species delimitation in the African genus Milicia, currently divided into M. regia (West Africa) and M. excelsa (from West to East Africa). We used 435 samples collected in West, Central and East Africa. We genotyped SNP and SSR loci to identify genetic clusters, and sequenced two plastid regions (psbA-trnH, trnC-ycf6) and a nuclear gene (At103) to confirm species' divergence and compare species delimitation methods. We also examined whether ecological niche differentiation was congruent with sampled genetic structure. West African M. regia, West African and East African M. excelsa samples constituted three well distinct genetic clusters according to SNPs and SSRs. In Central Africa, two genetic clusters were consistently inferred by both types of markers, while a few scattered samples, sympatric with the preceding clusters but exhibiting leaf traits of M. regia, were grouped with the West African M. regia cluster based on SNPs or formed a distinct cluster based on SSRs. SSR results were confirmed by sequence data from the nuclear region At103 which revealed three distinct 'Fields For Recombination' corresponding to (i) West African M. regia, (ii) Central African samples with leaf traits of M. regia, and (iii) all M. excelsa samples. None of the plastid sequences provide indication of distinct clades of the three species-like units. Niche modelling techniques yielded a significant correlation between niche overlap and genetic distance. Our genetic data suggest that three species of Milicia could be recognized. It is surprising that the occurrence of two species in Central Africa was not reported for this well-known timber tree. Globally, our work highlights the importance of collecting samples in a systematic way and the need for combining different nuclear markers when dealing with species complexes. Recognizing cryptic species is particularly crucial for economically exploited species because some hidden taxa might actually be endangered as they are merged with more abundant species.

Identification and Characterization of Unique Subgroups of Chronic Pain Individuals with Dispositional Personality Traits.

PubMed

Mehta, S; Rice, D; McIntyre, A; Getty, H; Speechley, M; Sequeira, K; Shapiro, A P; Morley-Forster, P; Teasell, R W

2016-01-01

Objective. The current study attempted to identify and characterize distinct CP subgroups based on their level of dispositional personality traits. The secondary objective was to compare the difference among the subgroups in mood, coping, and disability. Methods. Individuals with chronic pain were assessed for demographic, psychosocial, and personality measures. A two-step cluster analysis was conducted in order to identify distinct subgroups of patients based on their level of personality traits. Differences in clinical outcomes were compared using the multivariate analysis of variance based on cluster membership. Results. In 229 participants, three clusters were formed. No significant difference was seen among the clusters on patient demographic factors including age, sex, relationship status, duration of pain, and pain intensity. Those with high levels of dispositional personality traits had greater levels of mood impairment compared to the other two groups (p < 0.05). Significant difference in disability was seen between the subgroups. Conclusions. The study identified a high risk group of CP individuals whose level of personality traits significantly correlated with impaired mood and coping. Use of pharmacological treatment alone may not be successful in improving clinical outcomes among these individuals. Instead, a more comprehensive treatment involving psychological treatments may be important in managing the personality traits that interfere with recovery.

The High and Low Molecular Weight Forms of Hyaluronan Have Distinct Effects on CD44 Clustering*

PubMed Central

Yang, Cuixia; Cao, Manlin; Liu, Hua; He, Yiqing; Xu, Jing; Du, Yan; Liu, Yiwen; Wang, Wenjuan; Cui, Lian; Hu, Jiajie; Gao, Feng

2012-01-01

CD44 is a major cell surface receptor for the glycosaminoglycan hyaluronan (HA). Native high molecular weight hyaluronan (nHA) and oligosaccharides of hyaluronan (oHA) provoke distinct biological effects upon binding to CD44. Despite the importance of such interactions, however, the feature of binding with CD44 at the cell surface and the molecular basis for functional distinction between different sizes of HA is still unclear. In this study we investigated the effects of high and low molecular weight hyaluronan on CD44 clustering. For the first time, we provided direct evidence for a strong relationship between HA size and CD44 clustering in vivo. In CD44-transfected COS-7 cells, we showed that exogenous nHA stimulated CD44 clustering, which was disrupted by oHA. Moreover, naturally expressed CD44 was distributed into clusters due to abundantly expressed nHA in HK-2 cells (human renal proximal tubule cells) and BT549 cells (human breast cancer cell line) without exogenous stimulation. Our results suggest that native HA binding to CD44 selectively induces CD44 clustering, which could be inhibited by oHA. Finally, we demonstrated that HA regulates cell adhesion in a manner specifically dependent on its size. oHA promoted cell adhesion while nHA showed no effects. Our results might elucidate a molecular- and/or cellular-based mechanism for the diverse biological activities of nHA and oHA. PMID:23118219

The bacterial species definition in the genomic era

PubMed Central

Konstantinidis, Konstantinos T; Ramette, Alban; Tiedje, James M

2006-01-01

The bacterial species definition, despite its eminent practical significance for identification, diagnosis, quarantine and diversity surveys, remains a very difficult issue to advance. Genomics now offers novel insights into intra-species diversity and the potential for emergence of a more soundly based system. Although we share the excitement, we argue that it is premature for a universal change to the definition because current knowledge is based on too few phylogenetic groups and too few samples of natural populations. Our analysis of five important bacterial groups suggests, however, that more stringent standards for species may be justifiable when a solid understanding of gene content and ecological distinctiveness becomes available. Our analysis also reveals what is actually encompassed in a species according to the current standards, in terms of whole-genome sequence and gene-content diversity, and shows that this does not correspond to coherent clusters for the environmental Burkholderia and Shewanella genera examined. In contrast, the obligatory pathogens, which have a very restricted ecological niche, do exhibit clusters. Therefore, the idea of biologically meaningful clusters of diversity that applies to most eukaryotes may not be universally applicable in the microbial world, or if such clusters exist, they may be found at different levels of distinction. PMID:17062412

Signatures of cytoplasmic proteins in the exoproteome distinguish community- and hospital-associated methicillin-resistant Staphylococcus aureus USA300 lineages.

PubMed

Mekonnen, Solomon A; Palma Medina, Laura M; Glasner, Corinna; Tsompanidou, Eleni; de Jong, Anne; Grasso, Stefano; Schaffer, Marc; Mäder, Ulrike; Larsen, Anders R; Gumpert, Heidi; Westh, Henrik; Völker, Uwe; Otto, Andreas; Becher, Dörte; van Dijl, Jan Maarten

2017-08-18

Methicillin-resistant Staphylococcus aureus (MRSA) is the common name for a heterogeneous group of highly drug-resistant staphylococci. Two major MRSA classes are distinguished based on epidemiology, namely community-associated (CA) and hospital-associated (HA) MRSA. Notably, the distinction of CA- and HA-MRSA based on molecular traits remains difficult due to the high genomic plasticity of S. aureus. Here we sought to pinpoint global distinguishing features of CA- and HA-MRSA through a comparative genome and proteome analysis of the notorious MRSA lineage USA300. We show for the first time that CA- and HA-MRSA isolates can be distinguished by 2 distinct extracellular protein abundance clusters that are predictive not only for epidemiologic behavior, but also for their growth and survival within epithelial cells. This 'exoproteome profiling' also groups more distantly related HA-MRSA isolates into the HA exoproteome cluster. Comparative genome analysis suggests that these distinctive features of CA- and HA-MRSA isolates relate predominantly to the accessory genome. Intriguingly, the identified exoproteome clusters differ in the relative abundance of typical cytoplasmic proteins, suggesting that signatures of cytoplasmic proteins in the exoproteome represent a new distinguishing feature of CA- and HA-MRSA. Our comparative genome and proteome analysis focuses attention on potentially distinctive roles of 'liberated' cytoplasmic proteins in the epidemiology and intracellular survival of CA- and HA-MRSA isolates. Such extracellular cytoplasmic proteins were recently invoked in staphylococcal virulence, but their implication in the epidemiology of MRSA is unprecedented.

Left inferior parietal lobe engagement in social cognition and language

PubMed Central

Bzdok, Danilo; Hartwigsen, Gesa; Reid, Andrew; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.

2017-01-01

Social cognition and language are two core features of the human species. Despite distributed recruitment of brain regions in each mental capacity, the left parietal lobe (LPL) represents a zone of topographical convergence. The present study quantitatively summarizes hundreds of neuroimaging studies on social cognition and language. Using connectivity-based parcellation on a meta-analytically defined volume of interest (VOI), regional coactivation patterns within this VOI allowed identifying distinct subregions. Across parcellation solutions, two clusters emerged consistently in rostro-ventral and caudo-ventral aspects of the parietal VOI. Both clusters were functionally significantly associated with social-cognitive and language processing. In particular, the rostro-ventral cluster was associated with lower-level processing facets, while the caudo-ventral cluster was associated with higher-level processing facets in both mental capacities. Contrarily, in the (less stable) dorsal parietal VOI, all clusters reflected computation of general-purpose processes, such as working memory and matching tasks, that are frequently co-recruited by social or language processes. Our results hence favour a rostro-caudal distinction of lower-versus higher-level processes underlying social cognition and language in the left inferior parietal lobe. PMID:27241201

Tropospheric Ozonesonde Profiles at Long-term U.S. Monitoring Sites: 1. A Climatology Based on Self-Organizing Maps

NASA Technical Reports Server (NTRS)

Stauffer, Ryan M.; Thompson, Anne M.; Young, George S.

2016-01-01

Sonde-based climatologies of tropospheric ozone (O3) are vital for developing satellite retrieval algorithms and evaluating chemical transport model output. Typical O3 climatologies average measurements by latitude or region, and season. A recent analysis using self-organizing maps (SOM) to cluster ozonesondes from two tropical sites found that clusters of O3 mixing ratio profiles are an excellent way to capture O3variability and link meteorological influences to O3 profiles. Clusters correspond to distinct meteorological conditions, e.g., convection, subsidence, cloud cover, and transported pollution. Here the SOM technique is extended to four long-term U.S. sites (Boulder, CO; Huntsville, AL; Trinidad Head, CA; and Wallops Island, VA) with4530 total profiles. Sensitivity tests on k-means algorithm and SOM justify use of 3 3 SOM (nine clusters). Ateach site, SOM clusters together O3 profiles with similar tropopause height, 500 hPa height temperature, and amount of tropospheric and total column O3. Cluster means are compared to monthly O3 climatologies.For all four sites, near-tropopause O3 is double (over +100 parts per billion by volume; ppbv) the monthly climatological O3 mixing ratio in three clusters that contain 1316 of profiles, mostly in winter and spring.Large midtropospheric deviations from monthly means (6 ppbv, +710 ppbv O3 at 6 km) are found in two of the most populated clusters (combined 3639 of profiles). These two clusters contain distinctly polluted(summer) and clean O3 (fall-winter, high tropopause) profiles, respectively. As for tropical profiles previously analyzed with SOM, O3 averages are often poor representations of U.S. O3 profile statistics.

Tropospheric ozonesonde profiles at long-term U.S. monitoring sites: 1. A climatology based on self-organizing maps

PubMed Central

Stauffer, Ryan M.; Thompson, Anne M.; Young, George S.

2018-01-01

Sonde-based climatologies of tropospheric ozone (O3) are vital for developing satellite retrieval algorithms and evaluating chemical transport model output. Typical O3 climatologies average measurements by latitude or region, and season. Recent analysis using self-organizing maps (SOM) to cluster ozonesondes from two tropical sites found clusters of O3 mixing ratio profiles are an excellent way to capture O3 variability and link meteorological influences to O3 profiles. Clusters correspond to distinct meteorological conditions, e.g. convection, subsidence, cloud cover, and transported pollution. Here, the SOM technique is extended to four long-term U.S. sites (Boulder, CO; Huntsville, AL; Trinidad Head, CA; Wallops Island, VA) with 4530 total profiles. Sensitivity tests on k-means algorithm and SOM justify use of 3×3 SOM (nine clusters). At each site, SOM clusters together O3 profiles with similar tropopause height, 500 hPa height/temperature, and amount of tropospheric and total column O3. Cluster means are compared to monthly O3 climatologies. For all four sites, near-tropopause O3 is double (over +100 parts per billion by volume; ppbv) the monthly climatological O3 mixing ratio in three clusters that contain 13 – 16% of profiles, mostly in winter and spring. Large mid-tropospheric deviations from monthly means (−6 ppbv, +7 – 10 ppbv O3 at 6 km) are found in two of the most populated clusters (combined 36 – 39% of profiles). These two clusters contain distinctly polluted (summer) and clean O3 (fall-winter, high tropopause) profiles, respectively. As for tropical profiles previously analyzed with SOM, O3 averages are often poor representations of U.S. O3 profile statistics. PMID:29619288

Tropospheric ozonesonde profiles at long-term U.S. monitoring sites: 1. A climatology based on self-organizing maps.

PubMed

Stauffer, Ryan M; Thompson, Anne M; Young, George S

2016-02-16

Sonde-based climatologies of tropospheric ozone (O 3 ) are vital for developing satellite retrieval algorithms and evaluating chemical transport model output. Typical O 3 climatologies average measurements by latitude or region, and season. Recent analysis using self-organizing maps (SOM) to cluster ozonesondes from two tropical sites found clusters of O 3 mixing ratio profiles are an excellent way to capture O 3 variability and link meteorological influences to O 3 profiles. Clusters correspond to distinct meteorological conditions, e.g. convection, subsidence, cloud cover, and transported pollution. Here, the SOM technique is extended to four long-term U.S. sites (Boulder, CO; Huntsville, AL; Trinidad Head, CA; Wallops Island, VA) with 4530 total profiles. Sensitivity tests on k-means algorithm and SOM justify use of 3×3 SOM (nine clusters). At each site, SOM clusters together O 3 profiles with similar tropopause height, 500 hPa height/temperature, and amount of tropospheric and total column O 3 . Cluster means are compared to monthly O 3 climatologies. For all four sites, near-tropopause O 3 is double (over +100 parts per billion by volume; ppbv) the monthly climatological O 3 mixing ratio in three clusters that contain 13 - 16% of profiles, mostly in winter and spring. Large mid-tropospheric deviations from monthly means (-6 ppbv, +7 - 10 ppbv O 3 at 6 km) are found in two of the most populated clusters (combined 36 - 39% of profiles). These two clusters contain distinctly polluted (summer) and clean O 3 (fall-winter, high tropopause) profiles, respectively. As for tropical profiles previously analyzed with SOM, O 3 averages are often poor representations of U.S. O 3 profile statistics.

Clustering the Orion B giant molecular cloud based on its molecular emission.

PubMed

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. A clustering analysis based only on the J = 1 - 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes ( n H ~ 100 cm -3 , ~ 500 cm -3 , and > 1000 cm -3 ), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 - 0 line of HCO + and the N = 1 - 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO + and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO + intensity ratio in UV-illuminated regions. Finer distinctions in density classes ( n H ~ 7 × 10 3 cm -3 ~ 4 × 10 4 cm -3 ) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO + (1 - 0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers.

Profiles of Reactivity in Cocaine-Exposed Children

PubMed Central

Schuetze, Pamela; Molnar, Danielle S.; Eiden, Rina D.

2012-01-01

This study explored the possibility that specific, theoretically consistent profiles of reactivity could be identified in a sample of cocaine-exposed infants and whether these profiles were associated with a range of infant and/or maternal characteristics. Cluster analysis was used to identify distinct groups of infants based on physiological, behavioral and maternal reported measures of reactivity. Five replicable clusters were identified which corresponded to 1) Dysregulated/High Maternal Report Reactors, 2) Low Behavioral Reactors, 3) High Reactors, 4) Optimal Reactors and 5) Dysregulated/Low Maternal Report Reactors. These clusters were associated with differences in prenatal cocaine exposure status, birthweight, maternal depressive symptoms, and maternal negative affect during mother-infant interactions. These results support the presence of distinct reactivity profiles among high risk infants recruited on the basis of prenatal cocaine exposure and demographically similar control group infants not exposed to cocaine. PMID:23204615

Genetic diversity analysis of Capparis spinosa L. populations by using ISSR markers.

PubMed

Liu, C; Xue, G P; Cheng, B; Wang, X; He, J; Liu, G H; Yang, W J

2015-12-09

Capparis spinosa L. is an important medicinal species in the Xinjiang Province of China. Ten natural populations of C. spinosa from 3 locations in North, Central, and South Xinjiang were studied using morphological trait inter simple sequence repeat (ISSR) molecular markers to assess the genetic diversity and population structure. In this study, the 10 ISSR primers produced 313 amplified DNA fragments, with 52% of fragments being polymorphic. Unweighted pair-group method with arithmetic average (UPGMA) cluster analysis indicated that 10 C. spinosa populations were clustered into 3 geographically distinct groups. The Nei gene of C. spinosa populations in different regions had Diversity and Shannon's information index ranges of 0.1312-0.2001 and 0.1004-0.1875, respectively. The 362 markers were used to construct the dendrogram based on the UPGMA cluster analysis. The dendrogram indicated that 10 populations of C. spinosa were clustered into 3 geographically distinct groups. The results showed these genotypes have high genetic diversity, and can be used for an alternative breeding program.

Conformational Transition Pathways of Epidermal Growth Factor Receptor Kinase Domain from Multiple Molecular Dynamics Simulations and Bayesian Clustering.

PubMed

Li, Yan; Li, Xiang; Ma, Weiya; Dong, Zigang

2014-08-12

The epidermal growth factor receptor (EGFR) is aberrantly activated in various cancer cells and an important target for cancer treatment. Deep understanding of EGFR conformational changes between the active and inactive states is of pharmaceutical interest. Here we present a strategy combining multiply targeted molecular dynamics simulations, unbiased molecular dynamics simulations, and Bayesian clustering to investigate transition pathways during the activation/inactivation process of EGFR kinase domain. Two distinct pathways between the active and inactive forms are designed, explored, and compared. Based on Bayesian clustering and rough two-dimensional free energy surfaces, the energy-favorable pathway is recognized, though DFG-flip happens in both pathways. In addition, another pathway with different intermediate states appears in our simulations. Comparison of distinct pathways also indicates that disruption of the Lys745-Glu762 interaction is critically important in DFG-flip while movement of the A-loop significantly facilitates the conformational change. Our simulations yield new insights into EGFR conformational transitions. Moreover, our results verify that this approach is valid and efficient in sampling of protein conformational changes and comparison of distinct pathways.

Two Distinct Patterns of Clostridium Difficile Diversity Across Europe Indicates Contrasting Routes of Spread.

PubMed

Eyre, David W; Davies, Kerrie A; Davis, Georgina; Fawley, Warren N; Dingle, Kate E; De Maio, Nicola; Karas, Andreas; Crook, Derrick W; Peto, Tim E A; Walker, A Sarah; Wilcox, Mark H

2018-04-06

Rates of Clostridium difficile infection vary widely across Europe, as do prevalent ribotypes. The extent of Europe-wide diversity within each ribotype is however unknown. Inpatient diarrhoeal faecal samples submitted on one day in summer and winter (2012-2013) to laboratories in 482 European hospitals were cultured for C. difficile, and isolates ribotyped; those from the 10 most prevalent ribotypes were Illumina whole-genome sequenced. Pairwise single nucleotide differences (SNPs) were obtained from recombination-corrected maximum-likelihood phylogenies. Within each ribotype, country-based sequence clustering was assessed using the ratio of the median SNPs between isolates within versus across different countries using permutation tests. Time-scaled Bayesian phylogenies where used to reconstruct the historic location of each lineage. Sequenced isolates (n=624) were from 19 countries. Five ribotypes had within-country clustering: ribotype-356, only in Italy; ribotype-018, predominantly in Italy; ribotype-176, with distinct Czech and German clades; ribotype-001/072, including distinct German, Slovakian, and Spanish clades; and ribotype-027, with multiple predominantly country-specific clades including in Hungary, Italy, Germany, Romania and Poland. By contrast, we found no within-country clustering for ribotypes 078, 015, 002, 014, and 020, consistent with a Europe-wide distribution. Fluoroquinolone-resistance was significantly more common in within-country clustered ribotypes (p=0.009). Fluoroquinolone-resistant isolates were also more tightly geographically clustered, median (IQR) 43 (0-213) miles between each isolate and the most closely genetically-related isolate vs. 421 (204-680) in non-resistant pairs (p<0.001). Two distinct patterns of C. difficile ribotype spread were observed, consistent with either predominantly healthcare-associated acquisition or Europe-wide dissemination via other routes/sources, e.g. the food chain.

Comparative genomic analysis of clinical and environmental Vibrio vulnificus isolates revealed biotype 3 evolutionary relationships.

PubMed

Koton, Yael; Gordon, Michal; Chalifa-Caspi, Vered; Bisharat, Naiel

2014-01-01

In 1996 a common-source outbreak of severe soft tissue and bloodstream infections erupted among Israeli fish farmers and fish consumers due to changes in fish marketing policies. The causative pathogen was a new strain of Vibrio vulnificus, named biotype 3, which displayed a unique biochemical and genotypic profile. Initial observations suggested that the pathogen erupted as a result of genetic recombination between two distinct populations. We applied a whole genome shotgun sequencing approach using several V. vulnificus strains from Israel in order to study the pan genome of V. vulnificus and determine the phylogenetic relationship of biotype 3 with existing populations. The core genome of V. vulnificus based on 16 draft and complete genomes consisted of 3068 genes, representing between 59 and 78% of the whole genome of 16 strains. The accessory genome varied in size from 781 to 2044 kbp. Phylogenetic analysis based on whole, core, and accessory genomes displayed similar clustering patterns with two main clusters, clinical (C) and environmental (E), all biotype 3 strains formed a distinct group within the E cluster. Annotation of accessory genomic regions found in biotype 3 strains and absent from the core genome yielded 1732 genes, of which the vast majority encoded hypothetical proteins, phage-related proteins, and mobile element proteins. A total of 1916 proteins (including 713 hypothetical proteins) were present in all human pathogenic strains (both biotype 3 and non-biotype 3) and absent from the environmental strains. Clustering analysis of the non-hypothetical proteins revealed 148 protein clusters shared by all human pathogenic strains; these included transcriptional regulators, arylsulfatases, methyl-accepting chemotaxis proteins, acetyltransferases, GGDEF family proteins, transposases, type IV secretory system (T4SS) proteins, and integrases. Our study showed that V. vulnificus biotype 3 evolved from environmental populations and formed a genetically distinct group within the E-cluster. The unique epidemiological circumstances facilitated disease outbreak and brought this genotype to the attention of the scientific community.

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…

Mass functions for globular cluster main sequences based on CCD photometry and stellar models

NASA Astrophysics Data System (ADS)

McClure, Robert D.; Vandenberg, Don A.; Smith, Graeme H.; Fahlman, Gregory G.; Richer, Harvey B.; Hesser, James E.; Harris, William E.; Stetson, Peter B.; Bell, R. A.

1986-08-01

Main-sequence luminosity functions constructed from CCD observations of globular clusters reveal a strong trend in slope with metal abundance. Theoretical luminosity functions constructed from VandenBerg and Bell's (1985) isochrones have been fitted to the observations and reveal a trend between x, the power-law index of the mass function, and metal abundance. The most metal-poor clusters require an index of about x = 2.5, whereas the most metal-rich clusters exhibit an index of x of roughly -0.5. The luminosity functions for two sparse clusters, E3 and Pal 5, are distinct from those of the more massive clusters, in that they show a turndown which is possibly a result of mass loss or tidal disruption.

Cross-entropy clustering framework for catchment classification

NASA Astrophysics Data System (ADS)

Tongal, Hakan; Sivakumar, Bellie

2017-09-01

There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.

Novel approach to classifying patients with pulmonary arterial hypertension using cluster analysis.

PubMed

Parikh, Kishan S; Rao, Youlan; Ahmad, Tariq; Shen, Kai; Felker, G Michael; Rajagopal, Sudarshan

2017-01-01

Pulmonary arterial hypertension (PAH) patients have distinct disease courses and responses to treatment, but current diagnostic and treatment schemes provide limited insight. We aimed to see if cluster analysis could distinguish clinical phenotypes in PAH. An unbiased cluster analysis was performed on 17 baseline clinical variables of PAH patients from the FREEDOM-M, FREEDOM-C, and FREEDOM-C2 randomized trials of oral treprostinil versus placebo. Participants were either treatment-naïve (FREEDOM-M) or on background therapy (FREEDOM-C, FREEDOM-C2). We tested for association of clusters with outcomes and interaction with respect to treatment. Primary outcome was 6-minute walking distance (6MWD) change. We included 966 participants with 12-week (FREEDOM-M) or 16-week (FREEDOM-C and FREEDOM-C2) follow-up. Four patient clusters were identified. Compared with Clusters 1 (n = 131) and 2 (n = 496), Clusters 3 (n = 246) and 4 (n = 93) patients were older, heavier, had worse baseline functional class, 6MWD, Borg Dyspnea Index, and fewer years since PAH diagnosis. Clusters also differed by PAH etiology and background therapies, but not gender or race. Mean treatment effect of oral treprostinil differed across Clusters 1-4 increased in a monotonic fashion (Cluster 1: 10.9 m; Cluster 2: 13.0 m; Cluster 3: 25.0 m; Cluster 4: 50.9 m; interaction P value = 0.048). We identified four distinct clusters of PAH patients based on common patient characteristics. Patients who were older, diagnosed with PAH for a shorter period, and had worse baseline symptoms and exercise capacity had the greatest response to oral treprostinil treatment.

Typology of patients with fibromyalgia: cluster analysis of duloxetine study patients.

PubMed

Lipkovich, Ilya A; Choy, Ernest H; Van Wambeke, Peter; Deberdt, Walter; Sagman, Doron

2014-12-23

To identify distinct groups of patients with fibromyalgia (FM) with respect to multiple outcome measures. Data from 631 duloxetine-treated women in 4 randomized, placebo-controlled trials were included in a cluster analysis based on outcomes after up to 12 weeks of treatment. Corresponding classification rules were constructed using a classification tree method. Probabilities for transitioning from baseline to Week 12 category were estimated for placebo and duloxetine patients (Ntotal = 1188) using logistic regression. Five clusters were identified, from "worst" (high pain levels and severe mental/physical impairment) to "best" (low pain levels and nearly normal mental/physical function). For patients with moderate overall severity, mental and physical symptoms were less correlated, resulting in 2 distinct clusters based on these 2 symptom domains. Three key variables with threshold values were identified for classification of patients: Brief Pain Inventory (BPI) pain interference overall scores of <3.29 and <7.14, respectively, a Fibromyalgia Impact Questionnaire (FIQ) interference with work score of <2, and an FIQ depression score of ≥5. Patient characteristics and frequencies per baseline category were similar between treatments; >80% of patients were in the 3 worst categories. Duloxetine patients were significantly more likely to improve after 12 weeks than placebo patients. A sustained effect was seen with continued duloxetine treatment. FM patients are heterogeneous and can be classified into distinct subgroups by simple descriptive rules derived from only 3 variables, which may guide individual patient management. Duloxetine showed higher improvement rates than placebo and had a sustained effect beyond 12 weeks.

Left inferior parietal lobe engagement in social cognition and language.

PubMed

Bzdok, Danilo; Hartwigsen, Gesa; Reid, Andrew; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B

2016-09-01

Social cognition and language are two core features of the human species. Despite distributed recruitment of brain regions in each mental capacity, the left parietal lobe (LPL) represents a zone of topographical convergence. The present study quantitatively summarizes hundreds of neuroimaging studies on social cognition and language. Using connectivity-based parcellation on a meta-analytically defined volume of interest (VOI), regional coactivation patterns within this VOI allowed identifying distinct subregions. Across parcellation solutions, two clusters emerged consistently in rostro-ventral and caudo-ventral aspects of the parietal VOI. Both clusters were functionally significantly associated with social-cognitive and language processing. In particular, the rostro-ventral cluster was associated with lower-level processing facets, while the caudo-ventral cluster was associated with higher-level processing facets in both mental capacities. Contrarily, in the (less stable) dorsal parietal VOI, all clusters reflected computation of general-purpose processes, such as working memory and matching tasks, that are frequently co-recruited by social or language processes. Our results hence favour a rostro-caudal distinction of lower- versus higher-level processes underlying social cognition and language in the left inferior parietal lobe. Copyright © 2016 Elsevier Ltd. All rights reserved.

Distinct Phenotypes of Cigarette Smokers Identified by Cluster Analysis of Patients with Severe Asthma.

PubMed

Konno, Satoshi; Taniguchi, Natsuko; Makita, Hironi; Nakamaru, Yuji; Shimizu, Kaoruko; Shijubo, Noriharu; Fuke, Satoshi; Takeyabu, Kimihiro; Oguri, Mitsuru; Kimura, Hirokazu; Maeda, Yukiko; Suzuki, Masaru; Nagai, Katsura; Ito, Yoichi M; Wenzel, Sally E; Nishimura, Masaharu

2015-12-01

Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asthma. Cluster analysis has been applied to explore novel phenotypes, which are not based on any a priori hypotheses. To explore novel severe asthma phenotypes by cluster analysis when including cigarette smokers. We recruited a total of 127 subjects with severe asthma, including 59 current or ex-smokers, from our university hospital and its 29 affiliated hospitals/pulmonary clinics. Twelve clinical variables obtained during a 2-day hospital stay were used for cluster analysis. After clustering using clinical variables, the sputum levels of 14 molecules were measured to biologically characterize the clinical clusters. Five clinical clusters were identified, including two characterized by high pack-year exposure to cigarette smoking and low FEV1/FVC. There were marked differences between the two clusters of cigarette smokers. One had high levels of circulating eosinophils, high IgE levels, and a high sinus disease score. The other was characterized by low levels of the same parameters. Sputum analysis revealed increased levels of IL-5 in the former cluster and increased levels of IL-6 and osteopontin in the latter. The other three clusters were similar to those previously reported: young onset/atopic, nonsmoker/less eosinophilic, and female/obese. Key clinical variables were confirmed to be stable and consistent 1 year later. This study reveals two distinct phenotypes of severe asthma in current and former cigarette smokers with potentially different biological pathways contributing to fixed airflow limitation. Clinical trial registered with www.umin.ac.jp (000003254).

Distinct collective states due to trade-off between attractive and repulsive couplings

NASA Astrophysics Data System (ADS)

Sathiyadevi, K.; Chandrasekar, V. K.; Senthilkumar, D. V.; Lakshmanan, M.

2018-03-01

We investigate the effect of repulsive coupling together with an attractive coupling in a network of nonlocally coupled oscillators. To understand the complex interaction between these two couplings we introduce a control parameter in the repulsive coupling which plays a crucial role in inducing distinct complex collective patterns. In particular, we show the emergence of various cluster chimera death states through a dynamically distinct transition route, namely the oscillatory cluster state and coherent oscillation death state as a function of the repulsive coupling in the presence of the attractive coupling. In the oscillatory cluster state, the oscillators in the network are grouped into two distinct dynamical states of homogeneous and inhomogeneous oscillatory states. Further, the network of coupled oscillators follow the same transition route in the entire coupling range. Depending upon distinct coupling ranges, the system displays different number of clusters in the death state and oscillatory state. We also observe that the number of coherent domains in the oscillatory cluster state exponentially decreases with increase in coupling range and obeys a power-law decay. Additionally, we show analytical stability for observed solitary state, synchronized state, and incoherent oscillation death state.

Clustering the Orion B giant molecular cloud based on its molecular emission

PubMed Central

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2017-01-01

Context Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results A clustering analysis based only on the J = 1 – 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes (nH ~ 100 cm−3, ~ 500 cm−3, and > 1000 cm−3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 − 0 line of HCO+ and the N = 1 − 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH ~ 7 × 103 cm−3 ~ 4 × 104 cm−3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1 – 0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers. PMID:29456256

A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition

PubMed Central

Austin, Elena; Coull, Brent A.; Zanobetti, Antonella; Koutrakis, Petros

2013-01-01

Background Heterogeneity in the response to PM2.5 is hypothesized to be related to differences in particle composition across monitoring sites which reflect differences in source types as well as climatic and topographic conditions impacting different geographic locations. Identifying spatial patterns in particle composition is a multivariate problem that requires novel methodologies. Objectives Use cluster analysis methods to identify spatial patterns in PM2.5 composition. Verify that the resulting clusters are distinct and informative. Methods 109 monitoring sites with 75% reported speciation data during the period 2003–2008 were selected. These sites were categorized based on their average PM2.5 composition over the study period using k-means cluster analysis. The obtained clusters were validated and characterized based on their physico-chemical characteristics, geographic locations, emissions profiles, population density and proximity to major emission sources. Results Overall 31 clusters were identified. These include 21 clusters with 2 or more sites which were further grouped into 4 main types using hierarchical clustering. The resulting groupings are chemically meaningful and represent broad differences in emissions. The remaining clusters, encompassing single sites, were characterized based on their particle composition and geographic location. Conclusions The framework presented here provides a novel tool which can be used to identify and further classify sites based on their PM2.5 composition. The solution presented is fairly robust and yielded groupings that were meaningful in the context of air-pollution research. PMID:23850585

Fast graph-based relaxed clustering for large data sets using minimal enclosing ball.

PubMed

Qian, Pengjiang; Chung, Fu-Lai; Wang, Shitong; Deng, Zhaohong

2012-06-01

Although graph-based relaxed clustering (GRC) is one of the spectral clustering algorithms with straightforwardness and self-adaptability, it is sensitive to the parameters of the adopted similarity measure and also has high time complexity O(N(3)) which severely weakens its usefulness for large data sets. In order to overcome these shortcomings, after introducing certain constraints for GRC, an enhanced version of GRC [constrained GRC (CGRC)] is proposed to increase the robustness of GRC to the parameters of the adopted similarity measure, and accordingly, a novel algorithm called fast GRC (FGRC) based on CGRC is developed in this paper by using the core-set-based minimal enclosing ball approximation. A distinctive advantage of FGRC is that its asymptotic time complexity is linear with the data set size N. At the same time, FGRC also inherits the straightforwardness and self-adaptability from GRC, making the proposed FGRC a fast and effective clustering algorithm for large data sets. The advantages of FGRC are validated by various benchmarking and real data sets.

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

PubMed Central

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

2012-01-01

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

Cluster-guided imaging-based CFD analysis of airflow and particle deposition in asthmatic human lungs

NASA Astrophysics Data System (ADS)

Choi, Jiwoong; Leblanc, Lawrence; Choi, Sanghun; Haghighi, Babak; Hoffman, Eric; Lin, Ching-Long

2017-11-01

The goal of this study is to assess inter-subject variability in delivery of orally inhaled drug products to small airways in asthmatic lungs. A recent multiscale imaging-based cluster analysis (MICA) of computed tomography (CT) lung images in an asthmatic cohort identified four clusters with statistically distinct structural and functional phenotypes associating with unique clinical biomarkers. Thus, we aimed to address inter-subject variability via inter-cluster variability. We selected a representative subject from each of the 4 asthma clusters as well as 1 male and 1 female healthy controls, and performed computational fluid and particle simulations on CT-based airway models of these subjects. The results from one severe and one non-severe asthmatic cluster subjects characterized by segmental airway constriction had increased particle deposition efficiency, as compared with the other two cluster subjects (one non-severe and one severe asthmatics) without airway constriction. Constriction-induced jets impinging on distal bifurcations led to excessive particle deposition. The results emphasize the impact of airway constriction on regional particle deposition rather than disease severity, demonstrating the potential of using cluster membership to tailor drug delivery. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837. XSEDE.

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

NASA Astrophysics Data System (ADS)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

Integrated genetic and epigenetic analysis identifies three different subclasses of colon cancer

PubMed Central

Shen, Lanlan; Toyota, Minoru; Kondo, Yutaka; Lin, E; Zhang, Li; Guo, Yi; Hernandez, Natalie Supunpong; Chen, Xinli; Ahmed, Saira; Konishi, Kazuo; Hamilton, Stanley R.; Issa, Jean-Pierre J.

2007-01-01

Colon cancer has been viewed as the result of progressive accumulation of genetic and epigenetic abnormalities. However, this view does not fully reflect the molecular heterogeneity of the disease. We have analyzed both genetic (mutations of BRAF, KRAS, and p53 and microsatellite instability) and epigenetic alterations (DNA methylation of 27 CpG island promoter regions) in 97 primary colorectal cancer patients. Two clustering analyses on the basis of either epigenetic profiling or a combination of genetic and epigenetic profiling were performed to identify subclasses with distinct molecular signatures. Unsupervised hierarchical clustering of the DNA methylation data identified three distinct groups of colon cancers named CpG island methylator phenotype (CIMP) 1, CIMP2, and CIMP negative. Genetically, these three groups correspond to very distinct profiles. CIMP1 are characterized by MSI (80%) and BRAF mutations (53%) and rare KRAS and p53 mutations (16% and 11%, respectively). CIMP2 is associated with 92% KRAS mutations and rare MSI, BRAF, or p53 mutations (0, 4, and 31% respectively). CIMP-negative cases have a high rate of p53 mutations (71%) and lower rates of MSI (12%) or mutations of BRAF (2%) or KRAS (33%). Clustering based on both genetic and epigenetic parameters also identifies three distinct (and homogeneous) groups that largely overlap with the previous classification. The three groups are independent of age, gender, or stage, but CIMP1 and 2 are more common in proximal tumors. Together, our integrated genetic and epigenetic analysis reveals that colon cancers correspond to three molecularly distinct subclasses of disease. PMID:18003927

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.

What is your patient’s cognitive profile? Three distinct subgroups of cognitive function in persons with heart failure

PubMed Central

Hawkins, Misty A.W.; Schaefer, Julie T.; Gunstad, John; Dolansky, Mary A.; Redle, Joseph D.; Josephson, Richard; Moore, Shirley M.; Hughes, Joel W.

2014-01-01

Purpose To determine whether patients with heart failure (HF) have distinct profiles of cognitive impairment. Background Cognitive impairment is common in HF. Recent work found three cognitive profiles in HF patients— (1) intact, (2) impaired, and (3) memory-impaired. We examined the reproducibility of these profiles and clarified mechanisms. Methods HF patients (68.6±9.7years; N=329) completed neuropsychological testing. Composite scores were created for cognitive domains and used to identify clusters via agglomerative-hierarchical cluster analysis. Results A 3-cluster solution emerged. Cluster 1 (n=109) had intact cognition. Cluster 2 (n=123) was impaired across all domains. Cluster 3 (n=97) had impaired memory only. Clusters differed in age, race, education, SES, IQ, BMI, and diabetes (ps ≤.026) but not in mood, anxiety, cardiovascular, or pulmonary disease (ps≥.118). Conclusions We replicated three distinct patterns of cognitive function in persons with HF. These profiles may help providers offer tailored care to patients with different cognitive and clinical needs. PMID:25510559

Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.

PubMed

Santiago-Rivas, Marimer; Schnur, Julie B; Jandorf, Lina

2016-12-01

This study aimed (i) to determine whether people could be differentiated on the basis of their sun protection belief profiles and individual characteristics and (ii) explore the use of a crowdsourcing web service for the assessment of sun protection beliefs. A sample of 500 adults completed an online survey of sun protection belief items using Amazon Mechanical Turk. A two-phased cluster analysis (i.e., hierarchical and non-hierarchical K-means) was utilized to determine clusters of sun protection barriers and facilitators. Results yielded three distinct clusters of sun protection barriers and three distinct clusters of sun protection facilitators. Significant associations between gender, age, sun sensitivity, and cluster membership were identified. Results also showed an association between barrier and facilitator cluster membership. The results of this study provided a potential alternative approach to developing future sun protection promotion initiatives in the population. Findings add to our knowledge regarding individuals who support, oppose, or are ambivalent toward sun protection and inform intervention research by identifying distinct subtypes that may best benefit from (or have a higher need for) skin cancer prevention efforts.

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

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

Tjong, Harianto; Li, Wenyuan; Kalhor, Reza

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm themore » presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.« less

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

DOE PAGES

Tjong, Harianto; Li, Wenyuan; Kalhor, Reza; ...

2016-03-07

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm themore » presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.« less

Chandra Studies of the X-ray gas properties of fossil systems

NASA Astrophysics Data System (ADS)

Qin, Zhen-Zhen

2016-03-01

We study ten galaxy groups and clusters suggested in the literature to be “fossil systems (FSs)” based on Chandra observations. According to the M500 - T and LX - T relations, the gas properties of FSs are not physically distinct from ordinary galaxy groups or clusters. We also first study the fgas, 2500 - T relation and find that the FSs exhibit the same trend as ordinary systems. The gas densities of FSs within 0.1r200 are ˜ 10-3 cm-3, which is the same order of magnitude as galaxy clusters. The entropies within 01r200 (S0.1r200) of FSs are systematically lower than those inordinary galaxy groups, which is consistent with previous reports, but we find their S0.1r200 - T relation is more similar to galaxy clusters. The derived mass profiles of FSs are consistent with the Navarro, Frenk and White model in (0.1 - 1)r200, and the relation between scale radius rs and characteristic mass density δc indicates self-similarity of dark matter halos of FSs. The ranges of rs and δc for FSs are also close to those of galaxy clusters. Therefore, FSs share more common characteristics with galaxy clusters. The special birth place of the FS makes it a distinct type of galaxy system.

Effective traffic features selection algorithm for cyber-attacks samples

NASA Astrophysics Data System (ADS)

Li, Yihong; Liu, Fangzheng; Du, Zhenyu

2018-05-01

By studying the defense scheme of Network attacks, this paper propose an effective traffic features selection algorithm based on k-means++ clustering to deal with the problem of high dimensionality of traffic features which extracted from cyber-attacks samples. Firstly, this algorithm divide the original feature set into attack traffic feature set and background traffic feature set by the clustering. Then, we calculates the variation of clustering performance after removing a certain feature. Finally, evaluating the degree of distinctiveness of the feature vector according to the result. Among them, the effective feature vector is whose degree of distinctiveness exceeds the set threshold. The purpose of this paper is to select out the effective features from the extracted original feature set. In this way, it can reduce the dimensionality of the features so as to reduce the space-time overhead of subsequent detection. The experimental results show that the proposed algorithm is feasible and it has some advantages over other selection algorithms.

Thematic clustering of text documents using an EM-based approach

PubMed Central

2012-01-01

Clustering textual contents is an important step in mining useful information on the web or other text-based resources. The common task in text clustering is to handle text in a multi-dimensional space, and to partition documents into groups, where each group contains documents that are similar to each other. However, this strategy lacks a comprehensive view for humans in general since it cannot explain the main subject of each cluster. Utilizing semantic information can solve this problem, but it needs a well-defined ontology or pre-labeled gold standard set. In this paper, we present a thematic clustering algorithm for text documents. Given text, subject terms are extracted and used for clustering documents in a probabilistic framework. An EM approach is used to ensure documents are assigned to correct subjects, hence it converges to a locally optimal solution. The proposed method is distinctive because its results are sufficiently explanatory for human understanding as well as efficient for clustering performance. The experimental results show that the proposed method provides a competitive performance compared to other state-of-the-art approaches. We also show that the extracted themes from the MEDLINE® dataset represent the subjects of clusters reasonably well. PMID:23046528

A Scale-Independent Clustering Method with Automatic Variable Selection Based on Trees

DTIC Science & Technology

2014-03-01

veterans fought. They then clustered the data and were able to identify three distinct post-combat syndromes associated with different eras...granting some legitimacy to proposed medical conditions such as the Gulf War Syndrome (Jones et al., 2002, pp. 321–324) D. MEASURING DISTANCES BETWEEN...chosen so as to minimize the sum of squared errors of the response across the two regions (Equation 2.1). The average y for the left and right child

Immature MEF2C-dysregulated T-cell leukemia patients have an early T-cell precursor acute lymphoblastic leukemia gene signature and typically have non-rearranged T-cell receptors

PubMed Central

Zuurbier, Linda; Gutierrez, Alejandro; Mullighan, Charles G.; Canté-Barrett, Kirsten; Gevaert, A. Olivier; de Rooi, Johan; Li, Yunlei; Smits, Willem K.; Buijs-Gladdines, Jessica G.C.A.M.; Sonneveld, Edwin; Look, A. Thomas; Horstmann, Martin; Pieters, Rob; Meijerink, Jules P.P.

2014-01-01

Three distinct immature T-cell acute lymphoblastic leukemia entities have been described including cases that express an early T-cell precursor immunophenotype or expression profile, immature MEF2C-dysregulated T-cell acute lymphoblastic leukemia cluster cases based on gene expression analysis (immature cluster) and cases that retain non-rearranged TRG@ loci. Early T-cell precursor acute lymphoblastic leukemia cases exclusively overlap with immature cluster samples based on the expression of early T-cell precursor acute lymphoblastic leukemia signature genes, indicating that both are featuring a single disease entity. Patients lacking TRG@ rearrangements represent only 40% of immature cluster cases, but no further evidence was found to suggest that cases with absence of bi-allelic TRG@ deletions reflect a distinct and even more immature disease entity. Immature cluster/early T-cell precursor acute lymphoblastic leukemia cases are strongly enriched for genes expressed in hematopoietic stem cells as well as genes expressed in normal early thymocyte progenitor or double negative-2A T-cell subsets. Identification of early T-cell precursor acute lymphoblastic leukemia cases solely by defined immunophenotypic criteria strongly underestimates the number of cases that have a corresponding gene signature. However, early T-cell precursor acute lymphoblastic leukemia samples correlate best with a CD1 negative, CD4 and CD8 double negative immunophenotype with expression of CD34 and/or myeloid markers CD13 or CD33. Unlike various other studies, immature cluster/early T-cell precursor acute lymphoblastic leukemia patients treated on the COALL-97 protocol did not have an overall inferior outcome, and demonstrated equal sensitivity levels to most conventional therapeutic drugs compared to other pediatric T-cell acute lymphoblastic leukemia patients. PMID:23975177

Organization and number of orexinergic neurons in the hypothalamus of two species of Cetartiodactyla: A comparison of giraffe (Giraffa camelopardalis) and harbour porpoise (Phocoena phocoena)

PubMed Central

Dell, Leigh-Anne; Patzke, Nina; Bhagwandin, Adhil; Bux, Faiza; Fuxe, Kjell; Barber, Grace; Siegel, Jerome M.; Manger, Paul R.

2012-01-01

The present study describes the organization of the orexinergic (hypocretinergic) neurons in the hypothalamus of the giraffe and harbour porpoise – two members of the mammalian Order Cetartiodactyla which is comprised of the even-toed ungulates and the cetaceans as they share a monophyletic ancestry. Diencephalons from two sub-adult male giraffes and two adult male harbour porpoises were coronally sectioned and immunohistochemically stained for orexin-A. The staining revealed that the orexinergic neurons could be readily divided into two distinct neuronal types based on somal volume, area and length, these being the parvocellular and magnocellular orexin-A immunopositive (OxA+) groups. The magnocellular group could be further subdivided, on topological grounds, into three distinct clusters – a main cluster in the perifornical and lateral hypothalamus, a cluster associated with the zona incerta and a cluster associated with the optic tract. The parvocellular neurons were found in the medial hypothalamus, but could not be subdivided, rather they form a topologically amorphous cluster. The parvocellular cluster appears to be unique to the Cetartiodactyla as these neurons have not been described in other mammals to date, while the magnocellular nuclei appear to be homologous to similar nuclei described in other mammals. The overall size of both the parvocellular and magnocellular neurons (based on somal volume, area and length) were larger in the giraffe than the harbour porpoise, but the harbour porpoise had a higher number of both parvocellular and magnocellular orexinergic neurons than the giraffe despite both having a similar brain mass. The higher number of both parvocellular and magnocellular orexinergic neurons in the harbour porpoise may relate to the unusual sleep mechanisms in the cetaceans. PMID:22683547

Identification of Clusters of Foot Pain Location in a Community Sample.

PubMed

Gill, Tiffany K; Menz, Hylton B; Landorf, Karl B; Arnold, John B; Taylor, Anne W; Hill, Catherine L

2017-12-01

To identify foot pain clusters according to pain location in a community-based sample of the general population. This study analyzed data from the North West Adelaide Health Study. Data were obtained between 2004 and 2006, using computer-assisted telephone interviewing, clinical assessment, and self-completed questionnaire. The location of foot pain was assessed using a diagram during the clinical assessment. Hierarchical cluster analysis was undertaken to identify foot pain location clusters, which were then compared in relation to demographics, comorbidities, and podiatry services utilization. There were 558 participants with foot pain (mean age 54.4 years, 57.5% female). Five clusters were identified: 1 with predominantly arch and ball pain (26.8%), 1 with rearfoot pain (20.9%), 1 with heel pain (13.3%), and 2 with predominantly forefoot, toe, and nail pain (28.3% and 10.7%). Each cluster was distinct in age, sex, and comorbidity profile. Of the two clusters with predominantly forefoot, toe, and nail pain, one of them had a higher proportion of men and those classified as obese, had diabetes mellitus, and used podiatry services (30%), while the other was comprised of a higher proportion of women who were overweight and reported less use of podiatry services (17.5%). Five clusters of foot pain according to pain location were identified, all with distinct age, sex, and comorbidity profiles. These findings may assist in the identification of individuals at risk for developing foot pain and in the development of targeted preventive strategies and treatments. © 2017, American College of Rheumatology.

Redundant synthesis of a conidial polyketide by two distinct secondary metabolite clusters in Aspergillus fumigatus

PubMed Central

Throckmorton, Kurt; Lim, Fang Yun; Kontoyiannis, Dimitrios P.; Zheng, Weifa; Keller, Nancy P.

2016-01-01

Summary Filamentous fungi are renowned for the production of bioactive secondary metabolites. Typically, one distinct metabolite is generated from a specific secondary metabolite cluster. Here, we characterize the newly described trypacidin (tpc) cluster in the opportunistic human pathogen Aspergillus fumigatus. We find that this cluster as well as the previously characterized endocrocin (enc) cluster both contribute to the production of the spore metabolite endocrocin. Whereas trypacidin is eliminated when only tpc cluster genes are deleted, endocrocin production is only eliminated when both the tpc and enc non-reducing polyketide synthase-encoding genes, tpcC and encA, respectively, are deleted. EncC, an anthrone oxidase, converts the product released from EncA to endocrocin as a final product. In contrast, endocrocin synthesis by the tpc cluster likely results from incomplete catalysis by TpcK (a putative decarboxylase), as its deletion results in a nearly 10-fold increase in endocrocin production. We suggest endocrocin is likely a shunt product in all related non-reducing polyketide synthase clusters containing homologues of TpcK and TpcL (a putative anthrone oxidase), e.g. geodin and monodictyphenone. This finding represents an unusual example of two physically discrete secondary metabolite clusters generating the same natural product in one fungal species by distinct routes. PMID:26242966

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.

Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.

PubMed

Andreatta, Massimo; Lund, Ole; Nielsen, Morten

2013-01-01

Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and/or the motifs are found at different locations within distinct peptides. The algorithm presented in this article, based on Gibbs sampling, identifies multiple specificities in peptide data by performing two essential tasks simultaneously: alignment and clustering of peptide data. We apply the method to de-convolute binding motifs in a panel of peptide datasets with different degrees of complexity spanning from the simplest case of pre-aligned fixed-length peptides to cases of unaligned peptide datasets of variable length. Example applications described in this article include mixtures of binders to different MHC class I and class II alleles, distinct classes of ligands for SH3 domains and sub-specificities of the HLA-A*02:01 molecule. The Gibbs clustering method is available online as a web server at http://www.cbs.dtu.dk/services/GibbsCluster.

The fine-scale genetic structure and evolution of the Japanese population.

PubMed

Takeuchi, Fumihiko; Katsuya, Tomohiro; Kimura, Ryosuke; Nabika, Toru; Isomura, Minoru; Ohkubo, Takayoshi; Tabara, Yasuharu; Yamamoto, Ken; Yokota, Mitsuhiro; Liu, Xuanyao; Saw, Woei-Yuh; Mamatyusupu, Dolikun; Yang, Wenjun; Xu, Shuhua; Teo, Yik-Ying; Kato, Norihiro

2017-01-01

The contemporary Japanese populations largely consist of three genetically distinct groups-Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics.

Major depressive disorder subtypes to predict long-term course

PubMed Central

van Loo, Hanna M.; Cai, Tianxi; Gruber, Michael J.; Li, Junlong; de Jonge, Peter; Petukhova, Maria; Rose, Sherri; Sampson, Nancy A.; Schoevers, Robert A.; Wardenaar, Klaas J.; Wilcox, Marsha A.; Al-Hamzawi, Ali Obaid; Andrade, Laura Helena; Bromet, Evelyn J.; Bunting, Brendan; Fayyad, John; Florescu, Silvia E.; Gureje, Oye; Hu, Chiyi; Huang, Yueqin; Levinson, Daphna; Medina-Mora, Maria Elena; Nakane, Yoshibumi; Posada-Villa, Jose; Scott, Kate M.; Xavier, Miguel; Zarkov, Zahari; Kessler, Ronald C.

2016-01-01

Background Variation in course of major depressive disorder (MDD) is not strongly predicted by existing subtype distinctions. A new subtyping approach is considered here. Methods Two data mining techniques, ensemble recursive partitioning and Lasso generalized linear models (GLMs) followed by k-means cluster analysis, are used to search for subtypes based on index episode symptoms predicting subsequent MDD course in the World Mental Health (WMH) Surveys. The WMH surveys are community surveys in 16 countries. Lifetime DSM-IV MDD was reported by 8,261 respondents. Retrospectively reported outcomes included measures of persistence (number of years with an episode; number of with an episode lasting most of the year) and severity (hospitalization for MDD; disability due to MDD). Results Recursive partitioning found significant clusters defined by the conjunctions of early onset, suicidality, and anxiety (irritability, panic, nervousness-worry-anxiety) during the index episode. GLMs found additional associations involving a number of individual symptoms. Predicted values of the four outcomes were strongly correlated. Cluster analysis of these predicted values found three clusters having consistently high, intermediate, or low predicted scores across all outcomes. The high-risk cluster (30.0% of respondents) accounted for 52.9-69.7% of high persistence and severity and was most strongly predicted by index episode severe dysphoria, suicidality, anxiety, and early onset. A total symptom count, in comparison, was not a significant predictor. Conclusions Despite being based on retrospective reports, results suggest that useful MDD subtyping distinctions can be made using data mining methods. Further studies are needed to test and expand these results with prospective data. PMID:24425049

Genetic Diversity and Differentiation of Colletotrichum spp. Isolates Associated with Leguminosae Using Multigene Loci, RAPD and ISSR

PubMed Central

Mahmodi, Farshid; Kadir, J. B.; Puteh, A.; Pourdad, S. S.; Nasehi, A.; Soleimani, N.

2014-01-01

Genetic diversity and differentiation of 50 Colletotrichum spp. isolates from legume crops studied through multigene loci, RAPD and ISSR analysis. DNA sequence comparisons by six genes (ITS, ACT, Tub2, CHS-1, GAPDH, and HIS3) verified species identity of C. truncatum, C. dematium and C. gloeosporiodes and identity C. capsici as a synonym of C. truncatum. Based on the matrix distance analysis of multigene sequences, the Colletotrichum species showed diverse degrees of intera and interspecific divergence (0.0 to 1.4%) and (15.5–19.9), respectively. A multilocus molecular phylogenetic analysis clustered Colletotrichum spp. isolates into 3 well-defined clades, representing three distinct species; C. truncatum, C. dematium and C. gloeosporioides. The ISSR and RAPD and cluster analysis exhibited a high degree of variability among different isolates and permitted the grouping of isolates of Colletotrichum spp. into three distinct clusters. Distinct populations of Colletotrichum spp. isolates were genetically in accordance with host specificity and inconsistent with geographical origins. The large population of C. truncatum showed greater amounts of genetic diversity than smaller populations of C. dematium and C. gloeosporioides species. Results of ISSR and RAPD markers were congruent, but the effective maker ratio and the number of private alleles were greater in ISSR markers. PMID:25288981

Clustering the Orion B giant molecular cloud based on its molecular emission

NASA Astrophysics Data System (ADS)

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Context. Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims: We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods: We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional probability density function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results: A clustering analysis based only on the J = 1-0 lines of three isotopologues of CO proves sufficient to reveal distinct density/column density regimes (nH 100 cm-3, 500 cm-3, and >1000 cm-3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1-0 line of HCO+ and the N = 1-0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH 7 × 103 cm-3, 4 × 104 cm-3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1-0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions: Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers. Data products associated with this paper are 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/610/A12 and at http://www.iram.fr/ pety/ORION-B

Diversity, origins and virulence of Avipoxviruses in Hawaiian Forest Birds

USGS Publications Warehouse

Jarvi, S.I.; Triglia, D.; Giannoulis, A.; Farias, M.; Bianchi, K.; Atkinson, C.T.

2008-01-01

We cultured avian pox (Avipoxvirus spp.) from lesions collected on Hawai'i, Maui, Moloka'i, and 'Oahu in the Hawaiian Islands from 15 native or non-native birds representing three avian orders. Phylogenetic analysis of a 538 bp fragment of the gene encoding the virus 4b core polypeptide revealed two distinct variant clusters, with sequences from chickens (fowlpox) forming a third distinct basal cluster. Pox isolates from one of these two clusters appear closely related to canarypox and other passerine pox viruses, while the second appears more specific to Hawai'i. There was no evidence that birds were infected simultaneously with multiple pox virus variants based on evaluation of multiples clones from four individuals. No obvious temporal or geographic associations were observed and strict host specificity was not apparent among the 4b-defined field isolates. We amplified a 116 bp 4b core protein gene fragment from an 'Elepaio (Chasiempis sandwichensis) collected in 1900 on Hawai'i Island that clustered closely with the second of the two variants, suggesting that this variant has been in Hawai'i for at least 100 years. The high variation detected between the three 4b clusters provides evidence for multiple, likely independent introductions, and does not support the hypothesis of infection of native species through introduction of infected fowl. Preliminary experimental infections in native Hawai'i 'Amakihi (Hemignathus virens) suggest that the 4b-defined variants may be biologically distinct, with one variant appearing more virulent. These pox viruses may interact with avian malaria (Plasmodium relictum), another introduced pathogen in Hawaiian forest bird populations, through modulation of host immune responses. ?? 2007 Springer Science+Business Media B.V.

Identifying eating behavior phenotypes and their correlates: a novel direction toward improving weight management interventions

PubMed Central

Bouhlal, Sofia; McBride, Colleen M.; Trivedi, Niraj S.; Agurs-Collins, Tanya; Persky, Susan

2017-01-01

Common reports of over-response to food cues, difficulties with calorie restriction, and difficulty adhering to dietary guidelines suggest that eating behaviors could be interrelated in ways that influence weight management efforts. The feasibility of identifying robust eating phenotypes (showing face, content, and criterion validity) was explored based on well-validated individual eating behavior assessments. Adults (n=260; mean age 34 years) completed online questionnaires with measurements of nine eating behaviors including: appetite for palatable foods, binge eating, bitter taste sensitivity, disinhibition, food neophobia, pickiness and satiety responsiveness. Discovery-based visualization procedures that have the combined strengths of heatmaps and hierarchical clustering were used to investigate: 1) how eating behaviors cluster, 2) how participants can be grouped within eating behavior clusters, and 3) whether group clustering is associated with body mass index (BMI) and dietary self-efficacy levels. Two distinct eating behavior clusters and participant groups that aligned within these clusters were identified: one with higher drive to eat and another with food avoidance behaviors. Participants’ BMI (p=.0002) and dietary self-efficacy (p<.0001) were associated with cluster membership. Eating behavior clusters showed content and criterion validity based on their association with BMI (associated, but not entirely overlapping) and dietary self-efficacy. Identifying eating behavior phenotypes appears viable. These efforts could be expanded and ultimately inform tailored weight management interventions. PMID:28043857

Mapping similarities in temporal parking occupancy behavior based on city-wide parking meter data

NASA Astrophysics Data System (ADS)

Bock, Fabian; Xia, Karen; Sester, Monika

2018-05-01

The search for a parking space is a severe and stressful problem for drivers in many cities. The provision of maps with parking space occupancy information assists drivers in avoiding the most crowded roads at certain times. Since parking occupancy reveals a repetitive pattern per day and per week, typical parking occupancy patterns can be extracted from historical data. In this paper, we analyze city-wide parking meter data from Hannover, Germany, for a full year. We describe an approach of clustering these parking meters to reduce the complexity of this parking occupancy information and to reveal areas with similar parking behavior. The parking occupancy at every parking meter is derived from a timestamp of ticket payment and the validity period of the parking tickets. The similarity of the parking meters is computed as the mean-squared deviation of the average daily patterns in parking occupancy at the parking meters. Based on this similarity measure, a hierarchical clustering is applied. The number of clusters is determined with the Davies-Bouldin Index and the Silhouette Index. Results show that, after extensive data cleansing, the clustering leads to three clusters representing typical parking occupancy day patterns. Those clusters differ mainly in the hour of the maximum occupancy. In addition, the lo-cations of parking meter clusters, computed only based on temporal similarity, also show clear spatial distinctions from other clusters.

Interpersonal Subtypes Within Social Anxiety: The Identification of Distinct Social Features.

PubMed

Cooper, Danielle; Anderson, Timothy

2017-10-05

Although social anxiety disorder is defined by anxiety-related symptoms, little research has focused on the interpersonal features of social anxiety. Prior studies (Cain, Pincus, & Grosse Holtforth, 2010; Kachin, Newman, & Pincus, 2001) identified distinct subgroups of socially anxious individuals' interpersonal circumplex problems that were blends of agency and communion, and yet inconsistencies remain. We predicted 2 distinct interpersonal subtypes would exist for individuals with high social anxiety, and that these social anxiety subtypes would differ on empathetic concern, paranoia, received peer victimization, perspective taking, and emotional suppression. From a sample of 175 undergraduate participants, 51 participants with high social anxiety were selected as above a clinical cutoff on the social phobia scale. Cluster analyses identified 2 interpersonal subtypes of socially anxious individuals: low hostility-high submissiveness (Cluster 1) and high hostility-high submissiveness (Cluster 2). Cluster 1 reported higher levels of empathetic concern, lower paranoia, less peer victimization, and lower emotional suppression compared to Cluster 2. There were no differences between subtypes on perspective taking or cognitive reappraisal. Findings are consistent with an interpersonal conceptualization of social anxiety, and provide evidence of distinct social features between these subtypes. Findings have implications for the etiology, classification, and treatment of social anxiety.

A time-series approach for clustering farms based on slaughterhouse health aberration data.

PubMed

Hulsegge, B; de Greef, K H

2018-05-01

A large amount of data is collected routinely in meat inspection in pig slaughterhouses. A time series clustering approach is presented and applied that groups farms based on similar statistical characteristics of meat inspection data over time. A three step characteristic-based clustering approach was used from the idea that the data contain more info than the incidence figures. A stratified subset containing 511,645 pigs was derived as a study set from 3.5 years of meat inspection data. The monthly averages of incidence of pleuritis and of pneumonia of 44 Dutch farms (delivering 5149 batches to 2 pig slaughterhouses) were subjected to 1) derivation of farm level data characteristics 2) factor analysis and 3) clustering into groups of farms. The characteristic-based clustering was able to cluster farms for both lung aberrations. Three groups of data characteristics were informative, describing incidence, time pattern and degree of autocorrelation. The consistency of clustering similar farms was confirmed by repetition of the analysis in a larger dataset. The robustness of the clustering was tested on a substantially extended dataset. This confirmed the earlier results, three data distribution aspects make up the majority of distinction between groups of farms and in these groups (clusters) the majority of the farms was allocated comparable to the earlier allocation (75% and 62% for pleuritis and pneumonia, respectively). The difference between pleuritis and pneumonia in their seasonal dependency was confirmed, supporting the biological relevance of the clustering. Comparison of the identified clusters of statistically comparable farms can be used to detect farm level risk factors causing the health aberrations beyond comparison on disease incidence and trend alone. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparative genome analysis of Pseudomonas genomes including Populus-associated isolates

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

Jun, Se Ran; Wassenaar, Trudy; Nookaew, Intawat

The Pseudomonas genus contains a metabolically versatile group of organisms that are known to occupy numerous ecological niches including the rhizosphere and endosphere of many plants influencing phylogenetic diversity and heterogeneity. In this study, comparative genome analysis was performed on over one thousand Pseudomonas genomes, including 21 Pseudomonas strains isolated from the roots of native Populus deltoides. Based on average amino acid identity, genomic clusters were identified within the Pseudomonas genus, which showed agreements with clades by NCBI and cliques by IMG. The P. fluorescens group was organized into 20 distinct genomic clusters, representing enormous diversity and heterogeneity. The speciesmore » P. aeruginosa showed clear distinction in their genomic relatedness compared to other Pseudomonas species groups based on the pan and core genome analysis. The 19 isolates of our 21 Populus-associated isolates formed three distinct subgroups within the P. fluorescens major group, supported by pathway profiles analysis, while two isolates were more closely related to P. chlororaphis and P. putida. The specific genes to Populus-associated subgroups were identified where genes specific to subgroup 1 include several sensory systems such as proteins which act in two-component signal transduction, a TonB-dependent receptor, and a phosphorelay sensor; specific genes to subgroup 2 contain unique hypothetical genes; and genes specific to subgroup 3 organisms have a different hydrolase activity. IMPORTANCE The comparative genome analyses of the genus Pseudomonas that included Populus-associated isolates resulted in novel insights into high diversity of Pseudomonas. Consistent and robust genomic clusters with phylogenetic homogeneity were identified, which resolved species-clades that are not clearly defined by 16S rRNA gene sequence analysis alone. The genomic clusters may be reflective of distinct ecological niches to which the organisms have adapted, but this needs to be experimentally characterized with ecologically relevant phenotype properties. This study justifies the need to sequence multiple isolates, especially from P. fluorescens group in order to study functional capabilities from a pangenomic perspective. This information will prove useful when choosing Pseudomonas strains for use to promote growth and increase disease resistance in plants.« less

Comparative genome analysis of Pseudomonas genomes including Populus-associated isolates

DOE PAGES

Jun, Se Ran; Wassenaar, Trudy; Nookaew, Intawat; ...

2016-01-01

The Pseudomonas genus contains a metabolically versatile group of organisms that are known to occupy numerous ecological niches including the rhizosphere and endosphere of many plants influencing phylogenetic diversity and heterogeneity. In this study, comparative genome analysis was performed on over one thousand Pseudomonas genomes, including 21 Pseudomonas strains isolated from the roots of native Populus deltoides. Based on average amino acid identity, genomic clusters were identified within the Pseudomonas genus, which showed agreements with clades by NCBI and cliques by IMG. The P. fluorescens group was organized into 20 distinct genomic clusters, representing enormous diversity and heterogeneity. The speciesmore » P. aeruginosa showed clear distinction in their genomic relatedness compared to other Pseudomonas species groups based on the pan and core genome analysis. The 19 isolates of our 21 Populus-associated isolates formed three distinct subgroups within the P. fluorescens major group, supported by pathway profiles analysis, while two isolates were more closely related to P. chlororaphis and P. putida. The specific genes to Populus-associated subgroups were identified where genes specific to subgroup 1 include several sensory systems such as proteins which act in two-component signal transduction, a TonB-dependent receptor, and a phosphorelay sensor; specific genes to subgroup 2 contain unique hypothetical genes; and genes specific to subgroup 3 organisms have a different hydrolase activity. IMPORTANCE The comparative genome analyses of the genus Pseudomonas that included Populus-associated isolates resulted in novel insights into high diversity of Pseudomonas. Consistent and robust genomic clusters with phylogenetic homogeneity were identified, which resolved species-clades that are not clearly defined by 16S rRNA gene sequence analysis alone. The genomic clusters may be reflective of distinct ecological niches to which the organisms have adapted, but this needs to be experimentally characterized with ecologically relevant phenotype properties. This study justifies the need to sequence multiple isolates, especially from P. fluorescens group in order to study functional capabilities from a pangenomic perspective. This information will prove useful when choosing Pseudomonas strains for use to promote growth and increase disease resistance in plants.« less

Cognitive subtypes of dyslexia are characterized by distinct patterns of grey matter volume.

PubMed

Jednoróg, Katarzyna; Gawron, Natalia; Marchewka, Artur; Heim, Stefan; Grabowska, Anna

2014-09-01

The variety of different causal theories together with inconsistencies about the anatomical brain markers emphasize the heterogeneity of developmental dyslexia. Attempts were made to test on a behavioral level the existence of subtypes of dyslexia showing distinguishable cognitive deficits. Importantly, no research was directly devoted to the investigation of structural brain correlates of these subtypes. Here, for the first time, we applied voxel-based morphometry (VBM) to study grey matter volume (GMV) differences in a relatively large sample (n = 46) of dyslexic children split into three subtypes based on the cognitive deficits: phonological, rapid naming, magnocellular/dorsal, and auditory attention shifting. VBM revealed GMV clusters specific for each studied group including areas of left inferior frontal gyrus, cerebellum, right putamen, and bilateral parietal cortex. In addition, using discriminant analysis on these clusters 79% of cross-validated cases were correctly re-classified into four groups (controls vs. three subtypes). Current results indicate that dyslexia may result from distinct cognitive impairments characterized by distinguishable anatomical markers.

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.

Discrimination of multilocus sequence typing-based Campylobacter jejuni subgroups by MALDI-TOF mass spectrometry.

PubMed

Zautner, Andreas Erich; Masanta, Wycliffe Omurwa; Tareen, Abdul Malik; Weig, Michael; Lugert, Raimond; Groß, Uwe; Bader, Oliver

2013-11-07

Campylobacter jejuni, the most common bacterial pathogen causing gastroenteritis, shows a wide genetic diversity. Previously, we demonstrated by the combination of multi locus sequence typing (MLST)-based UPGMA-clustering and analysis of 16 genetic markers that twelve different C. jejuni subgroups can be distinguished. Among these are two prominent subgroups. The first subgroup contains the majority of hyperinvasive strains and is characterized by a dimeric form of the chemotaxis-receptor Tlp7(m+c). The second has an extended amino acid metabolism and is characterized by the presence of a periplasmic asparaginase (ansB) and gamma-glutamyl-transpeptidase (ggt). Phyloproteomic principal component analysis (PCA) hierarchical clustering of MALDI-TOF based intact cell mass spectrometry (ICMS) spectra was able to group particular C. jejuni subgroups of phylogenetic related isolates in distinct clusters. Especially the aforementioned Tlp7(m+c)(+) and ansB+/ ggt+ subgroups could be discriminated by PCA. Overlay of ICMS spectra of all isolates led to the identification of characteristic biomarker ions for these specific C. jejuni subgroups. Thus, mass peak shifts can be used to identify the C. jejuni subgroup with an extended amino acid metabolism. Although the PCA hierarchical clustering of ICMS-spectra groups the tested isolates into a different order as compared to MLST-based UPGMA-clustering, the isolates of the indicator-groups form predominantly coherent clusters. These clusters reflect phenotypic aspects better than phylogenetic clustering, indicating that the genes corresponding to the biomarker ions are phylogenetically coupled to the tested marker genes. Thus, PCA clustering could be an additional tool for analyzing the relatedness of bacterial isolates.

Clustering of self-organizing map identifies five distinct medulloblastoma subgroups.

PubMed

Cao, Changjun; Wang, Wei; Jiang, Pucha

2016-01-01

Medulloblastoma is one the most malignant paediatric brain tumours. Molecular subgrouping these medulloblastomas will not only help identify specific cohorts for certain treatment but also improve confidence in prognostic prediction. Currently, there is a consensus of the existences of four distinct subtypes of medulloblastoma. We proposed a novel bioinformatics method, clustering of self-organizing map, to determine the subgroups and their molecular diversity. Microarray expression profiles of 46 medulloblastoma samples were analysed and five clusters with distinct demographics, clinical outcome and transcriptional profiles were identified. The previously reported Wnt subgroup was identified as expected. Three other novel subgroups were proposed for later investigation. Our findings underscore the value of SOM clustering for discovering the medulloblastoma subgroups. When the suggested subdivision has been confirmed in large cohorts, this method should serve as a part of routine classification of clinical samples.

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.

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

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

Young, M; Craft, D

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchicalmore » clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.« less

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

PubMed

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

2016-01-01

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

Typing of Human Mycobacterium avium Isolates in Italy by IS1245-Based Restriction Fragment Length Polymorphism Analysis

PubMed Central

Lari, Nicoletta; Cavallini, Michela; Rindi, Laura; Iona, Elisabetta; Fattorini, Lanfranco; Garzelli, Carlo

1998-01-01

All but 2 of 63 Mycobacterium avium isolates from distinct geographic areas of Italy exhibited markedly polymorphic, multibanded IS1245 restriction fragment length polymorphism (RFLP) patterns; 2 isolates showed the low-number banding pattern typical of bird isolates. By computer analysis, 41 distinct IS1245 patterns and 10 clusters of essentially identical strains were detected; 40% of the 63 isolates showed genetic relatedness, suggesting the existence of a predominant AIDS-associated IS1245 RFLP pattern. PMID:9817900

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

Metrics and methods for characterizing dairy farm intensification using farm survey data.

PubMed

Gonzalez-Mejia, Alejandra; Styles, David; Wilson, Paul; Gibbons, James

2018-01-01

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the "average farm" level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

PubMed Central

Babbitt, Patricia C.; Ferrin, Thomas E.

2017-01-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially—MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method’s novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences. PMID:28187133

Metrics and methods for characterizing dairy farm intensification using farm survey data

PubMed Central

Gonzalez-Mejia, Alejandra; Styles, David; Wilson, Paul

2018-01-01

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the “average farm” level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales. PMID:29742166

Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria

PubMed Central

Balagam, Rajesh; Igoshin, Oleg A.

2015-01-01

Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. PMID:26308508

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.

Sensory Processing Subtypes in Autism: Association with Adaptive Behavior

ERIC Educational Resources Information Center

Lane, Alison E.; Young, Robyn L.; Baker, Amy E. Z.; Angley, Manya T.

2010-01-01

Children with autism are frequently observed to experience difficulties in sensory processing. This study examined specific patterns of sensory processing in 54 children with autistic disorder and their association with adaptive behavior. Model-based cluster analysis revealed three distinct sensory processing subtypes in autism. These subtypes…

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

DOE PAGES

Old, L.; Wojtak, R.; Pearce, F. R.; ...

2017-12-20

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously withmore » commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

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

Old, L.; Wojtak, R.; Pearce, F. R.

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously withmore » commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

2010-11-01

The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Expert Assessment of Human-Human Stigmergy

DTIC Science & Technology

2005-10-01

paradigm for marker based stigmergy is the use of pheromones by certain social insects to coordinate their actions. Most insect species use a few...dozen distinct pheromone “flavors,” and thus use qualitative as well as quantitative decision-making. In engineered systems, stigmergic markers can...Gradient following in a single pheromone field Ant cemetery clustering Qualitative Decisions based on combinations of pheromones Wasp nest

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

Drinker Types, Harm, and Policy-Related Variables: Results from the 2011 International Alcohol Control Study in New Zealand.

PubMed

Wall, Martin; Casswell, Sally

2017-05-01

The aim was to identify a typology of drinkers in New Zealand based on alcohol consumption, beverage choice, and public versus private drinking locations and investigate the relationship between drinker types, harms experienced, and policy-related variables. Model-based cluster analysis of male and female drinkers including volumes of alcohol consumed in the form of beer, wine, spirits, and ready-to-drinks (RTDs) in off- and on-premise settings. Cluster membership was then related to harm measures: alcohol dependence, self-rated health; and to 3 policy-relevant variables: liking for alcohol adverts, price paid for alcohol, and time of purchase. Males and females were analyzed separately. Men fell into 4 and women into 14 clearly discriminated clusters. The male clusters consumed a relatively high proportion of alcohol in the form of beer. Women had a number of small extreme clusters and some consumed mainly spirits-based RTDs, while others drank mainly wine. Those in the higher consuming clusters were more likely to have signs of alcohol dependency, to report lower satisfaction with their health, to like alcohol ads, and to have purchased late at night. Consumption patterns are sufficiently distinctive to identify typologies of male and female alcohol consumers. Women drinkers are more heterogeneous than men. The clusters relate differently to policy-related variables. Copyright © 2017 by the Research Society on Alcoholism.

Coresets vs clustering: comparison of methods for redundancy reduction in very large white matter fiber sets

NASA Astrophysics Data System (ADS)

Alexandroni, Guy; Zimmerman Moreno, Gali; Sochen, Nir; Greenspan, Hayit

2016-03-01

Recent advances in Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) of white matter in conjunction with improved tractography produce impressive reconstructions of White Matter (WM) pathways. These pathways (fiber sets) often contain hundreds of thousands of fibers, or more. In order to make fiber based analysis more practical, the fiber set needs to be preprocessed to eliminate redundancies and to keep only essential representative fibers. In this paper we demonstrate and compare two distinctive frameworks for selecting this reduced set of fibers. The first framework entails pre-clustering the fibers using k-means, followed by Hierarchical Clustering and replacing each cluster with one representative. For the second clustering stage seven distance metrics were evaluated. The second framework is based on an efficient geometric approximation paradigm named coresets. Coresets present a new approach to optimization and have huge success especially in tasks requiring large computation time and/or memory. We propose a modified version of the coresets algorithm, Density Coreset. It is used for extracting the main fibers from dense datasets, leaving a small set that represents the main structures and connectivity of the brain. A novel approach, based on a 3D indicator structure, is used for comparing the frameworks. This comparison was applied to High Angular Resolution Diffusion Imaging (HARDI) scans of 4 healthy individuals. We show that among the clustering based methods, that cosine distance gives the best performance. In comparing the clustering schemes with coresets, Density Coreset method achieves the best performance.

Closed-cage tungsten oxide clusters in the gas phase.

PubMed

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

2010-05-06

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

Distinct functional domains within the acidic cluster of tegument protein pp28 required for trafficking and cytoplasmic envelopment of human cytomegalovirus.

PubMed

Seo, Jun-Young; Jeon, Hyejin; Hong, Sookyung; Britt, William J

2016-10-01

Human cytomegalovirus UL99-encoded tegument protein pp28 contains a 16 aa acidic cluster that is required for pp28 trafficking to the assembly compartment (AC) and the virus assembly. However, functional signals within the acidic cluster of pp28 remain undefined. Here, we demonstrated that an acidic cluster rather than specific sorting signals was required for trafficking to the AC. Recombinant viruses with chimeric pp28 proteins expressing non-native acidic clusters exhibited delayed viral growth kinetics and decreased production of infectious virus, indicating that the native acidic cluster of pp28 was essential for wild-type virus assembly. These results suggested that the acidic cluster of pp28 has distinct functional domains required for trafficking and for efficient virus assembly. The first half (aa 44-50) of the acidic cluster was sufficient for pp28 trafficking, whereas the native acidic cluster consisting of aa 51-59 was required for the assembly of wild-type levels of infectious virus.

Recent Insights Into the Prenucleation Cluster Pathway

NASA Astrophysics Data System (ADS)

Gebauer, D.; Kellermeier, M.; Berg, J. K.

2012-12-01

Stable calcium carbonate pre-nucleation clusters (PNCs) form in aqueous solution prior to nucleation of CaCO3 (1). Computer simulations suggest that the thermodynamic stability of PNCs is based upon strong hydration in combination with a distinct entropic contribution (2). In this way, PNCs can compete enthalpically with ion pairs and entropically with amorpous calcium carbonate (ACC). The clue is a high degree of structural disorder in highly dynamic, liquid- and chain-like polymeric structures of calcium carbonate ion pairs (2). Nucleation of solid calcium carbonate from these polymeric species proceeds via PNC aggregation rather than via ion-by-ion additions to un-/metastable nuclei (3). Owing to these basic characteristics, the pre-nucleation cluster pathway has been referred to as "non-classical nucleation" (4). Non-classical nucleation leads to distinct short-range structural features in ACC, and depending on pH they relate to the crystalline long-range order of calcite or vaterite (5). This suggests that calcium carbonate exhibits polyamorphism, and that distinct polyamorphs may play a central role during polymorph selection. In this contribution, we outline the scenario described above, and focus on recent insights into the pre-nucleation cluster pathway. 1. D. Gebauer, A. Völkel & H. Cölfen, Science 322, 1819-1822 (2008). 2. R. Demichelis, P. Raiteri, J.D. Gale, D. Quigley, D. Gebauer, Nat. Commun. 2, 590 (2011). 3. M. Kellermeier et al., Adv. Funct. Mater., DOI: 10.1002/adfm.201200953 (2012). 4. D. Gebauer, H. Cölfen, Nano Today 6, 564-584 (2011). 5. D. Gebauer et al., Angew. Chem. Int. Ed. 49, 8889-8891 (2010).

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.

EClerize: A customized force-directed graph drawing algorithm for biological graphs with EC attributes.

PubMed

Danaci, Hasan Fehmi; Cetin-Atalay, Rengul; Atalay, Volkan

2018-03-26

Visualizing large-scale data produced by the high throughput experiments as a biological graph leads to better understanding and analysis. This study describes a customized force-directed layout algorithm, EClerize, for biological graphs that represent pathways in which the nodes are associated with Enzyme Commission (EC) attributes. The nodes with the same EC class numbers are treated as members of the same cluster. Positions of nodes are then determined based on both the biological similarity and the connection structure. EClerize minimizes the intra-cluster distance, that is the distance between the nodes of the same EC cluster and maximizes the inter-cluster distance, that is the distance between two distinct EC clusters. EClerize is tested on a number of biological pathways and the improvement brought in is presented with respect to the original algorithm. EClerize is available as a plug-in to cytoscape ( http://apps.cytoscape.org/apps/eclerize ).

DNA-Templated Molecular Silver Fluorophores

PubMed Central

Petty, Jeffrey T.; Story, Sandra P.; Hsiang, Jung-Cheng; Dickson, Robert M.

2013-01-01

Conductive and plasmon-supporting noble metals exhibit an especially wide range of size-dependent properties, with discrete electronic levels, strong optical absorption, and efficient radiative relaxation dominating optical behavior at the ~10-atom cluster scale. In this Perspective, we describe the formation and stabilization of silver clusters using DNA templates and highlight the distinct spectroscopic and photophysical properties of the resulting hybrid fluorophores. Strong visible to near-IR emission from DNA-encapsulated silver clusters ranging in size from 5–11 atoms has been produced and characterized. Importantly, this strong Ag cluster fluorescence can be directly modulated and selectively recovered by optically controlling the dark state residence, even when faced with an overwhelming background. The strength and sequence sensitivity of the oligonucleotide-Ag interaction suggests strategies for fine tuning and stabilizing cluster-based emitters in a host of sensing and biolabeling applications that would benefit from brighter, more photostable, and quantifiable emitters in high background environments. PMID:23745165

Public Administration Education in Europe: Continuity or Reorientation?

ERIC Educational Resources Information Center

Hajnal, Gyorgy

2015-01-01

The article explores the changing patterns of disciplinary orientation in European public administration (PA) education. The study builds on an earlier research, which defined three distinct clusters of countries, based on their specific PA education tradition. It asks whether countries' movement away from the Legalist paradigm has continued since…

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…

Profiles of Reactivity in Cocaine-Exposed Children

ERIC Educational Resources Information Center

Schuetze, Pamela; Molnar, Danielle S.; Eiden, Rina D.

2012-01-01

This study explored the possibility that specific, theoretically consistent profiles of reactivity could be identified in a sample of cocaine-exposed infants and whether these profiles were associated with a range of infant and/or maternal characteristics. Cluster analysis was used to identify distinct groups of infants based on physiological,…

Brief Report: Further Evidence of Sensory Subtypes in Autism

ERIC Educational Resources Information Center

Lane, Alison E.; Dennis, Simon J.; Geraghty, Maureen E.

2011-01-01

Distinct sensory processing (SP) subtypes in autism have been reported previously. This study sought to replicate the previous findings in an independent sample of thirty children diagnosed with an Autism Spectrum Disorder. Model-based cluster analysis of parent-reported sensory functioning (measured using the Short Sensory Profile) confirmed the…

pySAPC, a python package for sparse affinity propagation clustering: Application to odontogenesis whole genome time series gene-expression data.

PubMed

Cao, Huojun; Amendt, Brad A

2016-11-01

Developmental dental anomalies are common forms of congenital defects. The molecular mechanisms of dental anomalies are poorly understood. Systematic approaches such as clustering genes based on similar expression patterns could identify novel genes involved in dental anomalies and provide a framework for understanding molecular regulatory mechanisms of these genes during tooth development (odontogenesis). A python package (pySAPC) of sparse affinity propagation clustering algorithm for large datasets was developed. Whole genome pair-wise similarity was calculated based on expression pattern similarity based on 45 microarrays of several stages during odontogenesis. pySAPC identified 743 gene clusters based on expression pattern similarity during mouse tooth development. Three clusters are significantly enriched for genes associated with dental anomalies (with FDR <0.1). The three clusters of genes have distinct expression patterns during odontogenesis. Clustering genes based on similar expression profiles recovered several known regulatory relationships for genes involved in odontogenesis, as well as many novel genes that may be involved with the same genetic pathways as genes that have already been shown to contribute to dental defects. By using sparse similarity matrix, pySAPC use much less memory and CPU time compared with the original affinity propagation program that uses a full similarity matrix. This python package will be useful for many applications where dataset(s) are too large to use full similarity matrix. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016. Published by Elsevier B.V.

Identifying eating behavior phenotypes and their correlates: A novel direction toward improving weight management interventions.

PubMed

Bouhlal, Sofia; McBride, Colleen M; Trivedi, Niraj S; Agurs-Collins, Tanya; Persky, Susan

2017-04-01

Common reports of over-response to food cues, difficulties with calorie restriction, and difficulty adhering to dietary guidelines suggest that eating behaviors could be interrelated in ways that influence weight management efforts. The feasibility of identifying robust eating phenotypes (showing face, content, and criterion validity) was explored based on well-validated individual eating behavior assessments. Adults (n = 260; mean age 34 years) completed online questionnaires with measurements of nine eating behaviors including: appetite for palatable foods, binge eating, bitter taste sensitivity, disinhibition, food neophobia, pickiness and satiety responsiveness. Discovery-based visualization procedures that have the combined strengths of heatmaps and hierarchical clustering were used to investigate: 1) how eating behaviors cluster, 2) how participants can be grouped within eating behavior clusters, and 3) whether group clustering is associated with body mass index (BMI) and dietary self-efficacy levels. Two distinct eating behavior clusters and participant groups that aligned within these clusters were identified: one with higher drive to eat and another with food avoidance behaviors. Participants' BMI (p = 0.0002) and dietary self-efficacy (p < 0.0001) were associated with cluster membership. Eating behavior clusters showed content and criterion validity based on their association with BMI (associated, but not entirely overlapping) and dietary self-efficacy. Identifying eating behavior phenotypes appears viable. These efforts could be expanded and ultimately inform tailored weight management interventions. Published by Elsevier Ltd.

Automatic identification of the number of food items in a meal using clustering techniques based on the monitoring of swallowing and chewing.

PubMed

Lopez-Meyer, Paulo; Schuckers, Stephanie; Makeyev, Oleksandr; Fontana, Juan M; Sazonov, Edward

2012-09-01

The number of distinct foods consumed in a meal is of significant clinical concern in the study of obesity and other eating disorders. This paper proposes the use of information contained in chewing and swallowing sequences for meal segmentation by food types. Data collected from experiments of 17 volunteers were analyzed using two different clustering techniques. First, an unsupervised clustering technique, Affinity Propagation (AP), was used to automatically identify the number of segments within a meal. Second, performance of the unsupervised AP method was compared to a supervised learning approach based on Agglomerative Hierarchical Clustering (AHC). While the AP method was able to obtain 90% accuracy in predicting the number of food items, the AHC achieved an accuracy >95%. Experimental results suggest that the proposed models of automatic meal segmentation may be utilized as part of an integral application for objective Monitoring of Ingestive Behavior in free living conditions.

Distinct subtypes of behavioral-variant frontotemporal dementia based on patterns of network degeneration

PubMed Central

Ranasinghe, Kamalini G; Rankin, Katherine P; Pressman, Peter S; Perry, David C; Lobach, Iryna V; Seeley, William W; Coppola, Giovanni; Karydas, Anna M; Grinberg, Lea T; Shany-Ur, Tal; Lee, Suzee E; Rabinovici, Gil D; Rosen, Howard J; Gorno-Tempini, Maria Luisa; Boxer, Adam L; Miller, Zachary A; Chiong, Winston; DeMay, Mary; Kramer, Joel H; Possin, Katherine L; Sturm, Virginia E; Bettcher, Brianne M; Neylan, Michael; Zackey, Diana D; Nguyen, Lauren A; Ketelle, Robin; Block, Nikolas; Wu, Teresa Q; Dallich, Alison; Russek, Natanya; Caplan, Alyssa; Geschwind, Daniel H; Vossel, Keith A; Miller, Bruce L

2016-01-01

Importance Clearer delineation of the phenotypic heterogeneity within behavioral variant frontotemporal dementia (bvFTD) will help uncover underlying biological mechanisms, and will improve clinicians’ ability to predict disease course and design targeted management strategies. Objective To identify subtypes of bvFTD syndrome based on distinctive patterns of atrophy defined by selective vulnerability of specific functional networks targeted in bvFTD, using statistical classification approaches. Design, Setting and Participants In this retrospective observational study, 104 patients meeting the Frontotemporal Dementia Consortium consensus criteria for bvFTD were evaluated at the Memory and Aging Center of Department of Neurology at University of California, San Francisco. Patients underwent a multidisciplinary clinical evaluation, including clinical demographics, genetic testing, symptom evaluation, neurological exam, neuropsychological bedside testing, and socioemotional assessments. Ninety patients underwent structural Magnetic Resonance Imaging at their earliest evaluation at the memory clinic. From each patients’ structural imaging, the mean volumes of 18 regions of interest (ROI) comprising the functional networks specifically vulnerable in bvFTD, including the ‘salience network’ (SN), with key nodes in the frontoinsula and pregenual anterior cingulate, and the ‘semantic appraisal network’ (SAN) anchored in the anterior temporal lobe and subgenual cingulate, were estimated. Principal component and cluster analyses of ROI volumes were used to identify patient clusters with anatomically distinct atrophy patterns. Main Outcome Measures We evaluated brain morphology and other clinical features including presenting symptoms, neurologic exam signs, neuropsychological performance, rate of dementia progression, and socioemotional function in each patient cluster. Results We identified four subgroups of bvFTD patients with distinct anatomic patterns of network degeneration, including two separate salience network–predominant subgroups: frontal/temporal (SN-FT), and frontal (SN-F), and a semantic appraisal network–predominant group (SAN), and a subcortical–predominant group. Subgroups demonstrated distinct patterns of cognitive, socioemotional, and motor symptoms, as well as genetic compositions and estimated rates of disease progression. Conclusions Divergent patterns of vulnerability in specific functional network components make an important contribution to clinical heterogeneity of bvFTD. The data-driven anatomical classification identifies biologically meaningful phenotypes and provides a replicable approach to disambiguate the bvFTD syndrome. PMID:27429218

The fine-scale genetic structure and evolution of the Japanese population

PubMed Central

Katsuya, Tomohiro; Kimura, Ryosuke; Nabika, Toru; Isomura, Minoru; Ohkubo, Takayoshi; Tabara, Yasuharu; Yamamoto, Ken; Yokota, Mitsuhiro; Liu, Xuanyao; Saw, Woei-Yuh; Mamatyusupu, Dolikun; Yang, Wenjun; Xu, Shuhua

2017-01-01

The contemporary Japanese populations largely consist of three genetically distinct groups—Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics. PMID:29091727

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

PubMed

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

2014-03-01

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

Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm.

PubMed

Kamali, Tahereh; Stashuk, Daniel

2016-10-01

Robust and accurate segmentation of brain white matter (WM) fiber bundles assists in diagnosing and assessing progression or remission of neuropsychiatric diseases such as schizophrenia, autism and depression. Supervised segmentation methods are infeasible in most applications since generating gold standards is too costly. Hence, there is a growing interest in designing unsupervised methods. However, most conventional unsupervised methods require the number of clusters be known in advance which is not possible in most applications. The purpose of this study is to design an unsupervised segmentation algorithm for brain white matter fiber bundles which can automatically segment fiber bundles using intrinsic diffusion tensor imaging data information without considering any prior information or assumption about data distributions. Here, a new density based clustering algorithm called neighborhood distance entropy consistency (NDEC), is proposed which discovers natural clusters within data by simultaneously utilizing both local and global density information. The performance of NDEC is compared with other state of the art clustering algorithms including chameleon, spectral clustering, DBSCAN and k-means using Johns Hopkins University publicly available diffusion tensor imaging data. The performance of NDEC and other employed clustering algorithms were evaluated using dice ratio as an external evaluation criteria and density based clustering validation (DBCV) index as an internal evaluation metric. Across all employed clustering algorithms, NDEC obtained the highest average dice ratio (0.94) and DBCV value (0.71). NDEC can find clusters with arbitrary shapes and densities and consequently can be used for WM fiber bundle segmentation where there is no distinct boundary between various bundles. NDEC may also be used as an effective tool in other pattern recognition and medical diagnostic systems in which discovering natural clusters within data is a necessity. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification of Neuropsychiatric Symptoms Requiring Antipsychotic Treatment in Patients with Alzheimer's Disease: Analysis of the CATIE-AD Study.

PubMed

Nagata, Tomoyuki; Shinagawa, Shunichiro; Nakajima, Shinichiro; Plitman, Eric; Mihashi, Yukiko; Hayashi, Shogo; Mimura, Masaru; Nakayama, Kazuhiko

2016-01-01

The Neuropsychiatric Inventory (NPI) comprises 12 items, which were conventionally determined by psychopathological symptoms of patients with dementia. The clinical rating scales with structured questionnaires have been useful to evaluate neuropsychiatric symptoms (NPSs) of patients with dementia over the past twenty year. The aim of this study was to classify the conventional NPSs in patients with Alzheimer's disease (AD) requiring antipsychotic treatment for their NPSs into distinct clusters to simplify assessment of these numerous symptoms. Twelve items scores (product of severity and frequency of each symptom) in the NPI taken from the baseline visit were classified into subgroups by principle component analysis using data from 421 outpatients with AD enrolled in the Clinical Antipsychotic Trials of Intervention Effectiveness-Alzheimer's Disease (CATIE-AD) Phase 1. Chi square tests were conducted to examine the co-occurrence of the subgroups. We found four distinct clusters: aggressiveness (agitation and irritabilities), apathy and eating problems (apathy and appetite/eating disturbance), psychosis (delusions and hallucinations), and emotion and disinhibition (depression, euphoria, and disinhibition). Anxiety, aberrant motor behavior, and sleep disturbance were not included by these clusters. Apathy and eating problems, and emotion and disinhibition co-occurred (p = 0.002), whereas aggressiveness and psychosis occurred independent of the other clusters. Four distinct category clusters were identified from NPSs in patients with AD requiring antipsychotic treatment. Future studies should investigate psychosocial backgrounds or risk factors of each distinct cluster, in addition to their longitudinal course over treatment intervention.

Psychosocial Costs of Racism to Whites: Exploring Patterns through Cluster Analysis

ERIC Educational Resources Information Center

Spanierman, Lisa B.; Poteat, V. Paul; Beer, Amanda M.; Armstrong, Patrick Ian

2006-01-01

Participants (230 White college students) completed the Psychosocial Costs of Racism to Whites (PCRW) Scale. Using cluster analysis, we identified 5 distinct cluster groups on the basis of PCRW subscale scores: the unempathic and unaware cluster contained the lowest empathy scores; the insensitive and afraid cluster consisted of low empathy and…

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

PubMed Central

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

2017-01-01

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

Infrared detection of (H 2O) 20 isomers of exceptional stability: A drop-like and a face-sharing pentagonal prism cluster

DOE PAGES

Pradzynski, Christoph C.; Dierking, Christoph W.; Zurheide, Florian; ...

2014-09-01

Water clusters containing fully coordinated water molecules are model systems that mimic the local environment of the condensed phase. Present knowledge about the water cluster size regime in which the transition from the allsurface to the fully solvated water molecules occurs is mainly based on theoretical predictions in lieu of the absence of precisely size resolved experimental measurements. Here, we report size and isomer selective infrared (IR) spectra of (H 2O) 20 clusters tagged with a sodium atom by employing IR excitation modulated photoionization spectroscopy. The observed absorption patterns in the OH stretching ”fingerprint” region are consistent with the theoreticallymore » predicted spectra of two structurally distinct isomers: A drop-like cluster with a fully coordinated (interior) water and an edge-sharing pentagonal prism cluster in which all atoms are on the surface. The observed isomers show exceptional stability and are predicted to be nearly isoenergetic.« less

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).

Deconvolving the Fate of Carbon in Coastal Sediments

NASA Astrophysics Data System (ADS)

Van der Voort, Tessa S.; Mannu, Utsav; Blattmann, Thomas M.; Bao, Rui; Zhao, Meixun; Eglinton, Timothy I.

2018-05-01

Coastal oceans play a crucial role in the global carbon cycle, and are increasingly affected by anthropogenic forcing. Understanding carbon cycling in coastal environments is hindered by convoluted sources and myriad processes that vary over a range of spatial and temporal scales. In this study, we deconvolve the complex mosaic of organic carbon manifested in Chinese Marginal Sea (CMS) sediments using a novel numerical clustering algorithm based on 14C and total OC content. Results reveal five regions that encompass geographically distinct depositional settings. Complementary statistical analyses reveal contrasting region-dependent controls on carbon dynamics and composition. Overall, clustering is shown to be highly effective in demarcating areas of distinct organic facies by disentangling intertwined organic geochemical patterns resulting from superimposed effects of OC provenance, reworking and deposition on a shelf region exhibiting pronounced spatial heterogeneity. This information will aid in constraining region-specific budgets of carbon burial and carbon cycle processes.

Analysis of the nutritional status of algae by Fourier transform infrared chemical imaging

NASA Astrophysics Data System (ADS)

Hirschmugl, Carol J.; Bayarri, Zuheir-El; Bunta, Maria; Holt, Justin B.; Giordano, Mario

2006-09-01

A new non-destructive method to study the nutritional status of algal cells and their environments is demonstrated. This approach allows rapid examination of whole cells without any or little pre-treatment providing a large amount of information on the biochemical composition of cells and growth medium. The method is based on the analysis of a collection of infrared (IR) spectra for individual cells; each spectrum describes the biochemical composition of a portion of a cell; a complete set of spectra is used to reconstruct an image of the entire cell. To obtain spatially resolved information synchrotron radiation was used as a bright IR source. We tested this method on the green flagellate Euglena gracilis; a comparison was conducted between cells grown in nutrient replete conditions (Type 1) and on cells allowed to deplete their medium (Type 2). Complete sets of spectra for individual cells of both types were analyzed with agglomerative hierarchical clustering, leading to distinct clusters representative of the two types of cells. The average spectra for the clusters confirmed the similarities between the clusters and the types of cells. The clustering analysis, therefore, allows the distinction of cells of the same species, but with different nutritional histories. In order to facilitate the application of the method and reduce manipulation (washing), we analyzed the cells in the presence of residual medium. The results obtained showed that even with residual medium the outcome of the clustering analysis is reliable. Our results demonstrate the applicability FTIR microspectroscopy for ecological and ecophysiological studies.

Different disease subtypes with distinct clinical expression in familial Mediterranean fever: results of a cluster analysis.

PubMed

Akar, Servet; Solmaz, Dilek; Kasifoglu, Timucin; Bilge, Sule Yasar; Sari, Ismail; Gumus, Zeynep Zehra; Tunca, Mehmet

2016-02-01

The aim of this study was to evaluate whether there are clinical subgroups that may have different prognoses among FMF patients. The cumulative clinical features of a large group of FMF patients [1168 patients, 593 (50.8%) male, mean age 35.3 years (s.d. 12.4)] were studied. To analyse our data and identify groups of FMF patients with similar clinical characteristics, a two-step cluster analysis using log-likelihood distance measures was performed. For clustering the FMF patients, we evaluated the following variables: gender, current age, age at symptom onset, age at diagnosis, presence of major clinical features, variables related with therapy and family history for FMF, renal failure and carriage of M694V. Three distinct groups of FMF patients were identified. Cluster 1 was characterized by a high prevalence of arthritis, pleuritis, erysipelas-like erythema (ELE) and febrile myalgia. The dosage of colchicine and the frequency of amyloidosis were lower in cluster 1. Patients in cluster 2 had an earlier age of disease onset and diagnosis. M694V carriage and amyloidosis prevalence were the highest in cluster 2. This group of patients was using the highest dose of colchicine. Patients in cluster 3 had the lowest prevalence of arthritis, ELE and febrile myalgia. The frequencies of M694V carriage and amyloidosis were lower in cluster 3 than the overall FMF patients. Non-response to colchicine was also slightly lower in cluster 3. Patients with FMF can be clustered into distinct patterns of clinical and genetic manifestations and these patterns may have different prognostic significance. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Spatial and kinematic distributions of transition populations in intermediate redshift galaxy clusters

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

Crawford, Steven M.; Wirth, Gregory D.; Bershady, Matthew A., E-mail: crawford@saao.ac.za, E-mail: wirth@keck.hawaii.edu, E-mail: mab@astro.wisc.edu

2014-05-01

We analyze the spatial and velocity distributions of confirmed members in five massive clusters of galaxies at intermediate redshift (0.5 < z < 0.9) to investigate the physical processes driving galaxy evolution. Based on spectral classifications derived from broad- and narrow-band photometry, we define four distinct galaxy populations representing different evolutionary stages: red sequence (RS) galaxies, blue cloud (BC) galaxies, green valley (GV) galaxies, and luminous compact blue galaxies (LCBGs). For each galaxy class, we derive the projected spatial and velocity distribution and characterize the degree of subclustering. We find that RS, BC, and GV galaxies in these clusters havemore » similar velocity distributions, but that BC and GV galaxies tend to avoid the core of the two z ≈ 0.55 clusters. GV galaxies exhibit subclustering properties similar to RS galaxies, but their radial velocity distribution is significantly platykurtic compared to the RS galaxies. The absence of GV galaxies in the cluster cores may explain their somewhat prolonged star-formation history. The LCBGs appear to have recently fallen into the cluster based on their larger velocity dispersion, absence from the cores of the clusters, and different radial velocity distribution than the RS galaxies. Both LCBG and BC galaxies show a high degree of subclustering on the smallest scales, leading us to conclude that star formation is likely triggered by galaxy-galaxy interactions during infall into the cluster.« less

Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

NASA Astrophysics Data System (ADS)

Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

2014-12-01

Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers.

PubMed

Tomassen, Peter; Vandeplas, Griet; Van Zele, Thibaut; Cardell, Lars-Olaf; Arebro, Julia; Olze, Heidi; Förster-Ruhrmann, Ulrike; Kowalski, Marek L; Olszewska-Ziąber, Agnieszka; Holtappels, Gabriele; De Ruyck, Natalie; Wang, Xiangdong; Van Drunen, Cornelis; Mullol, Joaquim; Hellings, Peter; Hox, Valerie; Toskala, Elina; Scadding, Glenis; Lund, Valerie; Zhang, Luo; Fokkens, Wytske; Bachert, Claus

2016-05-01

Current phenotyping of chronic rhinosinusitis (CRS) into chronic rhinosinusitis with nasal polyps (CRSwNP) and chronic rhinosinusitis without nasal polyps (CRSsNP) might not adequately reflect the pathophysiologic diversity within patients with CRS. We sought to identify inflammatory endotypes of CRS. Therefore we aimed to cluster patients with CRS based solely on immune markers in a phenotype-free approach. Secondarily, we aimed to match clusters to phenotypes. In this multicenter case-control study patients with CRS and control subjects underwent surgery, and tissue was analyzed for IL-5, IFN-γ, IL-17A, TNF-α, IL-22, IL-1β, IL-6, IL-8, eosinophilic cationic protein, myeloperoxidase, TGF-β1, IgE, Staphylococcus aureus enterotoxin-specific IgE, and albumin. We used partition-based clustering. Clustering of 173 cases resulted in 10 clusters, of which 4 clusters with low or undetectable IL-5, eosinophilic cationic protein, IgE, and albumin concentrations, and 6 clusters with high concentrations of those markers. The group of IL-5-negative clusters, 3 clusters clinically resembled a predominant chronic rhinosinusitis without nasal polyps (CRSsNP) phenotype without increased asthma prevalence, and 1 cluster had a TH17 profile and had mixed CRSsNP/CRSwNP. The IL-5-positive clusters were divided into a group with moderate IL-5 concentrations, a mixed CRSsNP/CRSwNP and increased asthma phenotype, and a group with high IL-5 levels, an almost exclusive nasal polyp phenotype with strongly increased asthma prevalence. In the latter group, 2 clusters demonstrated the highest concentrations of IgE and asthma prevalence, with all samples expressing Staphylococcus aureus enterotoxin-specific IgE. Distinct CRS clusters with diverse inflammatory mechanisms largely correlated with phenotypes and further differentiated them and provided a more accurate description of the inflammatory mechanisms involved than phenotype information only. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Response to traumatic brain injury neurorehabilitation through an artificial intelligence and statistics hybrid knowledge discovery from databases methodology.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; García-Molina, Alberto; Roig-Rovira, Teresa; Bernabeu, Montse; Tormos, José María

2008-01-01

Develop a classificatory tool to identify different populations of patients with Traumatic Brain Injury based on the characteristics of deficit and response to treatment. A KDD framework where first, descriptive statistics of every variable was done, data cleaning and selection of relevant variables. Then data was mined using a generalization of Clustering based on rules (CIBR), an hybrid AI and Statistics technique which combines inductive learning (AI) and clustering (Statistics). A prior Knowledge Base (KB) is considered to properly bias the clustering; semantic constraints implied by the KB hold in final clusters, guaranteeing interpretability of the resultis. A generalization (Exogenous Clustering based on rules, ECIBR) is presented, allowing to define the KB in terms of variables which will not be considered in the clustering process itself, to get more flexibility. Several tools as Class panel graph are introduced in the methodology to assist final interpretation. A set of 5 classes was recommended by the system and interpretation permitted profiles labeling. From the medical point of view, composition of classes is well corresponding with different patterns of increasing level of response to rehabilitation treatments. All the patients initially assessable conform a single group. Severe impaired patients are subdivided in four profiles which clearly distinct response patterns. Particularly interesting the partial response profile, where patients could not improve executive functions. Meaningful classes were obtained and, from a semantics point of view, the results were sensibly improved regarding classical clustering, according to our opinion that hybrid AI & Stats techniques are more powerful for KDD than pure ones.

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

PubMed

Zhang, Xianchang; Cheng, Hewei; Zuo, Zhentao; Zhou, Ke; Cong, Fei; Wang, Bo; Zhuo, Yan; Chen, Lin; Xue, Rong; Fan, Yong

2018-01-01

The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo . In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

A Comparison of Classification Approaches for Cyberbullying and Traditional Bullying Using Data from Six European Countries

ERIC Educational Resources Information Center

Schultze-Krumbholz, Anja; Göbel, Kristin; Scheithauer, Herbert; Brighi, Antonella; Guarini, Annalisa; Tsorbatzoudis, Haralambos; Barkoukis, Vassilis; Pyzalski, Jacek; Plichta, Piotr; Del Rey, Rosario; Casas, José A.; Thompson, Fran; Smith, Peter K.

2015-01-01

In recently published studies on cyberbullying, students are frequently categorized into distinct (cyber)bully and (cyber)victim clusters based on theoretical assumptions and arbitrary cut-off scores adapted from traditional bullying research. The present study identified involvement classes empirically using latent class analysis (LCA), to…

Assessment of sediment quality in the Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia): GIS approach-based chemometric methods.

PubMed

Kharroubi, Adel; Gargouri, Dorra; Baati, Houda; Azri, Chafai

2012-06-01

Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I (geo)) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments.

Generalization of Clustering Coefficients to Signed Correlation Networks

PubMed Central

Costantini, Giulio; Perugini, Marco

2014-01-01

The recent interest in network analysis applications in personality psychology and psychopathology has put forward new methodological challenges. Personality and psychopathology networks are typically based on correlation matrices and therefore include both positive and negative edge signs. However, some applications of network analysis disregard negative edges, such as computing clustering coefficients. In this contribution, we illustrate the importance of the distinction between positive and negative edges in networks based on correlation matrices. The clustering coefficient is generalized to signed correlation networks: three new indices are introduced that take edge signs into account, each derived from an existing and widely used formula. The performances of the new indices are illustrated and compared with the performances of the unsigned indices, both on a signed simulated network and on a signed network based on actual personality psychology data. The results show that the new indices are more resistant to sample variations in correlation networks and therefore have higher convergence compared with the unsigned indices both in simulated networks and with real data. PMID:24586367

Genetic relatedness among indigenous rice varieties in the Eastern Himalayan region based on nucleotide sequences of the Waxy gene.

PubMed

Choudhury, Baharul I; Khan, Mohammed L; Dayanandan, Selvadurai

2014-12-29

Indigenous rice varieties in the Eastern Himalayan region of Northeast India are traditionally classified into sali, boro and jum ecotypes based on geographical locality and the season of cultivation. In this study, we used DNA sequence data from the Waxy (Wx) gene to infer the genetic relatedness among indigenous rice varieties in Northeast India and to assess the genetic distinctiveness of ecotypes. The results of all three analyses (Bayesian, Maximum Parsimony and Neighbor Joining) were congruent and revealed two genetically distinct clusters of rice varieties in the region. The large group comprised several varieties of sali and boro ecotypes, and all agronomically improved varieties. The small group consisted of only traditionally cultivated indigenous rice varieties, which included one boro, few sali and all jum varieties. The fixation index analysis revealed a very low level of differentiation between sali and boro (F(ST) = 0.005), moderate differentiation between sali and jum (F(ST) = 0.108) and high differentiation between jum and boro (F(ST) = 0.230) ecotypes. The genetic relatedness analyses revealed that sali, boro and jum ecotypes are genetically heterogeneous, and the current classification based on cultivation type is not congruent with the genetic background of rice varieties. Indigenous rice varieties chosen from genetically distinct clusters could be used in breeding programs to improve genetic gain through heterosis, while maintaining high genetic diversity.

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

USGS Publications Warehouse

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

2018-01-01

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

Genetic diversity of Leishmania donovani that causes cutaneous leishmaniasis in Sri Lanka: a cross sectional study with regional comparisons.

PubMed

Kariyawasam, Udeshika Lakmini; Selvapandiyan, Angamuthu; Rai, Keshav; Wani, Tasaduq Hussain; Ahuja, Kavita; Beg, Mizra Adil; Premathilake, Hasitha Upendra; Bhattarai, Narayan Raj; Siriwardena, Yamuna Deepani; Zhong, Daibin; Zhou, Guofa; Rijal, Suman; Nakhasi, Hira; Karunaweera, Nadira D

2017-12-22

Leishmania donovani is the etiological agent of visceral leishmaniasis (VL) in the Indian subcontinent. However, it is also known to cause cutaneous leishmaniasis (CL) in Sri Lanka. Sri Lankan L. donovani differs from other L. donovani strains, both at the molecular and biochemical level. To investigate the different species or strain-specific differences of L. donovani in Sri Lanka we evaluated sequence variation of the kinetoplastid DNA (kDNA). Parasites isolated from skin lesions of 34 CL patients and bone marrow aspirates from 4 VL patients were genotyped using the kDNA minicircle PCR analysis. A total of 301 minicircle sequences that included sequences from Sri Lanka, India, Nepal and six reference species of Leishmania were analyzed. Haplotype diversity of Sri Lankan isolates were high (H d  = 0.757) with strong inter-geographical genetic differentiation (F ST  > 0.25). In this study, L. donovani isolates clustered according to their geographic origin, while Sri Lankan isolates formed a separate cluster and were clearly distinct from other Leishmania species. Within the Sri Lankan group, there were three distinct sub-clusters formed, from CL patients who responded to standard antimony therapy, CL patients who responded poorly to antimony therapy and from VL patients. There was no specific clustering of sequences based on geographical origin within Sri Lanka. This study reveals high levels of haplotype diversity of L. donovani in Sri Lanka with a distinct genetic association with clinically relevant phenotypic characteristics. The use of genetic tools to identify clinically relevant features of Leishmania parasites has important therapeutic implications for leishmaniasis.

Corticostriatal connectivity fingerprints: Probability maps based on resting-state functional connectivity.

PubMed

Jaspers, Ellen; Balsters, Joshua H; Kassraian Fard, Pegah; Mantini, Dante; Wenderoth, Nicole

2017-03-01

Over the last decade, structure-function relationships have begun to encompass networks of brain areas rather than individual structures. For example, corticostriatal circuits have been associated with sensorimotor, limbic, and cognitive information processing, and damage to these circuits has been shown to produce unique behavioral outcomes in Autism, Parkinson's Disease, Schizophrenia and healthy ageing. However, it remains an open question how abnormal or absent connectivity can be detected at the individual level. Here, we provide a method for clustering gross morphological structures into subregions with unique functional connectivity fingerprints, and generate network probability maps usable as a baseline to compare individual cases against. We used connectivity metrics derived from resting-state fMRI (N = 100), in conjunction with hierarchical clustering methods, to parcellate the striatum into functionally distinct clusters. We identified three highly reproducible striatal subregions, across both hemispheres and in an independent replication dataset (N = 100) (dice-similarity values 0.40-1.00). Each striatal seed region resulted in a highly reproducible distinct connectivity fingerprint: the putamen showed predominant connectivity with cortical and cerebellar sensorimotor and language processing areas; the ventromedial striatum cluster had a distinct limbic connectivity pattern; the caudate showed predominant connectivity with the thalamus, frontal and occipital areas, and the cerebellum. Our corticostriatal probability maps agree with existing connectivity data in humans and non-human primates, and showed a high degree of replication. We believe that these maps offer an efficient tool to further advance hypothesis driven research and provide important guidance when investigating deviant connectivity in neurological patient populations suffering from e.g., stroke or cerebral palsy. Hum Brain Mapp 38:1478-1491, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Use of Conserved Randomly Amplified Polymorphic DNA (RAPD) Fragments and RAPD Pattern for Characterization of Lactobacillus fermentum in Ghanaian Fermented Maize Dough

PubMed Central

Hayford, Alice E.; Petersen, Anne; Vogensen, Finn K.; Jakobsen, Mogens

1999-01-01

The present work describes the use of randomly amplified polymorphic DNA (RAPD) for the characterization of 172 dominant Lactobacillus isolates from present and previous studies of Ghanaian maize fermentation. Heterofermentative lactobacilli dominate the fermentation flora, since approximately 85% of the isolates belong to this group. Cluster analysis of the RAPD profiles obtained showed the presence of two main clusters. Cluster 1 included Lactobacillus fermentum, whereas cluster 2 comprised the remaining Lactobacillus spp. The two distinct clusters emerged at the similarity level of <50%. All isolates in cluster 1 showed similarity in their RAPD profile to the reference strains of L. fermentum included in the study. These isolates, yielding two distinct bands of approximately 695 and 773 bp with the primers used, were divided into four subclusters, indicating that several strains are involved in the fermentation and remain dominant throughout the process. The two distinct RAPD fragments were cloned, sequenced, and used as probes in Southern hybridization experiments. With one exception, Lactobacillus reuteri LMG 13045, the probes hybridized only to fragments of different sizes in EcoRI-digested chromosomal DNA of L. fermentum strains, thus indicating the specificity of the probes and variation within the L. fermentum isolates. PMID:10388723

Cluster Analysis Identifies Distinct Pathogenetic Patterns in C3 Glomerulopathies/Immune Complex-Mediated Membranoproliferative GN.

PubMed

Iatropoulos, Paraskevas; Daina, Erica; Curreri, Manuela; Piras, Rossella; Valoti, Elisabetta; Mele, Caterina; Bresin, Elena; Gamba, Sara; Alberti, Marta; Breno, Matteo; Perna, Annalisa; Bettoni, Serena; Sabadini, Ettore; Murer, Luisa; Vivarelli, Marina; Noris, Marina; Remuzzi, Giuseppe

2018-01-01

Membranoproliferative GN (MPGN) was recently reclassified as alternative pathway complement-mediated C3 glomerulopathy (C3G) and immune complex-mediated membranoproliferative GN (IC-MPGN). However, genetic and acquired alternative pathway abnormalities are also observed in IC-MPGN. Here, we explored the presence of distinct disease entities characterized by specific pathophysiologic mechanisms. We performed unsupervised hierarchical clustering, a data-driven statistical approach, on histologic, genetic, and clinical data and data regarding serum/plasma complement parameters from 173 patients with C3G/IC-MPGN. This approach divided patients into four clusters, indicating the existence of four different pathogenetic patterns. Specifically, this analysis separated patients with fluid-phase complement activation (clusters 1-3) who had low serum C3 levels and a high prevalence of genetic and acquired alternative pathway abnormalities from patients with solid-phase complement activation (cluster 4) who had normal or mildly altered serum C3, late disease onset, and poor renal survival. In patients with fluid-phase complement activation, those in clusters 1 and 2 had massive activation of the alternative pathway, including activation of the terminal pathway, and the highest prevalence of subendothelial deposits, but those in cluster 2 had additional activation of the classic pathway and the highest prevalence of nephrotic syndrome at disease onset. Patients in cluster 3 had prevalent activation of C3 convertase and highly electron-dense intramembranous deposits. In addition, we provide a simple algorithm to assign patients with C3G/IC-MPGN to specific clusters. These distinct clusters may facilitate clarification of disease etiology, improve risk assessment for ESRD, and pave the way for personalized treatment. Copyright © 2018 by the American Society of Nephrology.

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.

Observational Evidence for a Dark Side to NGC 5128's Globular Cluster System

NASA Astrophysics Data System (ADS)

Taylor, Matthew A.; Puzia, Thomas H.; Gomez, Matias; Woodley, Kristin A.

2015-05-01

We present a study of the dynamical properties of 125 compact stellar systems (CSSs) in the nearby giant elliptical galaxy NGC 5128, using high-resolution spectra (R ≈ 26, 000) obtained with Very Large Telescope/FLAMES. Our results provide evidence for a new type of star cluster, based on the CSS dynamical mass scaling relations. All radial velocity (vr) and line-of-sight velocity dispersion (σlos) measurements are performed with the penalized pixel fitting (ppxf ) technique, which provided σppxf estimates for 115 targets. The σppxf estimates are corrected to the 2D projected half-light radii, σ1/2, as well as the cluster cores, σ0, accounting for observational/aperture effects and are combined with structural parameters, from high spatial resolution imaging, in order to derive total dynamical masses ({{M}dyn}) for 112 members of NGC 5128’s star cluster system. In total, 89 CSSs have dynamical masses measured for the first time along with the corresponding dynamical mass-to-light ratios (\\Upsilon Vdyn). We find two distinct sequences in the \\Upsilon Vdyn-{{M}dyn} plane, which are well approximated by power laws of the forms \\Upsilon Vdyn\\propto Mdyn0.33+/- 0.04 and \\Upsilon Vdyn\\propto Mdyn0.79+/- 0.04. The shallower sequence corresponds to the very bright tail of the globular cluster luminosity function (GCLF), while the steeper relation appears to be populated by a distinct group of objects that require significant dark gravitating components such as central massive black holes and/or exotically concentrated dark matter distributions. This result would suggest that the formation and evolution of these CSSs are markedly different from the “classical” globular clusters in NGC 5128 and the Local Group, despite the fact that these clusters have luminosities similar to the GCLF turnover magnitude. We include a thorough discussion of myriad factors potentially influencing our measurements. Based on observations collected under program 081.D-0651 (PI: Matias Gomez) with FLAMES at the Very Large Telescope of the Paranal Observatory in Chile, operated by the ESO.

Segmentation of overweight Americans and opportunities for social marketing

PubMed Central

Kolodinsky, Jane; Reynolds, Travis

2009-01-01

Background The food industry uses market segmentation to target products toward specific groups of consumers with similar attitudinal, demographic, or lifestyle characteristics. Our aims were to identify distinguishable segments within the US overweight population to be targeted with messages and media aimed at moving Americans toward more healthy weights. Methods Cluster analysis was used to identify segments of consumers based on both food and lifestyle behaviors related to unhealthy weights. Drawing from Social Learning Theory, the Health Belief Model, and existing market segmentation literature, the study identified five distinct, recognizable market segments based on knowledge and behavioral and environmental factors. Implications for social marketing campaigns designed to move Americans toward more healthy weights were explored. Results The five clusters identified were: Highest Risk (19%); At Risk (22%); Right Behavior/Wrong Results (33%); Getting Best Results (13%); and Doing OK (12%). Ninety-nine percent of those in the Highest Risk cluster were overweight; members watched the most television and exercised the least. Fifty-five percent of those in the At Risk cluster were overweight; members logged the most computer time and almost half rarely or never read food labels. Sixty-six percent of those in the Right Behavior/Wrong Results cluster were overweight; however, 95% of them were familiar with the food pyramid. Members reported eating a low percentage of fast food meals (8%) compared to other groups but a higher percentage of other restaurant meals (15%). Less than six percent of those in the Getting Best Results cluster were overweight; every member read food labels and 75% of members' meals were "made from scratch." Eighteen percent of those in the Doing OK cluster were overweight; members watched the least television and reported eating 78% of their meals "made from scratch." Conclusion This study demonstrated that five distinct market segments can be identified for social marketing efforts aimed at addressing the obesity epidemic. Through the identification of these five segments, social marketing campaigns can utilize selected channels and messages that communicate the most relevant and important information. The results of this study offer insight into how segmentation strategies and social marketing messages may improve public health. PMID:19267936

Segmentation of overweight Americans and opportunities for social marketing.

PubMed

Kolodinsky, Jane; Reynolds, Travis

2009-03-08

The food industry uses market segmentation to target products toward specific groups of consumers with similar attitudinal, demographic, or lifestyle characteristics. Our aims were to identify distinguishable segments within the US overweight population to be targeted with messages and media aimed at moving Americans toward more healthy weights. Cluster analysis was used to identify segments of consumers based on both food and lifestyle behaviors related to unhealthy weights. Drawing from Social Learning Theory, the Health Belief Model, and existing market segmentation literature, the study identified five distinct, recognizable market segments based on knowledge and behavioral and environmental factors. Implications for social marketing campaigns designed to move Americans toward more healthy weights were explored. The five clusters identified were: Highest Risk (19%); At Risk (22%); Right Behavior/Wrong Results (33%); Getting Best Results (13%); and Doing OK (12%). Ninety-nine percent of those in the Highest Risk cluster were overweight; members watched the most television and exercised the least. Fifty-five percent of those in the At Risk cluster were overweight; members logged the most computer time and almost half rarely or never read food labels. Sixty-six percent of those in the Right Behavior/Wrong Results cluster were overweight; however, 95% of them were familiar with the food pyramid. Members reported eating a low percentage of fast food meals (8%) compared to other groups but a higher percentage of other restaurant meals (15%). Less than six percent of those in the Getting Best Results cluster were overweight; every member read food labels and 75% of members' meals were "made from scratch." Eighteen percent of those in the Doing OK cluster were overweight; members watched the least television and reported eating 78% of their meals "made from scratch." This study demonstrated that five distinct market segments can be identified for social marketing efforts aimed at addressing the obesity epidemic. Through the identification of these five segments, social marketing campaigns can utilize selected channels and messages that communicate the most relevant and important information. The results of this study offer insight into how segmentation strategies and social marketing messages may improve public health.

Estimating metallicities with isochrone fits to photometric data of open clusters

NASA Astrophysics Data System (ADS)

Monteiro, H.; Oliveira, A. F.; Dias, W. S.; Caetano, T. C.

2014-10-01

The metallicity is a critical parameter that affects the correct determination of stellar cluster's fundamental characteristics and has important implications in Galactic and Stellar evolution research. Fewer than 10% of the 2174 currently catalogued open clusters have their metallicity determined in the literature. In this work we present a method for estimating the metallicity of open clusters via non-subjective isochrone fitting using the cross-entropy global optimization algorithm applied to UBV photometric data. The free parameters distance, reddening, age, and metallicity are simultaneously determined by the fitting method. The fitting procedure uses weights for the observational data based on the estimation of membership likelihood for each star, which considers the observational magnitude limit, the density profile of stars as a function of radius from the center of the cluster, and the density of stars in multi-dimensional magnitude space. We present results of [Fe/H] for well-studied open clusters based on distinct UBV data sets. The [Fe/H] values obtained in the ten cases for which spectroscopic determinations were available in the literature agree, indicating that our method provides a good alternative to estimating [Fe/H] by using an objective isochrone fitting. Our results show that the typical precision is about 0.1 dex.

Tri-city study of Ecstasy use problems: a latent class analysis.

PubMed

Scheier, Lawrence M; Ben Abdallah, Arbi; Inciardi, James A; Copeland, Jan; Cottler, Linda B

2008-12-01

This study used latent class analysis to examine distinctive subtypes of Ecstasy users based on 24 abuse and dependence symptoms underlying standard DSM-IV criteria. Data came from a three site, population-based, epidemiological study to examine diagnostic nosology for Ecstasy use. Subject inclusion criteria included lifetime Ecstasy use exceeding five times and once in the past year, with participants ranging in age between 16 and 47 years of age from St. Louis, Miami, U.S. and Sydney, Australia. A satisfactory model typified four latent classes representing clearly differentiated diagnostic clusters including: (1) a group of sub-threshold users endorsing few abuse and dependence symptoms (negatives), (2) a group of 'diagnostic orphans' who had characteristic features of dependence for a select group of symptoms (mild dependent), (3) a 'transitional group' mimicking the orphans with regard to their profile of dependence also but reporting some abuse symptoms (moderate dependent), and (4) a 'severe dependent' group with a distinct profile of abuse and dependence symptoms. A multinomial logistic regression model indicated that certain latent classes showed unique associations with external non-diagnostic markers. Controlling for demographic characteristics and lifetime quantity of Ecstasy pill use, criminal behavior and motivational cues for Ecstasy use were the most efficient predictors of cluster membership. This study reinforces the heuristic utility of DSM-IV criteria applied to Ecstasy but with a different collage of symptoms that produced four distinct classes of Ecstasy users.

Conformational Clusters of Phosphorylated Tyrosine.

PubMed

Abdelrasoul, Maha; Ponniah, Komala; Mao, Alice; Warden, Meghan S; Elhefnawy, Wessam; Li, Yaohang; Pascal, Steven M

2017-12-06

Tyrosine phosphorylation plays an important role in many cellular and intercellular processes including signal transduction, subcellular localization, and regulation of enzymatic activity. In 1999, Blom et al., using the limited number of protein data bank (PDB) structures available at that time, reported that the side chain structures of phosphorylated tyrosine (pY) are partitioned into two conserved conformational clusters ( Blom, N.; Gammeltoft, S.; Brunak, S. J. Mol. Biol. 1999 , 294 , 1351 - 1362 ). We have used the spectral clustering algorithm to cluster the increasingly growing number of protein structures with pY sites, and have found that the pY residues cluster into three distinct side chain conformations. Two of these pY conformational clusters associate strongly with a narrow range of tyrosine backbone conformation. The novel cluster also highly correlates with the identity of the n + 1 residue, and is strongly associated with a sequential pYpY conformation which places two adjacent pY side chains in a specific relative orientation. Further analysis shows that the three pY clusters are associated with distinct distributions of cognate protein kinases.

Clustering of gamma-ray burst types in the Fermi GBM catalogue: indications of photosphere and synchrotron emissions during the prompt phase

NASA Astrophysics Data System (ADS)

Acuner, Zeynep; Ryde, Felix

2018-04-01

Many different physical processes have been suggested to explain the prompt gamma-ray emission in gamma-ray bursts (GRBs). Although there are examples of both bursts with photospheric and synchrotron emission origins, these distinct spectral appearances have not been generalized to large samples of GRBs. Here, we search for signatures of the different emission mechanisms in the full Fermi Gamma-ray Space Telescope/GBM (Gamma-ray Burst Monitor) catalogue. We use Gaussian Mixture Models to cluster bursts according to their parameters from the Band function (α, β, and Epk) as well as their fluence and T90. We find five distinct clusters. We further argue that these clusters can be divided into bursts of photospheric origin (2/3 of all bursts, divided into three clusters) and bursts of synchrotron origin (1/3 of all bursts, divided into two clusters). For instance, the cluster that contains predominantly short bursts is consistent of photospheric emission origin. We discuss several reasons that can determine which cluster a burst belongs to: jet dissipation pattern and/or the jet content, or viewing angle.

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

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

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

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

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

DOE PAGES

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

2017-06-30

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

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

VizieR Online Data Catalog: HST Frontier Fields Herschel sources (Rawle+, 2016)

NASA Astrophysics Data System (ADS)

Rawle, T. D.; Altieri, B.; Egami, E.; Perez-Gonzalez, P. G.; Boone, F.; Clement, B.; Ivison, R. J.; Richard, J.; Rujopakarn, W.; Valtchanov, I.; Walth, G.; Weiner, B. J.; Blain, A. W.; Dessauges-Zavadsky, M.; Kneib, J.-P.; Lutz, D.; Rodighiero, G.; Schaerer, D.; Smail, I.

2017-07-01

We present a complete census of the 263 Herschel-detected sources within the HST Frontier Fields, including 163 lensed sources located behind the clusters. Our primary aim is to provide a robust legacy catalogue of the Herschel fluxes, which we combine with archival data from Spitzer and WISE to produce IR SEDs. We optimally combine the IR photometry with data from HST, VLA and ground-based observatories in order to identify optical counterparts and gain source redshifts. Each cluster is observed in two distinct regions, referred to as the central and parallel footprints. (2 data files).

Evolution of Streptococcus pneumoniae and Its Close Commensal Relatives

PubMed Central

Kilian, Mogens; Poulsen, Knud; Blomqvist, Trinelise; Håvarstein, Leiv S.; Bek-Thomsen, Malene; Tettelin, Hervé; Sørensen, Uffe B. S.

2008-01-01

Streptococcus pneumoniae is a member of the Mitis group of streptococci which, according to 16S rRNA-sequence based phylogenetic reconstruction, includes 12 species. While other species of this group are considered prototypes of commensal bacteria, S. pneumoniae is among the most frequent microbial killers worldwide. Population genetic analysis of 118 strains, supported by demonstration of a distinct cell wall carbohydrate structure and competence pheromone sequence signature, shows that S. pneumoniae is one of several hundred evolutionary lineages forming a cluster separate from Streptococcus oralis and Streptococcus infantis. The remaining lineages of this distinct cluster are commensals previously collectively referred to as Streptococcus mitis and each represent separate species by traditional taxonomic standard. Virulence genes including the operon for capsule polysaccharide synthesis and genes encoding IgA1 protease, pneumolysin, and autolysin were randomly distributed among S. mitis lineages. Estimates of the evolutionary age of the lineages, the identical location of remnants of virulence genes in the genomes of commensal strains, the pattern of genome reductions, and the proportion of unique genes and their origin support the model that the entire cluster of S. pneumoniae, S. pseudopneumoniae, and S. mitis lineages evolved from pneumococcus-like bacteria presumably pathogenic to the common immediate ancestor of hominoids. During their adaptation to a commensal life style, most of the lineages gradually lost the majority of genes determining virulence and became genetically distinct due to sexual isolation in their respective hosts. PMID:18628950

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data.

PubMed

Mwangi, Benson; Soares, Jair C; Hasan, Khader M

2014-10-30

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data. We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm. t-SNE was evaluated against classical principal component analysis. Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders. Copyright © 2014 Elsevier B.V. All rights reserved.

A social network analysis approach to alcohol use and co-occurring addictive behavior in young adults.

PubMed

Meisel, Matthew K; Clifton, Allan D; MacKillop, James; Goodie, Adam S

2015-12-01

The current study applied egocentric social network analysis (SNA) to investigate the prevalence of addictive behavior and co-occurring substance use in college students' networks. Specifically, we examined individuals' perceptions of the frequency of network members' co-occurring addictive behavior and investigated whether co-occurring addictive behavior is spread evenly throughout networks or is more localized in clusters. We also examined differences in network composition between individuals with varying levels of alcohol use. The study utilized an egocentric SNA approach in which respondents ("egos") enumerated 30 of their closest friends, family members, co-workers, and significant others ("alters") and the relations among alters listed. Participants were 281 undergraduates at a large university in the Southeastern United States. Robust associations were observed among the frequencies of gambling, smoking, drinking, and using marijuana by network members. We also found that alters tended to cluster together into two distinct groups: one cluster moderate-to-high on co-occurring addictive behavior and the other low on co-occurring addictive behavior. Lastly, significant differences were present when examining egos' perceptions of alters' substance use between the networks of at-risk, light, and nondrinkers. These findings provide empirical evidence of distinct clustering of addictive behavior among young adults and suggest the promise of social network-based interventions for this cohort. Copyright © 2015. Published by Elsevier Ltd.

Hypersexuality and high sexual desire: exploring the structure of problematic sexuality.

PubMed

Carvalho, Joana; Štulhofer, Aleksandar; Vieira, Armando L; Jurin, Tanja

2015-06-01

The concept of hypersexuality has been accompanied by fierce debates and conflicting conclusions about its nature. One of the central questions under the discussion is a potential overlap between hypersexuality and high sexual desire. With the relevant research in its early phase, the structure of hypersexuality remains largely unknown. The aim of the present study was to systematically explore the overlap between problematic sexuality and high sexual desire. A community online survey was carried out in Croatia in 2014. The data were first cluster analyzed (by gender) based on sexual desire, sexual activity, perceived lack of control over one's sexuality, and negative behavioral consequences. Participants in the meaningful clusters were then compared for psychosocial characteristics. To complement cluster analysis (CA), multigroup confirmatory factor analysis (CFA) of the same four constructs was carried out. Indicators representing the proposed structure of hypersexuality were included: sexual desire, frequency of sexual activity, lack of control over one's sexuality, and negative behavioral outcomes. Psychosocial characteristics such as religiosity, attitudes toward pornography, and general psychopathology were also evaluated. CA pointed to the existence of two meaningful clusters, one representing problematic sexuality, that is, lack of control over one's sexuality and negative outcomes (control/consequences cluster), and the other reflecting high sexual desire and frequent sexual activity (desire/activity cluster). Compared with the desire/activity cluster, individuals from the control/consequences cluster reported more psychopathology and were characterized by more traditional attitudes. Complementing the CA findings, CFA pointed to two distinct latent dimensions-problematic sexuality and high sexual desire/activity. Our study supports the distinctiveness of hypersexuality and high sexual desire/activity, suggesting that problematic sexuality might be more associated with the perceived lack of personal control over sexuality and moralistic attitudes than with high levels of sexual desire and activity. © 2015 International Society for Sexual Medicine.

Automatic script identification from images using cluster-based templates

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

Hochberg, J.; Kerns, L.; Kelly, P.

We have developed a technique for automatically identifying the script used to generate a document that is stored electronically in bit image form. Our approach differs from previous work in that the distinctions among scripts are discovered by an automatic learning procedure, without any handson analysis. We first develop a set of representative symbols (templates) for each script in our database (Cyrillic, Roman, etc.). We do this by identifying all textual symbols in a set of training documents, scaling each symbol to a fixed size, clustering similar symbols, pruning minor clusters, and finding each cluster`s centroid. To identify a newmore » document`s script, we identify and scale a subset of symbols from the document and compare them to the templates for each script. We choose the script whose templates provide the best match. Our current system distinguishes among the Armenian, Burmese, Chinese, Cyrillic, Ethiopic, Greek, Hebrew, Japanese, Korean, Roman, and Thai scripts with over 90% accuracy.« less

Patterns of Interactive Media Use among Contemporary Youth

ERIC Educational Resources Information Center

van den Beemt, A.; Akkerman, S.; Simons, P. R. J.

2011-01-01

The intensive use of interactive media has led to assertions about the effect of these media on youth. Rather than following the assumption of a distinct Net generation, this study investigates diversity in interactive media use among youth. Results from a pilot study show that contemporary youth can be divided into clusters based on the use of…

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…

Characteristic differences in metabolite profile in male and female plants of dioecious Piper betle L.

PubMed

Bajpai, Vikas; Pandey, Renu; Negi, Mahendra Pal Singh; Bindu, K Hima; Kumar, Nikhil; Kumar, Brijesh

2012-12-01

Piper betle is a dioecious pan-Asiatic plant having cultural and medicinal uses. It belongs to the family Piperaceae and is a native of the tropics although it is also cultivated in subtropical areas. Flowering in P. betle occurs only in tropical regions. Due to lack of inductive floral cycles the plant remains in its vegetative state in the subtropics. Therefore, due to lack of flowering, gender distinction cannot be made the in the subtropics. Gender distinction in P. betle in vegetative state can be made using Direct Analysis in Real Time Mass Spectroscopy (DARTMS), a robust highthroughput method. DARTMS analysis of leaf samples of two male and six female plants showed characteristic differences in the spectra between male and female plants. Semi-quantitative differences in some of the identified peaks in male and female landraces showed gender-based differences in metabolites. Cluster analysis using the peaks at m/z 151, 193, 235 and 252 showed two distinct clusters of male and female landraces. It appears that male and female plants besides having flowers of different sexes also have characteristic differences in the metabolites representing two metabolic types.

Discovery of the Kinematic Alignment of Early-type Galaxies in the Virgo Cluster

NASA Astrophysics Data System (ADS)

Kim, Suk; Jeong, Hyunjin; Lee, Jaehyun; Lee, Youngdae; Joo, Seok-Joo; Kim, Hak-Sub; Rey, Soo-Chang

2018-06-01

Using the kinematic position angles (PAkin), an accurate indicator for the spin axis of a galaxy, obtained from the ATLAS3D integral-field-unit (IFU) spectroscopic data, we discovered that 57 Virgo early-type galaxies tend to prefer the specific PAkin values of 20° and 100°, suggesting that they are kinematically aligned with each other. These kinematic alignment angles are further associated with the directions of the two distinct axes of the Virgo cluster extending east–west and north–south, strongly suggesting that the two distinct axes are the filamentary structures within the cluster as a trace of infall patterns of galaxies. Given that the spin axis of a massive early-type galaxy does not change easily even in clusters from the hydrodynamic simulations, Virgo early-type galaxies are likely to fall into the cluster along the filamentary structures while maintaining their angular momentum. This implies that many early-type galaxies in clusters are formed in filaments via major mergers before subsequently falling into the cluster. Investigating the kinematic alignment in other clusters will allow us to understand the formation of galaxy clusters and early-type galaxies.

Identifying Patient Attitudinal Clusters Associated with Asthma Control: The European REALISE Survey.

PubMed

van der Molen, Thys; Fletcher, Monica; Price, David

Asthma is a highly heterogeneous disease that can be classified into different clinical phenotypes, and treatment may be tailored accordingly. However, factors beyond purely clinical traits, such as patient attitudes and behaviors, can also have a marked impact on treatment outcomes. The objective of this study was to further analyze data from the REcognise Asthma and LInk to Symptoms and Experience (REALISE) Europe survey, to identify distinct patient groups sharing common attitudes toward asthma and its management. Factor analysis of respondent data (N = 7,930) from the REALISE Europe survey consolidated the 34 attitudinal variables provided by the study population into a set of 8 summary factors. Cluster analyses were used to identify patient clusters that showed similar attitudes and behaviors toward each of the 8 summary factors. Five distinct patient clusters were identified and named according to the key characteristics comprising that cluster: "Confident and self-managing," "Confident and accepting of their asthma," "Confident but dependent on others," "Concerned but confident in their health care professional (HCP)," and "Not confident in themselves or their HCP." Clusters showed clear variability in attributes such as degree of confidence in managing their asthma, use of reliever and preventer medication, and level of asthma control. The 5 patient clusters identified in this analysis displayed distinctly different personal attitudes that would require different approaches in the consultation room certainly for asthma but probably also for other chronic diseases. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Feasibility of feature-based indexing, clustering, and search of clinical trials: A case study of breast cancer trials from ClinicalTrials.gov

PubMed Central

Boland, Mary Regina; Miotto, Riccardo; Gao, Junfeng; Weng, Chunhua

2013-01-01

Summary Background When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. Objectives This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. Methods We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. Results We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. Conclusions It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency. PMID:23666475

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov.

PubMed

Boland, M R; Miotto, R; Gao, J; Weng, C

2013-01-01

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.

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.

Strand swapping regulates the iron-sulfur cluster in the diabetes drug target mitoNEET

PubMed Central

Baxter, Elizabeth Leigh; Jennings, Patricia A.; Onuchic, José N.

2012-01-01

MitoNEET is a recently identified diabetes drug target that coordinates a transferable 2Fe-2S cluster, and additionally contains an unusual strand swap. In this manuscript, we use a dual basin structure-based model to predict and characterize the folding and functionality of strand swapping in mitoNEET. We demonstrate that a strand unswapped conformation is kinetically accessible and that multiple levels of control are employed to regulate the conformational dynamics of the system. Environmental factors such as temperature can shift route preference toward the unswapped pathway. Additionally we see that a region recently identified as contributing to frustration in folding acts as a regulatory hinge loop that modulates conformational balance. Interestingly, strand unswapping transfers strain specifically to cluster-coordinating residues, opening the cluster-coordinating pocket. Strengthening contacts within the cluster-coordinating pocket opens a new pathway between the swapped and unswapped conformation that utilizes cracking to bypass the unfolded basin. These results suggest that local control within distinct regions affect motions important in regulating mitoNEET’s 2Fe-2S clusters. PMID:22308404

75 FR 16424 - Proposed Information Collection; Comment Request; Census Coverage Measurement Final Housing Unit...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-01

... unit is a block cluster, which consists of one or more geographically contiguous census blocks. As in... a number of distinct processes, ranging from forming block clusters, selecting the block clusters... sample of block clusters, while the E Sample is the census of housing units and enumerations in the same...

Structure and Sequence Analyses of Clustered Protocadherins Reveal Antiparallel Interactions that Mediate Homophilic Specificity.

PubMed

Nicoludis, John M; Lau, Sze-Yi; Schärfe, Charlotta P I; Marks, Debora S; Weihofen, Wilhelm A; Gaudet, Rachelle

2015-11-03

Clustered protocadherin (Pcdh) proteins mediate dendritic self-avoidance in neurons via specific homophilic interactions in their extracellular cadherin (EC) domains. We determined crystal structures of EC1-EC3, containing the homophilic specificity-determining region, of two mouse clustered Pcdh isoforms (PcdhγA1 and PcdhγC3) to investigate the nature of the homophilic interaction. Within the crystal lattices, we observe antiparallel interfaces consistent with a role in trans cell-cell contact. Antiparallel dimerization is supported by evolutionary correlations. Two interfaces, located primarily on EC2-EC3, involve distinctive clustered Pcdh structure and sequence motifs, lack predicted glycosylation sites, and contain residues highly conserved in orthologs but not paralogs, pointing toward their biological significance as homophilic interaction interfaces. These two interfaces are similar yet distinct, reflecting a possible difference in interaction architecture between clustered Pcdh subfamilies. These structures initiate a molecular understanding of clustered Pcdh assemblies that are required to produce functional neuronal networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Clinical Subtypes of Dementia with Lewy Bodies Based on the Initial Clinical Presentation.

PubMed

Morenas-Rodríguez, Estrella; Sala, Isabel; Subirana, Andrea; Pascual-Goñi, Elba; Sánchez-Saudinós, MaBelén; Alcolea, Daniel; Illán-Gala, Ignacio; Carmona-Iragui, María; Ribosa-Nogué, Roser; Camacho, Valle; Blesa, Rafael; Fortea, Juan; Lleó, Alberto

2018-06-04

Dementia with Lewy bodies (DLB) is a heterogeneous disease in which clinical presentation, symptoms, and evolution widely varies between patients. To investigate the existence of clinical subtypes in DLB based on the initial clinical presentation. 81 patients with a clinical diagnosis of probable DLB were consecutively included. All patients underwent a neurological evaluation including a structured questionnaire about neuropsychiatric symptoms and sleep, an assessment of motor impairment (Unified Parkinson Disease Rating Scale subscale III), and a formal neuropsychological evaluation. Onset of core symptoms (hallucinations, parkinsonism, and fluctuations) and dementia were systematically reviewed from medical records. We applied a K-means clustering method based on the initial clinical presentation. Cluster analysis yielded three different groups. Patients in cluster I (cognitive-predominant, n = 46) presented more frequently with cognitive symptoms (95.7%, n = 44, p < 0.001), and showed a longer duration from onset to DLB diagnosis (p < 0.001) than the other clusters. Patients in cluster II (neuropsychiatric-predominant, n = 22) were older at disease onset (78.1±5 versus 73.6±6.1 and 73.6±4.2 in clusters I and III, respectively, both p < 0.01), presented more frequently with psychotic symptoms (77.3%, n = 17), and had a shorter duration until the onset of hallucinations (p < 0.001). Patients in cluster III (parkinsonism-predominant, n = 13) showed a shorter time from onset to presence of parkinsonism (p < 0.001) and dementia (0.008). Three subtypes of clinical DLB can be defined when considering the differential initial presentations. The proposed subtypes have distinct clinical profiles and progression patterns.

The neural correlates of apathy in schizophrenia: An exploratory investigation.

PubMed

Caravaggio, Fernando; Fervaha, Gagan; Menon, Mahesh; Remington, Gary; Graff-Guerrero, Ariel; Gerretsen, Philip

2017-10-25

Motivational deficits represent a core negative symptom in patients with schizophrenia. Previous morphology studies have demonstrated that apathy in patients with schizophrenia is associated with reduced frontal grey matter (GM). We attempted to replicate this previous finding, and explored whether it was distinct from potential associations with a distinct subdomain of negative symptoms, namely Affective Flattening, and GM. Twenty medicated patients with schizophrenia provided structural T1-weighted images acquired on a 3-Tesla MRI scanner and negative symptoms were evaluated using the Scale for the Assessment of Negative Symptoms. Voxel-based morphometry (VBM) was used to explore the correlations between whole-brain GM and i) Apathy, and ii) Affective Flattening, respectively. Apathy scores were negatively correlated with several GM clusters in frontal regions, including the frontal inferior operculum and the left dorsal anterior cingulate cortex. Only positive correlations with GM clusters were observed for Affective Flattening, particularly in the inferior temporal lobe. Notably, the regions associated with apathy scores were distinct from those associated with Affective Flattening, and these findings remained after controlling for antipsychotic medication dosage. We replicated previous associations between reduced frontal GM and apathy in patients with schizophrenia. Moreover, we demonstrated that these GM associations are distinct from those with Affective Flattening. The present findings set the stage for future larger-scale studies confirming the structural and neurochemical substrates of apathy in schizophrenia. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparative Study of IS6110 Restriction Fragment Length Polymorphism and Variable-Number Tandem-Repeat Typing of Mycobacterium tuberculosis Isolates in the Netherlands, Based on a 5-Year Nationwide Survey

PubMed Central

de Beer, Jessica L.; van Ingen, Jakko; de Vries, Gerard; Erkens, Connie; Sebek, Maruschka; Mulder, Arnout; Sloot, Rosa; van den Brandt, Anne-Marie; Enaimi, Mimount; Kremer, Kristin; Supply, Philip

2013-01-01

In order to switch from IS6110 and polymorphic GC-rich repetitive sequence (PGRS) restriction fragment length polymorphism (RFLP) to 24-locus variable-number tandem-repeat (VNTR) typing of Mycobacterium tuberculosis complex isolates in the national tuberculosis control program in The Netherlands, a detailed evaluation on discriminatory power and agreement with findings in a cluster investigation was performed on 3,975 tuberculosis cases during the period of 2004 to 2008. The level of discrimination of the two typing methods did not differ substantially: RFLP typing yielded 2,733 distinct patterns compared to 2,607 in VNTR typing. The global concordance, defined as isolates labeled unique or identically distributed in clusters by both methods, amounted to 78.5% (n = 3,123). Of the remaining 855 cases, 12% (n = 479) of the cases were clustered only by VNTR, 7.7% (n = 305) only by RFLP typing, and 1.8% (n = 71) revealed different cluster compositions in the two approaches. A cluster investigation was performed for 87% (n = 1,462) of the cases clustered by RFLP. For the 740 cases with confirmed or presumed epidemiological links, 92% were concordant with VNTR typing. In contrast, only 64% of the 722 cases without an epidemiological link but clustered by RFLP typing were also clustered by VNTR typing. We conclude that VNTR typing has a discriminatory power equal to IS6110 RFLP typing but is in better agreement with findings in a cluster investigation performed on an RFLP-clustering-based cluster investigation. Both aspects make VNTR typing a suitable method for tuberculosis surveillance systems. PMID:23363841

From Innovation to Impact at Scale: Lessons Learned from a Cluster of Research-Community Partnerships

PubMed Central

Schindler, Holly S.; Fisher, Philip A.; Shonkoff, Jack P.

2017-01-01

This paper presents a description of how an interdisciplinary network of academic researchers, community-based programs, parents, and state agencies have joined together to design, test, and scale a suite of innovative intervention strategies rooted in new knowledge about the biology of adversity. Through a process of co-creation, collective pilot-testing, and the support of a measurement and evaluation hub, the Washington State Innovation Cluster is using rapid cycle, iterative learning to elucidate differential impacts of interventions designed to build child and caregiver capacities and address the developmental consequences of socioeconomic disadvantage. Key characteristics of the Innovation Cluster model are described and an example is presented of a video-coaching intervention that has been implemented, adapted, and evaluated through this distinctive, collaborative process. PMID:28777436

Community pharmacy customer segmentation based on factors influencing their selection of pharmacy and over-the-counter medicines.

PubMed

Kevrekidis, Dimitrios Phaedon; Minarikova, Daniela; Markos, Angelos; Malovecka, Ivona; Minarik, Peter

2018-01-01

Within the competitive pharmacy market environment, community pharmacies are required to develop efficient marketing strategies based on contemporary information about consumer behavior in order to attract clients and develop customer loyalty. This study aimed to investigate the consumers' preferences concerning the selection of pharmacy and over-the-counter (OTC) medicines, and to identify customer segments in relation to these preferences. A cross-sectional study was conducted between February and March 2016 on a convenient quota sample of 300 participants recruited in the metropolitan area of Thessaloniki, Greece. The main instrument used for data collection was a structured questionnaire with close-ended, multiple choice questions. To identify customer segments, Two-Step cluster analysis was conducted. Three distinct pharmacy customer clusters emerged. Customers of the largest cluster (49%; 'convenience customers') were mostly younger consumers. They gave moderate to positive ratings to factors affecting the selection of pharmacy and OTCs; convenience, and previous experience and the pharmacist's opinion, received the highest ratings. Customers of the second cluster (35%; 'loyal customers') were mainly retired; most of them reported visiting a single pharmacy. They gave high ratings to all factors that influence pharmacy selection, especially the pharmacy's staff, and factors influencing the purchase of OTCs, particularly previous experience and the pharmacist's opinion. Customers of the smallest cluster (16%; 'convenience and price-sensitive customers') were mainly retired or unemployed with low to moderate education, and low personal income. They gave the lowest ratings to most of the examined factors; convenience among factors influencing pharmacy selection, whereas previous experience, the pharmacist's opinion and product price among those affecting the purchase of OTCs, received the highest ratings. The community pharmacy market comprised of distinct customer segments that varied in the consumer preferences concerning the selection of pharmacy and OTCs, the evaluation of pharmaceutical services and products, and demographic characteristics.

FACTOR ANALYTIC MODELS OF CLUSTERED MULTIVARIATE DATA WITH INFORMATIVE CENSORING

EPA Science Inventory

This paper describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censorin...

Efficient evaluation of sampling quality of molecular dynamics simulations by clustering of dihedral torsion angles and Sammon mapping.

PubMed

Frickenhaus, Stephan; Kannan, Srinivasaraghavan; Zacharias, Martin

2009-02-01

A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.

Genetically distinct genogroup IV norovirus strains identified in wastewater.

PubMed

Kitajima, Masaaki; Rachmadi, Andri T; Iker, Brandon C; Haramoto, Eiji; Gerba, Charles P

2016-12-01

We investigated the prevalence and genetic diversity of genogroup IV norovirus (GIV NoV) strains in wastewater in Arizona, United States, over a 13-month period. Among 50 wastewater samples tested, GIV NoVs were identified in 13 (26 %) of the samples. A total of 47 different GIV NoV strains were identified, which were classified into two genetically distinct clusters: the GIV.1 human cluster and a unique genetic cluster closely related to strains previously identified in Japanese wastewater. The results provide additional evidence of the considerable genetic diversity among GIV NoV strains through the analysis of wastewater containing virus strains shed from all populations.

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

PubMed

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

2016-10-18

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

Distinct anatomical subtypes of the behavioural variant of frontotemporal dementia: a cluster analysis study.

PubMed

Whitwell, Jennifer L; Przybelski, Scott A; Weigand, Stephen D; Ivnik, Robert J; Vemuri, Prashanthi; Gunter, Jeffrey L; Senjem, Matthew L; Shiung, Maria M; Boeve, Bradley F; Knopman, David S; Parisi, Joseph E; Dickson, Dennis W; Petersen, Ronald C; Jack, Clifford R; Josephs, Keith A

2009-11-01

The behavioural variant of frontotemporal dementia is a progressive neurodegenerative syndrome characterized by changes in personality and behaviour. It is typically associated with frontal lobe atrophy, although patterns of atrophy are heterogeneous. The objective of this study was to examine case-by-case variability in patterns of grey matter atrophy in subjects with the behavioural variant of frontotemporal dementia and to investigate whether behavioural variant of frontotemporal dementia can be divided into distinct anatomical subtypes. Sixty-six subjects that fulfilled clinical criteria for a diagnosis of the behavioural variant of frontotemporal dementia with a volumetric magnetic resonance imaging scan were identified. Grey matter volumes were obtained for 26 regions of interest, covering frontal, temporal and parietal lobes, striatum, insula and supplemental motor area, using the automated anatomical labelling atlas. Regional volumes were divided by total grey matter volume. A hierarchical agglomerative cluster analysis using Ward's clustering linkage method was performed to cluster the behavioural variant of frontotemporal dementia subjects into different anatomical clusters. Voxel-based morphometry was used to assess patterns of grey matter loss in each identified cluster of subjects compared to an age and gender-matched control group at P < 0.05 (family-wise error corrected). We identified four potentially useful clusters with distinct patterns of grey matter loss, which we posit represent anatomical subtypes of the behavioural variant of frontotemporal dementia. Two of these subtypes were associated with temporal lobe volume loss, with one subtype showing loss restricted to temporal lobe regions (temporal-dominant subtype) and the other showing grey matter loss in the temporal lobes as well as frontal and parietal lobes (temporofrontoparietal subtype). Another two subtypes were characterized by a large amount of frontal lobe volume loss, with one subtype showing grey matter loss in the frontal lobes as well as loss of the temporal lobes (frontotemporal subtype) and the other subtype showing loss relatively restricted to the frontal lobes (frontal-dominant subtype). These four subtypes differed on clinical measures of executive function, episodic memory and confrontation naming. There were also associations between the four subtypes and genetic or pathological diagnoses which were obtained in 48% of the cohort. The clusters did not differ in behavioural severity as measured by the Neuropsychiatric Inventory; supporting the original classification of the behavioural variant of frontotemporal dementia in these subjects. Our findings suggest behavioural variant of frontotemporal dementia can therefore be subdivided into four different anatomical subtypes.

CHEMICAL TAGGING OF THREE DISTINCT POPULATIONS OF RED GIANTS IN THE GLOBULAR CLUSTER NGC 6752

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

Carretta, E.; Bragaglia, A.; Gratton, R. G.

2012-05-01

We present aluminum, magnesium, and silicon abundances in the metal-poor globular cluster NGC 6752 for a sample of more than 130 red giants with homogeneous oxygen and sodium abundances. We find that [Al/Fe] shows a spread of about 1.4 dex among giants in NGC 6752 and is anticorrelated with [Mg/Fe] and [O/Fe] and correlated with [Na/Fe] and [Si/Fe]. These relations are not continuous in nature, but the distribution of stars is clearly clustered around three distinct Al values, low, intermediate, and high. These three groups nicely correspond to the three distinct sequences previously detected using Stroemgren photometry along the redmore » giant branch. These two independent findings strongly indicate the existence of three distinct stellar populations in NGC 6752. Comparing the abundances of O and Mg, we find that the population with intermediate chemical abundances cannot originate from material with the same composition of the most O- and Mg-poor population, diluted by material with that of the most O- and Mg-rich one. This calls for different polluters.« less

Beyond fitness tracking: The use of consumer-grade wearable data from normal volunteers in cardiovascular and lipidomics research

PubMed Central

Teo, Jing Xian; Yang, Chengxi; Pua, Chee Jian; Blöcker, Christopher; Lim, Jing Quan; Ching, Jianhong; Yap, Jonathan Jiunn Liang; Tan, Swee Yaw; Sahlén, Anders; Chin, Calvin Woon-Loong; Teh, Bin Tean; Rozen, Steven G.; Cook, Stuart Alexander; Yeo, Khung Keong; Tan, Patrick

2018-01-01

The use of consumer-grade wearables for purposes beyond fitness tracking has not been comprehensively explored. We generated and analyzed multidimensional data from 233 normal volunteers, integrating wearable data, lifestyle questionnaires, cardiac imaging, sphingolipid profiling, and multiple clinical-grade cardiovascular and metabolic disease markers. We show that subjects can be stratified into distinct clusters based on daily activity patterns and that these clusters are marked by distinct demographic and behavioral patterns. While resting heart rates (RHRs) performed better than step counts in being associated with cardiovascular and metabolic disease markers, step counts identified relationships between physical activity and cardiac remodeling, suggesting that wearable data may play a role in reducing overdiagnosis of cardiac hypertrophy or dilatation in active individuals. Wearable-derived activity levels can be used to identify known and novel activity-modulated sphingolipids that are in turn associated with insulin sensitivity. Our findings demonstrate the potential for wearables in biomedical research and personalized health. PMID:29485983

Patterns of Coping Preference among Persons with Schizophrenia: Associations with Self-Esteem, Hope, Symptoms and Function

ERIC Educational Resources Information Center

Lysaker, Paul H.; Tsai, Jack; Hammoud, Kristin; Davis, Louanne W.

2009-01-01

Maladaptive styles of coping are believed to be a barrier to recovery from schizophrenia. In this study we obtained measures of coping for 133 persons with schizophrenia or schizoaffective disorder. A cluster analysis was then performed based on those scores and produced five distinctive coping profiles. These five groups were then compared on…

Patterns of Depressive Symptoms, Drinking Motives, and Sexual Behavior among Substance Abusing Adolescents: Implications for Health Risk

ERIC Educational Resources Information Center

Tubman, Jonathan G.; Wagner, Eric F.; Langer, Lilly M.

2003-01-01

Adolescents with substance use problems were classified into four distinct and meaningful subgroups based on patterns of depressive symptoms and motives for drinking before sex (i.e., avoidance, enhancement and social motives) using cluster analysis. Data were collected in face-to-face interviews from 120 adolescents and young adults (87 men, 33…

Carpinus tibetana (Betulaceae), a new species from southeast Tibet, China

PubMed Central

Lu, Zhiqiang; Li, Ying; Yang, Xiaoyue; Liu, Jianquan

2018-01-01

Abstract A new species Carpinus tibetana Z. Qiang Lu & J. Quan Liu from southeast Tibet is described and illustrated. The specimens of this new species were previously identified and placed under C. monbeigiana Hand.-Mazz. or C. mollicoma Hu. However, the specimens from southeast Tibet differ from those of C. monbeigiana from other regions with more lateral veins (19–24 vs 14–18) on each side of the midvein and dense pubescence on the abaxial leaf surface, while from those of C. mollicoma from other regions differ by nutlet with dense resinous glands and glabrous or sparsely villous at apex. Principal Component Analyses based on morphometric characters recognise the Tibetan populations as a separate group. Nuclear ribosomal ITS sequence variations show stable and distinct genetic divergences between the Tibetan populations and C. monbeigiana or C. mollicoma by two or three fixed nucleotide mutations. Phylogenetic analysis also identified three respective genetic clusters and the C. mollicoma cluster diverged early. In addition, the Tibetan populations show a disjunct geographic isolation from the other two species. Therefore, C. tibetana, based on the Tibetan populations, is here erected as a new species, distinctly different from C. monbeigiana and C. mollicoma. PMID:29750069

Carpinus tibetana (Betulaceae), a new species from southeast Tibet, China.

PubMed

Lu, Zhiqiang; Li, Ying; Yang, Xiaoyue; Liu, Jianquan

2018-01-01

A new species Carpinus tibetana Z. Qiang Lu & J. Quan Liu from southeast Tibet is described and illustrated. The specimens of this new species were previously identified and placed under C. monbeigiana Hand.-Mazz. or C. mollicoma Hu. However, the specimens from southeast Tibet differ from those of C. monbeigiana from other regions with more lateral veins (19-24 vs 14-18) on each side of the midvein and dense pubescence on the abaxial leaf surface, while from those of C. mollicoma from other regions differ by nutlet with dense resinous glands and glabrous or sparsely villous at apex. Principal Component Analyses based on morphometric characters recognise the Tibetan populations as a separate group. Nuclear ribosomal ITS sequence variations show stable and distinct genetic divergences between the Tibetan populations and C. monbeigiana or C. mollicoma by two or three fixed nucleotide mutations. Phylogenetic analysis also identified three respective genetic clusters and the C. mollicoma cluster diverged early. In addition, the Tibetan populations show a disjunct geographic isolation from the other two species. Therefore, C. tibetana , based on the Tibetan populations, is here erected as a new species, distinctly different from C. monbeigiana and C. mollicoma .

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

PubMed

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

2014-11-01

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

Investigations of Potential Phenotypes of Foot Osteoarthritis: Cross‐Sectional Analysis From the Clinical Assessment Study of the Foot

PubMed Central

Marshall, Michelle; Thomas, Martin J.; Menz, Hylton B.; Myers, Helen L.; Thomas, Elaine; Downes, Thomas; Peat, George; Roddy, Edward

2016-01-01

Objective To investigate the existence of distinct foot osteoarthritis (OA) phenotypes based on pattern of joint involvement and comparative symptom and risk profiles. Methods Participants ages ≥50 years reporting foot pain in the previous year were drawn from a population‐based cohort. Radiographs were scored for OA in the first metatarsophalangeal (MTP) joint, first and second cuneometatarsal, navicular first cuneiform, and talonavicular joints according to a published atlas. Chi‐square tests established clustering, and odds ratios (ORs) examined symmetry and pairwise associations of radiographic OA in the feet. Distinct underlying classes of foot OA were investigated by latent class analysis (LCA) and their association with symptoms and risk factors was assessed. Results In 533 participants (mean age 64.9 years, 55.9% female) radiographic OA clustered across both feet (P < 0.001) and was highly symmetrical (adjusted OR 3.0, 95% confidence interval 2.1, 4.2). LCA identified 3 distinct classes of foot OA: no or minimal foot OA (64%), isolated first MTP joint OA (22%), and polyarticular foot OA (15%). After adjustment for age and sex, polyarticular foot OA was associated with nodal OA, increased body mass index, and more pain and functional limitation compared to the other classes. Conclusion Patterning of radiographic foot OA has provided insight into the existence of 2 forms of foot OA: isolated first MTP joint OA and polyarticular foot OA. The symptom and risk factor profiles in individuals with polyarticular foot OA indicate a possible distinctive phenotype of foot OA, but further research is needed to explore the characteristics of isolated first MTP joint and polyarticular foot OA. PMID:26238801

Genome-scale analysis of aberrant DNA methylation in colorectal cancer

PubMed Central

Hinoue, Toshinori; Weisenberger, Daniel J.; Lange, Christopher P.E.; Shen, Hui; Byun, Hyang-Min; Van Den Berg, David; Malik, Simeen; Pan, Fei; Noushmehr, Houtan; van Dijk, Cornelis M.; Tollenaar, Rob A.E.M.; Laird, Peter W.

2012-01-01

Colorectal cancer (CRC) is a heterogeneous disease in which unique subtypes are characterized by distinct genetic and epigenetic alterations. Here we performed comprehensive genome-scale DNA methylation profiling of 125 colorectal tumors and 29 adjacent normal tissues. We identified four DNA methylation–based subgroups of CRC using model-based cluster analyses. Each subtype shows characteristic genetic and clinical features, indicating that they represent biologically distinct subgroups. A CIMP-high (CIMP-H) subgroup, which exhibits an exceptionally high frequency of cancer-specific DNA hypermethylation, is strongly associated with MLH1 DNA hypermethylation and the BRAFV600E mutation. A CIMP-low (CIMP-L) subgroup is enriched for KRAS mutations and characterized by DNA hypermethylation of a subset of CIMP-H-associated markers rather than a unique group of CpG islands. Non-CIMP tumors are separated into two distinct clusters. One non-CIMP subgroup is distinguished by a significantly higher frequency of TP53 mutations and frequent occurrence in the distal colon, while the tumors that belong to the fourth group exhibit a low frequency of both cancer-specific DNA hypermethylation and gene mutations and are significantly enriched for rectal tumors. Furthermore, we identified 112 genes that were down-regulated more than twofold in CIMP-H tumors together with promoter DNA hypermethylation. These represent ∼7% of genes that acquired promoter DNA methylation in CIMP-H tumors. Intriguingly, 48/112 genes were also transcriptionally down-regulated in non-CIMP subgroups, but this was not attributable to promoter DNA hypermethylation. Together, we identified four distinct DNA methylation subgroups of CRC and provided novel insight regarding the role of CIMP-specific DNA hypermethylation in gene silencing. PMID:21659424

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

PubMed

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

2017-10-01

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1 / PD-L2 expression, or epigenetic mutations ( IDH1/2, BAP1 ) and FGFR / PRKA -related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116-35. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1047 . ©2017 American Association for Cancer Research.

Progressive colonization and restricted gene flow shape island-dependent population structure in Galápagos marine iguanas (Amblyrhynchus cristatus)

PubMed Central

2009-01-01

Background Marine iguanas (Amblyrhynchus cristatus) inhabit the coastlines of large and small islands throughout the Galápagos archipelago, providing a rich system to study the spatial and temporal factors influencing the phylogeographic distribution and population structure of a species. Here, we analyze the microevolution of marine iguanas using the complete mitochondrial control region (CR) as well as 13 microsatellite loci representing more than 1200 individuals from 13 islands. Results CR data show that marine iguanas occupy three general clades: one that is widely distributed across the northern archipelago, and likely spread from east to west by way of the South Equatorial current, a second that is found mostly on the older eastern and central islands, and a third that is limited to the younger northern and western islands. Generally, the CR haplotype distribution pattern supports the colonization of the archipelago from the older, eastern islands to the younger, western islands. However, there are also signatures of recurrent, historical gene flow between islands after population establishment. Bayesian cluster analysis of microsatellite genotypes indicates the existence of twenty distinct genetic clusters generally following a one-cluster-per-island pattern. However, two well-differentiated clusters were found on the easternmost island of San Cristóbal, while nine distinct and highly intermixed clusters were found on youngest, westernmost islands of Isabela and Fernandina. High mtDNA and microsatellite genetic diversity were observed for populations on Isabela and Fernandina that may be the result of a recent population expansion and founder events from multiple sources. Conclusions While a past genetic study based on pure FST analysis suggested that marine iguana populations display high levels of nuclear (but not mitochondrial) gene flow due to male-biased dispersal, the results of our sex-biased dispersal tests and the finding of strong genetic differentiation between islands do not support this view. Therefore, our study is a nice example of how recently developed analytical tools such as Bayesian clustering analysis and DNA sequence-based demographic analyses can overcome potential biases introduced by simply relying on FST estimates from markers with different inheritance patterns. PMID:20028547

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

PubMed

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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.

CYP76M7 Is an ent-Cassadiene C11α-Hydroxylase Defining a Second Multifunctional Diterpenoid Biosynthetic Gene Cluster in Rice[W][OA

PubMed Central

Swaminathan, Sivakumar; Morrone, Dana; Wang, Qiang; Fulton, D. Bruce; Peters, Reuben J.

2009-01-01

Biosynthetic gene clusters are common in microbial organisms, but rare in plants, raising questions regarding the evolutionary forces that drive their assembly in multicellular eukaryotes. Here, we characterize the biochemical function of a rice (Oryza sativa) cytochrome P450 monooxygenase, CYP76M7, which seems to act in the production of antifungal phytocassanes and defines a second diterpenoid biosynthetic gene cluster in rice. This cluster is uniquely multifunctional, containing enzymatic genes involved in the production of two distinct sets of phytoalexins, the antifungal phytocassanes and antibacterial oryzalides/oryzadiones, with the corresponding genes being subject to distinct transcriptional regulation. The lack of uniform coregulation of the genes within this multifunctional cluster suggests that this was not a primary driving force in its assembly. However, the cluster is dedicated to specialized metabolism, as all genes in the cluster are involved in phytoalexin metabolism. We hypothesize that this dedication to specialized metabolism led to the assembly of the corresponding biosynthetic gene cluster. Consistent with this hypothesis, molecular phylogenetic comparison demonstrates that the two rice diterpenoid biosynthetic gene clusters have undergone independent elaboration to their present-day forms, indicating continued evolutionary pressure for coclustering of enzymatic genes encoding components of related biosynthetic pathways. PMID:19825834

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-03-01

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

[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.

Pinus ponderosa: A checkered past obscured four species.

PubMed

Willyard, Ann; Gernandt, David S; Potter, Kevin; Hipkins, Valerie; Marquardt, Paula; Mahalovich, Mary Frances; Langer, Stephen K; Telewski, Frank W; Cooper, Blake; Douglas, Connor; Finch, Kristen; Karemera, Hassani H; Lefler, Julia; Lea, Payton; Wofford, Austin

2017-01-01

Molecular genetic evidence can help delineate taxa in species complexes that lack diagnostic morphological characters. Pinus ponderosa (Pinaceae; subsection Ponderosae) is recognized as a problematic taxon: plastid phylogenies of exemplars were paraphyletic, and mitochondrial phylogeography suggested at least four subdivisions of P. ponderosa. These patterns have not been examined in the context of other Ponderosae species. We hypothesized that putative intraspecific subdivisions might each represent a separate taxon. We genotyped six highly variable plastid simple sequence repeats in 1903 individuals from 88 populations of P. ponderosa and related Ponderosae (P. arizonica, P. engelmannii, and P. jeffreyi). We used multilocus haplotype networks and discriminant analysis of principal components to test clustering of individuals into genetically and geographically meaningful taxonomic units. There are at least four distinct plastid clusters within P. ponderosa that roughly correspond to the geographic distribution of mitochondrial haplotypes. Some geographic regions have intermixed plastid lineages, and some mitochondrial and plastid boundaries do not coincide. Based on relative distances to other species of Ponderosae, these clusters diagnose four distinct taxa. Newly revealed geographic boundaries of four distinct taxa (P. benthamiana, P. brachyptera, P. scopulorum, and a narrowed concept of P. ponderosa) do not correspond completely with taxonomies. Further research is needed to understand their morphological and nuclear genetic makeup, but we suggest that resurrecting originally published species names would more appropriately reflect the taxonomy of this checkered classification than their current treatment as varieties of P. ponderosa. © 2017 Willyard et al. Published by the Botanical Society of America. This work is licensed under a Creative Commons public domain license (CC0 1.0).

Exploring the atomic structure of 1.8nm monolayer-protected gold clusters with aberration-corrected STEM.

PubMed

Liu, Jian; Jian, Nan; Ornelas, Isabel; Pattison, Alexander J; Lahtinen, Tanja; Salorinne, Kirsi; Häkkinen, Hannu; Palmer, Richard E

2017-05-01

Monolayer-protected (MP) Au clusters present attractive quantum systems with a range of potential applications e.g. in catalysis. Knowledge of the atomic structure is needed to obtain a full understanding of their intriguing physical and chemical properties. Here we employed aberration-corrected scanning transmission electron microscopy (ac-STEM), combined with multislice simulations, to make a round-robin investigation of the atomic structure of chemically synthesised clusters with nominal composition Au 144 (SCH 2 CH 2 Ph) 60 provided by two different research groups. The MP Au clusters were "weighed" by the atom counting method, based on their integrated intensities in the high angle annular dark field (HAADF) regime and calibrated exponent of the Z dependence. For atomic structure analysis, we compared experimental images of hundreds of clusters, with atomic resolution, against a variety of structural models. Across the size range 123-151 atoms, only 3% of clusters matched the theoretically predicted Au 144 (SR) 60 structure, while a large proportion of the clusters were amorphous (i.e. did not match any model structure). However, a distinct ring-dot feature, characteristic of local icosahedral symmetry, was observed in about 20% of the clusters. Copyright © 2017. Published by Elsevier B.V.

Two distinct Photobacterium populations thrive in ancient Mediterranean sapropels.

PubMed

Süss, Jacqueline; Herrmann, Kerstin; Seidel, Michael; Cypionka, Heribert; Engelen, Bert; Sass, Henrik

2008-04-01

Eastern Mediterranean sediments are characterized by the periodic occurrence of conspicuous, organic matter-rich sapropel layers. Phylogenetic analysis of a large culture collection isolated from these sediments revealed that about one third of the isolates belonged to the genus Photobacterium. In the present study, 22 of these strains were examined with respect to their phylogenetic and metabolic diversity. The strains belonged to two distinct Photobacterium populations (Mediterranean cluster I and II). Strains of cluster I were isolated almost exclusively from organic-rich sapropel layers and were closely affiliated with P. aplysiae (based on their 16S rRNA gene sequences). They possessed almost identical Enterobacterial Repetitive Intergenic Consensus (ERIC) and substrate utilization patterns, even among strains from different sampling sites or from layers differing up to 100,000 years in age. Strains of cluster II originated from sapropels and from the surface and carbon-lean intermediate layers. They were related to Photobacterium frigidiphilum but differed significantly in their fingerprint patterns and substrate spectra, even when these strains were obtained from the same sampling site and layer. Temperature range for growth (4 to 33 degrees C), salinity tolerance (5 to 100 per thousand), pH requirements (5.5-9.3), and the composition of polar membrane lipids were similar for both clusters. All strains grew by fermentation (glucose, organic acids) and all but five by anaerobic respiration (nitrate, dimethyl sulfoxide, anthraquinone disulfonate, or humic acids). These results indicate that the genus Photobacterium forms subsurface populations well adapted to life in the deep biosphere.

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.

A homeotic gene cluster patterns the anteroposterior body axis of C. elegans.

PubMed

Wang, B B; Müller-Immergluck, M M; Austin, J; Robinson, N T; Chisholm, A; Kenyon, C

1993-07-16

In insects and vertebrates, clusters of Antennapedia class homeobox (HOM-C) genes specify anteroposterior body pattern. The nematode C. elegans also contains a small cluster of HOM-C genes, one of which has been shown to specify positional identity. Here we show that two additional C. elegans HOM-C genes also specify positional identity and that together these three HOM-C genes function along the anteroposterior axis in the same order as their homologs in other organisms. Thus, HOM-C-based pattern formation has been conserved in nematodes despite the many differences in morphology and embryology that distinguish them from other phyla. Each C. elegans HOM-C gene is responsible for a distinct body region; however, where their domains overlap, two HOM-C genes can act together to specify the fates of individual cells.

Identifying At-Risk Students in General Chemistry via Cluster Analysis of Affective Characteristics

ERIC Educational Resources Information Center

Chan, Julia Y. K.; Bauer, Christopher F.

2014-01-01

The purpose of this study is to identify academically at-risk students in first-semester general chemistry using affective characteristics via cluster analysis. Through the clustering of six preselected affective variables, three distinct affective groups were identified: low (at-risk), medium, and high. Students in the low affective group…

Module Cluster: UG - 001.00 (GSC) Urban Geography.

ERIC Educational Resources Information Center

Currier, Wade R.

This is one of several module clusters developed for the Camden Teacher Corps project. This module cluster is designed to introduce students to urban studies through the application of a geographic approach. Although geography shares with other social sciences many concepts and methods, it has contributed a distinctive set of viewpoints and a…

Sample size determination for GEE analyses of stepped wedge cluster randomized trials.

PubMed

Li, Fan; Turner, Elizabeth L; Preisser, John S

2018-06-19

In stepped wedge cluster randomized trials, intact clusters of individuals switch from control to intervention from a randomly assigned period onwards. Such trials are becoming increasingly popular in health services research. When a closed cohort is recruited from each cluster for longitudinal follow-up, proper sample size calculation should account for three distinct types of intraclass correlations: the within-period, the inter-period, and the within-individual correlations. Setting the latter two correlation parameters to be equal accommodates cross-sectional designs. We propose sample size procedures for continuous and binary responses within the framework of generalized estimating equations that employ a block exchangeable within-cluster correlation structure defined from the distinct correlation types. For continuous responses, we show that the intraclass correlations affect power only through two eigenvalues of the correlation matrix. We demonstrate that analytical power agrees well with simulated power for as few as eight clusters, when data are analyzed using bias-corrected estimating equations for the correlation parameters concurrently with a bias-corrected sandwich variance estimator. © 2018, The International Biometric Society.

Variability in research ethics review of cluster randomized trials: a scenario-based survey in three countries

PubMed Central

2014-01-01

Background Cluster randomized trials (CRTs) present unique ethical challenges. In the absence of a uniform standard for their ethical design and conduct, problems such as variability in procedures and requirements by different research ethics committees will persist. We aimed to assess the need for ethics guidelines for CRTs among research ethics chairs internationally, investigate variability in procedures for research ethics review of CRTs within and among countries, and elicit research ethics chairs’ perspectives on specific ethical issues in CRTs, including the identification of research subjects. The proper identification of research subjects is a necessary requirement in the research ethics review process, to help ensure, on the one hand, that subjects are protected from harm and exploitation, and on the other, that reviews of CRTs are completed efficiently. Methods A web-based survey with closed- and open-ended questions was administered to research ethics chairs in Canada, the United States, and the United Kingdom. The survey presented three scenarios of CRTs involving cluster-level, professional-level, and individual-level interventions. For each scenario, a series of questions was posed with respect to the type of review required (full, expedited, or no review) and the identification of research subjects at cluster and individual levels. Results A total of 189 (35%) of 542 chairs responded. Overall, 144 (84%, 95% CI 79 to 90%) agreed or strongly agreed that there is a need for ethics guidelines for CRTs and 158 (92%, 95% CI 88 to 96%) agreed or strongly agreed that research ethics committees could be better informed about distinct ethical issues surrounding CRTs. There was considerable variability among research ethics chairs with respect to the type of review required, as well as the identification of research subjects. The cluster-cluster and professional-cluster scenarios produced the most disagreement. Conclusions Research ethics committees identified a clear need for ethics guidelines for CRTs and education about distinct ethical issues in CRTs. There is disagreement among committees, even within the same countries, with respect to key questions in the ethics review of CRTs. This disagreement reflects variability of opinion and practices pointing toward possible gaps in knowledge, and supports the need for explicit guidelines for the ethical conduct and review of CRTs. PMID:24495542

Passion and intrinsic motivation in digital gaming.

PubMed

Wang, Chee Keng John; Khoo, Angeline; Liu, Woon Chia; Divaharan, Shanti

2008-02-01

Digital gaming is fast becoming a favorite activity all over the world. Yet very few studies have examined the underlying motivational processes involved in digital gaming. One motivational force that receives little attention in psychology is passion, which could help us understand the motivation of gamers. The purpose of the present study was to identify subgroups of young people with distinctive passion profiles on self-determined regulations, flow dispositions, affect, and engagement time in gaming. One hundred fifty-five students from two secondary schools in Singapore participated in the survey. There were 134 males and 8 females (13 unspecified). The participants completed a questionnaire to measure harmonious passion (HP), obsessive passion (OP), perceived locus of causality, disposition flow, positive and negative affects, and engagement time in gaming. Cluster analysis found three clusters with distinct passion profiles. The first cluster had an average HP/OP profile, the second cluster had a low HP/OP profile, and the third cluster had a high HP/OP profile. The three clusters displayed different levels of cognitive, affective, and behavioral outcomes. Cluster analysis, as this study shows, is useful in identifying groups of gamers with different passion profiles. It has helped us gain a deeper understanding of motivation in digital gaming.

Effect of Clustering Algorithm on Establishing Markov State Model for Molecular Dynamics Simulations.

PubMed

Li, Yan; Dong, Zigang

2016-06-27

Recently, the Markov state model has been applied for kinetic analysis of molecular dynamics simulations. However, discretization of the conformational space remains a primary challenge in model building, and it is not clear how the space decomposition by distinct clustering strategies exerts influence on the model output. In this work, different clustering algorithms are employed to partition the conformational space sampled in opening and closing of fatty acid binding protein 4 as well as inactivation and activation of the epidermal growth factor receptor. Various classifications are achieved, and Markov models are set up accordingly. On the basis of the models, the total net flux and transition rate are calculated between two distinct states. Our results indicate that geometric and kinetic clustering perform equally well. The construction and outcome of Markov models are heavily dependent on the data traits. Compared to other methods, a combination of Bayesian and hierarchical clustering is feasible in identification of metastable states.

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

NASA Astrophysics Data System (ADS)

Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.

Consumer Perception of Retail Pork Bacon Attributes Using Adaptive Choice-based Conjoint Analysis and Maximum Differential Scaling.

PubMed

McLean, K G; Hanson, D J; Jervis, S M; Drake, M A

2017-11-01

Bacon is one of the most recognizable consumer pork products and is differentiated by appearance, flavor, thickness, and several possible product claims. The objective of this study was to explore the attributes of retail bacon that influence consumers to purchase and consume bacon. An Adaptive Choice-Based Conjoint (ACBC) survey was designed for attributes of raw American-style bacon. An ACBC survey (N = 1410 consumers) and Kano questioning were applied to determine the key attributes that influenced consumer purchase. Attributes included package size, brand, thickness, label claims, flavor, price, and images of the bacon package displaying fat:lean ratio. Maximum Difference Scaling (MaxDiff) was used to rank appeal of 20 different bacon images with variable fat:lean ration and slice shape. The most important attribute for bacon purchase was price followed by fat:lean appearance and then flavor. Three consumer clusters were identified with distinct preferences. For 2 clusters, price was not the primary attribute. Understanding preferences of distinct consumer clusters will enable manufacturers to target consumers and make more appealing bacon. Adaptive Choice-Based Conjoint (ACBC) is a research technique that allows consumers to react to assembled products and identify product attributes that they prefer. Kano questions allow researchers to look at the individual aspects of a product and understand consumer sentiment and expectations towards those product qualities while Maximum Difference scaling allows consumers to directly rank single attributes of a product relative to one another. A combination of these 3 approaches can provide key understandings on consumer perception of retail bacon allowing companies to optimize and maximize their development and advertising resources. © 2017 Institute of Food Technologists®.

Assessment of body fat based on potential function clustering segmentation of computed tomography images

NASA Astrophysics Data System (ADS)

Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong

2005-01-01

In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.

Screening interspecific hybrids of Populus (P. ciliata x maximowiczii) using AFLP markers.

PubMed

Chauhan, N; Negi, M S; Sabharwal, V; Khurana, D K; Lakshmikumaran, M

2004-03-01

Hybrids of Populus ciliata x maximowiczii are very vigorous and outperform both the parents in growth performance and yield. Genetic evaluation of 24 of these interspecific hybrids along with the two mother trees ( Populus ciliata), and five male-parent ( Populus maximowiczii) genotypes was carried out using the AFLP marker assay. Eight AFLP primer combinations detected 428 markers, of which 280 (66%) were polymorphic. Genetic relationships within the samples were evaluated by generating the similarity matrix based on Jaccard's coefficient. The phenetic dendrograms, as well as the PCO plots, separated the hybrids and the two parent species into three distinct clusters. The hybrids grouped closer to the P. ciliata (female parent) cluster as compared to the P. maximowiczii (male parent) cluster. The hybrid cluster contained internal groupings, which correlated to some extent with growth performance. The four best performing hybrids (42m1, 65m1, 23m2, Cm2-5-20/91) formed a distinct sub-cluster. Data from a single primer combination was sufficient for distinguishing the hybrids from the parents and assigning paternity. The hybrids showed 22 markers that were absent in P. ciliata but were monomorphically present in all the hybrids, suggesting outcrossing and common paternity. Further, these 22 markers were found in all the P. maximowiczii genotypes confirming it as the male parent. These male-specific markers can be converted to SCAR markers and used for rapid screening of the P.ciliata x maximowiczii hybrids. The primer combination E-AAC x M-CAA was identified as most suitable for ascertaining true hybridity. AFLP proves to be a useful tool for screening of P. ciliata x maximowiczii hybrids at the early stages of development.

Big Data and Dysmenorrhea: What Questions Do Women and Men Ask About Menstrual Pain?

PubMed

Chen, Chen X; Groves, Doyle; Miller, Wendy R; Carpenter, Janet S

2018-04-30

Menstrual pain is highly prevalent among women of reproductive age. As the general public increasingly obtains health information online, Big Data from online platforms provide novel sources to understand the public's perspectives and information needs about menstrual pain. The study's purpose was to describe salient queries about dysmenorrhea using Big Data from a question and answer platform. We performed text-mining of 1.9 billion queries from ChaCha, a United States-based question and answer platform. Dysmenorrhea-related queries were identified by using keyword searching. Each relevant query was split into token words (i.e., meaningful words or phrases) and stop words (i.e., not meaningful functional words). Word Adjacency Graph (WAG) modeling was used to detect clusters of queries and visualize the range of dysmenorrhea-related topics. We constructed two WAG models respectively from queries by women of reproductive age and bymen. Salient themes were identified through inspecting clusters of WAG models. We identified two subsets of queries: Subset 1 contained 507,327 queries from women aged 13-50 years. Subset 2 contained 113,888 queries from men aged 13 or above. WAG modeling revealed topic clusters for each subset. Between female and male subsets, topic clusters overlapped on dysmenorrhea symptoms and management. Among female queries, there were distinctive topics on approaching menstrual pain at school and menstrual pain-related conditions; while among male queries, there was a distinctive cluster of queries on menstrual pain from male's perspectives. Big Data mining of the ChaCha ® question and answer service revealed a series of information needs among women and men on menstrual pain. Findings may be useful in structuring the content and informing the delivery platform for educational interventions.

Specialized piRNA Pathways Act in Germline and Somatic Tissues of the Drosophila Ovary

PubMed Central

Malone, Colin D.; Brennecke, Julius; Dus, Monica; Stark, Alexander; McCombie, W. Richard; Sachidanandam, Ravi; Hannon, Gregory J.

2010-01-01

SUMMARY In Drosophila gonads, Piwi proteins and associated piRNAs collaborate with additional factors to form a small RNA-based immune system that silences mobile elements. Here, we analyzed nine Drosophila piRNA pathway mutants for their impacts on both small RNA populations and the subcellular localization patterns of Piwi proteins. We find that distinct piRNA pathways with differing components function in ovarian germ and somatic cells. In the soma, Piwi acts singularly with the conserved flamenco piRNA cluster to enforce silencing of retroviral elements that may propagate by infecting neighboring germ cells. In the germline, silencing programs encoded within piRNA clusters are optimized via a slicer-dependent amplification loop to suppress a broad spectrum of elements. The classes of transposons targeted by germline and somatic piRNA clusters, though not the precise elements, are conserved among Drosophilids, demonstrating that the architecture of piRNA clusters has coevolved with the transposons that they are tasked to control. PMID:19395010

Typologies of Post-divorce Coparenting and Parental Well-Being, Parenting Quality and Children's Psychological Adjustment.

PubMed

Lamela, Diogo; Figueiredo, Bárbara; Bastos, Alice; Feinberg, Mark

2016-10-01

The aim of this study was to identify post-divorce coparenting profiles and examine whether these profiles differentiate between levels of parents' well-being, parenting practices, and children's psychological problems. Cluster analysis was conducted with Portuguese heterosexual divorced parents (N = 314) to yield distinct post-divorce coparenting patterns. Clusters were based on parents' self-reported coparenting relationship assessed along four dimensions: agreement, exposure to conflict, undermining/support, and division of labor. A three cluster solution was found and replicated. Parents in the high-conflict coparenting group exhibited significantly lower life satisfaction, as well as significantly higher divorce-related negative affect and inconsistent parenting than parents in undermining and cooperative coparenting clusters. The cooperative coparenting group reported higher levels of positive family functioning and lower externalizing and internalizing problems in their children. These results suggested that a positive coparenting alliance may be a protective factor for individual and family outcomes after parental divorce.

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

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

Is transgendered male androphilia familial in non-Western populations? The case of a Samoan village.

PubMed

Vanderlaan, Doug P; Vokey, John R; Vasey, Paul L

2013-04-01

In Western populations, male gender atypicality (i.e., cross-gender behavior and identity) and male androphilia (i.e., sexual attraction to adult males) tend to cluster in particular families. Here, we examined whether this familial clustering effect extended to non-Western populations by examining the genealogical relationships of 17 Samoan transgendered androphilic males, known locally as fa'afafine, who were born in the same rural Samoan village. Specifically, we compared the genealogies of these 17 fa'afafine and those of 17 age-matched comparison males born in the same village. In addition to familial clustering, we examined birth order, sibship sex ratio, and sibship size. The fa'afafine were significantly later born than the comparison males and clustered into five and 16 distinct lineages, respectively, which constituted a statistically significant degree of family clustering among the 17 fa'afafine. Hence, the present study indicated that transgendered male androphilia is familial in this particular Samoan village, thus adding to a growing literature demonstrating that male androphilia and gender atypicality have consistent developmental correlates across populations. Discussion focused on the possible bases of this familial clustering effect and directions for future research.

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

Multiple Basinal Fluid Events in the Lower Belt Supergroup, Montana: Constraints From CHIME Ages and REE Patterns of Monazites

NASA Astrophysics Data System (ADS)

Gonzalez-Alvarez, I.; Kusiak, M. A.

2004-05-01

Chemical dates (CHIME) on 105 spots and REE patterns of monazites were obtained from coarse sandstones and siltstones in the Mesoproterozoic siliciclastic Appekunny and Grinnell formations, lower Belt Supergroup, Montana, by EMPA. At least three post-depositional events induced by basinal fluids can be recognized: (a) red coloration accompanied by a major K-addition; (b) a green overprint of red siltstones; and (c) dolomitization. Fluid advection in the unmineralized lower Belt is pervasive and may have been alkaline and oxidizing. These three events progressively modified the primary geochemical characteristics of the siliciclastic rocks. Calculated ages show similar ranges in the fine and coarse-grained facies. For siltstones there are two age clusters: (1) at 1,801 ± 21 to 1,968 ± 26 Ma, as well as (2) at 854 ± 7 to 962 ± 13 Ma. Coarse sandstones show similar age clusters (3) at 1,831 ± 14 to 1,982 ± 12 Ma, and (4) at 803 ± 6 to 944 ± 9 Ma. A wide range of dates plots between the clusters for both facies. Clusters (1) and (3) are interpreted as the result of detrital monazites from a source area ~1.8 to 1.9 Ga old. Mineralogical variations and trace element systematic reveal basinal brines, which mobilized MREE and HREE, locally generating secondary monazites, influencing large domains of the lower Belt. The lower Belt Supergroup is estimated to have been deposited between 1.47 Ga and 1.45 Ga; consequently, the second age cluster for sandstones and siltstones is viewed as constraining the timeframe of a major basinal fluid event at ~0.80 to 0.96 Ga. That event is clearly distinct from the hydrothermal system associated with the Sullivan sedex base metal deposit at the base of the Belt. Ages between the clusters are interpreted either as secondary, formed during additional basinal fluid events or as reset of detrital monazites. Accordingly, the Belt basin was intermittently an open system to fluids from ~1.47 to ~0.80 Ga. Chondrite-normalized REE patterns for both facies display three unusual features: (A) on a linear scale for both facies for clusters (1) and (3) monazites reveal a straight line from La to Sm. For clusters (2) and (4) the profiles between La and Sm are concave or convex; concave profiles are produced mainly because of the Ce values. All reset monazites have convex or concave La-Sm profiles; (B) LREE/HREE and La/Y ratios average values for both facies in clusters (1) and (3) exhibit distinctively lower values than in clusters (2) and (4); (C) on log scale, charts show an unusually heterogeneous MREE and HREE profile for all monazites.

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.

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

Chill, Be Cool Man: African American Men, Identity, Coping, and Aggressive Ideation

PubMed Central

Thomas, Alvin; Hammond, Wizdom Powell; Kohn-Wood, Laura P.

2016-01-01

Aggression is an important correlate of violence, depression, coping, and suicide among emerging young African American males. Yet most researchers treat aggression deterministically, fail to address cultural factors, or consider the potential for individual characteristics to exert an intersectional influence on this psychosocial outcome. Addressing this gap, we consider the moderating effect of coping on the relationship between masculine and racial identity and aggressive ideation among African American males (N = 128) drawn from 2 large Midwestern universities. Using the phenomenological variant of ecological systems theory and person-centered methodology as a guide, hierarchical cluster analysis grouped participants into profile groups based on their responses to both a measure of racial identity and a measure of masculine identity. Results from the cluster analysis revealed 3 distinct identity clusters: Identity Ambivalent, Identity Appraising, and Identity Consolidated. Although these cluster groups did not differ with regard to coping, significant differences were observed between cluster groups in relation to aggressive ideation. Further, a full model with identity profile clusters, coping, and aggressive ideation indicates that cluster membership significantly moderates the relationship between coping and aggressive ideation. The implications of these data for intersecting identities of African American men, and the association of identity and outcomes related to risk for mental health and violence, are discussed. PMID:25090145

Chill, be cool man: African American men, identity, coping, and aggressive ideation.

PubMed

Thomas, Alvin; Hammond, Wizdom Powell; Kohn-Wood, Laura P

2015-07-01

Aggression is an important correlate of violence, depression, coping, and suicide among emerging young African American males. Yet most researchers treat aggression deterministically, fail to address cultural factors, or consider the potential for individual characteristics to exert an intersectional influence on this psychosocial outcome. Addressing this gap, we consider the moderating effect of coping on the relationship between masculine and racial identity and aggressive ideation among African American males (N = 128) drawn from 2 large Midwestern universities. Using the phenomenological variant of ecological systems theory and person-centered methodology as a guide, hierarchical cluster analysis grouped participants into profile groups based on their responses to both a measure of racial identity and a measure of masculine identity. Results from the cluster analysis revealed 3 distinct identity clusters: Identity Ambivalent, Identity Appraising, and Identity Consolidated. Although these cluster groups did not differ with regard to coping, significant differences were observed between cluster groups in relation to aggressive ideation. Further, a full model with identity profile clusters, coping, and aggressive ideation indicates that cluster membership significantly moderates the relationship between coping and aggressive ideation. The implications of these data for intersecting identities of African American men, and the association of identity and outcomes related to risk for mental health and violence, are discussed. (c) 2015 APA, all rights reserved).

Obesigenic families: parents’ physical activity and dietary intake patterns predict girls’ risk of overweight

PubMed Central

Davison, K Krahnstoever; Birch, L Lipps

2008-01-01

OBJECTIVE To determine whether obesigenic families can be identified based on mothers’ and fathers’ dietary and activity patterns. METHODS A total of 197 girls and their parents were assessed when girls were 5 y old; 192 families were reassessed when girls were 7 y old. Measures of parents’ physical activity and dietary intake were obtained and entered into a cluster analysis to assess whether distinct family clusters could be identified. Girls’ skinfold thickness and body mass index (BMI) were also assessed and were used to examine the predictive validity of the clusters. RESULTS Obesigenic and a non-obesigenic family clusters were identified. Mothers and fathers in the obesigenic cluster reported high levels of dietary intake and low levels of physical activity, while mothers and fathers in the non-obesigenic cluster reported low levels of dietary intake and high levels of activity. Girls from families in the obesigenic cluster had significantly higher BMI and skinfold thickness values at age 7 and showed significantly greater increases in BMI and skinfold thickness from ages 5 to 7 y than girls from non-obesigenic families; differences were reduced but not eliminated after controlling for parents’ BMI. CONCLUSIONS Obesigenic families, defined in terms of parents’ activity and dietary patterns, can be used predict children’s risk of obesity. PMID:12187395

Chandra Observation of the WAT Radio Source/ICM Interaction in Abell 623

NASA Astrophysics Data System (ADS)

Anand, Gagandeep; Blanton, Elizabeth L.; Randall, Scott W.; Paterno-Mahler, Rachel; Douglass, Edmund

2017-01-01

Galaxy clusters are important objects for studying the physics of the intracluster medium (ICM), galaxy formation and evolution, and cosmological parameters. Clusters containing wide-angle tail (WAT) radio sources are particularly valuable for studies of the interaction between these sources and the surrounding ICM. These sources are thought to form when the ram pressure from the ICM caused by the relative motion between the host radio galaxy and the cluster bends the radio lobes into a distinct wide-angle morphology. We present our results from the analysis of a Chandra observation of the nearby WAT hosting galaxy cluster Abell 623. A clear decrement in X-ray emission is coincident with the southern radio lobe, consistent with being a cavity carved out by the radio source. We present profiles of surface brightness, temperature, density, and pressure and find evidence for a possible shock. Based on the X-ray pressure in the vicinity of the radio lobes and assumptions about the content of the lobes, we estimate the relative ICM velocity required to bend the lobes into the observed angle. We also present spectral model fits to the overall diffuse cluster emission and see no strong signature for a cool core. The sum of the evidence indicates that Abell 623 may be undergoing a large scale cluster-cluster merger.

Revealing cancer subtypes with higher-order correlations applied to imaging and omics data.

PubMed

Graim, Kiley; Liu, Tiffany Ting; Achrol, Achal S; Paull, Evan O; Newton, Yulia; Chang, Steven D; Harsh, Griffith R; Cordero, Sergio P; Rubin, Daniel L; Stuart, Joshua M

2017-03-31

Patient stratification to identify subtypes with different disease manifestations, severity, and expected survival time is a critical task in cancer diagnosis and treatment. While stratification approaches using various biomarkers (including high-throughput gene expression measurements) for patient-to-patient comparisons have been successful in elucidating previously unseen subtypes, there remains an untapped potential of incorporating various genotypic and phenotypic data to discover novel or improved groupings. Here, we present HOCUS, a unified analytical framework for patient stratification that uses a community detection technique to extract subtypes out of sparse patient measurements. HOCUS constructs a patient-to-patient network from similarities in the data and iteratively groups and reconstructs the network into higher order clusters. We investigate the merits of using higher-order correlations to cluster samples of cancer patients in terms of their associations with survival outcomes. In an initial test of the method, the approach identifies cancer subtypes in mutation data of glioblastoma, ovarian, breast, prostate, and bladder cancers. In several cases, HOCUS provides an improvement over using the molecular features directly to compare samples. Application of HOCUS to glioblastoma images reveals a size and location classification of tumors that improves over human expert-based stratification. Subtypes based on higher order features can reveal comparable or distinct groupings. The distinct solutions can provide biologically- and treatment-relevant solutions that are just as significant as solutions based on the original data.

Evidence for cluster shape effects on the kinetic energy spectrum in thermionic emission.

PubMed

Calvo, F; Lépine, F; Baguenard, B; Pagliarulo, F; Concina, B; Bordas, C; Parneix, P

2007-11-28

Experimental kinetic energy release distributions obtained for the thermionic emission from C(n) (-) clusters, 10< or =n< or =20, exhibit significant non-Boltzmann variations. Using phase space theory, these different features are analyzed and interpreted as the consequence of contrasting shapes in the daughter clusters; linear and nonlinear isomers have clearly distinct signatures. These results provide a novel indirect structural probe for atomic clusters associated with their thermionic emission spectra.

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

Mathematical Geology

ERIC Educational Resources Information Center

Merriam, Daniel F.

1978-01-01

Geomathematics is a developing field that is being used in practical applications. Classification is an important element and the dynamic-cluster method (DCM), a nonhierarchial procedure, was introduced this past year. A method for testing the degree of cluster distinctness was developed also. (MA)

Spectroscopic constraints on the form of the stellar cluster mass function

NASA Astrophysics Data System (ADS)

Bastian, N.; Konstantopoulos, I. S.; Trancho, G.; Weisz, D. R.; Larsen, S. S.; Fouesneau, M.; Kaschinski, C. B.; Gieles, M.

2012-05-01

This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (<10 Myr) clusters, however this has proven difficult due to low-number statistics. In this contribution we use an alternative method based on the luminosities of the brightest clusters, combined with their ages. The advantages are that more clusters can be used and that the ICMF leaves a distinct pattern on the global relation between the cluster luminosity and median age within a population. If a truncation is present, a generic prediction (nearly independent of the cluster disruption law adopted) is that the median age of bright clusters should be younger than that of fainter clusters. In the case of an non-truncated ICMF, the median age should be independent of cluster luminosity. Here, we present optical spectroscopy of twelve young stellar clusters in the face-on spiral galaxy NGC 2997. The spectra are used to estimate the age of each cluster, and the brightness of the clusters is taken from the literature. The observations are compared with the model expectations of Larsen (2009, A&A, 494, 539) for various ICMF forms and both mass dependent and mass independent cluster disruption. While there exists some degeneracy between the truncation mass and the amount of mass independent disruption, the observations favour a truncated ICMF. For low or modest amounts of mass independent disruption, a truncation mass of 5-6 × 105 M⊙ is estimated, consistent with previous determinations. Additionally, we investigate possible truncations in the ICMF in the spiral galaxy M 83, the interacting Antennae galaxies, and the collection of spiral and dwarf galaxies present in Larsen (2009, A&A, 494, 539) based on photometric catalogues taken from the literature, and find that all catalogues are consistent with having a truncation in the cluster mass functions. However for the case of the Antennae, we find a truncation mass of a few × 106M⊙ , suggesting a dependence on the environment, as has been previously suggested.

Stable isotope phenotyping via cluster analysis of NanoSIMS data as a method for characterizing distinct microbial ecophysiologies and sulfur-cycling in the environment

NASA Astrophysics Data System (ADS)

Dawson, K.; Scheller, S.; Dillon, J. G.; Orphan, V. J.

2016-12-01

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned 2200 cellular regions of interest (ROIs) into 5 distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA.

Stable Isotope Phenotyping via Cluster Analysis of NanoSIMS Data As a Method for Characterizing Distinct Microbial Ecophysiologies and Sulfur-Cycling in the Environment

PubMed Central

Dawson, Katherine S.; Scheller, Silvan; Dillon, Jesse G.; Orphan, Victoria J.

2016-01-01

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned ~2200 cellular regions of interest (ROIs) into five distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA. PMID:27303371

G-protein coupled receptor expression patterns delineate medulloblastoma subgroups

PubMed Central

2013-01-01

Background Medulloblastoma is the most common malignant brain tumor in children. Genetic profiling has identified four principle tumor subgroups; each subgroup is characterized by different initiating mutations, genetic and clinical profiles, and prognoses. The two most well-defined subgroups are caused by overactive signaling in the WNT and SHH mitogenic pathways; less is understood about Groups 3 and 4 medulloblastoma. Identification of tumor subgroup using molecular classification is set to become an important component of medulloblastoma diagnosis and staging, and will likely guide therapeutic options. However, thus far, few druggable targets have emerged. G-protein coupled receptors (GPCRs) possess characteristics that make them ideal targets for molecular imaging and therapeutics; drugs targeting GPCRs account for 30-40% of all current pharmaceuticals. While expression patterns of many proteins in human medulloblastoma subgroups have been discerned, the expression pattern of GPCRs in medulloblastoma has not been investigated. We hypothesized that analysis of GPCR expression would identify clear subsets of medulloblastoma and suggest distinct GPCRs that might serve as molecular targets for both imaging and therapy. Results Our study found that medulloblastoma tumors fall into distinct clusters based solely on GPCR expression patterns. Normal cerebellum clustered separately from the tumor samples. Further, two of the tumor clusters correspond with high fidelity to the WNT and SHH subgroups of medulloblastoma. Distinct over-expressed GPCRs emerge; for example, LGR5 and GPR64 are significantly and uniquely over-expressed in the WNT subgroup of tumors, while PTGER4 is over-expressed in the SHH subgroup. Uniquely under-expressed GPCRs were also observed. Our key findings were independently validated using a large international dataset. Conclusions Our results identify GPCRs with potential to act as imaging and therapeutic targets. Elucidating tumorigenic pathways is a secondary benefit to identifying differential GPCR expression patterns in medulloblastoma tumors. PMID:24252460

Spectroscopy of Luminous Compact Blue Galaxies in Distant Clusters. I. Spectroscopic Data

NASA Astrophysics Data System (ADS)

Crawford, Steven M.; Wirth, Gregory D.; Bershady, Matthew A.; Hon, Kimo

2011-11-01

We used the DEIMOS spectrograph on the Keck II Telescope to obtain spectra of galaxies in the fields of five distant, rich galaxy clusters over the redshift range 0.5 < z < 0.9 in a search for luminous compact blue galaxies (LCBGs). Unlike traditional studies of galaxy clusters, we preferentially targeted blue cluster members identified via multi-band photometric pre-selection based on imaging data from the WIYN telescope. Of the 1288 sources that we targeted, we determined secure spectroscopic redshifts for 848 sources, yielding a total success rate of 66%. Our redshift measurements are in good agreement with those previously reported in the literature, except for 11 targets which we believe were previously in error. Within our sample, we confirm the presence of 53 LCBGs in the five galaxy clusters. The clusters all stand out as distinct peaks in the redshift distribution of LCBGs with the average number density of LCBGs ranging from 1.65 ± 0.25 Mpc-3 at z = 0.55 to 3.13 ± 0.65 Mpc-3 at z = 0.8. The number density of LCBGs in clusters exceeds the field density by a factor of 749 ± 116 at z = 0.55; at z = 0.8, the corresponding ratio is E = 416 ± 95. At z = 0.55, this enhancement is well above that seen for blue galaxies or the overall cluster population, indicating that LCBGs are preferentially triggered in high-density environments at intermediate redshifts. Based in part on data obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA, and was made possible by the generous financial support of the W. M. Keck Foundation.

A pyrosequencing assay for the quantitative methylation analysis of the PCDHB gene cluster, the major factor in neuroblastoma methylator phenotype.

PubMed

Banelli, Barbara; Brigati, Claudio; Di Vinci, Angela; Casciano, Ida; Forlani, Alessandra; Borzì, Luana; Allemanni, Giorgio; Romani, Massimo

2012-03-01

Epigenetic alterations are hallmarks of cancer and powerful biomarkers, whose clinical utilization is made difficult by the absence of standardization and of common methods of data interpretation. The coordinate methylation of many loci in cancer is defined as 'CpG island methylator phenotype' (CIMP) and identifies clinically distinct groups of patients. In neuroblastoma (NB), CIMP is defined by a methylation signature, which includes different loci, but its predictive power on outcome is entirely recapitulated by the PCDHB cluster only. We have developed a robust and cost-effective pyrosequencing-based assay that could facilitate the clinical application of CIMP in NB. This assay permits the unbiased simultaneous amplification and sequencing of 17 out of 19 genes of the PCDHB cluster for quantitative methylation analysis, taking into account all the sequence variations. As some of these variations were at CpG doublets, we bypassed the data interpretation conducted by the methylation analysis software to assign the corrected methylation value at these sites. The final result of the assay is the mean methylation level of 17 gene fragments in the protocadherin B cluster (PCDHB) cluster. We have utilized this assay to compare the methylation levels of the PCDHB cluster between high-risk and very low-risk NB patients, confirming the predictive value of CIMP. Our results demonstrate that the pyrosequencing-based assay herein described is a powerful instrument for the analysis of this gene cluster that may simplify the data comparison between different laboratories and, in perspective, could facilitate its clinical application. Furthermore, our results demonstrate that, in principle, pyrosequencing can be efficiently utilized for the methylation analysis of gene clusters with high internal homologies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Genetic diversity studies in pea (Pisum sativum L.) using simple sequence repeat markers.

PubMed

Kumari, P; Basal, N; Singh, A K; Rai, V P; Srivastava, C P; Singh, P K

2013-03-13

The genetic diversity among 28 pea (Pisum sativum L.) genotypes was analyzed using 32 simple sequence repeat markers. A total of 44 polymorphic bands, with an average of 2.1 bands per primer, were obtained. The polymorphism information content ranged from 0.657 to 0.309 with an average of 0.493. The variation in genetic diversity among these cultivars ranged from 0.11 to 0.73. Cluster analysis based on Jaccard's similarity coefficient using the unweighted pair-group method with arithmetic mean (UPGMA) revealed 2 distinct clusters, I and II, comprising 6 and 22 genotypes, respectively. Cluster II was further differentiated into 2 subclusters, IIA and IIB, with 12 and 10 genotypes, respectively. Principal component (PC) analysis revealed results similar to those of UPGMA. The first, second, and third PCs contributed 21.6, 16.1, and 14.0% of the variation, respectively; cumulative variation of the first 3 PCs was 51.7%.

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.

Compensated Crystal Assemblies for Type-II Entangled Photon Generation in Quantum Cluster States

DTIC Science & Technology

2010-03-01

in quantum computational architectures that operate by principles entirely distinct from any based on classical physics. In contrast with other...of the SPDC spectral function, to enable applications in regions that have not been accessible with other methods. Quantum Information and Computation ...Eliminating frequency and space-time correlations in multi-photon states, PRA 64, 063815, 2001 [2]A. Zeilinger et.al. Experimental One-way computing

Analytical network process based optimum cluster head selection in wireless sensor network.

PubMed

Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Analytical network process based optimum cluster head selection in wireless sensor network

PubMed Central

Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. PMID:28719616

Anticancer Properties of Distinct Antimalarial Drug Classes

PubMed Central

Hooft van Huijsduijnen, Rob; Guy, R. Kiplin; Chibale, Kelly; Haynes, Richard K.; Peitz, Ingmar; Kelter, Gerhard; Phillips, Margaret A.; Vennerstrom, Jonathan L.; Yuthavong, Yongyuth; Wells, Timothy N. C.

2013-01-01

We have tested five distinct classes of established and experimental antimalarial drugs for their anticancer potential, using a panel of 91 human cancer lines. Three classes of drugs: artemisinins, synthetic peroxides and DHFR (dihydrofolate reductase) inhibitors effected potent inhibition of proliferation with IC50s in the nM- low µM range, whereas a DHODH (dihydroorotate dehydrogenase) and a putative kinase inhibitor displayed no activity. Furthermore, significant synergies were identified with erlotinib, imatinib, cisplatin, dasatinib and vincristine. Cluster analysis of the antimalarials based on their differential inhibition of the various cancer lines clearly segregated the synthetic peroxides OZ277 and OZ439 from the artemisinin cluster that included artesunate, dihydroartemisinin and artemisone, and from the DHFR inhibitors pyrimethamine and P218 (a parasite DHFR inhibitor), emphasizing their shared mode of action. In order to further understand the basis of the selectivity of these compounds against different cancers, microarray-based gene expression data for 85 of the used cell lines were generated. For each compound, distinct sets of genes were identified whose expression significantly correlated with compound sensitivity. Several of the antimalarials tested in this study have well-established and excellent safety profiles with a plasma exposure, when conservatively used in malaria, that is well above the IC50s that we identified in this study. Given their unique mode of action and potential for unique synergies with established anticancer drugs, our results provide a strong basis to further explore the potential application of these compounds in cancer in pre-clinical or and clinical settings. PMID:24391728

Cirripede Cypris Antennules: How Much Structural Variation Exists Among Balanomorphan Species from Hard-Bottom Habitats?

PubMed

Chan, Benny K K; Sari, Alireza; Høeg, Jens T

2017-10-01

Barnacle cypris antennules are important for substratum attachment during settlement and on through metamorphosis from the larval stage to sessile adult. Studies on the morphology of cirripede cyprids are mostly qualitative, based on descriptions from images obtained using a scanning electron microscope (SEM). To our knowledge, our study is the first to use scanning electron microscopy to quantify overall structural diversity in cypris antennules by measuring 26 morphological parameters, including the structure of sensory organs. We analyzed cyprids from seven species of balanomorphan barnacles inhabiting rocky shore communities; for comparison, we also included a sponge-inhabiting balanomorphan and a verrucomorphan species. Multivariate analysis of the structural parameters resulted in two distinct clusters of species. From nonmetric multidimensional scaling plots, the sponge-inhabiting Balanus spongicola and Verruca stroemia formed one cluster, while the other balanomorphan species, all from hard bottoms, grouped together in the other cluster. The shape of the attachment disk on segment 3 is the key parameter responsible for the separation into two clusters. The present results show that species from a coastal hard-bottom habitat may share a nearly identical antennular structure that is distinct from barnacles from other habitats, and this finding supports the fact that such species also have rather similar reactions to substratum cues during settlement. Any differences that may be found in settlement biology among such species must therefore be due either to differences in the properties of their adhesive mechanisms or to the way that sensory stimuli are detected by virtually identical setae and processed into settlement behavior by the cyprid.

Cell Lineage Analysis of the Mammalian Female Germline

PubMed Central

Elbaz, Judith; Jinich, Adrian; Chapal-Ilani, Noa; Maruvka, Yosef E.; Nevo, Nava; Marx, Zipora; Horovitz, Inna; Wasserstrom, Adam; Mayo, Avi; Shur, Irena; Benayahu, Dafna; Skorecki, Karl; Segal, Eran; Dekel, Nava; Shapiro, Ehud

2012-01-01

Fundamental aspects of embryonic and post-natal development, including maintenance of the mammalian female germline, are largely unknown. Here we employ a retrospective, phylogenetic-based method for reconstructing cell lineage trees utilizing somatic mutations accumulated in microsatellites, to study female germline dynamics in mice. Reconstructed cell lineage trees can be used to estimate lineage relationships between different cell types, as well as cell depth (number of cell divisions since the zygote). We show that, in the reconstructed mouse cell lineage trees, oocytes form clusters that are separate from hematopoietic and mesenchymal stem cells, both in young and old mice, indicating that these populations belong to distinct lineages. Furthermore, while cumulus cells sampled from different ovarian follicles are distinctly clustered on the reconstructed trees, oocytes from the left and right ovaries are not, suggesting a mixing of their progenitor pools. We also observed an increase in oocyte depth with mouse age, which can be explained either by depth-guided selection of oocytes for ovulation or by post-natal renewal. Overall, our study sheds light on substantial novel aspects of female germline preservation and development. PMID:22383887

Bayesian Analysis and Characterization of Multiple Populations in Galactic Globular Clusters

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, Rachel A.; Stenning, David; Sarajedini, Ata; von Hippel, Ted; van Dyk, David A.; Robinson, Elliot; Stein, Nathan; Jefferys, William H.; BASE-9, HST UVIS Globular Cluster Treasury Program

2017-01-01

Globular clusters have long been important tools to unlock the early history of galaxies. Thus, it is crucial we understand the formation and characteristics of the globular clusters (GCs) themselves. Historically, GCs were thought to be simple and largely homogeneous populations, formed via collapse of a single molecular cloud. However, this classical view has been overwhelmingly invalidated by recent work. It is now clear that the vast majority of globular clusters in our Galaxy host two or more chemically distinct populations of stars, with variations in helium and light elements at discrete abundance levels. No coherent story has arisen that is able to fully explain the formation of multiple populations in globular clusters nor the mechanisms that drive stochastic variations from cluster to cluster.We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic Globular Clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of 0.04 to 0.11. Because adequate models varying in CNO are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster. We also find that the proportion of the first population of stars increases with mass. Our results are examined in the context of proposed globular cluster formation scenarios.

[Prognostic differences of phenotypes in pT1-2N0 invasive breast cancer: a large cohort study with cluster analysis].

PubMed

Wang, Z; Wang, W H; Wang, S L; Jin, J; Song, Y W; Liu, Y P; Ren, H; Fang, H; Tang, Y; Chen, B; Qi, S N; Lu, N N; Li, N; Tang, Y; Liu, X F; Yu, Z H; Li, Y X

2016-06-23

To find phenotypic subgroups of patients with pT1-2N0 invasive breast cancer by means of cluster analysis and estimate the prognosis and clinicopathological features of these subgroups. From 1999 to 2013, 4979 patients with pT1-2N0 invasive breast cancer were recruited for hierarchical clustering analysis. Age (≤40, 41-70, 70+ years), size of primary tumor, pathological type, grade of differentiation, microvascular invasion, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER-2) were chosen as distance metric between patients. Hierarchical cluster analysis was performed using Ward's method. Cophenetic correlation coefficient (CPCC) and Spearman correlation coefficient were used to validate clustering structures. The CPCC was 0.603. The Spearman correlation coefficient was 0.617 (P<0.001), which indicated a good fit of hierarchy to the data. A twelve-cluster model seemed to best illustrate our patient cohort. Patients in cluster 5, 9 and 12 had best prognosis and were characterized by age >40 years, smaller primary tumor, lower histologic grade, positive ER and PR status, and mainly negative HER-2. Patients in the cluster 1 and 11 had the worst prognosis, The cluster 1 was characterized by a larger tumor, higher grade and negative ER and PR status, while the cluster 11 was characterized by positive microvascular invasion. Patients in other 7 clusters had a moderate prognosis, and patients in each cluster had distinctive clinicopathological features and recurrent patterns. This study identified distinctive clinicopathologic phenotypes in a large cohort of patients with pT1-2N0 breast cancer through hierarchical clustering and revealed different prognosis. This integrative model may help physicians to make more personalized decisions regarding adjuvant therapy.

Chemotaxonomy of heterocystous cyanobacteria using FAME profiling as species markers.

PubMed

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

2012-07-01

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

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

Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

NASA Astrophysics Data System (ADS)

Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

2014-03-01

Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

Classification of patients based on their evaluation of hospital outcomes: cluster analysis following a national survey in Norway

PubMed Central

2013-01-01

Background A general trend towards positive patient-reported evaluations of hospitals could be taken as a sign that most patients form a homogeneous, reasonably pleased group, and consequently that there is little need for quality improvement. The objective of this study was to explore this assumption by identifying and statistically validating clusters of patients based on their evaluation of outcomes related to overall satisfaction, malpractice and benefit of treatment. Methods Data were collected using a national patient-experience survey of 61 hospitals in the 4 health regions in Norway during spring 2011. Postal questionnaires were mailed to 23,420 patients after their discharge from hospital. Cluster analysis was performed to identify response clusters of patients, based on their responses to single items about overall patient satisfaction, benefit of treatment and perception of malpractice. Results Cluster analysis identified six response groups, including one cluster with systematically poorer evaluation across outcomes (18.5% of patients) and one small outlier group (5.3%) with very poor scores across all outcomes. One-Way ANOVA with post-hoc tests showed that most differences between the six response groups on the three outcome items were significant. The response groups were significantly associated with nine patient-experience indicators (p < 0.001), and all groups were significantly different from each of the other groups on a majority of the patient-experience indicators. Clusters were significantly associated with age, education, self-perceived health, gender, and the degree to write open comments in the questionnaire. Conclusions The study identified five response clusters with distinct patient-reported outcome scores, in addition to a heterogeneous outlier group with very poor scores across all outcomes. The outlier group and the cluster with systematically poorer evaluation across outcomes comprised almost one-quarter of all patients, clearly demonstrating the need to tailor quality initiatives and improve patient-perceived quality in hospitals. More research on patient clustering in patient evaluation is needed, as well as standardization of methodology to increase comparability across studies. PMID:23433450

Anatomical relationships between serotonin 5-HT2A and dopamine D2 receptors in living human brain.

PubMed

Ishii, Tatsuya; Kimura, Yasuyuki; Ichise, Masanori; Takahata, Keisuke; Kitamura, Soichiro; Moriguchi, Sho; Kubota, Manabu; Zhang, Ming-Rong; Yamada, Makiko; Higuchi, Makoto; Okubo, Yoshinori; Suhara, Tetsuya

2017-01-01

Seven healthy volunteers underwent PET scans with [18F]altanserin and [11C]FLB 457 for 5-HT2A and D2 receptors, respectively. As a measure of receptor density, a binding potential (BP) was calculated from PET data for 76 cerebral cortical regions. A correlation matrix was calculated between the binding potentials of [18F]altanserin and [11C]FLB 457 for those regions. The regional relationships were investigated using a bicluster analysis of the correlation matrix with an iterative signature algorithm. We identified two clusters of regions. The first cluster identified a distinct profile of correlation coefficients between 5-HT2A and D2 receptors, with the former in regions related to sensorimotor integration (supplementary motor area, superior parietal gyrus, and paracentral lobule) and the latter in most cortical regions. The second cluster identified another distinct profile of correlation coefficients between 5-HT2A receptors in the bilateral hippocampi and D2 receptors in most cortical regions. The observation of two distinct clusters in the correlation matrix suggests regional interactions between 5-HT2A and D2 receptors in sensorimotor integration and hippocampal function. A bicluster analysis of the correlation matrix of these neuroreceptors may be beneficial in understanding molecular networks in the human brain.

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.

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.

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

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

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

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.

Mothers of young children cluster into 4 groups based on psychographic food decision influencers.

PubMed

Byrd-Bredbenner, Carol; Abbot, Jaclyn Maurer; Cussler, Ellen

2008-08-01

This study explored how mothers grouped into clusters according to multiple psychographic food decision influencers and how the clusters differed in nutrient intake and nutrient content of their household food supply. Mothers (n = 201) completed a survey assessing basic demographic characteristics, food shopping and meal preparation activities, self and spouse employment, exposure to formal food or nutrition education, education level and occupation, weight status, nutrition and food preparation knowledge and skill, family member health and nutrition status, food decision influencer constructs, and dietary intake. In addition, an in-home inventory of 100 participants' household food supplies was conducted. Four distinct clusters presented when 26 psychographic food choice influencers were evaluated. These clusters appear to be valid and robust classifications of mothers in that they discriminated well on the psychographic variables used to construct the clusters as well as numerous other variables not used in the cluster analysis. In addition, the clusters appear to transcend demographic variables that often segment audiences (eg, race, mother's age, socioeconomic status), thereby adding a new dimension to the way in which this audience can be characterized. Furthermore, psychographically defined clusters predicted dietary quality. This study demonstrates that mothers are not a homogenous group and need to have their unique characteristics taken into consideration when designing strategies to promote health. These results can help health practitioners better understand factors affecting food decisions and tailor interventions to better meet the needs of mothers.

COVARIATE-ADAPTIVE CLUSTERING OF EXPOSURES FOR AIR POLLUTION EPIDEMIOLOGY COHORTS*

PubMed Central

Keller, Joshua P.; Drton, Mathias; Larson, Timothy; Kaufman, Joel D.; Sandler, Dale P.; Szpiro, Adam A.

2017-01-01

Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP. PMID:28572869

Characterizing the Temporal and Spatial Distribution of Earthquake Swarms in the Puerto Rico - Virgin Island Block

NASA Astrophysics Data System (ADS)

Hernandez, F. J.; Lopez, A. M.; Vanacore, E. A.

2017-12-01

The presence of earthquake swarms and clusters in the north and northeast of the island of Puerto Rico in the northeastern Caribbean have been recorded by the Puerto Rico Seismic Network (PRSN) since it started operations in 1974. Although clusters in the Puerto Rico-Virgin Island (PRVI) block have been observed for over forty years, the nature of their enigmatic occurrence is still poorly understood. In this study, the entire seismic catalog of the PRSN, of approximately 31,000 seismic events, has been limited to a sub-set of 18,000 events located all along north of Puerto Rico in an effort to characterize and understand the underlying mechanism of these clusters. This research uses two de-clustering methods to identify cluster events in the PRVI block. The first method, known as Model Independent Stochastic Declustering (MISD), filters the catalog sub-set into cluster and background seismic events, while the second method uses a spatio-temporal algorithm applied to the catalog in order to link the separate seismic events into clusters. After using these two methods, identified clusters were classified into either earthquake swarms or seismic sequences. Once identified, each cluster was analyzed to identify correlations against other clusters in their geographic region. Results from this research seek to : (1) unravel their earthquake clustering behavior through the use of different statistical methods and (2) better understand the mechanism for these clustering of earthquakes. Preliminary results have allowed to identify and classify 128 clusters categorized in 11 distinctive regions based on their centers, and their spatio-temporal distribution have been used to determine intra- and interplate dynamics.

Dietary patterns by cluster analysis in pregnant women: relationship with nutrient intakes and dietary patterns in 7-year-old offspring.

PubMed

Freitas-Vilela, Ana Amélia; Smith, Andrew D A C; Kac, Gilberto; Pearson, Rebecca M; Heron, Jon; Emond, Alan; Hibbeln, Joseph R; Castro, Maria Beatriz Trindade; Emmett, Pauline M

2017-04-01

Little is known about how dietary patterns of mothers and their children track over time. The objectives of this study are to obtain dietary patterns in pregnancy using cluster analysis, to examine women's mean nutrient intakes in each cluster and to compare the dietary patterns of mothers to those of their children. Pregnant women (n = 12 195) from the Avon Longitudinal Study of Parents and Children reported their frequency of consumption of 47 foods and food groups. These data were used to obtain dietary patterns during pregnancy by cluster analysis. The absolute and energy-adjusted nutrient intakes were compared between clusters. Women's dietary patterns were compared with previously derived clusters of their children at 7 years of age. Multinomial logistic regression was performed to evaluate relationships comparing maternal and offspring clusters. Three maternal clusters were identified: 'fruit and vegetables', 'meat and potatoes' and 'white bread and coffee'. After energy adjustment women in the 'fruit and vegetables' cluster had the highest mean nutrient intakes. Mothers in the 'fruit and vegetables' cluster were more likely than mothers in 'meat and potatoes' (adjusted odds ratio [OR]: 2.00; 95% Confidence Interval [CI]: 1.69-2.36) or 'white bread and coffee' (OR: 2.18; 95% CI: 1.87-2.53) clusters to have children in a 'plant-based' cluster. However the majority of children were in clusters unrelated to their mother dietary pattern. Three distinct dietary patterns were obtained in pregnancy; the 'fruit and vegetables' pattern being the most nutrient dense. Mothers' dietary patterns were associated with but did not dominate offspring dietary patterns. © 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.

Cluster subgroups based on overall pressure pain sensitivity and psychosocial factors in chronic musculoskeletal pain: Differences in clinical outcomes.

PubMed

Almeida, Suzana C; George, Steven Z; Leite, Raquel D V; Oliveira, Anamaria S; Chaves, Thais C

2018-05-17

We aimed to empirically derive psychosocial and pain sensitivity subgroups using cluster analysis within a sample of individuals with chronic musculoskeletal pain (CMP) and to investigate derived subgroups for differences in pain and disability outcomes. Eighty female participants with CMP answered psychosocial and disability scales and were assessed for pressure pain sensitivity. A cluster analysis was used to derive subgroups, and analysis of variance (ANOVA) was used to investigate differences between subgroups. Psychosocial factors (kinesiophobia, pain catastrophizing, anxiety, and depression) and overall pressure pain threshold (PPT) were entered into the cluster analysis. Three subgroups were empirically derived: cluster 1 (high pain sensitivity and high psychosocial distress; n = 12) characterized by low overall PPT and high psychosocial scores; cluster 2 (high pain sensitivity and intermediate psychosocial distress; n = 39) characterized by low overall PPT and intermediate psychosocial scores; and cluster 3 (low pain sensitivity and low psychosocial distress; n = 29) characterized by high overall PPT and low psychosocial scores compared to the other subgroups. Cluster 1 showed higher values for mean pain intensity (F (2,77)  = 10.58, p < 0.001) compared with cluster 3, and cluster 1 showed higher values for disability (F (2,77)  = 3.81, p = 0.03) compared with both clusters 2 and 3. Only cluster 1 was distinct from cluster 3 according to both pain and disability outcomes. Pain catastrophizing, depression, and anxiety were the psychosocial variables that best differentiated the subgroups. Overall, these results call attention to the importance of considering pain sensitivity and psychosocial variables to obtain a more comprehensive characterization of CMP patients' subtypes.

Genome-guided Investigation of Antibiotic Substances produced by Allosalinactinospora lopnorensis CA15-2T from Lop Nor region, China

PubMed Central

Huang, Chen; Leung, Ross Ka-Kit; Guo, Min; Tuo, Li; Guo, Lin; Yew, Wing Wai; Lou, Inchio; Lee, Simon Ming Yuen; Sun, Chenghang

2016-01-01

Microbial secondary metabolites are valuable resources for novel drug discovery. In particular, actinomycetes expressed a range of antibiotics against a spectrum of bacteria. In genus level, strain Allosalinactinospora lopnorensis CA15-2T is the first new actinomycete isolated from the Lop Nor region, China. Antimicrobial assays revealed that the strain could inhibit the growth of certain types of bacteria, including Acinetobacter baumannii and Staphylococcus aureus, highlighting its clinical significance. Here we report the 5,894,259 base pairs genome of the strain, containing 5,662 predicted genes, and 832 of them cannot be detected by sequence similarity-based methods, suggesting the new species may carry a novel gene pool. Furthermore, our genome-mining investigation reveals that A. lopnorensis CA15-2T contains 17 gene clusters coding for known or novel secondary metabolites. Meanwhile, at least six secondary metabolites were disclosed from ethyl acetate (EA) extract of the fermentation broth of the strain by high-resolution UPLC-MS. Compared with reported clusters of other species, many new genes were found in clusters, and the physical chromosomal location and order of genes in the clusters are distinct. This study presents evidence in support of A. lopnorensis CA15-2T as a potent natural products source for drug discovery. PMID:26864220

Scaffold Architecture Controls Insulinoma Clustering, Viability, and Insulin Production

PubMed Central

Blackstone, Britani N.; Palmer, Andre F.; Rilo, Horacio R.

2014-01-01

Recently, in vitro diagnostic tools have shifted focus toward personalized medicine by incorporating patient cells into traditional test beds. These cell-based platforms commonly utilize two-dimensional substrates that lack the ability to support three-dimensional cell structures seen in vivo. As monolayer cell cultures have previously been shown to function differently than cells in vivo, the results of such in vitro tests may not accurately reflect cell response in vivo. It is therefore of interest to determine the relationships between substrate architecture, cell structure, and cell function in 3D cell-based platforms. To investigate the effect of substrate architecture on insulinoma organization and function, insulinomas were seeded onto 2D gelatin substrates and 3D fibrous gelatin scaffolds with three distinct fiber diameters and fiber densities. Cell viability and clustering was assessed at culture days 3, 5, and 7 with baseline insulin secretion and glucose-stimulated insulin production measured at day 7. Small, closely spaced gelatin fibers promoted the formation of large, rounded insulinoma clusters, whereas monolayer organization and large fibers prevented cell clustering and reduced glucose-stimulated insulin production. Taken together, these data show that scaffold properties can be used to control the organization and function of insulin-producing cells and may be useful as a 3D test bed for diabetes drug development. PMID:24410263

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.

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

PubMed

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

2016-12-30

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

Genetic variation in resistance to blast (Pyricularia oryzae Cavara) in rice (Oryza sativa L.) germplasms of Bangladesh

PubMed Central

Khan, Mohammad Ashik Iqbal; Latif, Mohammad Abdul; Khalequzzaman, Mohammad; Tomita, Asami; Ali, Mohammad Ansar; Fukuta, Yoshimichi

2017-01-01

Genetic variation in blast resistance was clarified in 334 Bangladesh rice accessions from 4 major ecotypes (Aus, Aman, Boro and Jhum). Cluster analysis of polymorphism data of 74 SSR markers separated these accessions into cluster I (corresponding to the Japonica Group) and cluster II (corresponding to the Indica Group). Cluster II accessions were represented with high frequency in all ecotypes. Cluster II was further subdivided into subclusters IIa and IIb. Subcluster IIa accessions were represented with high frequency in only Aus and Jhum ecotypes. Cluster I accessions were more frequent in the Aman ecotype than in other ecotypes. Distinct variations in resistance were found, and accessions were classified into 4 groups (A1, A2, B1 and B2) based on their reactions to standard differential blast isolates. The most susceptible group was A2 (which included susceptible variety Lijiangxintuanheigu, most of the differential varieties, and a few Bangladesh accessions), followed in order by A1, B2 and B1 (the most resistant). Accessions from 4 ecotypes fell with different frequencies into each of these resistance groups. These results demonstrated that Japonica Group accessions were found mainly in Aman, and Indica Group accessions were distributed across all ecotypes. Susceptible accessions were limited in Aus and Aman. PMID:29398943

Mechanism of cell alignment in groups of Myxococcus xanthus bacteria

NASA Astrophysics Data System (ADS)

Balgam, Rajesh; Igoshin, Oleg

2015-03-01

Myxococcus xanthus is a model for studying self-organization in bacteria. These flexible cylindrical bacteria move along. In groups, M. xanthus cells align themselves into dynamic cell clusters but the mechanism underlying their formation is unknown. It has been shown that steric interactions can cause alignment in self-propelled hard rods but it is not clear how flexibility and reversals affect the alignment and cluster formation. We have investigated cell alignment process using our biophysical model of M. xanthus cell in an agent-based simulation framework under realistic cell flexibility values. We observed that flexible model cells can form aligned cell clusters when reversals are suppressed but these clusters disappeared when reversals frequency becomes similar to the observed value. However, M. xanthus cells follow slime (polysaccharide gel like material) trails left by other cells and we show that implementing this into our model rescues cell clustering for reversing cells. Our results show that slime following along with periodic cell reversals act as positive feedback to reinforce existing slime trails and recruit more cells. Furthermore, we have observed that mechanical cell alignment combined with slime following is sufficient to explain the distinct clustering patterns of reversing and non-reversing cells as observed in recent experiments. This work is supported by NSF MCB 0845919 and 1411780.

Phylogenomic and MALDI-TOF MS Analysis of Streptococcus sinensis HKU4T Reveals a Distinct Phylogenetic Clade in the Genus Streptococcus

PubMed Central

Tse, Herman; Chen, Jonathan H.K.; Tang, Ying; Lau, Susanna K.P.; Woo, Patrick C.Y.

2014-01-01

Streptococcus sinensis is a recently discovered human pathogen isolated from blood cultures of patients with infective endocarditis. Its phylogenetic position, as well as those of its closely related species, remains inconclusive when single genes were used for phylogenetic analysis. For example, S. sinensis branched out from members of the anginosus, mitis, and sanguinis groups in the 16S ribosomal RNA gene phylogenetic tree, but it was clustered with members of the anginosus and sanguinis groups when groEL gene sequences used for analysis. In this study, we sequenced the draft genome of S. sinensis and used a polyphasic approach, including concatenated genes, whole genomes, and matrix-assisted laser desorption ionization-time of flight mass spectrometry to analyze the phylogeny of S. sinensis. The size of the S. sinensis draft genome is 2.06 Mb, with GC content of 42.2%. Phylogenetic analysis using 50 concatenated genes or whole genomes revealed that S. sinensis formed a distinct cluster with Streptococcus oligofermentans and Streptococcus cristatus, and these three streptococci were clustered with the “sanguinis group.” As for phylogenetic analysis using hierarchical cluster analysis of the mass spectra of streptococci, S. sinensis also formed a distinct cluster with S. oligofermentans and S. cristatus, but these three streptococci were clustered with the “mitis group.” On the basis of the findings, we propose a novel group, named “sinensis group,” to include S. sinensis, S. oligofermentans, and S. cristatus, in the Streptococcus genus. Our study also illustrates the power of phylogenomic analyses for resolving ambiguities in bacterial taxonomy. PMID:25331233

Phylogenomic and MALDI-TOF MS analysis of Streptococcus sinensis HKU4T reveals a distinct phylogenetic clade in the genus Streptococcus.

PubMed

Teng, Jade L L; Huang, Yi; Tse, Herman; Chen, Jonathan H K; Tang, Ying; Lau, Susanna K P; Woo, Patrick C Y

2014-10-20

Streptococcus sinensis is a recently discovered human pathogen isolated from blood cultures of patients with infective endocarditis. Its phylogenetic position, as well as those of its closely related species, remains inconclusive when single genes were used for phylogenetic analysis. For example, S. sinensis branched out from members of the anginosus, mitis, and sanguinis groups in the 16S ribosomal RNA gene phylogenetic tree, but it was clustered with members of the anginosus and sanguinis groups when groEL gene sequences used for analysis. In this study, we sequenced the draft genome of S. sinensis and used a polyphasic approach, including concatenated genes, whole genomes, and matrix-assisted laser desorption ionization-time of flight mass spectrometry to analyze the phylogeny of S. sinensis. The size of the S. sinensis draft genome is 2.06 Mb, with GC content of 42.2%. Phylogenetic analysis using 50 concatenated genes or whole genomes revealed that S. sinensis formed a distinct cluster with Streptococcus oligofermentans and Streptococcus cristatus, and these three streptococci were clustered with the "sanguinis group." As for phylogenetic analysis using hierarchical cluster analysis of the mass spectra of streptococci, S. sinensis also formed a distinct cluster with S. oligofermentans and S. cristatus, but these three streptococci were clustered with the "mitis group." On the basis of the findings, we propose a novel group, named "sinensis group," to include S. sinensis, S. oligofermentans, and S. cristatus, in the Streptococcus genus. Our study also illustrates the power of phylogenomic analyses for resolving ambiguities in bacterial taxonomy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Suicide in the oldest old: an observational study and cluster analysis.

PubMed

Sinyor, Mark; Tan, Lynnette Pei Lin; Schaffer, Ayal; Gallagher, Damien; Shulman, Kenneth

2016-01-01

The older population are at a high risk for suicide. This study sought to learn more about the characteristics of suicide in the oldest-old and to use a cluster analysis to determine if oldest-old suicide victims assort into clinically meaningful subgroups. Data were collected from a coroner's chart review of suicide victims in Toronto from 1998 to 2011. We compared two age groups (65-79 year olds, n = 335, and 80+ year olds, n = 191) and then conducted a hierarchical agglomerative cluster analysis using Ward's method to identify distinct clusters in the 80+ group. The younger and older age groups differed according to marital status, living circumstances and pattern of stressors. The cluster analysis identified three distinct clusters in the 80+ group. Cluster 1 was the largest (n = 124) and included people who were either married or widowed who had significantly more depression and somewhat more medical health stressors. In contrast, cluster 2 (n = 50) comprised people who were almost all single and living alone with significantly less identified depression and slightly fewer medical health stressors. All members of cluster 3 (n = 17) lived in a retirement residence or nursing home, and this group had the highest rates of depression, dementia, other mental illness and past suicide attempts. This is the first study to use the cluster analysis technique to identify meaningful subgroups among suicide victims in the oldest-old. The results reveal different patterns of suicide in the older population that may be relevant for clinical care. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Characterizing Suicide in Toronto: An Observational Study and Cluster Analysis

PubMed Central

Sinyor, Mark; Schaffer, Ayal; Streiner, David L

2014-01-01

Objective: To determine whether people who have died from suicide in a large epidemiologic sample form clusters based on demographic, clinical, and psychosocial factors. Method: We conducted a coroner’s chart review for 2886 people who died in Toronto, Ontario, from 1998 to 2010, and whose death was ruled as suicide by the Office of the Chief Coroner of Ontario. A cluster analysis using known suicide risk factors was performed to determine whether suicide deaths separate into distinct groups. Clusters were compared according to person- and suicide-specific factors. Results: Five clusters emerged. Cluster 1 had the highest proportion of females and nonviolent methods, and all had depression and a past suicide attempt. Cluster 2 had the highest proportion of people with a recent stressor and violent suicide methods, and all were married. Cluster 3 had mostly males between the ages of 20 and 64, and all had either experienced recent stressors, suffered from mental illness, or had a history of substance abuse. Cluster 4 had the youngest people and the highest proportion of deaths by jumping from height, few were married, and nearly one-half had bipolar disorder or schizophrenia. Cluster 5 had all unmarried people with no prior suicide attempts, and were the least likely to have an identified mental illness and most likely to leave a suicide note. Conclusions: People who die from suicide assort into different patterns of demographic, clinical, and death-specific characteristics. Identifying and studying subgroups of suicides may advance our understanding of the heterogeneous nature of suicide and help to inform development of more targeted suicide prevention strategies. PMID:24444321

Two distinct sequences of blue straggler stars in the globular cluster M 30.

PubMed

Ferraro, F R; Beccari, G; Dalessandro, E; Lanzoni, B; Sills, A; Rood, R T; Pecci, F Fusi; Karakas, A I; Miocchi, P; Bovinelli, S

2009-12-24

Stars in globular clusters are generally believed to have all formed at the same time, early in the Galaxy's history. 'Blue stragglers' are stars massive enough that they should have evolved into white dwarfs long ago. Two possible mechanisms have been proposed for their formation: mass transfer between binary companions and stellar mergers resulting from direct collisions between two stars. Recently the binary explanation was claimed to be dominant. Here we report that there are two distinct parallel sequences of blue stragglers in M 30. This globular cluster is thought to have undergone 'core collapse', during which both the collision rate and the mass transfer activity in binary systems would have been enhanced. We suggest that the two observed sequences are a consequence of cluster core collapse, with the bluer population arising from direct stellar collisions and the redder one arising from the evolution of close binaries that are probably still experiencing an active phase of mass transfer.

Stationary and non-stationary extreme value modeling of extreme temperature in Malaysia

NASA Astrophysics Data System (ADS)

Hasan, Husna; Salleh, Nur Hanim Mohd; Kassim, Suraiya

2014-09-01

Extreme annual temperature of eighteen stations in Malaysia is fitted to the Generalized Extreme Value distribution. Stationary and non-stationary models with trend are considered for each station and the Likelihood Ratio test is used to determine the best-fitting model. Results show that three out of eighteen stations i.e. Bayan Lepas, Labuan and Subang favor a model which is linear in the location parameter. A hierarchical cluster analysis is employed to investigate the existence of similar behavior among the stations. Three distinct clusters are found in which one of them consists of the stations that favor the non-stationary model. T-year estimated return levels of the extreme temperature are provided based on the chosen models.

Language Networks Associated with Computerized Semantic Indices

PubMed Central

Pakhomov, Serguei V. S.; Jones, David T.; Knopman, David S.

2014-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. PMID:25315785

Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity.

PubMed

Ellegood, J; Anagnostou, E; Babineau, B A; Crawley, J N; Lin, L; Genestine, M; DiCicco-Bloom, E; Lai, J K Y; Foster, J A; Peñagarikano, O; Geschwind, D H; Pacey, L K; Hampson, D R; Laliberté, C L; Mills, A A; Tam, E; Osborne, L R; Kouser, M; Espinosa-Becerra, F; Xuan, Z; Powell, C M; Raznahan, A; Robins, D M; Nakai, N; Nakatani, J; Takumi, T; van Eede, M C; Kerr, T M; Muller, C; Blakely, R D; Veenstra-VanderWeele, J; Henkelman, R M; Lerch, J P

2015-02-01

Autism is a heritable disorder, with over 250 associated genes identified to date, yet no single gene accounts for >1-2% of cases. The clinical presentation, behavioural symptoms, imaging and histopathology findings are strikingly heterogeneous. A more complete understanding of autism can be obtained by examining multiple genetic or behavioural mouse models of autism using magnetic resonance imaging (MRI)-based neuroanatomical phenotyping. Twenty-six different mouse models were examined and the consistently found abnormal brain regions across models were parieto-temporal lobe, cerebellar cortex, frontal lobe, hypothalamus and striatum. These models separated into three distinct clusters, two of which can be linked to the under and over-connectivity found in autism. These clusters also identified previously unknown connections between Nrxn1α, En2 and Fmr1; Nlgn3, BTBR and Slc6A4; and also between X monosomy and Mecp2. With no single treatment for autism found, clustering autism using neuroanatomy and identifying these strong connections may prove to be a crucial step in predicting treatment response.

The effect of host cluster gravitational tidal forces on the internal dynamics of spiral galaxies

NASA Astrophysics Data System (ADS)

Mayer, Alexander

2013-04-01

New empirical observation by Bidin, Carraro, Mendez & Smith finds ``a lack of dark matter in the Solar neighborhood" (2012 ApJ 751, 30). This, and the discovery of a vast polar structure of Milky Way satellites by Pawlowski, Pflamm-Altenburg & Kroupa (2012 MNRAS 423, 1109), conflict with the prevailing interpretation of the measured Galactic rotation curve. Simulating the dynamical effects of host cluster tidal forces on galaxy disks reveals radial migration in a spiral structure and an orbital velocity that accelerates with increasing galactocentric radial coordinate. A virtual ``toy model,'' which is based on an Earth-orbiting system of particles and is physically realizable in principle, is available at GravitySim.net. Given the perturbing gravitational effect of the host cluster on a spiral galaxy disk and that a similar effect does not exist for the Solar System, the two systems represent distinct classes of gravitational dynamical systems. The observed `flat' and accelerating rotation curves of spiral galaxies can be attributed to gravitational interaction with the host cluster; no `dark matter halo' is required to explain the observable.

Fibers in the NGC 1333 proto-cluster

NASA Astrophysics Data System (ADS)

Hacar, A.; Tafalla, M.; Alves, J.

2017-10-01

Are the initial conditions for clustered star formation the same as for non-clustered star formation? To investigate the initial gas properties in young proto-clusters we carried out a comprehensive and high-sensitivity study of the internal structure, density, temperature, and kinematics of the dense gas content of the NGC 1333 region in Perseus, one of the nearest and best studied embedded clusters. The analysis of the gas velocities in the position-position-velocity space reveals an intricate underlying gas organization both in space and velocity. We identified a total of 14 velocity-coherent, (tran-)sonic structures within NGC 1333, with similar physical and kinematic properties than those quiescent, star-forming (aka fertile) fibers previously identified in low-mass star-forming clouds. These fibers are arranged in a complex spatial network, build-up the observed total column density, and contain the dense cores and protostars in this cloud. Our results demonstrate that the presence of fibers is not restricted to low-mass clouds but can be extended to regions of increasing mass and complexity. We propose that the observational dichotomy between clustered and non-clustered star-forming regions might be naturally explained by the distinct spatial density of fertile fibers in these environments. Based on observations carried out under project number 169-11 with the IRAM 30 m Telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).Based on observations with the 100-m telescope of the MPIfR (Max-Planck-Institut für Radioastronomie) at Effelsberg.Molecular line observations (spectral cubes) 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/A123

Behçet's: A Disease or a Syndrome? Answer from an Expression Profiling Study.

PubMed

Oğuz, Ali Kemal; Yılmaz, Seda Taşır; Oygür, Çağdaş Şahap; Çandar, Tuba; Sayın, Irmak; Kılıçoğlu, Sibel Serin; Ergün, İhsan; Ateş, Aşkın; Özdağ, Hilal; Akar, Nejat

2016-01-01

Behçet's disease (BD) is a chronic, relapsing, multisystemic inflammatory disorder with unanswered questions regarding its etiology/pathogenesis and classification. Distinct manifestation based subsets, pronounced geographical variations in expression, and discrepant immunological abnormalities raised the question whether Behçet's is "a disease or a syndrome". To answer the preceding question we aimed to display and compare the molecular mechanisms underlying distinct subsets of BD. For this purpose, the expression data of the gene expression profiling and association study on BD by Xavier et al (2013) was retrieved from GEO database and reanalysed by gene expression data analysis/visualization and bioinformatics enrichment tools. There were 15 BD patients (B) and 14 controls (C). Three subsets of BD patients were generated: MB (isolated mucocutaneous manifestations, n = 7), OB (ocular involvement, n = 4), and VB (large vein thrombosis, n = 4). Class comparison analyses yielded the following numbers of differentially expressed genes (DEGs); B vs C: 4, MB vs C: 5, OB vs C: 151, VB vs C: 274, MB vs OB: 215, MB vs VB: 760, OB vs VB: 984. Venn diagram analysis showed that there were no common DEGs in the intersection "MB vs C" ∩ "OB vs C" ∩ "VB vs C". Cluster analyses successfully clustered distinct expressions of BD. During gene ontology term enrichment analyses, categories with relevance to IL-8 production (MB vs C) and immune response to microorganisms (OB vs C) were differentially enriched. Distinct subsets of BD display distinct expression profiles and different disease associated pathways. Based on these clear discrepancies, the designation as "Behçet's syndrome" (BS) should be encouraged and future research should take into consideration the immunogenetic heterogeneity of BS subsets. Four gene groups, namely, negative regulators of inflammation (CD69, CLEC12A, CLEC12B, TNFAIP3), neutrophil granule proteins (LTF, OLFM4, AZU1, MMP8, DEFA4, CAMP), antigen processing and presentation proteins (CTSS, ERAP1), and regulators of immune response (LGALS2, BCL10, ITCH, CEACAM8, CD36, IL8, CCL4, EREG, NFKBIZ, CCR2, CD180, KLRC4, NFAT5) appear to be instrumental in BS immunopathogenesis.

Symptom clusters and quality of life among patients with advanced heart failure

PubMed Central

Yu, Doris SF; Chan, Helen YL; Leung, Doris YP; Hui, Elsie; Sit, Janet WH

2016-01-01

Objectives To identify symptom clusters among patients with advanced heart failure (HF) and the independent relationships with their quality of life (QoL). Methods This is the secondary data analysis of a cross-sectional study which interviewed 119 patients with advanced HF in the geriatric unit of a regional hospital in Hong Kong. The symptom profile and QoL were assessed by using the Edmonton Symptom Assessment Scale (ESAS) and the McGill QoL Questionnaire. Exploratory factor analysis was used to identify the symptom clusters. Hierarchical regression analysis was used to examine the independent relationships with their QoL, after adjusting the effects of age, gender, and comorbidities. Results The patients were at an advanced age (82.9 ± 6.5 years). Three distinct symptom clusters were identified: they were the distress cluster (including shortness of breath, anxiety, and depression), the decondition cluster (fatigue, drowsiness, nausea, and reduced appetite), and the discomfort cluster (pain, and sense of generalized discomfort). These three symptom clusters accounted for 63.25% of variance of the patients' symptom experience. The small to moderate correlations between these symptom clusters indicated that they were rather independent of one another. After adjusting the age, gender and comorbidities, the distress (β = −0.635, P < 0.001), the decondition (β = −0.148, P = 0.01), and the discomfort (β = −0.258, P < 0.001) symptom clusters independently predicted their QoL. Conclusions This study identified the distinctive symptom clusters among patients with advanced HF. The results shed light on the need to develop palliative care interventions for optimizing the symptom control for this life-limiting disease. PMID:27403150

Optical Materials with a Genome: Nanophotonics with DNA-Stabilized Silver Clusters

NASA Astrophysics Data System (ADS)

Copp, Stacy M.

Fluorescent silver clusters with unique rod-like geometries are stabilized by DNA. The sizes and colors of these clusters, or AgN-DNA, are selected by DNA base sequence, which can tune peak emission from blue-green into the near-infrared. Combined with DNA nanostructures, AgN-DNA promise exciting applications in nanophotonics and sensing. Until recently, however, a lack of understanding of the mechanisms controlling AgN-DNA fluorescence has challenged such applications. This dissertation discusses progress toward understanding the role of DNA as a "genome" for silver clusters and toward using DNA to achieve atomic-scale precision of silver cluster size and nanometer-scale precision of silver cluster position on a DNA breadboard. We also investigate sensitivity of AgN-DNA to local solvent environment, with an eye toward applications in chemical and biochemical sensing. Using robotic techniques to generate large data sets, we show that fluorescent silver clusters are templated by certain DNA base motifs that select "magic-sized" cluster cores of enhanced stabilities. The linear arrangement of bases on the phosphate backbone imposes a unique rod-like geometry on the clusters. Harnessing machine learning and bioinformatics techniques, we also demonstrate that sequences of DNA templates can be selected to stabilize silver clusters with desired optical properties, including high fluorescence intensity and specific fluorescence wavelengths, with much higher rates of success as compared to current strategies. The discovered base motifs can be also used to design modular DNA host strands that enable individual silver clusters with atomically precise sizes to bind at specific programmed locations on a DNA nanostructure. We show that DNA-mediated nanoscale arrangement enables near-field coupling of distinct clusters, demonstrated by dual-color cluster assemblies exhibiting resonant energy transfer. These results demonstrate a new degree of control over the optical properties and relative positions of nanoparticles, selected almost solely by the sequence of DNA. AgN-DNA are promising chemical and biochemical sensors due to the sensitivity of their fluorescence to local environment. However, the mechanisms behind many sensing schemes are not understood, and the nature of the excited state of the silver cluster itself remains unknown. To probe the fluorescence mechanisms of AgN-DNA, we investigate the behavior of purified solutions of these clusters in various solvents. We find that standard models for fluorophore solvatochromism, including the Lippert-Mataga model, do not describe AgN-DNA fluorescence because such models neglect specific interactions between the cluster and surrounding solvent molecules. Fluorescence colors are well-modeled by Mie-Gans theory, suggesting that the local dielectric environment of the cluster does play a role in fluorescence, although additional specific solvent interactions and cluster shape changes may also determine fluorescence color and intensity. These results suggest that AgN-DNA may be sensitive to changes in local dielectric environment on nanometer length scales and may also act as sensors for small molecules with affinity for DNA.

Phytoplasma phylogenetics based on analysis of secA and 23S rRNA gene sequences for improved resolution of candidate species of 'Candidatus Phytoplasma'.

PubMed

Hodgetts, Jennifer; Boonham, Neil; Mumford, Rick; Harrison, Nigel; Dickinson, Matthew

2008-08-01

Phytoplasma phylogenetics has focused primarily on sequences of the non-coding 16S rRNA gene and the 16S-23S rRNA intergenic spacer region (16-23S ISR), and primers that enable amplification of these regions from all phytoplasmas by PCR are well established. In this study, primers based on the secA gene have been developed into a semi-nested PCR assay that results in a sequence of the expected size (about 480 bp) from all 34 phytoplasmas examined, including strains representative of 12 16Sr groups. Phylogenetic analysis of secA gene sequences showed similar clustering of phytoplasmas when compared with clusters resolved by similar sequence analyses of a 16-23S ISR-23S rRNA gene contig or of the 16S rRNA gene alone. The main differences between trees were in the branch lengths, which were elongated in the 16-23S ISR-23S rRNA gene tree when compared with the 16S rRNA gene tree and elongated still further in the secA gene tree, despite this being a shorter sequence. The improved resolution in the secA gene-derived phylogenetic tree resulted in the 16SrII group splitting into two distinct clusters, while phytoplasmas associated with coconut lethal yellowing-type diseases split into three distinct groups, thereby supporting past proposals that they represent different candidate species within 'Candidatus Phytoplasma'. The ability to differentiate 16Sr groups and subgroups by virtual RFLP analysis of secA gene sequences suggests that this gene may provide an informative alternative molecular marker for pathogen identification and diagnosis of phytoplasma diseases.

The genomic bases of morphological divergence and reproductive isolation driven by ecological speciation in Senecio (Asteraceae).

PubMed

Chapman, M A; Hiscock, S J; Filatov, D A

2016-01-01

Ecological speciation, driven by adaptation to contrasting environments, provides an attractive opportunity to study the formation of distinct species, and the role of selection and genomic divergence in this process. Here, we focus on a particularly clear-cut case of ecological speciation to reveal the genomic bases of reproductive isolation and morphological differences between closely related Senecio species, whose recent divergence within the last ~200,000 years was likely driven by the uplift of Mt. Etna (Sicily). These species form a hybrid zone, yet remain morphologically and ecologically distinct, despite active gene exchange. Here, we report a high-density genetic map of the Senecio genome and map hybrid breakdown to one large and several small quantitative trait loci (QTL). Loci under diversifying selection cluster in three 5 cM regions which are characterized by a significant increase in relative (F(ST)), but not absolute (d(XY)), interspecific differentiation. They also correspond to some of the regions of greatest marker density, possibly corresponding to 'cold-spots' of recombination, such as centromeres or chromosomal inversions. Morphological QTL for leaf and floral traits overlap these clusters. We also detected three genomic regions with significant transmission ratio distortion (TRD), possibly indicating accumulation of intrinsic genetic incompatibilities between these recently diverged species. One of the TRD regions overlapped with a cluster of high species differentiation, and another overlaps the large QTL for hybrid breakdown, indicating that divergence of these species may have occurred due to a complex interplay of ecological divergence and accumulation of intrinsic genetic incompatibilities. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Comparison of advanced whole genome sequence-based methods to distinguish strains of Salmonella enterica serovar Heidelberg involved in foodborne outbreaks in Québec.

PubMed

Vincent, Caroline; Usongo, Valentine; Berry, Chrystal; Tremblay, Denise M; Moineau, Sylvain; Yousfi, Khadidja; Doualla-Bell, Florence; Fournier, Eric; Nadon, Céline; Goodridge, Lawrence; Bekal, Sadjia

2018-08-01

Salmonella enterica serovar Heidelberg (S. Heidelberg) is one of the top serovars causing human salmonellosis. This serovar ranks second and third among serovars that cause human infections in Québec and Canada, respectively, and has been associated with severe infections. Traditional typing methods such as PFGE do not display adequate discrimination required to resolve outbreak investigations due to the low level of genetic diversity of isolates belonging to this serovar. This study evaluates the ability of four whole genome sequence (WGS)-based typing methods to differentiate among 145 S. Heidelberg strains involved in four distinct outbreak events and sporadic cases of salmonellosis that occurred in Québec between 2007 and 2016. Isolates from all outbreaks were indistinguishable by PFGE. The core genome single nucleotide variant (SNV), core genome multilocus sequence typing (MLST) and whole genome MLST approaches were highly discriminatory and separated outbreak strains into four distinct phylogenetic clusters that were concordant with the epidemiological data. The clustered regularly interspaced short palindromic repeats (CRISPR) typing method was less discriminatory. However, CRISPR typing may be used as a secondary method to differentiate isolates of S. Heidelberg that are genetically similar but epidemiologically unrelated to outbreak events. WGS-based typing methods provide a highly discriminatory alternative to PFGE for the laboratory investigation of foodborne outbreaks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Framing life and death on YouTube: the strategic communication of organ donation messages by organ procurement organizations.

PubMed

VanderKnyff, Jeremy; Friedman, Daniela B; Tanner, Andrea

2015-01-01

Using a sample of YouTube videos posted on the YouTube channels of organ procurement organizations, a content analysis was conducted to identify the frames used to strategically communicate prodonation messages. A total of 377 videos were coded for general characteristics, format, speaker characteristics, organs discussed, structure, problem definition, and treatment. Principal components analysis identified message frames, and k-means cluster analysis established distinct groupings of videos on the basis of the strength of their relationship to message frames. Analysis of these frames and clusters found that organ procurement organizations present multiple, and sometimes competing, video types and message frames on YouTube. This study serves as important formative research that will inform future studies to measure the effectiveness of the distinct message frames and clusters identified.

THE YOUNG STELLAR POPULATION OF THE CYGNUS-X DR15 REGION

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

Rivera-Gálvez, S.; Román-Zúñiga, C. G.; Jiménez-Bailón, E.

We present a multi-wavelength study of the young stellar population in the Cygnus-X DR15 region. We studied young stars that were forming or recently formed at and around the tip of a prominent molecular pillar and an infrared dark cloud. Using a combination of ground-based near-infrared, space-based infrared, and X-ray data, we constructed a point source catalog from which we identified 226 young stellar sources, which we classified into evolutionary classes. We studied their spatial distributions across the molecular gas structures and identified several groups that possibly belong to distinct young star clusters. We obtained samples of these groups andmore » constructed K-band luminosity functions that we compared with those of artificial clusters, allowing us to make first order estimates of the mean ages and age spreads of the groups. We used a {sup 13}CO(1-0) map to investigate the gas kinematics at the prominent gaseous envelope of the central cluster in DR15, and we inferred that the removal of this envelope is relatively slow compared to other cluster regions, in which the gas dispersal timescale could be similar or shorter than the circumstellar disk dissipation timescale. The presence of other groups with slightly older ages, associated with much less prominent gaseous structures, may imply that the evolution of young clusters in this part of the complex proceeds in periods that last 3–5 Myr, perhaps after a slow dissipation of their dense molecular cloud birthplaces.« less

The Distinctive Difficulties of Disagreeable Youth

ERIC Educational Resources Information Center

Laursen, Brett; Hafen, Christopher A.; Rubin, Kenneth H.; Booth-LaForce, Cathryn; Rose-Krasnor, Linda

2010-01-01

This study examines whether disagreeable youth are distinct from aggressive youth, victimized youth, and withdrawn youth. Young adolescents (120 girls and 104 boys, M = 13.59 years old) completed personality and adjustment inventories. Aggression, withdrawal, and victimization scores were derived from peer nominations (N = 807). Cluster analyses…

Variability of O3 and NO2 profile shapes during DISCOVER-AQ: Implications for satellite observations and comparisons to model-simulated profiles

NASA Astrophysics Data System (ADS)

Flynn, Clare Marie; Pickering, Kenneth E.; Crawford, James H.; Weinheimer, Andrew J.; Diskin, Glenn; Thornhill, K. Lee; Loughner, Christopher; Lee, Pius; Strode, Sarah A.

2016-12-01

To investigate the variability of in situ profile shapes under a variety of meteorological and pollution conditions, results are presented of an agglomerative hierarchical cluster analysis of the in situ O3 and NO2 profiles for each of the four campaigns of the NASA DISCOVER-AQ mission. Understanding the observed profile variability for these trace gases is useful for understanding the accuracy of the assumed profile shapes used in satellite retrieval algorithms as well as for understanding the correlation between satellite column observations and surface concentrations. The four campaigns of the DISCOVER-AQ mission took place in Maryland during July 2011, the San Joaquin Valley of California during January-February 2013, the Houston, Texas, metropolitan region during September 2013, and the Denver-Front Range region of Colorado during July-August 2014. Several distinct profile clusters emerged for the California, Texas, and Colorado campaigns for O3, indicating significant variability of O3 profile shapes, while the Maryland campaign presented only one distinct O3 cluster. In contrast, very few distinct profile clusters emerged for NO2 during any campaign for this particular clustering technique, indicating the NO2 profile behavior was relatively uniform throughout each campaign. However, changes in NO2 profile shape were evident as the boundary layer evolved through the day, but they were apparently not significant enough to yield more clusters. The degree of vertical mixing (as indicated by temperature lapse rate) associated with each cluster exerted an important influence on the shapes of the median cluster profiles for O3, as well as impacted the correlations between the associated column and surface data for each cluster for O3. The correlation analyses suggest satellites may have the best chance to relate to surface O3 under the conditions encountered during the Maryland campaign Clusters 1 and 2, which include deep, convective boundary layers and few interruptions to this connection from complex meteorology, chemical environments, or orography. The regional CMAQ model captured the shape factors for O3, and moderately well captured the NO2 shape factors, for the conditions associated with the Maryland campaign, suggesting that a regional air quality model may adequately specify a priori profile shapes for remote sensing retrievals. CMAQ shape factor profiles were not as well represented for the other regions.

Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

PubMed Central

Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

2016-01-01

Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

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

PubMed

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

2015-01-01

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

Cluster analysis of the national weight control registry to identify distinct subgroups maintaining successful weight loss.

PubMed

Ogden, Lorraine G; Stroebele, Nanette; Wyatt, Holly R; Catenacci, Victoria A; Peters, John C; Stuht, Jennifer; Wing, Rena R; Hill, James O

2012-10-01

The National Weight Control Registry (NWCR) is the largest ongoing study of individuals successful at maintaining weight loss; the registry enrolls individuals maintaining a weight loss of at least 13.6 kg (30 lb) for a minimum of 1 year. The current report uses multivariate latent class cluster analysis to identify unique clusters of individuals within the NWCR that have distinct experiences, strategies, and attitudes with respect to weight loss and weight loss maintenance. The cluster analysis considers weight and health history, weight control behaviors and strategies, effort and satisfaction with maintaining weight, and psychological and demographic characteristics. The analysis includes 2,228 participants enrolled between 1998 and 2002. Cluster 1 (50.5%) represents a weight-stable, healthy, exercise conscious group who are very satisfied with their current weight. Cluster 2 (26.9%) has continuously struggled with weight since childhood; they rely on the greatest number of resources and strategies to lose and maintain weight, and report higher levels of stress and depression. Cluster 3 (12.7%) represents a group successful at weight reduction on the first attempt; they were least likely to be overweight as children, are maintaining the longest duration of weight loss, and report the least difficulty maintaining weight. Cluster 4 (9.9%) represents a group less likely to use exercise to control weight; they tend to be older, eat fewer meals, and report more health problems. Further exploration of the unique characteristics of these clusters could be useful for tailoring future weight loss and weight maintenance programs to the specific characteristics of an individual.

Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

PubMed

Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

2015-10-01

Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

An Objective Classification of Saturn Cloud Features from Cassini ISS Images

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Lifestyles through Expenditures: A Case-Based Approach to Saving

PubMed Central

Keister, Lisa A.; Benton, Richard; Moody, James

2016-01-01

Treating people as cases that are proximate in a behavior space—representing lifestyles—rather than as markers of single variables has a long history in sociology. Yet, because it is difficult to find analytically tractable ways to implement this idea, this approach is rarely used. We take seriously the idea that people are whole packages, and we use household spending to identify groups who occupy similar positions in social space. Using detailed data on household consumption, we identify eight positions that are clearly similar in lifestyle. We then study how the lifestyles we identify are associated with saving, an important measure of household well-being. We find that households cluster into distinct lifestyles based on similarities and differences in consumption. These lifestyles are meaningfully related in social space and save in distinct ways that have important implications for understanding inequality and stratification. PMID:27904877

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.

Clustering Teachers' Motivations for Teaching

ERIC Educational Resources Information Center

Visser-Wijnveen, Gerda J.; Stes, Ann; Van Petegem, Peter

2014-01-01

The motivation to teach is a powerful, yet neglected, force in teaching at institutes of higher education. A better understanding of academics' motivations for teaching is necessary. The aim of this mixed-method study was to identify groups with distinctively different motivations for teaching. Six clusters were identified: expertise, duty,…

Parental Influences on Adolescent Adjustment: Parenting Styles Versus Parenting Practices

ERIC Educational Resources Information Center

Lee, Sang Min; Daniels, M. Harry; Kissinger, Daniel B.

2006-01-01

The study identified distinct patterns of parental practices that differentially influence adolescent behavior using the National Educational Longitudinal Survey (NELS:88) database. Following Brenner and Fox's research model (1999), the cluster analysis was used to classify the four types of parental practices. The clusters of parenting practices…

Distinct ADHD Symptom Clusters Differentially Associated with Personality Traits

ERIC Educational Resources Information Center

McKinney, Ashley A.; Canu, Will H.; Schneider, H. G.

2013-01-01

Objective: ADHD has been linked to various constructs, yet there is a lack of focus on how its symptom clusters differentially associate with personality, which this study addresses. Method: The current study examines the relationship between impulsive and inattentive ADHD traits and personality, indexed by the Revised NEO Personality Inventory…

Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

PubMed

Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

2017-09-23

This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

Unsupervised classification of major depression using functional connectivity MRI.

PubMed

Zeng, Ling-Li; Shen, Hui; Liu, Li; Hu, Dewen

2014-04-01

The current diagnosis of psychiatric disorders including major depressive disorder based largely on self-reported symptoms and clinical signs may be prone to patients' behaviors and psychiatrists' bias. This study aims at developing an unsupervised machine learning approach for the accurate identification of major depression based on single resting-state functional magnetic resonance imaging scans in the absence of clinical information. Twenty-four medication-naive patients with major depression and 29 demographically similar healthy individuals underwent resting-state functional magnetic resonance imaging. We first clustered the voxels within the perigenual cingulate cortex into two subregions, a subgenual region and a pregenual region, according to their distinct resting-state functional connectivity patterns and showed that a maximum margin clustering-based unsupervised machine learning approach extracted sufficient information from the subgenual cingulate functional connectivity map to differentiate depressed patients from healthy controls with a group-level clustering consistency of 92.5% and an individual-level classification consistency of 92.5%. It was also revealed that the subgenual cingulate functional connectivity network with the highest discriminative power primarily included the ventrolateral and ventromedial prefrontal cortex, superior temporal gyri and limbic areas, indicating that these connections may play critical roles in the pathophysiology of major depression. The current study suggests that subgenual cingulate functional connectivity network signatures may provide promising objective biomarkers for the diagnosis of major depression and that maximum margin clustering-based unsupervised machine learning approaches may have the potential to inform clinical practice and aid in research on psychiatric disorders. Copyright © 2013 Wiley Periodicals, Inc.

Cluster analysis applied to localized dispersion curves in East Asia: the limits of surface wave resolution

NASA Astrophysics Data System (ADS)

Witek, M.; van der Lee, S.; Kang, T. S.; Chang, S. J.; Ning, J.; Ning, S.

2017-12-01

We have measured Rayleigh wave group velocity dispersion curves from one year of station-pair cross-correlations of continuous vertical-component broadband data from 1082 seismic stations in regional networks across China, Korea, Taiwan, and Japan for the year 2011. We use the measurements to map local dispersion anomalies for periods in the range 6-40 s. We combined our ambient noise data set with the earthquake group velocity data set of Ma et al. (2014), and then applied agglomerative hierarchical clustering to the localized dispersion curves. We find that the dispersion curves naturally organize themselves into distinct tectonic regions. For our distribution of interstation distances, only 8 distinct regions need to be defined. Additional clusters reduce the overall data misfit by increasingly smaller amounts. The size and number of clusters needed to suitably predict the data may give an indication of the resolving power of the data set. The regions that emerge from the cluster analysis include Tibet, the Sea of Japan, the South China Block and the Korean peninsula, the Ordos and Yangtze cratons, and Mesozoic rift basins such as the Songliao, Bohai Bay and Ulleung basins. We also performed a traditional inversion for 3D S-velocity structure, and the resulting model fits the data as well as the 8-cluster model, while both models fit the earthquake data and ambient noise data better than the LITHO1.0 model of Pasyanos et al. (2014). Our 3D model of the crust and upper mantle confirms many of the features seen in previous studies of the region, most notably the lithospheric thinning going from west to east and low velocity zones in the crust on the Tibetan periphery. We conclude that cluster analysis is able to greatly reduce the dimensionality of surface wave dispersion data, in the sense that a data set of over half a million dispersion curves is sufficiently predicted by appropriately averaging over a relatively small set of distinct tectonic regions. The resulting clustered model objectively quantifies the more intuitive ways in which we usually tend to interpret tomographic models.

Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis.

PubMed

Vavougios, George D; George D, George; Pastaka, Chaido; Zarogiannis, Sotirios G; Gourgoulianis, Konstantinos I

2016-02-01

Phenotyping obstructive sleep apnea syndrome's comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data-driven approach. Data from 1472 consecutive patient records were recovered from our hospital's database. Categorical principal component analysis and two-step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one-way analysis of variance with Bonferroni correction and chi-square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, 'healthy, reporting sleeping related symptoms'; B, 'mild obstructive sleep apnea syndrome without significant comorbidities'; C1: 'moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities'; C2: 'moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke'; D1: 'severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension'; and D2: 'severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index'. Clusters differed significantly in apnea-hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one-way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at-risk groups. Finally, determining predictors of comorbidity for the moderate and severe strata of these phenotypes implies a need to take these factors into account when considering obstructive sleep apnea syndrome treatment options. © 2015 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

Hydrophobic mismatch sorts SNARE proteins into distinct membrane domains

PubMed Central

Milovanovic, Dragomir; Honigmann, Alf; Koike, Seiichi; Göttfert, Fabian; Pähler, Gesa; Junius, Meike; Müllar, Stefan; Diederichsen, Ulf; Janshoff, Andreas; Grubmüller, Helmut; Risselada, Herre J.; Eggeling, Christian; Hell, Stefan W.; van den Bogaart, Geert; Jahn, Reinhard

2015-01-01

The clustering of proteins and lipids in distinct microdomains is emerging as an important principle for the spatial patterning of biological membranes. Such domain formation can be the result of hydrophobic and ionic interactions with membrane lipids as well as of specific protein–protein interactions. Here using plasma membrane-resident SNARE proteins as model, we show that hydrophobic mismatch between the length of transmembrane domains (TMDs) and the thickness of the lipid membrane suffices to induce clustering of proteins. Even when the TMDs differ in length by only a single residue, hydrophobic mismatch can segregate structurally closely homologous membrane proteins in distinct membrane domains. Domain formation is further fine-tuned by interactions with polyanionic phosphoinositides and homo and heterotypic protein interactions. Our findings demonstrate that hydrophobic mismatch contributes to the structural organization of membranes. PMID:25635869

Methylation profiling of choroid plexus tumors reveals 3 clinically distinct subgroups.

PubMed

Thomas, Christian; Sill, Martin; Ruland, Vincent; Witten, Anika; Hartung, Stefan; Kordes, Uwe; Jeibmann, Astrid; Beschorner, Rudi; Keyvani, Kathy; Bergmann, Markus; Mittelbronn, Michel; Pietsch, Torsten; Felsberg, Jörg; Monoranu, Camelia M; Varlet, Pascale; Hauser, Peter; Olar, Adriana; Grundy, Richard G; Wolff, Johannes E; Korshunov, Andrey; Jones, David T; Bewerunge-Hudler, Melanie; Hovestadt, Volker; von Deimling, Andreas; Pfister, Stefan M; Paulus, Werner; Capper, David; Hasselblatt, Martin

2016-06-01

Choroid plexus tumors are intraventricular neoplasms derived from the choroid plexus epithelium. A better knowledge of molecular factors involved in choroid plexus tumor biology may aid in identifying patients at risk for recurrence. Methylation profiles were examined in 29 choroid plexus papillomas (CPPs, WHO grade I), 32 atypical choroid plexus papillomas (aCPPs, WHO grade II), and 31 choroid plexus carcinomas (CPCs, WHO grade III) by Illumina Infinium HumanMethylation450 Bead Chip Array. Unsupervised hierarchical clustering identified 3 subgroups: methylation cluster 1 (pediatric CPP and aCPP of mainly supratentorial location), methylation cluster 2 (adult CPP and aCPP of mainly infratentorial location), and methylation cluster 3 (pediatric CPP, aCPP, and CPC of supratentorial location). In methylation cluster 3, progression-free survival (PFS) accounted for a mean of 72 months (CI, 55-89 mo), whereas only 1 of 42 tumors of methylation clusters 1 and 2 progressed (P< .001). On stratification of outcome data according to WHO grade, all CPCs clustered within cluster 3 and were associated with shorter overall survival (mean, 105 mo [CI, 81-128 mo]) and PFS (mean, 55 mo [CI, 36-73 mo]). The aCPP of methylation cluster 3 also progressed frequently (mean, 69 mo [CI, 44-93 mo]), whereas no tumor progression was observed in aCPP of methylation clusters 1 and 2 (P< .05). Only 1 of 29 CPPs recurred. Methylation profiling of choroid plexus tumors reveals 3 distinct subgroups (ie, pediatric low-risk choroid plexus tumors [cluster 1], adult low-risk choroid plexus tumors [cluster 2], and pediatric high-risk choroid plexus tumors [cluster 3]) and may provide useful prognostic information in addition to histopathology. Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

New Insights on Taxonomy, Phylogeny and Population Genetics of Leishmania (Viannia) Parasites Based on Multilocus Sequence Analysis

PubMed Central

Boité, Mariana C.; Mauricio, Isabel L.; Miles, Michael A.; Cupolillo, Elisa

2012-01-01

The Leishmania genus comprises up to 35 species, some with status still under discussion. The multilocus sequence typing (MLST)—extensively used for bacteria—has been proposed for pathogenic trypanosomatids. For Leishmania, however, a detailed analysis and revision on the taxonomy is still required. We have partially sequenced four housekeeping genes—glucose-6-phosphate dehydrogenase (G6PD), 6-phosphogluconate dehydrogenase (6PGD), mannose phosphate isomerase (MPI) and isocitrate dehydrogenase (ICD)—from 96 Leishmania (Viannia) strains and assessed their discriminatory typing capacity. The fragments had different degrees of diversity, and are thus suitable to be used in combination for intra- and inter-specific inferences. Species-specific single nucleotide polymorphisms were detected, but not for all species; ambiguous sites indicating heterozygosis were observed, as well as the putative homozygous donor. A large number of haplotypes were detected for each marker; for 6PGD a possible ancestral allele for L. (Viannia) was found. Maximum parsimony-based haplotype networks were built. Strains of different species, as identified by multilocus enzyme electrophoresis (MLEE), formed separated clusters in each network, with exceptions. NeighborNet of concatenated sequences confirmed species-specific clusters, suggesting recombination occurring in L. braziliensis and L. guyanensis. Phylogenetic analysis indicates L. lainsoni and L. naiffi as the most divergent species and does not support L. shawi as a distinct species, placing it in the L. guyanensis cluster. BURST analysis resulted in six clonal complexes (CC), corresponding to distinct species. The L. braziliensis strains evaluated correspond to one widely geographically distributed CC and another restricted to one endemic area. This study demonstrates the value of systematic multilocus sequence analysis (MLSA) for determining intra- and inter-species relationships and presents an approach to validate the species status of some entities. Furthermore, it contributes to the phylogeny of L. (Viannia) and might be helpful for epidemiological and population genetics analysis based on haplotype/diplotype determinations and inferences. PMID:23133690

Automated grouping of action potentials of human embryonic stem cell-derived cardiomyocytes.

PubMed

Gorospe, Giann; Zhu, Renjun; Millrod, Michal A; Zambidis, Elias T; Tung, Leslie; Vidal, Rene

2014-09-01

Methods for obtaining cardiomyocytes from human embryonic stem cells (hESCs) are improving at a significant rate. However, the characterization of these cardiomyocytes (CMs) is evolving at a relatively slower rate. In particular, there is still uncertainty in classifying the phenotype (ventricular-like, atrial-like, nodal-like, etc.) of an hESC-derived cardiomyocyte (hESC-CM). While previous studies identified the phenotype of a CM based on electrophysiological features of its action potential, the criteria for classification were typically subjective and differed across studies. In this paper, we use techniques from signal processing and machine learning to develop an automated approach to discriminate the electrophysiological differences between hESC-CMs. Specifically, we propose a spectral grouping-based algorithm to separate a population of CMs into distinct groups based on the similarity of their action potential shapes. We applied this method to a dataset of optical maps of cardiac cell clusters dissected from human embryoid bodies. While some of the nine cell clusters in the dataset are presented with just one phenotype, the majority of the cell clusters are presented with multiple phenotypes. The proposed algorithm is generally applicable to other action potential datasets and could prove useful in investigating the purification of specific types of CMs from an electrophysiological perspective.

Automated Grouping of Action Potentials of Human Embryonic Stem Cell-Derived Cardiomyocytes

PubMed Central

Gorospe, Giann; Zhu, Renjun; Millrod, Michal A.; Zambidis, Elias T.; Tung, Leslie; Vidal, René

2015-01-01

Methods for obtaining cardiomyocytes from human embryonic stem cells (hESCs) are improving at a significant rate. However, the characterization of these cardiomyocytes is evolving at a relatively slower rate. In particular, there is still uncertainty in classifying the phenotype (ventricular-like, atrial-like, nodal-like, etc.) of an hESC-derived cardiomyocyte (hESC-CM). While previous studies identified the phenotype of a cardiomyocyte based on electrophysiological features of its action potential, the criteria for classification were typically subjective and differed across studies. In this paper, we use techniques from signal processing and machine learning to develop an automated approach to discriminate the electrophysiological differences between hESC-CMs. Specifically, we propose a spectral grouping-based algorithm to separate a population of cardiomyocytes into distinct groups based on the similarity of their action potential shapes. We applied this method to a dataset of optical maps of cardiac cell clusters dissected from human embryoid bodies (hEBs). While some of the 9 cell clusters in the dataset presented with just one phenotype, the majority of the cell clusters presented with multiple phenotypes. The proposed algorithm is generally applicable to other action potential datasets and could prove useful in investigating the purification of specific types of cardiomyocytes from an electrophysiological perspective. PMID:25148658

The symptom cluster-based approach to individualize patient-centered treatment for major depression.

PubMed

Lin, Steven Y; Stevens, Michael B

2014-01-01

Unipolar major depressive disorder is a common, disabling, and costly disease that is the leading cause of ill health, early death, and suicide in the United States. Primary care doctors, in particular family physicians, are the first responders in this silent epidemic. Although more than a dozen different antidepressants in 7 distinct classes are widely used to treat depression in primary care, there is no evidence that one drug is superior to another. Comparative effectiveness studies have produced mixed results, and no specialty organization has published recommendations on how to choose antidepressants in a rational, evidence-based manner. In this article we present the theory and evidence for an individualized, patient-centered treatment model for major depression designed around a targeted symptom cluster-based approach to antidepressant selection. When using this model for healthy adults with major depressive disorder, the choice of antidepressants should be guided by the presence of 1 of 4 common symptom clusters: anxiety, fatigue, insomnia, and pain. This model was built to foster future research, provide a logical framework for teaching residents how to select antidepressants, and equip primary care doctors with a structured treatment strategy to deliver optimal patient-centered care in the management of a debilitating disease: major depressive disorder.

External tufted cells in the main olfactory bulb form two distinct subpopulations.

PubMed

Antal, Miklós; Eyre, Mark; Finklea, Bryson; Nusser, Zoltan

2006-08-01

The glomeruli of the main olfactory bulb are the first processing station of the olfactory pathway, where complex interactions occur between sensory axons, mitral cells and a variety of juxtaglomerular neurons, including external tufted cells (ETCs). Despite a number of studies characterizing ETCs, little is known about how their morphological and functional properties correspond to each other. Here we determined the active and passive electrical properties of ETCs using in vitro whole-cell recordings, and correlated them with their dendritic arborization patterns. Principal component followed by cluster analysis revealed two distinct subpopulations of ETCs based on their electrophysiological properties. Eight out of 12 measured physiological parameters exhibited significant difference between the two subpopulations, including the membrane time constant, amplitude of spike afterhyperpolarization, variance in the interspike interval distribution and subthreshold resonance. Cluster analysis of the morphological properties of the cells also revealed two subpopulations, the most prominent dissimilarity between the groups being the presence or absence of secondary, basal dendrites. Finally, clustering the cells taking all measured properties into account also indicated the presence of two subpopulations that mapped in an almost perfect one-to-one fashion to both the physiologically and the morphologically derived groups. Our results demonstrate that a number of functional and structural properties of ETCs are highly predictive of one another. However, cells within each subpopulation exhibit pronounced variability, suggesting a large degree of specialization evolved to fulfil specific functional requirements in olfactory information processing.

External tufted cells in the main olfactory bulb form two distinct subpopulations

PubMed Central

Antal, Miklós; Eyre, Mark; Finklea, Bryson; Nusser, Zoltan

2006-01-01

The glomeruli of the main olfactory bulb are the first processing station of the olfactory pathway, where complex interactions occur between sensory axons, mitral cells and a variety of juxtaglomerular neurons, including external tufted cells (ETCs). Despite a number of studies characterizing ETCs, little is known about how their morphological and functional properties correspond to each other. Here we determined the active and passive electrical properties of ETCs using in vitro whole-cell recordings, and correlated them with their dendritic arborization patterns. Principal component followed by cluster analysis revealed two distinct subpopulations of ETCs based on their electrophysiological properties. Eight out of 12 measured physiological parameters exhibited significant difference between the two subpopulations, including the membrane time constant, amplitude of spike afterhyperpolarization, variance in the interspike interval distribution and subthreshold resonance. Cluster analysis of the morphological properties of the cells also revealed two subpopulations, the most prominent dissimilarity between the groups being the presence or absence of secondary, basal dendrites. Finally, clustering the cells taking all measured properties into account also indicated the presence of two subpopulations that mapped in an almost perfect one-to-one fashion to both the physiologically and the morphologically derived groups. Our results demonstrate that a number of functional and structural properties of ETCs are highly predictive of one another. However, cells within each subpopulation exhibit pronounced variability, suggesting a large degree of specialization evolved to fulfil specific functional requirements in olfactory information processing. PMID:16930438

Hand kinematics of piano playing

PubMed Central

Flanders, Martha; Soechting, John F.

2011-01-01

Dexterous use of the hand represents a sophisticated sensorimotor function. In behaviors such as playing the piano, it can involve strong temporal and spatial constraints. The purpose of this study was to determine fundamental patterns of covariation of motion across joints and digits of the human hand. Joint motion was recorded while 5 expert pianists played 30 excerpts from musical pieces, which featured ∼50 different tone sequences and fingering. Principal component analysis and cluster analysis using an expectation-maximization algorithm revealed that joint velocities could be categorized into several patterns, which help to simplify the description of the movements of the multiple degrees of freedom of the hand. For the thumb keystroke, two distinct patterns of joint movement covariation emerged and they depended on the spatiotemporal patterns of the task. For example, the thumb-under maneuver was clearly separated into two clusters based on the direction of hand translation along the keyboard. While the pattern of the thumb joint velocities differed between these clusters, the motions at the metacarpo-phalangeal and proximal-phalangeal joints of the four fingers were more consistent. For a keystroke executed with one of the fingers, there were three distinct patterns of joint rotations, across which motion at the striking finger was fairly consistent, but motion of the other fingers was more variable. Furthermore, the amount of movement spillover of the striking finger to the adjacent fingers was small irrespective of the finger used for the keystroke. These findings describe an unparalleled amount of independent motion of the fingers. PMID:21880938

A convergent functional architecture of the insula emerges across imaging modalities.

PubMed

Kelly, Clare; Toro, Roberto; Di Martino, Adriana; Cox, Christine L; Bellec, Pierre; Castellanos, F Xavier; Milham, Michael P

2012-07-16

Empirical evidence increasingly supports the hypothesis that patterns of intrinsic functional connectivity (iFC) are sculpted by a history of evoked coactivation within distinct neuronal networks. This, together with evidence of strong correspondence among the networks defined by iFC and those delineated using a variety of other neuroimaging techniques, suggests a fundamental brain architecture detectable across multiple functional and structural imaging modalities. Here, we leverage this insight to examine the functional organization of the human insula. We parcellated the insula on the basis of three distinct neuroimaging modalities - task-evoked coactivation, intrinsic (i.e., task-independent) functional connectivity, and gray matter structural covariance. Clustering of these three different covariance-based measures revealed a convergent elemental organization of the insula that likely reflects a fundamental brain architecture governing both brain structure and function at multiple spatial scales. While not constrained to be hierarchical, our parcellation revealed a pseudo-hierarchical, multiscale organization that was consistent with previous clustering and meta-analytic studies of the insula. Finally, meta-analytic examination of the cognitive and behavioral domains associated with each of the insular clusters obtained elucidated the broad functional dissociations likely underlying the topography observed. To facilitate future investigations of insula function across healthy and pathological states, the insular parcels have been made freely available for download via http://fcon_1000.projects.nitrc.org, along with the analytic scripts used to perform the parcellations. Copyright © 2012 Elsevier Inc. All rights reserved.

There are four dynamically and functionally distinct populations of E-cadherin in cell junctions

PubMed Central

Erami, Zahra; Timpson, Paul; Yao, Wu; Zaidel-Bar, Ronen; Anderson, Kurt I.

2015-01-01

ABSTRACT E-cadherin is a trans-membrane tumor suppressor responsible for epithelial cell adhesion. E-cadherin forms adhesive clusters through combined extra-cellular cis- and trans-interactions and intracellular interaction with the actin cytoskeleton. Here we identify four populations of E-cadherin within cell junctions based on the molecular interactions which determine their mobility and adhesive properties. Adhesive and non-adhesive populations of E-cadherin each consist of mobile and immobile fractions. Up to half of the E-cadherin immobilized in cell junctions is non-adhesive. Incorporation of E-cadherin into functional adhesions require all three adhesive interactions, with deletion of any one resulting in loss of effective cell-cell adhesion. Interestingly, the only interaction which could independently slow the diffusion of E-cadherin was the tail-mediated intra-cellular interaction. The adhesive and non-adhesive mobile fractions of E-cadherin can be distinguished by their sensitivity to chemical cross-linking with adhesive clusters. Our data define the size, mobility, and adhesive properties of four distinct populations of E-cadherin within cell junctions, and support association with the actin cytoskeleton as the first step in adhesion formation. PMID:26471767

Detecting false positive sequence homology: a machine learning approach.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M

2016-02-24

Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.

One year nationwide evaluation of 24-locus MIRU-VNTR genotyping on Slovenian Mycobacterium tuberculosis isolates.

PubMed

Bidovec-Stojkovic, Urska; Zolnir-Dovc, Manca; Supply, Philip

2011-10-01

Slovenia is one of the few countries where IS6110 RFLP is applied for genotyping M. tuberculosis at a nationwide level, which has been in effect since 2000. Based on S6110 RFLP clustering, typical risk factors and routes of M. tuberculosis transmission were identified, such as alcohol abuse, homelessness, and bars. However, IS6110 RFLP typing suffers from important limitations including a long wait for results, which reduces the potential benefit of molecular-guided tuberculosis (TB) control. PCR-based 24-locus MIRU-VNTR typing combined with spoligotyping has recently emerged as a potential alternative for faster, large-scale genotyping of M. tuberculosis. We compared these genotyping methods for analyzing 196 Slovenian Mycobacterium tuberculosis isolates representing 97.5% of all culture-positive cases included in the Slovenian TB Registry in 2008. IS6110 RFLP and 24-locus MIRU-VNTR typing combined with spoligotyping identified 157 and 155 distinct profiles, 135 and 125 unique isolates, and 61 and 71 clustered isolates grouped into 22 and 29 clusters, respectively. The discriminatory indexes were very close, at 0.9963 and 0.9965, respectively. The majority of the molecular clusters defined by either of the two methods were identical, including in the few cases for which epidemiological links were available. The differences frequently consisted of single-band changes in IS6170-RFLP profiles subdividing a MIRU-VNTR/spoligotype-based cluster. Our one-year nationwide study showed that the results of 24-locus MIRU-VNTR typing combined with spoligotyping reached a high level of concordance with those obtained from IS6110 RFLP typing. Copyright © 2011 Elsevier Ltd. All rights reserved.

Subtypes of female juvenile offenders: a cluster analysis of the Millon Adolescent Clinical Inventory.

PubMed

Stefurak, Tres; Calhoun, Georgia B

2007-01-01

The current study sought to explore subtypes of adolescents within a sample of female juvenile offenders. Using the Millon Adolescent Clinical Inventory with 101 female juvenile offenders, a two-step cluster analysis was performed beginning with a Ward's method hierarchical cluster analysis followed by a K-Means iterative partitioning cluster analysis. The results suggest an optimal three-cluster solution, with cluster profiles leading to the following group labels: Externalizing Problems, Depressed/Interpersonally Ambivalent, and Anxious Prosocial. Analysis along the factors of age, race, offense typology and offense chronicity were conducted to further understand the nature of found clusters. Only the effect for race was significant with the Anxious Prosocial and Depressed Intepersonally Ambivalent clusters appearing disproportionately comprised of African American girls. To establish external validity, clusters were compared across scales of the Behavioral Assessment System for Children - Self Report of Personality, and corroborative distinctions between clusters were found here.

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.

Dehazed Image Quality Assessment by Haze-Line Theory

NASA Astrophysics Data System (ADS)

Song, Yingchao; Luo, Haibo; Lu, Rongrong; Ma, Junkai

2017-06-01

Images captured in bad weather suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. However, there is a lack of evaluation metrics to assess the performance of these algorithms or rate them. In this paper, an indicator of contrast enhancement is proposed basing on the newly proposed haze-line theory. The theory assumes that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. The presence of haze makes each color cluster forms a line, which is named haze-line. By using these haze-lines, we assess performance of dehazing algorithms designed to enhance the contrast by measuring the inter-cluster deviations between different colors of dehazed image. Experimental results demonstrated that the proposed Color Contrast (CC) index correlates well with human judgments of image contrast taken in a subjective test on various scene of dehazed images and performs better than state-of-the-art metrics.

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.

Identification and DUS Testing of Rice Varieties through Microsatellite Markers.

PubMed

Pourabed, Ehsan; Jazayeri Noushabadi, Mohammad Reza; Jamali, Seyed Hossein; Moheb Alipour, Naser; Zareyan, Abbas; Sadeghi, Leila

2015-01-01

Identification and registration of new rice varieties are very important to be free from environmental effects and using molecular markers that are more reliable. The objectives of this study were, first, the identification and distinction of 40 rice varieties consisting of local varieties of Iran, improved varieties, and IRRI varieties using PIC, and discriminating power, second, cluster analysis based on Dice similarity coefficient and UPGMA algorithm, and, third, determining the ability of microsatellite markers to separate varieties utilizing the best combination of markers. For this research, 12 microsatellite markers were used. In total, 83 polymorphic alleles (6.91 alleles per locus) were found. In addition, the variation of PIC was calculated from 0.52 to 0.9. The results of cluster analysis showed the complete discrimination of varieties from each other except for IR58025A and IR58025B. Moreover, cluster analysis could detect the most of the improved varieties from local varieties. Based on the best combination of markers analysis, five pair primers together have shown the same results of all markers for detection among all varieties. Considering the results of this research, we can propose that microsatellite markers can be used as a complementary tool for morphological characteristics in DUS tests.

Classification of neocortical interneurons using affinity propagation.

PubMed

Santana, Roberto; McGarry, Laura M; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2013-01-01

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

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.

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

PubMed

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

2017-09-01

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

Ab initio metadynamics simulations of oxygen/ligand interactions in organoaluminum clusters

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

Alnemrat, Sufian; Hooper, Joseph P., E-mail: jphooper@nps.edu

2014-10-14

Car-Parrinello molecular dynamics combined with a metadynamics algorithm is used to study the initial interaction of O{sub 2} with the low-valence organoaluminum clusters Al{sub 4}Cp{sub 4} (Cp=C{sub 5}H{sub 5}) and Al{sub 4}Cp{sub 4}{sup *} (Cp{sup *}=C{sub 5}[CH{sub 3}]{sub 5}). Prior to reaction with the aluminum core, simulations suggest that the oxygen undergoes a hindered crossing of the steric barrier presented by the outer ligand monolayer. A combination of two collective variables based on aluminum/oxygen distance and lateral oxygen displacement was found to produce distinct reactant, product, and transition states for this process. In the methylated cluster with Cp{sup *} ligands,more » a broad transition state of 45 kJ/mol was observed due to direct steric interactions with the ligand groups and considerable oxygen reorientation. In the non-methylated cluster the ligands distort away from the oxidizer, resulting in a barrier of roughly 34 kJ/mol with minimal O{sub 2} reorientation. A study of the oxygen/cluster system fixed in a triplet multiplicity suggests that the spin state does not affect the initial steric interaction with the ligands. The metadynamics approach appears to be a promising means of analyzing the initial steps of such oxidation reactions for ligand-protected clusters.« less

Organic dairy farmers put more emphasis on production traits than conventional farmers.

PubMed

Slagboom, M; Kargo, M; Edwards, D; Sørensen, A C; Thomasen, J R; Hjortø, L

2016-12-01

The overall aim of this research was to characterize the preferences of Danish dairy farmers for improvements in breeding goal traits. The specific aims were (1) to investigate the presence of heterogeneity in farmers' preferences by means of cluster analysis, and (2) to associate these clusters with herd characteristics and production systems (organic or conventional). We established a web-based survey to characterize the preferences of farmers for improvements in 10 traits, by means of pairwise rankings. We also collected a considerable number of herd characteristics. Overall, 106 organic farmers and 290 conventional farmers answered the survey, all with Holstein cows. The most preferred trait improvement was cow fertility, and the least preferred was calving difficulty. By means of cluster analysis, we identified 4 distinct clusters of farmers and named them according to the trait improvements that were most preferred: Health and Fertility, Production and Udder Health, Survival, and Fertility and Production. Some herd characteristics differed between clusters; for example, farmers in the Survival cluster had twice the percentage of dead cows in their herds compared with the other clusters, and farmers that gave the highest ranking to cow and heifer fertility had the lowest conception rate in their herds. This finding suggests that farmers prefer to improve traits that are more problematic in their herd. The proportion of organic and conventional farmers also differed between clusters; we found a higher proportion of organic farmers in the production-based clusters. When we analyzed organic and conventional data separately, we found that organic farmers ranked production traits higher than conventional farmers. The herds of organic farmers had lower milk yields and lower disease incidences, which might explain the high ranking of milk production and the low ranking of disease traits. This study shows that heterogeneity exists in farmers' preferences for improvements in breeding goal traits, that organic and conventional farmers differ in their preferences, and that herd characteristics can be linked to different farmer clusters. The results of this study could be used for the future development of breeding goals in Danish Holstein cows and for the development of customized total merit indices based on farmer preferences. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Statistical survey of day-side magnetospheric current flow using Cluster observations: magnetopause

NASA Astrophysics Data System (ADS)

Liebert, Evelyn; Nabert, Christian; Perschke, Christopher; Fornaçon, Karl-Heinz; Glassmeier, Karl-Heinz

2017-05-01

We present a statistical survey of current structures observed by the Cluster spacecraft at high-latitude day-side magnetopause encounters in the close vicinity of the polar cusps. Making use of the curlometer technique and the fluxgate magnetometer data, we calculate the 3-D current densities and investigate the magnetopause current direction, location, and magnitude during varying solar wind conditions. We find that the orientation of the day-side current structures is in accordance with existing magnetopause current models. Based on the ambient plasma properties, we distinguish five different transition regions at the magnetopause surface and observe distinctive current properties for each region. Additionally, we find that the location of currents varies with respect to the onset of the changes in the plasma environment during magnetopause crossings.

Cluster analysis of cognitive performance in elderly and demented subjects.

PubMed

Giaquinto, S; Nolfe, G; Calvani, M

1985-06-01

48 elderly normals, 14 demented subjects and 76 young controls were tested for basic cognitive functions. All the tests were quantified and could therefore be subjected to statistical analysis. The results show a difference in the speed of information processing and in memory load between the young controls and elderly normals but the age groups differed in quantitative terms only. Cluster analysis showed that the elderly and the demented formed two distinctly separate groups at the qualitative level, the basic cognitive processes being damaged in the demented group. Age thus appears to be only a risk factor for dementia and not its cause. It is concluded that batteries based on precise and measurable tasks are the most appropriate not only for the study of dementia but for rehabilitation purposes too.

Structures and Spectroscopic Properties of F-(H2O) n with n = 1-10 Clusters from a Global Search Based On Density Functional Theory.

PubMed

Shi, Ruili; Wang, Pengju; Tang, Lingli; Huang, Xiaoming; Chen, Yonggang; Su, Yan; Zhao, Jijun

2018-04-05

Using a genetic algorithm incorporated in density functional theory, we explore the ground state structures of fluoride anion-water clusters F - (H 2 O) n with n = 1-10. The F - (H 2 O) n clusters prefer structures in which the F - anion remains at the surface of the structure and coordinates with four water molecules, as the F - (H 2 O) n clusters have strong F - -H 2 O interactions as well as strong hydrogen bonds between H 2 O molecules. The strong interaction between the F - anion and adjacent H 2 O molecule leads to a longer O-H distance in the adjacent molecule than in an individual water molecule. The simulated infrared (IR) spectra of the F - (H 2 O) 1-5 clusters obtained via second-order vibrational perturbation theory (VPT2) and including anharmonic effects reproduce the experimental results quite well. The strong interaction between the F - anion and water molecules results in a large redshift (600-2300 cm -1 ) of the adjacent O-H stretching mode. Natural bond orbital (NBO) analysis of the lowest-energy structures of the F - (H 2 O) 1-10 clusters illustrates that charge transfer from the lone pair electron orbital of F - to the antibonding orbital of the adjacent O-H is mainly responsible for the strong interaction between the F - anion and water molecules, which leads to distinctly different geometric and vibrational properties compared with neutral water clusters.

A young solar twin in the Rosette cluster NGC 2244 line of sight

NASA Astrophysics Data System (ADS)

Huber, Jeremy M.; Kielkopf, John F.; Mengel, Matthew; Carter, Bradley D.; Ferland, Gary J.; Clark, Frank O.

2018-05-01

Based on prior precision photometry and cluster age analysis, the bright star GSC 00154-01819 is a possible young pre-main sequence member of the Rosette cluster, NGC 2244. As part of a comprehensive study of the large-scale structure of the Rosette and its excitation by the cluster stars, we noted this star as a potential backlight for a probe of the interstellar medium and extinction along the sight line towards a distinctive nebular feature projected on to the cluster centre. New high-resolution spectra of the star were taken with the University College London Echelle Spectrograph of the AAT. They reveal that rather than being a reddened spectral type B or A star within the Mon OB2 association, it is a nearby, largely unreddened, solar twin of spectral type G2V less than 180 Myr old. It is about 219 pc from the Sun with a barycentric radial velocity of +14.35 ± 1.99 km s-1. The spectrum of the Rosette behind it and along this line of sight shows a barycentric radial velocity of +26.0 ± 2.4 km s-1 in H α, and a full width at half-maximum velocity dispersion of 61.94 ± 1.38 km s-1.

A classification of substance-dependent men on temperament and severity variables.

PubMed

Henderson, Melinda J; Galen, Luke W

2003-06-01

This study examined the validity of classifying substance abusers based on temperament and dependence severity, and expanded the scope of typology differences to proximal determinants of use (e.g., expectancies, motives). Patients were interviewed about substance use, depression, and family history of alcohol and drug abuse. Self-report instruments measuring temperament, expectancies, and motives were completed. Participants were 147 male veterans admitted to inpatient substance abuse treatment at a U.S. Department of Veterans Affairs medical center. Cluster analysis identified four types of users with two high substance problem severity and two low substance problem severity groups. Two, high problem severity, early onset groups differed only on the cluster variable of negative affectivity (NA), but showed differences on antisocial personality characteristics, hypochondriasis, and coping motives for alcohol. The two low problem severity groups were distinguished by age of onset and positive affectivity (PA). The late onset, low PA group had a higher incidence of depression, a greater tendency to use substances in solitary contexts, and lower enhancement motives for alcohol compared to the early onset, high PA cluster. The four-cluster solution yielded more distinctions on external criteria than the two-cluster solution. Such temperament variation within both high and low severity substance abusers may be important for treatment planning.

Structural Principles or Frequency of Use? An ERP Experiment on the Learnability of Consonant Clusters

PubMed Central

Wiese, Richard; Orzechowska, Paula; Alday, Phillip M.; Ulbrich, Christiane

2017-01-01

Phonological knowledge of a language involves knowledge about which segments can be combined under what conditions. Languages vary in the quantity and quality of licensed combinations, in particular sequences of consonants, with Polish being a language with a large inventory of such combinations. The present paper reports on a two-session experiment in which Polish-speaking adult participants learned nonce words with final consonant clusters. The aim was to study the role of two factors which potentially play a role in the learning of phonotactic structures: the phonological principle of sonority (ordering sound segments within the syllable according to their inherent loudness) and the (non-) existence as a usage-based phenomenon. EEG responses in two different time windows (adversely to behavioral responses) show linguistic processing by native speakers of Polish to be sensitive to both distinctions, in spite of the fact that Polish is rich in sonority-violating clusters. In particular, a general learning effect in terms of an N400 effect was found which was demonstrated to be different for sonority-obeying clusters than for sonority-violating clusters. Furthermore, significant interactions of formedness and session, and of existence and session, demonstrate that both factors, the sonority principle and the frequency pattern, play a role in the learning process. PMID:28119642

Tiled Microarray Identification of Novel Viral Transcript Structures and Distinct Transcriptional Profiles during Two Modes of Productive Murine Gammaherpesvirus 68 Infection

PubMed Central

Cheng, Benson Yee Hin; Zhi, Jizu; Santana, Alexis; Khan, Sohail; Salinas, Eduardo; Forrest, J. Craig; Zheng, Yueting; Jaggi, Shirin; Leatherwood, Janet

2012-01-01

We applied a custom tiled microarray to examine murine gammaherpesvirus 68 (MHV68) polyadenylated transcript expression in a time course of de novo infection of fibroblast cells and following phorbol ester-mediated reactivation from a latently infected B cell line. During de novo infection, all open reading frames (ORFs) were transcribed and clustered into four major temporal groups that were overlapping yet distinct from clusters based on the phorbol ester-stimulated B cell reactivation time course. High-density transcript analysis at 2-h intervals during de novo infection mapped gene boundaries with a 20-nucleotide resolution, including a previously undefined ORF73 transcript and the MHV68 ORF63 homolog of Kaposi's sarcoma-associated herpesvirus vNLRP1. ORF6 transcript initiation was mapped by tiled array and confirmed by 5′ rapid amplification of cDNA ends. The ∼1.3-kb region upstream of ORF6 was responsive to lytic infection and MHV68 RTA, identifying a novel RTA-responsive promoter. Transcription in intergenic regions consistent with the previously defined expressed genomic regions was detected during both types of productive infection. We conclude that the MHV68 transcriptome is dynamic and distinct during de novo fibroblast infection and upon phorbol ester-stimulated B cell reactivation, highlighting the need to evaluate further transcript structure and the context-dependent molecular events that govern viral gene expression during chronic infection. PMID:22318145

Dating Violence & Sexual Harassment across the Bully-Victim Continuum among Middle and High School Students

ERIC Educational Resources Information Center

Espelage, Dorothy L.; Holt, Melissa K.

2007-01-01

Associations among bullying, peer victimization, sexual harassment, and dating violence were examined among 684 middle and high school students. Cluster analysis of self-report measures revealed four distinct bully-victim subtypes: uninvolved, victims, bully-victims, and bullies. African-American students comprised the bully cluster more than…

Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference

ERIC Educational Resources Information Center

Schochet, Peter Z.

2013-01-01

This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for…

Clustering P-Wave Receiver Functions To Constrain Subsurface Seismic Structure

NASA Astrophysics Data System (ADS)

Chai, C.; Larmat, C. S.; Maceira, M.; Ammon, C. J.; He, R.; Zhang, H.

2017-12-01

The acquisition of high-quality data from permanent and temporary dense seismic networks provides the opportunity to apply statistical and machine learning techniques to a broad range of geophysical observations. Lekic and Romanowicz (2011) used clustering analysis on tomographic velocity models of the western United States to perform tectonic regionalization and the velocity-profile clusters agree well with known geomorphic provinces. A complementary and somewhat less restrictive approach is to apply cluster analysis directly to geophysical observations. In this presentation, we apply clustering analysis to teleseismic P-wave receiver functions (RFs) continuing efforts of Larmat et al. (2015) and Maceira et al. (2015). These earlier studies validated the approach with surface waves and stacked EARS RFs from the USArray stations. In this study, we experiment with both the K-means and hierarchical clustering algorithms. We also test different distance metrics defined in the vector space of RFs following Lekic and Romanowicz (2011). We cluster data from two distinct data sets. The first, corresponding to the western US, was by smoothing/interpolation of receiver-function wavefield (Chai et al. 2015). Spatial coherence and agreement with geologic region increase with this simpler, spatially smoothed set of observations. The second data set is composed of RFs for more than 800 stations of the China Digital Seismic Network (CSN). Preliminary results show a first order agreement between clusters and tectonic region and each region cluster includes a distinct Ps arrival, which probably reflects differences in crustal thickness. Regionalization remains an important step to characterize a model prior to application of full waveform and/or stochastic imaging techniques because of the computational expense of these types of studies. Machine learning techniques can provide valuable information that can be used to design and characterize formal geophysical inversion, providing information on spatial variability in the subsurface geology.

Corepressive interaction and clustering of degrade-and-fire oscillators

PubMed Central

Fernandez, Bastien; Tsimring, Lev S.

2016-01-01

Strongly nonlinear degrade-and-fire (DF) oscillations may emerge in genetic circuits having a delayed negative feedback loop as their core element. Here we study the synchronization of DF oscillators coupled through a common repressor field. For weak coupling, initially distinct oscillators remain desynchronized. For stronger coupling, oscillators can be forced to wait in the repressed state until the global repressor field is sufficiently degraded, and then they fire simultaneously forming a synchronized cluster. Our analytical theory provides necessary and sufficient conditions for clustering and specifies the maximum number of clusters that can be formed in the asymptotic regime. We find that in the thermodynamic limit a phase transition occurs at a certain coupling strength from the weakly clustered regime with only microscopic clusters to a strongly clustered regime where at least one giant cluster has to be present. PMID:22181453

Structure of clusters with bimodal distribution of galaxy line-of-sight velocities III: A1831

NASA Astrophysics Data System (ADS)

Kopylov, A. I.; Kopylova, F. G.

2010-07-01

We study the A1831 cluster within the framework of our program of the investigation of galaxy clusters with bimodal velocity distributions (i.e., clusters where the velocities of subsystems differ by more than Δ cz ˜ 3000 km/s).We identify two subsystems in this cluster: A1831A ( cz = 18970 km/s) and A1831B ( cz = 22629 km/s) and directly estimate the distances to these subsystems using three methods applied to early-type galaxies: the Kormendy relation, the photometric plane, and the fundamental plane. To this end, we use the results of our observations made with the 1-m telescope of the Special Astrophysical Observatory of the Russian Academy of Sciences and the data adopted from the SDSS DR6 catalog. We confirmed at a 99% confidence level that (1) the two subsystems are located at different distances, which are close to their Hubble distances, and (2) the two subsystems are located behind one another along the line of sight and are not gravitationally bound to each other. Both clusters have a complex internal structure, which makes it difficult to determine their dynamical parameters. Our estimates for the velocity dispersions and masses of the two clusters: 480 km/s and 1.9 × 1014 M ⊙ for A1831A, 952 km/s and 1.4 × 1015 M ⊙ for A1831B should be views as upper limits. At least three spatially and kinematically distinct groups of galaxies can be identified in the foreground cluster A1831A, and this fact is indicative of its incomplete dynamical relaxation. Neither can we rule out the possibility of a random projection. The estimate of the mass of the main cluster A1831B based on the dispersion of the line-of-sight velocities of galaxies is two-to-three times greater than the independent mass estimates based on the total K-band luminosity, temperature, and luminosity of the X-ray gas of the cluster. This fact, combined with the peculiarities of its kinematical structure, leads us to conclude that the cluster is in a dynamically active state: galaxies and groups of galaxies with large line-of-sight velocities relative to the center of the cluster accrete onto the virialized nucleus of the cluster (possibly, along the filament directed close to the line of sight).

The Gap Procedure: for the identification of phylogenetic clusters in HIV-1 sequence data.

PubMed

Vrbik, Irene; Stephens, David A; Roger, Michel; Brenner, Bluma G

2015-11-04

In the context of infectious disease, sequence clustering can be used to provide important insights into the dynamics of transmission. Cluster analysis is usually performed using a phylogenetic approach whereby clusters are assigned on the basis of sufficiently small genetic distances and high bootstrap support (or posterior probabilities). The computational burden involved in this phylogenetic threshold approach is a major drawback, especially when a large number of sequences are being considered. In addition, this method requires a skilled user to specify the appropriate threshold values which may vary widely depending on the application. This paper presents the Gap Procedure, a distance-based clustering algorithm for the classification of DNA sequences sampled from individuals infected with the human immunodeficiency virus type 1 (HIV-1). Our heuristic algorithm bypasses the need for phylogenetic reconstruction, thereby supporting the quick analysis of large genetic data sets. Moreover, this fully automated procedure relies on data-driven gaps in sorted pairwise distances to infer clusters, thus no user-specified threshold values are required. The clustering results obtained by the Gap Procedure on both real and simulated data, closely agree with those found using the threshold approach, while only requiring a fraction of the time to complete the analysis. Apart from the dramatic gains in computational time, the Gap Procedure is highly effective in finding distinct groups of genetically similar sequences and obviates the need for subjective user-specified values. The clusters of genetically similar sequences returned by this procedure can be used to detect patterns in HIV-1 transmission and thereby aid in the prevention, treatment and containment of the disease.

Solid state, thermal synthesis of site-specific protein-boron cluster conjugates and their physicochemical and biochemical properties.

PubMed

Goszczyński, Tomasz M; Kowalski, Konrad; Leśnikowski, Zbigniew J; Boratyński, Janusz

2015-02-01

Boron clusters represent a vast family of boron-rich compounds with extraordinary properties that provide the opportunity of exploitation in different areas of chemistry and biology. In addition, boron clusters are clinically used in boron neutron capture therapy (BNCT) of tumors. In this paper, a novel, in solid state (solvent free), thermal method for protein modification with boron clusters has been proposed. The method is based on a cyclic ether ring opening in oxonium adduct of cyclic ether and a boron cluster with nucleophilic centers of the protein. Lysozyme was used as the model protein, and the physicochemical and biological properties of the obtained conjugates were characterized. The main residues of modification were identified as arginine-128 and threonine-51. No significant changes in the secondary or tertiary structures of the protein after tethering of the boron cluster were found using mass spectrometry and circular dichroism measurements. However, some changes in the intermolecular interactions and hydrodynamic and catalytic properties were observed. To the best of our knowledge, we have described the first example of an application of cyclic ether ring opening in the oxonium adducts of a boron cluster for protein modification. In addition, a distinctive feature of the proposed approach is performing the reaction in solid state and at elevated temperature. The proposed methodology provides a new route to protein modification with boron clusters and extends the range of innovative molecules available for biological and medical testing. Copyright © 2014 Elsevier B.V. All rights reserved.

Psychological profiling of offender characteristics from crime behaviors in serial rape offences.

PubMed

Kocsis, Richard N; Cooksey, Ray W; Irwin, Harvey J

2002-04-01

Criminal psychological profiling has progressively been incorporated into police procedures despite a dearth of empirical research. Indeed, in the study of serial violent crimes for the purpose of psychological profiling, very few original, quantitative, academically reviewed studies actually exist. This article reports on the analysis of 62 incidents of serial sexual assault. The statistical procedure of multidimensional scaling was employed in the analysis of this data, which in turn produced a five-cluster model of serial rapist behavior. First, a central cluster of behaviors were identified that represent common behaviors to all patterns of serial rape. Second, four distinct outlying patterns were identified as demonstrating distinct offence styles, these being assigned the following descriptive labels brutality, intercourse, chaotic, and ritual. Furthermore, analysis of these patterns also identified distinct offender characteristics that allow for the use of empirically robust offender profiles in future serial rape investigations.

Global Occurrence of Archaeal amoA Genes in Terrestrial Hot Springs▿

PubMed Central

Zhang, Chuanlun L.; Ye, Qi; Huang, Zhiyong; Li, WenJun; Chen, Jinquan; Song, Zhaoqi; Zhao, Weidong; Bagwell, Christopher; Inskeep, William P.; Ross, Christian; Gao, Lei; Wiegel, Juergen; Romanek, Christopher S.; Shock, Everett L.; Hedlund, Brian P.

2008-01-01

Despite the ubiquity of ammonium in geothermal environments and the thermodynamic favorability of aerobic ammonia oxidation, thermophilic ammonia-oxidizing microorganisms belonging to the crenarchaeota kingdom have only recently been described. In this study, we analyzed microbial mats and surface sediments from 21 hot spring samples (pH 3.4 to 9.0; temperature, 41 to 86°C) from the United States, China, and Russia and obtained 846 putative archaeal ammonia monooxygenase large-subunit (amoA) gene and transcript sequences, representing a total of 41 amoA operational taxonomic units (OTUs) at 2% identity. The amoA gene sequences were highly diverse, yet they clustered within two major clades of archaeal amoA sequences known from water columns, sediments, and soils: clusters A and B. Eighty-four percent (711/846) of the sequences belonged to cluster A, which is typically found in water columns and sediments, whereas 16% (135/846) belonged to cluster B, which is typically found in soils and sediments. Although a few amoA OTUs were present in several geothermal regions, most were specific to a single region. In addition, cluster A amoA genes formed geographic groups, while cluster B sequences did not group geographically. With the exception of only one hot spring, principal-component analysis and UPGMA (unweighted-pair group method using average linkages) based on the UniFrac metric derived from cluster A grouped the springs by location, regardless of temperature or bulk water pH, suggesting that geography may play a role in structuring communities of putative ammonia-oxidizing archaea (AOA). The amoA genes were distinct from those of low-temperature environments; in particular, pair-wise comparisons between hot spring amoA genes and those from sympatric soils showed less than 85% sequence identity, underscoring the distinctness of hot spring archaeal communities from those of the surrounding soil system. Reverse transcription-PCR showed that amoA genes were transcribed in situ in one spring and the transcripts were closely related to the amoA genes amplified from the same spring. Our study demonstrates the global occurrence of putative archaeal amoA genes in a wide variety of terrestrial hot springs and suggests that geography may play an important role in selecting different assemblages of AOA. PMID:18676703

Global occurrence of archaeal amoA genes in terrestrial hot springs.

PubMed

Zhang, Chuanlun L; Ye, Qi; Huang, Zhiyong; Li, Wenjun; Chen, Jinquan; Song, Zhaoqi; Zhao, Weidong; Bagwell, Christopher; Inskeep, William P; Ross, Christian; Gao, Lei; Wiegel, Juergen; Romanek, Christopher S; Shock, Everett L; Hedlund, Brian P

2008-10-01

Despite the ubiquity of ammonium in geothermal environments and the thermodynamic favorability of aerobic ammonia oxidation, thermophilic ammonia-oxidizing microorganisms belonging to the crenarchaeota kingdom have only recently been described. In this study, we analyzed microbial mats and surface sediments from 21 hot spring samples (pH 3.4 to 9.0; temperature, 41 to 86 degrees C) from the United States, China, and Russia and obtained 846 putative archaeal ammonia monooxygenase large-subunit (amoA) gene and transcript sequences, representing a total of 41 amoA operational taxonomic units (OTUs) at 2% identity. The amoA gene sequences were highly diverse, yet they clustered within two major clades of archaeal amoA sequences known from water columns, sediments, and soils: clusters A and B. Eighty-four percent (711/846) of the sequences belonged to cluster A, which is typically found in water columns and sediments, whereas 16% (135/846) belonged to cluster B, which is typically found in soils and sediments. Although a few amoA OTUs were present in several geothermal regions, most were specific to a single region. In addition, cluster A amoA genes formed geographic groups, while cluster B sequences did not group geographically. With the exception of only one hot spring, principal-component analysis and UPGMA (unweighted-pair group method using average linkages) based on the UniFrac metric derived from cluster A grouped the springs by location, regardless of temperature or bulk water pH, suggesting that geography may play a role in structuring communities of putative ammonia-oxidizing archaea (AOA). The amoA genes were distinct from those of low-temperature environments; in particular, pair-wise comparisons between hot spring amoA genes and those from sympatric soils showed less than 85% sequence identity, underscoring the distinctness of hot spring archaeal communities from those of the surrounding soil system. Reverse transcription-PCR showed that amoA genes were transcribed in situ in one spring and the transcripts were closely related to the amoA genes amplified from the same spring. Our study demonstrates the global occurrence of putative archaeal amoA genes in a wide variety of terrestrial hot springs and suggests that geography may play an important role in selecting different assemblages of AOA.

Model-based recursive partitioning to identify risk clusters for metabolic syndrome and its components: findings from the International Mobility in Aging Study

PubMed Central

Pirkle, Catherine M; Wu, Yan Yan; Zunzunegui, Maria-Victoria; Gómez, José Fernando

2018-01-01

Objective Conceptual models underpinning much epidemiological research on ageing acknowledge that environmental, social and biological systems interact to influence health outcomes. Recursive partitioning is a data-driven approach that allows for concurrent exploration of distinct mixtures, or clusters, of individuals that have a particular outcome. Our aim is to use recursive partitioning to examine risk clusters for metabolic syndrome (MetS) and its components, in order to identify vulnerable populations. Study design Cross-sectional analysis of baseline data from a prospective longitudinal cohort called the International Mobility in Aging Study (IMIAS). Setting IMIAS includes sites from three middle-income countries—Tirana (Albania), Natal (Brazil) and Manizales (Colombia)—and two from Canada—Kingston (Ontario) and Saint-Hyacinthe (Quebec). Participants Community-dwelling male and female adults, aged 64–75 years (n=2002). Primary and secondary outcome measures We apply recursive partitioning to investigate social and behavioural risk factors for MetS and its components. Model-based recursive partitioning (MOB) was used to cluster participants into age-adjusted risk groups based on variabilities in: study site, sex, education, living arrangements, childhood adversities, adult occupation, current employment status, income, perceived income sufficiency, smoking status and weekly minutes of physical activity. Results 43% of participants had MetS. Using MOB, the primary partitioning variable was participant sex. Among women from middle-incomes sites, the predicted proportion with MetS ranged from 58% to 68%. Canadian women with limited physical activity had elevated predicted proportions of MetS (49%, 95% CI 39% to 58%). Among men, MetS ranged from 26% to 41% depending on childhood social adversity and education. Clustering for MetS components differed from the syndrome and across components. Study site was a primary partitioning variable for all components except HDL cholesterol. Sex was important for most components. Conclusion MOB is a promising technique for identifying disease risk clusters (eg, vulnerable populations) in modestly sized samples. PMID:29500203

The emergence of the galactic stellar mass function from a non-universal IMF in clusters

NASA Astrophysics Data System (ADS)

Dib, Sami; Basu, Shantanu

2018-06-01

We investigate the dependence of a single-generation galactic mass function (SGMF) on variations in the initial stellar mass functions (IMF) of stellar clusters. We show that cluster-to-cluster variations of the IMF lead to a multi-component SGMF where each component in a given mass range can be described by a distinct power-law function. We also show that a dispersion of ≈0.3 M⊙ in the characteristic mass of the IMF, as observed for young Galactic clusters, leads to a low-mass slope of the SGMF that matches the observed Galactic stellar mass function even when the IMFs in the low-mass end of individual clusters are much steeper.

Identification of clinically relevant phenotypes in patients with Ebstein anomaly.

PubMed

Cabrera, Rodrigo; Miranda-Fernández, Marta Catalina; Huertas-Quiñones, Victor Manuel; Carreño, Marisol; Pineda, Ivonne; Restrepo, Carlos M; Silva, Claudia Tamar; Quero, Rossi; Cano, Juan David; Manrique, Diana Carolina; Camacho, Camila; Tabares, Sebastián; García, Alberto; Sandoval, Néstor; Moreno Medina, Karen Julieth; Dennis Verano, Rodolfo José

2018-03-01

Ebstein anomaly (EA) is a heterogeneous congenital heart defect (CHD), frequently accompanied by diverse cardiac and extracardiac comorbidities, resulting in a wide range of clinical outcomes. Phenotypic characterization of EA patients has the potential to identify variables that influence prognosis and subgroups with distinct contributing factors. A comprehensive cross-sectional phenotypic characterization of 147 EA patients from one of the main referral institutions for CHD in Colombia was carried out. The most prevalent comorbidities and distinct subgroups within the patient cohort were identified through cluster analysis. The most prevalent cardiac comorbidities identified were atrial septal defect (61%), Wolff-Parkinson-White syndrome (WPW; 27%), and right ventricular outflow tract obstruction (25%). Cluster analysis showed that patients can be classified into 2 distinct subgroups with defined phenotypes that determine disease severity and survival. Patients in cluster 1 represented a particularly homogeneous subgroup with a milder spectrum of disease, including only patients with WPW and/or supraventricular tachycardia (SVT). Cluster 2 included patients with more diverse cardiovascular comorbidities. This study represents one of the largest phenotypic characterizations of EA patients reported. The data show that EA is a heterogeneous disease, very frequently associated with cardiovascular and noncardiovascular comorbidities. Patients with WPW and SVT represent a homogeneous subgroup that presents with a less severe spectrum of disease and better survival when adequately managed. This should be considered when searching for genetic causes of EA and in the clinical setting. © 2018 Wiley Periodicals, Inc.

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-12-09

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

Data Analytics for Smart Parking Applications.

PubMed

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-09-23

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset.

Using sperm morphometry and multivariate analysis to differentiate species of gray Mazama

PubMed Central

Duarte, José Maurício Barbanti

2016-01-01

There is genetic evidence that the two species of Brazilian gray Mazama, Mazama gouazoubira and Mazama nemorivaga, belong to different genera. This study identified significant differences that separated them into distinct groups, based on characteristics of the spermatozoa and ejaculate of both species. The characteristics that most clearly differentiated between the species were ejaculate colour, white for M. gouazoubira and reddish for M. nemorivaga, and sperm head dimensions. Multivariate analysis of sperm head dimension and format data accurately discriminated three groups for species with total percentage of misclassified of 0.71. The individual analysis, by animal, and the multivariate analysis have also discriminated correctly all five animals (total percentage of misclassified of 13.95%), and the canonical plot has shown three different clusters: Cluster 1, including individuals of M. nemorivaga; Cluster 2, including two individuals of M. gouazoubira; and Cluster 3, including a single individual of M. gouazoubira. The results obtained in this work corroborate the hypothesis of the formation of new genera and species for gray Mazama. Moreover, the easily applied method described herein can be used as an auxiliary tool to identify sibling species of other taxonomic groups. PMID:28018612

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.

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

PubMed

Liao, Fuyuan; Jan, Yih-Kuen

2012-06-01

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

Data Analytics for Smart Parking Applications

PubMed Central

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-01-01

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset. PMID:27669259

Language networks associated with computerized semantic indices.

PubMed

Pakhomov, Serguei V S; Jones, David T; Knopman, David S

2015-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

Excess electrons in methanol clusters: Beyond the one-electron picture

NASA Astrophysics Data System (ADS)

Pohl, Gábor; Mones, Letif; Turi, László

2016-10-01

We performed a series of comparative quantum chemical calculations on various size negatively charged methanol clusters, ("separators=" CH 3 OH ) n - . The clusters are examined in their optimized geometries (n = 2-4), and in geometries taken from mixed quantum-classical molecular dynamics simulations at finite temperature (n = 2-128). These latter structures model potential electron binding sites in methanol clusters and in bulk methanol. In particular, we compute the vertical detachment energy (VDE) of an excess electron from increasing size methanol cluster anions using quantum chemical computations at various levels of theory including a one-electron pseudopotential model, several density functional theory (DFT) based methods, MP2 and coupled-cluster CCSD(T) calculations. The results suggest that at least four methanol molecules are needed to bind an excess electron on a hydrogen bonded methanol chain in a dipole bound state. Larger methanol clusters are able to form stronger interactions with an excess electron. The two simulated excess electron binding motifs in methanol clusters, interior and surface states, correlate well with distinct, experimentally found VDE tendencies with size. Interior states in a solvent cavity are stabilized significantly stronger than electron states on cluster surfaces. Although we find that all the examined quantum chemistry methods more or less overestimate the strength of the experimental excess electron stabilization, MP2, LC-BLYP, and BHandHLYP methods with diffuse basis sets provide a significantly better estimate of the VDE than traditional DFT methods (BLYP, B3LYP, X3LYP, PBE0). A comparison to the better performing many electron methods indicates that the examined one-electron pseudopotential can be reasonably used in simulations for systems of larger size.

Excess electrons in methanol clusters: Beyond the one-electron picture.

PubMed

Pohl, Gábor; Mones, Letif; Turi, László

2016-10-28

We performed a series of comparative quantum chemical calculations on various size negatively charged methanol clusters, CH 3 OH n - . The clusters are examined in their optimized geometries (n = 2-4), and in geometries taken from mixed quantum-classical molecular dynamics simulations at finite temperature (n = 2-128). These latter structures model potential electron binding sites in methanol clusters and in bulk methanol. In particular, we compute the vertical detachment energy (VDE) of an excess electron from increasing size methanol cluster anions using quantum chemical computations at various levels of theory including a one-electron pseudopotential model, several density functional theory (DFT) based methods, MP2 and coupled-cluster CCSD(T) calculations. The results suggest that at least four methanol molecules are needed to bind an excess electron on a hydrogen bonded methanol chain in a dipole bound state. Larger methanol clusters are able to form stronger interactions with an excess electron. The two simulated excess electron binding motifs in methanol clusters, interior and surface states, correlate well with distinct, experimentally found VDE tendencies with size. Interior states in a solvent cavity are stabilized significantly stronger than electron states on cluster surfaces. Although we find that all the examined quantum chemistry methods more or less overestimate the strength of the experimental excess electron stabilization, MP2, LC-BLYP, and BHandHLYP methods with diffuse basis sets provide a significantly better estimate of the VDE than traditional DFT methods (BLYP, B3LYP, X3LYP, PBE0). A comparison to the better performing many electron methods indicates that the examined one-electron pseudopotential can be reasonably used in simulations for systems of larger size.

Revealing common disease mechanisms shared by tumors of different tissues of origin through semantic representation of genomic alterations and topic modeling.

PubMed

Chen, Vicky; Paisley, John; Lu, Xinghua

2017-03-14

Cancer is a complex disease driven by somatic genomic alterations (SGAs) that perturb signaling pathways and consequently cellular function. Identifying patterns of pathway perturbations would provide insights into common disease mechanisms shared among tumors, which is important for guiding treatment and predicting outcome. However, identifying perturbed pathways is challenging, because different tumors can have the same perturbed pathways that are perturbed by different SGAs. Here, we designed novel semantic representations that capture the functional similarity of distinct SGAs perturbing a common pathway in different tumors. Combining this representation with topic modeling would allow us to identify patterns in altered signaling pathways. We represented each gene with a vector of words describing its function, and we represented the SGAs of a tumor as a text document by pooling the words representing individual SGAs. We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. We identified topics (consisting of co-occurring words) representing the common functional themes of different SGAs. Tumors were clustered based on their topic associations, such that each cluster consists of tumors sharing common functional themes. The resulting clusters contained mixtures of cancer types, which indicates that different cancer types can share disease mechanisms. Survival analysis based on the clusters revealed significant differences in survival among the tumors of the same cancer type that were assigned to different clusters. The results indicate that applying topic modeling to semantic representations of tumors identifies patterns in the combinations of altered functional pathways in cancer.

DNA Barcoding of Neotropical Sand Flies (Diptera, Psychodidae, Phlebotominae): Species Identification and Discovery within Brazil

PubMed Central

Pinto, Israel de Souza; Chagas, Bruna Dias das; Rodrigues, Andressa Alencastre Fuzari; Ferreira, Adelson Luiz; Rezende, Helder Ricas; Bruno, Rafaela Vieira; Falqueto, Aloisio; Andrade-Filho, José Dilermando; Galati, Eunice Aparecida Bianchi; Shimabukuro, Paloma Helena Fernandes; Brazil, Reginaldo Peçanha

2015-01-01

DNA barcoding has been an effective tool for species identification in several animal groups. Here, we used DNA barcoding to discriminate between 47 morphologically distinct species of Brazilian sand flies. DNA barcodes correctly identified approximately 90% of the sampled taxa (42 morphologically distinct species) using clustering based on neighbor-joining distance, of which four species showed comparatively higher maximum values of divergence (range 4.23–19.04%), indicating cryptic diversity. The DNA barcodes also corroborated the resurrection of two species within the shannoni complex and provided an efficient tool to differentiate between morphologically indistinguishable females of closely related species. Taken together, our results validate the effectiveness of DNA barcoding for species identification and the discovery of cryptic diversity in sand flies from Brazil. PMID:26506007

DNA Barcoding of Neotropical Sand Flies (Diptera, Psychodidae, Phlebotominae): Species Identification and Discovery within Brazil.

PubMed

Pinto, Israel de Souza; Chagas, Bruna Dias das; Rodrigues, Andressa Alencastre Fuzari; Ferreira, Adelson Luiz; Rezende, Helder Ricas; Bruno, Rafaela Vieira; Falqueto, Aloisio; Andrade-Filho, José Dilermando; Galati, Eunice Aparecida Bianchi; Shimabukuro, Paloma Helena Fernandes; Brazil, Reginaldo Peçanha; Peixoto, Alexandre Afranio

2015-01-01

DNA barcoding has been an effective tool for species identification in several animal groups. Here, we used DNA barcoding to discriminate between 47 morphologically distinct species of Brazilian sand flies. DNA barcodes correctly identified approximately 90% of the sampled taxa (42 morphologically distinct species) using clustering based on neighbor-joining distance, of which four species showed comparatively higher maximum values of divergence (range 4.23-19.04%), indicating cryptic diversity. The DNA barcodes also corroborated the resurrection of two species within the shannoni complex and provided an efficient tool to differentiate between morphologically indistinguishable females of closely related species. Taken together, our results validate the effectiveness of DNA barcoding for species identification and the discovery of cryptic diversity in sand flies from Brazil.

HSAN1 mutations in serine palmitoyltransferase reveal a close structure-function-phenotype relationship.

PubMed

Bode, Heiko; Bourquin, Florence; Suriyanarayanan, Saranya; Wei, Yu; Alecu, Irina; Othman, Alaa; Von Eckardstein, Arnold; Hornemann, Thorsten

2016-03-01

Hereditary sensory and autonomic neuropathy type 1 (HSAN1) is a rare autosomal dominant inherited peripheral neuropathy caused by mutations in the SPTLC1 and SPTLC2 subunits of serine palmitoyltransferase (SPT). The mutations induce a permanent shift in the substrate preference from L-serine to L-alanine, which results in the pathological formation of atypical and neurotoxic 1-deoxy-sphingolipids (1-deoxySL). Here we compared the enzymatic properties of 11 SPTLC1 and six SPTLC2 mutants using a uniform isotope labelling approach. In total, eight SPT mutants (STPLC1p.C133W, p.C133Y, p.S331F, p.S331Y and SPTLC2p.A182P, p.G382V, p.S384F, p.I504F) were associated with increased 1-deoxySL synthesis. Despite earlier reports, canonical activity with l-serine was not reduced in any of the investigated SPT mutants. Three variants (SPTLC1p.S331F/Y and SPTLC2p.I505Y) showed an increased canonical activity and increased formation of C20 sphingoid bases. These three mutations are associated with an exceptionally severe HSAN1 phenotype, and increased C20 sphingosine levels were also confirmed in plasma of patients. A principal component analysis of the analysed sphingoid bases clustered the mutations into three separate entities. Each cluster was related to a distinct clinical outcome (no, mild and severe HSAN1 phenotype). A homology model based on the protein structure of the prokaryotic SPT recapitulated the same grouping on a structural level. Mutations associated with the mild form clustered around the active site, whereas mutations associated with the severe form were located on the surface of the protein. In conclusion, we showed that HSAN1 mutations in SPT have distinct biochemical properties, which allowed for the prediction of the clinical symptoms on the basis of the plasma sphingoid base profile. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Characteristics of MHC class I genes in house sparrows Passer domesticus as revealed by long cDNA transcripts and amplicon sequencing.

PubMed

Karlsson, Maria; Westerdahl, Helena

2013-08-01

In birds the major histocompatibility complex (MHC) organization differs both among and within orders; chickens Gallus gallus of the order Galliformes have a simple arrangement, while many songbirds of the order Passeriformes have a more complex arrangement with larger numbers of MHC class I and II genes. Chicken MHC genes are found at two independent loci, classical MHC-B and non-classical MHC-Y, whereas non-classical MHC genes are yet to be verified in passerines. Here we characterize MHC class I transcripts (α1 to α3 domain) and perform amplicon sequencing using a next-generation sequencing technique on exon 3 from house sparrow Passer domesticus (a passerine) families. Then we use phylogenetic, selection, and segregation analyses to gain a better understanding of the MHC class I organization. Trees based on the α1 and α2 domain revealed a distinct cluster with short terminal branches for transcripts with a 6-bp deletion. Interestingly, this cluster was not seen in the tree based on the α3 domain. 21 exon 3 sequences were verified in a single individual and the average numbers within an individual were nine and five for sequences with and without a 6-bp deletion, respectively. All individuals had exon 3 sequences with and without a 6-bp deletion. The sequences with a 6-bp deletion have many characteristics in common with non-classical MHC, e.g., highly conserved amino acid positions were substituted compared with the other alleles, low nucleotide diversity and just a single site was subject to positive selection. However, these alleles also have characteristics that suggest they could be classical, e.g., complete linkage and absence of a distinct cluster in a tree based on the α3 domain. Thus, we cannot determine for certain whether or not the alleles with a 6-bp deletion are non-classical based on our present data. Further analyses on segregation patterns of these alleles in combination with dating the 6-bp deletion through MHC characterization across the genus Passer may solve this matter in the future.

Variation in tibial functionality and fracture susceptibility among healthy, young adults arises from the acquisition of biologically distinct sets of traits.

PubMed

Jepsen, Karl J; Evans, Rachel; Negus, Charles H; Gagnier, Joel J; Centi, Amanda; Erlich, Tomer; Hadid, Amir; Yanovich, Ran; Moran, Daniel S

2013-06-01

Physiological systems like bone respond to many genetic and environmental factors by adjusting traits in a highly coordinated, compensatory manner to establish organ-level function. To be mechanically functional, a bone should be sufficiently stiff and strong to support physiological loads. Factors impairing this process are expected to compromise strength and increase fracture risk. We tested the hypotheses that individuals with reduced stiffness relative to body size will show an increased risk of fracturing and that reduced strength arises from the acquisition of biologically distinct sets of traits (ie, different combinations of morphological and tissue-level mechanical properties). We assessed tibial functionality retrospectively for 336 young adult women and men engaged in military training, and calculated robustness (total area/bone length), cortical area (Ct.Ar), and tissue-mineral density (TMD). These three traits explained 69% to 72% of the variation in tibial stiffness (p < 0.0001). Having reduced stiffness relative to body size (body weight × bone length) was associated with odds ratios of 1.5 (95% confidence interval [CI], 0.5-4.3) and 7.0 (95% CI, 2.0-25.1) for women and men, respectively, for developing a stress fracture based on radiography and scintigraphy. K-means cluster analysis was used to segregate men and women into subgroups based on robustness, Ct.Ar, and TMD adjusted for body size. Stiffness varied 37% to 42% among the clusters (p < 0.0001, ANOVA). For men, 78% of stress fracture cases segregated to three clusters (p < 0.03, chi-square). Clusters showing reduced function exhibited either slender tibias with the expected Ct.Ar and TMD relative to body size and robustness (ie, well-adapted bones) or robust tibias with reduced residuals for Ct.Ar or TMD relative to body size and robustness (ie, poorly adapted bones). Thus, we show there are multiple biomechanical and thus biological pathways leading to reduced function and increased fracture risk. Our results have important implications for developing personalized preventative diagnostics and treatments. Copyright © 2013 American Society for Bone and Mineral Research.

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

PubMed

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

2018-01-06

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

Comprehensive Analysis of DNA Methylation in Head and Neck Squamous Cell Carcinoma Indicates Differences by Survival and Clinicopathologic Characteristics

PubMed Central

Colacino, Justin A.; Dolinoy, Dana C.; Duffy, Sonia A.; Sartor, Maureen A.; Chepeha, Douglas B.; Bradford, Carol R.; McHugh, Jonathan B.; Patel, Divya A.; Virani, Shama; Walline, Heather M.; Bellile, Emily; Terrell, Jeffrey E.; Stoerker, Jay A.; Taylor, Jeremy M. G.; Carey, Thomas E.; Wolf, Gregory T.; Rozek, Laura S.

2013-01-01

Head and neck squamous cell carcinoma (HNSCC) is the eighth most commonly diagnosed cancer in the United States. The risk of developing HNSCC increases with exposure to tobacco, alcohol and infection with human papilloma virus (HPV). HPV-associated HNSCCs have a distinct risk profile and improved prognosis compared to cancers associated with tobacco and alcohol exposure. Epigenetic changes are an important mechanism in carcinogenic progression, but how these changes differ between viral- and chemical-induced cancers remains unknown. CpG methylation at 1505 CpG sites across 807 genes in 68 well-annotated HNSCC tumor samples from the University of Michigan Head and Neck SPORE patient population were quantified using the Illumina Goldengate Methylation Cancer Panel. Unsupervised hierarchical clustering based on methylation identified 6 distinct tumor clusters, which significantly differed by age, HPV status, and three year survival. Weighted linear modeling was used to identify differentially methylated genes based on epidemiological characteristics. Consistent with previous in vitro findings by our group, methylation of sites in the CCNA1 promoter was found to be higher in HPV(+) tumors, which was validated in an additional sample set of 128 tumors. After adjusting for cancer site, stage, age, gender, alcohol consumption, and smoking status, HPV status was found to be a significant predictor for DNA methylation at an additional 11 genes, including CASP8 and SYBL1. These findings provide insight into the epigenetic regulation of viral vs. chemical carcinogenesis and could provide novel targets for development of individualized therapeutic and prevention regimens based on environmental exposures. PMID:23358896

Comprehensive analysis of DNA methylation in head and neck squamous cell carcinoma indicates differences by survival and clinicopathologic characteristics.

PubMed

Colacino, Justin A; Dolinoy, Dana C; Duffy, Sonia A; Sartor, Maureen A; Chepeha, Douglas B; Bradford, Carol R; McHugh, Jonathan B; Patel, Divya A; Virani, Shama; Walline, Heather M; Bellile, Emily; Terrell, Jeffrey E; Stoerker, Jay A; Taylor, Jeremy M G; Carey, Thomas E; Wolf, Gregory T; Rozek, Laura S

2013-01-01

Head and neck squamous cell carcinoma (HNSCC) is the eighth most commonly diagnosed cancer in the United States. The risk of developing HNSCC increases with exposure to tobacco, alcohol and infection with human papilloma virus (HPV). HPV-associated HNSCCs have a distinct risk profile and improved prognosis compared to cancers associated with tobacco and alcohol exposure. Epigenetic changes are an important mechanism in carcinogenic progression, but how these changes differ between viral- and chemical-induced cancers remains unknown. CpG methylation at 1505 CpG sites across 807 genes in 68 well-annotated HNSCC tumor samples from the University of Michigan Head and Neck SPORE patient population were quantified using the Illumina Goldengate Methylation Cancer Panel. Unsupervised hierarchical clustering based on methylation identified 6 distinct tumor clusters, which significantly differed by age, HPV status, and three year survival. Weighted linear modeling was used to identify differentially methylated genes based on epidemiological characteristics. Consistent with previous in vitro findings by our group, methylation of sites in the CCNA1 promoter was found to be higher in HPV(+) tumors, which was validated in an additional sample set of 128 tumors. After adjusting for cancer site, stage, age, gender, alcohol consumption, and smoking status, HPV status was found to be a significant predictor for DNA methylation at an additional 11 genes, including CASP8 and SYBL1. These findings provide insight into the epigenetic regulation of viral vs. chemical carcinogenesis and could provide novel targets for development of individualized therapeutic and prevention regimens based on environmental exposures.

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

PubMed

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

2016-05-01

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

The complex star cluster system of NGC 1316 (Fornax A)

NASA Astrophysics Data System (ADS)

Sesto, Leandro A.; Faifer, Favio R.; Forte, Juan C.

2016-10-01

This paper presents Gemini-gri' high-quality photometry for cluster candidates in the field of NGC 1316 (Fornax A) as part of a study that also includes GMOS spectroscopy. A preliminary discussion of the photometric data indicates the presence of four stellar cluster populations with distinctive features in terms of age, chemical abundance and spatial distribution. Two of them seem to be the usually old (metal poor and metal rich) populations typically found in elliptical galaxies. In turn, an intermediate-age (5 Gyr) globular cluster population is the dominant component of the sample (as reported by previous papers). We also find a younger cluster population with a tentative age of ≈ 1 Gyr.

Two distinct symptom-based phenotypes of depression in epilepsy yield specific clinical and etiological insights.

PubMed

Rayner, Genevieve; Jackson, Graeme D; Wilson, Sarah J

2016-11-01

Depression is common but underdiagnosed in epilepsy. A quarter of patients meet criteria for a depressive disorder, yet few receive active treatment. We hypothesize that the presentation of depression is less recognizable in epilepsy because the symptoms are heterogeneous and often incorrectly attributed to the secondary effects of seizures or medication. Extending the ILAE's new phenomenological approach to classification of the epilepsies to include psychiatric comorbidity, we use data-driven profiling of the symptoms of depression to perform a preliminary investigation of whether there is a distinctive symptom-based phenotype of depression in epilepsy that could facilitate its recognition in the neurology clinic. The psychiatric and neuropsychological functioning of 91 patients with focal epilepsy was compared with that of 77 healthy controls (N=168). Cluster analysis of current depressive symptoms identified three clusters: one comprising nondepressed patients and two symptom-based phenotypes of depression. The 'Cognitive' phenotype (base rate=17%) was characterized by symptoms taking the form of self-critical cognitions and dysphoria and was accompanied by pervasive memory deficits. The 'Somatic' phenotype (7%) was characterized by vegetative depressive symptoms and anhedonia and was accompanied by greater anxiety. It is hoped that identification of the features of these two phenotypes will ultimately facilitate improved detection and diagnosis of depression in patients with epilepsy and thereby lead to appropriate and timely treatment, to the benefit of patient wellbeing and the potential efficacy of treatment of the seizure disorder. This article is part of a Special Issue entitled "The new approach to classification: Rethinking cognition and behavior in epilepsy". Copyright © 2016 Elsevier Inc. All rights reserved.

Lineage diversification of fringe-toed lizards (Phrynosomatidae: Uma notata complex) in the Colorado Desert: Delimiting species in the presence of gene flow

USGS Publications Warehouse

Gottscho, Andrew D.; Wood, Dustin A.; Vandergast, Amy; Lemos Espinal, Julio A.; Gatesy, John; Reeder, Tod

2017-01-01

Multi-locus nuclear DNA data were used to delimit species of fringe-toed lizards of theUma notata complex, which are specialized for living in wind-blown sand habitats in the deserts of southwestern North America, and to infer whether Quaternary glacial cycles or Tertiary geological events were important in shaping the historical biogeography of this group. We analyzed ten nuclear loci collected using Sanger sequencing and genome-wide sequence and single-nucleotide polymorphism (SNP) data collected using restriction-associated DNA (RAD) sequencing. A combination of species discovery methods (concatenated phylogenies, parametric and non-parametric clustering algorithms) and species validation approaches (coalescent-based species tree/isolation-with-migration models) were used to delimit species, infer phylogenetic relationships, and to estimate effective population sizes, migration rates, and speciation times. Uma notata, U. inornata, U. cowlesi, and an undescribed species from Mohawk Dunes, Arizona (U. sp.) were supported as distinct in the concatenated analyses and by clustering algorithms, and all operational taxonomic units were decisively supported as distinct species by ranking hierarchical nested speciation models with Bayes factors based on coalescent-based species tree methods. However, significant unidirectional gene flow (2NM >1) from U. cowlesi and U. notata into U. rufopunctata was detected under the isolation-with-migration model. Therefore, we conservatively delimit four species-level lineages within this complex (U. inornata, U. notata, U. cowlesi, and U. sp.), treating U. rufopunctata as a hybrid population (U. notata x cowlesi). Both concatenated and coalescent-based estimates of speciation times support the hypotheses that speciation within the complex occurred during the late Pleistocene, and that the geological evolution of the Colorado River delta during this period was an important process shaping the observed phylogeographic patterns.

Comparison of Intra-cluster and M87 Halo Orphan Globular Clusters in the Virgo Cluster

NASA Astrophysics Data System (ADS)

Louie, Tiffany Kaye; Tuan, Jin Zong; Martellini, Adhara; Guhathakurta, Puragra; Toloba, Elisa; Peng, Eric; Longobardi, Alessia; Lim, Sungsoon

2018-01-01

We present a study of “orphan” globular clusters (GCs) — GCs with no identifiable nearby host galaxy — discovered in NGVS, a 104 deg2 CFHT/MegaCam imaging survey. At the distance of the Virgo cluster, GCs are bright enough to make good spectroscopic targets and many are barely resolved in good ground-based seeing. Our orphan GC sample is derived from a subset of NGVS-selected GC candidates that were followed up with Keck/DEIMOS spectroscopy. While our primary spectroscopic targets were candidate GC satellites of Virgo dwarf elliptical and ultra-diffuse galaxies, many objects turned out to be non-satellites based on a radial velocity mismatch with the Virgo galaxy they are projected close to. Using a combination of spectral characteristics (e.g., absorption vs. emission), Gaussian mixture modeling of radial velocity and positions, and extreme deconvolution analysis of ugrizk photometry and image morphology, these non-satellites were classified into: (1) intra-cluster GCs (ICGCs) in the Virgo cluster, (2) GCs in the outer halo of M87, (3) foreground Milky Way stars, and (4) background galaxies. The statistical distinction between ICGCs and M87 halo GCs is based on velocity distributions (mean of 1100 vs. 1300 km/s and dispersions of 700 vs. 400 km/s, respectively) and radial distribution (diffuse vs. centrally concentrated, respectively). We used coaddition to increase the spectral SNR for the two classes of orphan GCs and measured the equivalent widths (EWs) of the Mg b and H-beta absorption lines. These EWs were compared to single stellar population models to obtain mean age and metallicity estimates. The ICGCs and M87 halo GCs have <[Fe/H> = –0.6+/–0.3 and –0.4+/–0.3 dex, respectively, and mean ages of >~ 5 and >~ 10 Gyr, respectively. This suggests the M87 halo GCs formed in relatively high-mass galaxies that avoided being tidally disrupted by M87 until they were close to the cluster center, while IGCCs formed in relatively low-mass galaxies that were tidally disrupted in the cluster outskirts. Most of this work was carried out by high school students working under the auspices of the Science Internship Program (SIP) at UC Santa Cruz. We are grateful for financial support from the NSF and NASA/STScI.

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.

Profiles of More and Less Successful L2 Learners: A Cluster Analysis Study

ERIC Educational Resources Information Center

Sparks, Richard L.; Patton, Jon; Ganschow, Leonore

2012-01-01

This retrospective study examined L1 achievement, intelligence, L2 aptitude, and L2 proficiency profiles of 208 students completing two years of high school L2 courses. A cluster analysis was performed to determine whether distinct cognitive and achievement profiles of more and less successful L2 learners would emerge. The results of…

Identification of novel Theileria genotypes from Grant's gazelle

PubMed Central

Hooge, Janis; Howe, Laryssa; Ezenwa, Vanessa O.

2015-01-01

Blood samples collected from Grant's gazelles (Nanger granti) in Kenya were screened for hemoparasites using a combination of microscopic and molecular techniques. All 69 blood smears examined by microscopy were positive for hemoparasites. In addition, Theileria/Babesia DNA was detected in all 65 samples screened by PCR for a ~450-base pair fragment of the V4 hypervariable region of the 18S rRNA gene. Sequencing and BLAST analysis of a subset of PCR amplicons revealed widespread co-infection (25/39) and the existence of two distinct Grant's gazelle Theileria subgroups. One group of 11 isolates clustered as a subgroup with previously identified Theileria ovis isolates from small ruminants from Europe, Asia and Africa; another group of 3 isolates clustered with previously identified Theileria spp. isolates from other African antelope. Based on extensive levels of sequence divergence (1.2–2%) from previously reported Theileria species within Kenya and worldwide, the Theileria isolates detected in Grant's gazelles appear to represent at least two novel Theileria genotypes. PMID:25973394

Identification of novel Theileria genotypes from Grant's gazelle.

PubMed

Hooge, Janis; Howe, Laryssa; Ezenwa, Vanessa O

2015-08-01

Blood samples collected from Grant's gazelles (Nanger granti) in Kenya were screened for hemoparasites using a combination of microscopic and molecular techniques. All 69 blood smears examined by microscopy were positive for hemoparasites. In addition, Theileria/Babesia DNA was detected in all 65 samples screened by PCR for a ~450-base pair fragment of the V4 hypervariable region of the 18S rRNA gene. Sequencing and BLAST analysis of a subset of PCR amplicons revealed widespread co-infection (25/39) and the existence of two distinct Grant's gazelle Theileria subgroups. One group of 11 isolates clustered as a subgroup with previously identified Theileria ovis isolates from small ruminants from Europe, Asia and Africa; another group of 3 isolates clustered with previously identified Theileria spp. isolates from other African antelope. Based on extensive levels of sequence divergence (1.2-2%) from previously reported Theileria species within Kenya and worldwide, the Theileria isolates detected in Grant's gazelles appear to represent at least two novel Theileria genotypes.

Community detection for fluorescent lifetime microscopy image segmentation

NASA Astrophysics Data System (ADS)

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Achilefu, Samuel; Nussinov, Zohar

2014-03-01

Multiresolution community detection (CD) method has been suggested in a recent work as an efficient method for performing unsupervised segmentation of fluorescence lifetime (FLT) images of live cell images containing fluorescent molecular probes.1 In the current paper, we further explore this method in FLT images of ex vivo tissue slices. The image processing problem is framed as identifying clusters with respective average FLTs against a background or "solvent" in FLT imaging microscopy (FLIM) images derived using NIR fluorescent dyes. We have identified significant multiresolution structures using replica correlations in these images, where such correlations are manifested by information theoretic overlaps of the independent solutions ("replicas") attained using the multiresolution CD method from different starting points. In this paper, our method is found to be more efficient than a current state-of-the-art image segmentation method based on mixture of Gaussian distributions. It offers more than 1:25 times diversity based on Shannon index than the latter method, in selecting clusters with distinct average FLTs in NIR FLIM images.

Joint Spatial-Spectral Feature Space Clustering for Speech Activity Detection from ECoG Signals

PubMed Central

Kanas, Vasileios G.; Mporas, Iosif; Benz, Heather L.; Sgarbas, Kyriakos N.; Bezerianos, Anastasios; Crone, Nathan E.

2014-01-01

Brain machine interfaces for speech restoration have been extensively studied for more than two decades. The success of such a system will depend in part on selecting the best brain recording sites and signal features corresponding to speech production. The purpose of this study was to detect speech activity automatically from electrocorticographic signals based on joint spatial-frequency clustering of the ECoG feature space. For this study, the ECoG signals were recorded while a subject performed two different syllable repetition tasks. We found that the optimal frequency resolution to detect speech activity from ECoG signals was 8 Hz, achieving 98.8% accuracy by employing support vector machines (SVM) as a classifier. We also defined the cortical areas that held the most information about the discrimination of speech and non-speech time intervals. Additionally, the results shed light on the distinct cortical areas associated with the two syllable repetition tasks and may contribute to the development of portable ECoG-based communication. PMID:24658248

Quantification by qPCR of Pathobionts in Chronic Periodontitis: Development of Predictive Models of Disease Severity at Site-Specific Level.

PubMed

Tomás, Inmaculada; Regueira-Iglesias, Alba; López, Maria; Arias-Bujanda, Nora; Novoa, Lourdes; Balsa-Castro, Carlos; Tomás, Maria

2017-01-01

Currently, there is little evidence available on the development of predictive models for the diagnosis or prognosis of chronic periodontitis based on the qPCR quantification of subgingival pathobionts. Our objectives were to: (1) analyze and internally validate pathobiont-based models that could be used to distinguish different periodontal conditions at site-specific level within the same patient with chronic periodontitis; (2) develop nomograms derived from predictive models. Subgingival plaque samples were obtained from control and periodontal sites (probing pocket depth and clinical attachment loss <4 mm and >4 mm, respectively) from 40 patients with moderate-severe generalized chronic periodontitis. The samples were analyzed by qPCR using TaqMan probes and specific primers to determine the concentrations of Actinobacillus actinomycetemcomitans (Aa) , Fusobacterium nucleatum (Fn) , Parvimonas micra (Pm) , Porphyromonas gingivalis (Pg) , Prevotella intermedia (Pi) , Tannerella forsythia (Tf) , and Treponema denticola (Td) . The pathobiont-based models were obtained using multivariate binary logistic regression. The best models were selected according to specified criteria. The discrimination was assessed using receiver operating characteristic curves and numerous classification measures were thus obtained. The nomograms were built based on the best predictive models. Eight bacterial cluster-based models showed an area under the curve (AUC) ≥0.760 and a sensitivity and specificity ≥75.0%. The PiTfFn cluster showed an AUC of 0.773 (sensitivity and specificity = 75.0%). When Pm and AaPm were incorporated in the TdPiTfFn cluster, we detected the two best predictive models with an AUC of 0.788 and 0.789, respectively (sensitivity and specificity = 77.5%). The TdPiTfAa cluster had an AUC of 0.785 (sensitivity and specificity = 75.0%). When Pm was incorporated in this cluster, a new predictive model appeared with better AUC and specificity values (0.787 and 80.0%, respectively). Distinct clusters formed by species with different etiopathogenic role (belonging to different Socransky's complexes) had a good predictive accuracy for distinguishing a site with periodontal destruction in a periodontal patient. The predictive clusters with the lowest number of bacteria were PiTfFn and TdPiTfAa , while TdPiTfAaFnPm had the highest number. In all the developed nomograms, high concentrations of these clusters were associated with an increased probability of having a periodontal site in a patient with chronic periodontitis.

Quantification by qPCR of Pathobionts in Chronic Periodontitis: Development of Predictive Models of Disease Severity at Site-Specific Level

PubMed Central

Tomás, Inmaculada; Regueira-Iglesias, Alba; López, Maria; Arias-Bujanda, Nora; Novoa, Lourdes; Balsa-Castro, Carlos; Tomás, Maria

2017-01-01

Currently, there is little evidence available on the development of predictive models for the diagnosis or prognosis of chronic periodontitis based on the qPCR quantification of subgingival pathobionts. Our objectives were to: (1) analyze and internally validate pathobiont-based models that could be used to distinguish different periodontal conditions at site-specific level within the same patient with chronic periodontitis; (2) develop nomograms derived from predictive models. Subgingival plaque samples were obtained from control and periodontal sites (probing pocket depth and clinical attachment loss <4 mm and >4 mm, respectively) from 40 patients with moderate-severe generalized chronic periodontitis. The samples were analyzed by qPCR using TaqMan probes and specific primers to determine the concentrations of Actinobacillus actinomycetemcomitans (Aa), Fusobacterium nucleatum (Fn), Parvimonas micra (Pm), Porphyromonas gingivalis (Pg), Prevotella intermedia (Pi), Tannerella forsythia (Tf), and Treponema denticola (Td). The pathobiont-based models were obtained using multivariate binary logistic regression. The best models were selected according to specified criteria. The discrimination was assessed using receiver operating characteristic curves and numerous classification measures were thus obtained. The nomograms were built based on the best predictive models. Eight bacterial cluster-based models showed an area under the curve (AUC) ≥0.760 and a sensitivity and specificity ≥75.0%. The PiTfFn cluster showed an AUC of 0.773 (sensitivity and specificity = 75.0%). When Pm and AaPm were incorporated in the TdPiTfFn cluster, we detected the two best predictive models with an AUC of 0.788 and 0.789, respectively (sensitivity and specificity = 77.5%). The TdPiTfAa cluster had an AUC of 0.785 (sensitivity and specificity = 75.0%). When Pm was incorporated in this cluster, a new predictive model appeared with better AUC and specificity values (0.787 and 80.0%, respectively). Distinct clusters formed by species with different etiopathogenic role (belonging to different Socransky’s complexes) had a good predictive accuracy for distinguishing a site with periodontal destruction in a periodontal patient. The predictive clusters with the lowest number of bacteria were PiTfFn and TdPiTfAa, while TdPiTfAaFnPm had the highest number. In all the developed nomograms, high concentrations of these clusters were associated with an increased probability of having a periodontal site in a patient with chronic periodontitis. PMID:28848499

Behçet's: A Disease or a Syndrome? Answer from an Expression Profiling Study

PubMed Central

Oğuz, Ali Kemal; Yılmaz, Seda Taşır; Oygür, Çağdaş Şahap; Çandar, Tuba; Sayın, Irmak; Kılıçoğlu, Sibel Serin; Ergün, İhsan; Ateş, Aşkın; Özdağ, Hilal; Akar, Nejat

2016-01-01

Behçet’s disease (BD) is a chronic, relapsing, multisystemic inflammatory disorder with unanswered questions regarding its etiology/pathogenesis and classification. Distinct manifestation based subsets, pronounced geographical variations in expression, and discrepant immunological abnormalities raised the question whether Behçet’s is “a disease or a syndrome”. To answer the preceding question we aimed to display and compare the molecular mechanisms underlying distinct subsets of BD. For this purpose, the expression data of the gene expression profiling and association study on BD by Xavier et al (2013) was retrieved from GEO database and reanalysed by gene expression data analysis/visualization and bioinformatics enrichment tools. There were 15 BD patients (B) and 14 controls (C). Three subsets of BD patients were generated: MB (isolated mucocutaneous manifestations, n = 7), OB (ocular involvement, n = 4), and VB (large vein thrombosis, n = 4). Class comparison analyses yielded the following numbers of differentially expressed genes (DEGs); B vs C: 4, MB vs C: 5, OB vs C: 151, VB vs C: 274, MB vs OB: 215, MB vs VB: 760, OB vs VB: 984. Venn diagram analysis showed that there were no common DEGs in the intersection “MB vs C” ∩ “OB vs C” ∩ “VB vs C”. Cluster analyses successfully clustered distinct expressions of BD. During gene ontology term enrichment analyses, categories with relevance to IL-8 production (MB vs C) and immune response to microorganisms (OB vs C) were differentially enriched. Distinct subsets of BD display distinct expression profiles and different disease associated pathways. Based on these clear discrepancies, the designation as “Behçet’s syndrome” (BS) should be encouraged and future research should take into consideration the immunogenetic heterogeneity of BS subsets. Four gene groups, namely, negative regulators of inflammation (CD69, CLEC12A, CLEC12B, TNFAIP3), neutrophil granule proteins (LTF, OLFM4, AZU1, MMP8, DEFA4, CAMP), antigen processing and presentation proteins (CTSS, ERAP1), and regulators of immune response (LGALS2, BCL10, ITCH, CEACAM8, CD36, IL8, CCL4, EREG, NFKBIZ, CCR2, CD180, KLRC4, NFAT5) appear to be instrumental in BS immunopathogenesis. PMID:26890122

Grape cluster microclimate influences the aroma composition of Sauvignon blanc wine.

PubMed

Martin, Damian; Grose, Claire; Fedrizzi, Bruno; Stuart, Lily; Albright, Abby; McLachlan, Andrew

2016-11-01

New Zealand Sauvignon blanc (SB) wines are characterised by a distinctive combination of tropical-fruity and green-herbaceous aromatic compounds. The influence of sunlight exposure of grape clusters on juice and wine composition was investigated, with the aim of manipulating aromatic compounds in SB wine. In the absence of basal leaf removal SB clusters naturally exposed to sunlight were riper than shaded clusters, evidenced by higher total soluble solids (TSS) and proline, and lower malic acid, 3-isobutyl-2-methoxypyrazine (IBMP) and arginine. Volatile thiols in wines did not differ between shaded and exposed clusters. At equivalent TSS, cluster exposure had little or no effect on malic acid concentration. Conversely, wine from shaded clusters had almost double the IBMP concentration of wine from exposed clusters at equivalent TSS. The effects on SB juice and wine composition of natural variations in cluster microclimate are not comparable with the effects of cluster exposure created through leaf removal. Copyright © 2016 Elsevier Ltd. All rights reserved.

Theory of mind predicts severity level in autism.

PubMed

Hoogenhout, Michelle; Malcolm-Smith, Susan

2017-02-01

We investigated whether theory of mind skills can indicate autism spectrum disorder severity. In all, 62 children with autism spectrum disorder completed a developmentally sensitive theory of mind battery. We used intelligence quotient, Diagnostic and Statistical Manual of Mental Disorders (4th ed.) diagnosis and level of support needed as indicators of severity level. Using hierarchical cluster analysis, we found three distinct clusters of theory of mind ability: early-developing theory of mind (Cluster 1), false-belief reasoning (Cluster 2) and sophisticated theory of mind understanding (Cluster 3). The clusters corresponded to severe, moderate and mild autism spectrum disorder. As an indicator of level of support needed, cluster grouping predicted the type of school children attended. All Cluster 1 children attended autism-specific schools; Cluster 2 was divided between autism-specific and special needs schools and nearly all Cluster 3 children attended general special needs and mainstream schools. Assessing theory of mind skills can reliably discriminate severity levels within autism spectrum disorder.

Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

PubMed

Srivastava, Mousami; Khurana, Pankaj; Sugadev, Ragumani

2012-11-02

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

Genetic diversity and population structure analysis to construct a core collection from a large Capsicum germplasm.

PubMed

Lee, Hea-Young; Ro, Na-Young; Jeong, Hee-Jin; Kwon, Jin-Kyung; Jo, Jinkwan; Ha, Yeaseong; Jung, Ayoung; Han, Ji-Woong; Venkatesh, Jelli; Kang, Byoung-Cheorl

2016-11-14

Conservation of genetic diversity is an essential prerequisite for developing new cultivars with desirable agronomic traits. Although a large number of germplasm collections have been established worldwide, many of them face major difficulties due to large size and a lack of adequate information about population structure and genetic diversity. Core collection with a minimum number of accessions and maximum genetic diversity of pepper species and its wild relatives will facilitate easy access to genetic material as well as the use of hidden genetic diversity in Capsicum. To explore genetic diversity and population structure, we investigated patterns of molecular diversity using a transcriptome-based 48 single nucleotide polymorphisms (SNPs) in a large germplasm collection comprising 3,821 accessions. Among the 11 species examined, Capsicum annuum showed the highest genetic diversity (H E  = 0.44, I = 0.69), whereas the wild species C. galapagoense showed the lowest genetic diversity (H E  = 0.06, I = 0.07). The Capsicum germplasm collection was divided into 10 clusters (cluster 1 to 10) based on population structure analysis, and five groups (group A to E) based on phylogenetic analysis. Capsicum accessions from the five distinct groups in an unrooted phylogenetic tree showed taxonomic distinctness and reflected their geographic origins. Most of the accessions from European countries are distributed in the A and B groups, whereas the accessions from Asian countries are mainly distributed in C and D groups. Five different sampling strategies with diverse genetic clustering methods were used to select the optimal method for constructing the core collection. Using a number of allelic variations based on 48 SNP markers and 32 different phenotypic/morphological traits, a core collection 'CC240' with a total of 240 accessions (5.2 %) was selected from within the entire Capsicum germplasm. Compared to the other core collections, CC240 displayed higher genetic diversity (I = 0.95) and genetic evenness (J' = 0.80), and represented a wider range of phenotypic variation (MD = 9.45 %, CR = 98.40 %). A total of 240 accessions were selected from 3,821 Capsicum accessions based on transcriptome-based 48 SNP markers with genome-wide distribution and 32 traits using a systematic approach. This core collection will be a primary resource for pepper breeders and researchers for further genetic association and functional analyses.

Consumer clusters in Denmark based on coarse vegetable intake frequency, explained by hedonics, socio-demographic, health and food lifestyle factors. A cross-sectional national survey.

PubMed

Beck, Tove K; Jensen, Sidsel; Simmelsgaard, Sonni Hansen; Kjeldsen, Chris; Kidmose, Ulla

2015-08-01

Vegetable intake seems to play a protective role against major lifestyle diseases. Despite this, the Danish population usually eats far less than the recommended daily intake. The present study focused on the intake of 17 coarse vegetables and the potential barriers limiting their intake. The present study drew upon a large Danish survey (n = 1079) to study the intake of coarse vegetables among Danish consumers. Four population clusters were identified based on their intake of 17 different coarse vegetables, and profiled according to hedonics, socio-demographic, health, and food lifestyle factors. The four clusters were characterized by a very low intake frequency of coarse vegetables ('low frequency'), a low intake frequency of coarse vegetables; but high intake frequency of carrots ('carrot eaters'), a moderate coarse vegetable intake frequency and high intake frequency of beetroot ('beetroot eaters'), and a high intake frequency of all coarse vegetables ('high frequency'). There was a relationship between reported liking and reported intake frequency for all tested vegetables. Preference for foods with a sweet, salty or bitter taste, in general, was also identified to be decisive for the reported vegetable intake, as these differed across the clusters. Each cluster had distinct socio-demographic, health and food lifestyle profiles. 'Low frequency' was characterized by uninvolved consumers with lack of interest in food, 'carrot eaters' vegetable intake was driven by health aspects, 'beetroot eaters' were characterized as traditional food consumers, and 'high frequency' were individuals with a strong food engagement and high vegetable liking. 'Low frequency' identified more barriers than other consumer clusters and specifically regarded low availability of pre-cut/prepared coarse vegetables on the market as a barrier. Across all clusters a low culinary knowledge was identified as the main barrier. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of the DiversiLab Repetitive Element PCR System with spa Typing and Pulsed-Field Gel Electrophoresis for Clonal Characterization of Methicillin-Resistant Staphylococcus aureus▿

PubMed Central

Babouee, B.; Frei, R.; Schultheiss, E.; Widmer, A. F.; Goldenberger, D.

2011-01-01

The emergence of methicillin-resistant Staphylococcus aureus (MRSA) has become an increasing problem worldwide in recent decades. Molecular typing methods have been developed to identify clonality of strains and monitor spread of MRSA. We compared a new commercially available DiversiLab (DL) repetitive element PCR system with spa typing, spa clonal cluster analysis, and pulsed-field gel electrophoresis (PFGE) in terms of discriminatory power and concordance. A collection of 106 well-defined MRSA strains from our hospital was analyzed, isolated between 1994 and 2006. In addition, we analyzed 6 USA300 strains collected in our institution. DL typing separated the 106 MRSA isolates in 10 distinct clusters and 8 singleton patterns. Clustering analysis into spa clonal complexes resulted in 3 clusters: spa-CC 067/548, spa-CC 008, and spa-CC 012. The discriminatory powers (Simpson's index of diversity) were 0.982, 0.950, 0.846, and 0.757 for PFGE, spa typing, DL typing, and spa clonal clustering, respectively. DL typing and spa clonal clustering showed the highest concordance, calculated by adjusted Rand's coefficients. The 6 USA300 isolates grouped homogeneously into distinct PFGE and DL clusters, and all belonged to spa type t008 and spa-CC 008. Among the three methods, DL proved to be rapid and easy to perform. DL typing qualifies for initial screening during outbreak investigation. However, compared to PFGE and spa typing, DL typing has limited discriminatory power and therefore should be complemented by more discriminative methods in isolates that share identical DL patterns. PMID:21307215

Understanding students' motivation in project work: a 2 x 2 achievement goal approach.

PubMed

Liu, Woon Chia; Wang, C K John; Tan, Oon Seng; Ee, Jessie; Koh, Caroline

2009-03-01

The project work (PW) initiative was launched in 2000 by the Ministry of Education, Singapore, to encourage application of knowledge across disciplines, and to develop thinking, communication, collaboration, and metacognitive skills. Although PW has been introduced for a few years, few studies have examined the motivation of students in PW, especially with the use of the recently proposed 2 x 2 achievement goal framework. To use a cluster analytic approach to identify students' achievement goal profiles at an intra-individual level, and to examine their links to various psychological characteristics and perceived outcomes in PW. Participants were 491 Secondary 2 students (mean age = 13.78, SD = 0.77) from two government coeducational schools. Cluster analysis was performed to identify distinct subgroups of students with similar achievement goal profiles. One-way MANOVAs, followed by post hoc Tukey HSD tests for pairwise comparisons were used to determine whether there was any significant difference amongst clusters in terms of the psychological characteristics and perceived outcomes in PW. Four distinct clusters of students were identified. The cluster with high achievement goals and the cluster with moderately high goals had the most positive psychological characteristics and perceived outcomes. In contrast, the cluster with very low scores for all four achievement goals had the most maladaptive profile. The study provides support for the 2 x 2 achievement goal framework, and demonstrates that multiple goals can operate simultaneously. However, it highlights the need for cross-cultural studies to look into the approach-avoidance dimension in the 2 x 2 achievement goal framework.

New clinical grading scales and objective measurement for conjunctival injection.

PubMed

Park, In Ki; Chun, Yeoun Sook; Kim, Kwang Gi; Yang, Hee Kyung; Hwang, Jeong-Min

2013-08-05

To establish a new clinical grading scale and objective measurement method to evaluate conjunctival injection. Photographs of conjunctival injection with variable ocular diseases in 429 eyes were reviewed. Seventy-three images with concordance by three ophthalmologists were classified into a 4-step and 10-step subjective grading scale, and used as standard photographs. Each image was quantified in four ways: the relative magnitude of the redness component of each red-green-blue (RGB) pixel; two different algorithms based on the occupied area by blood vessels (K-means clustering with LAB color model and contrast-limited adaptive histogram equalization [CLAHE] algorithm); and the presence of blood vessel edges, based on the Canny edge-detection algorithm. Area under the receiver operating characteristic curves (AUCs) were calculated to summarize diagnostic accuracies of the four algorithms. The RGB color model, K-means clustering with LAB color model, and CLAHE algorithm showed good correlation with the clinical 10-step grading scale (R = 0.741, 0.784, 0.919, respectively) and with the clinical 4-step grading scale (R = 0.645, 0.702, 0.838, respectively). The CLAHE method showed the largest AUC, best distinction power (P < 0.001, ANOVA, Bonferroni multiple comparison test), and high reproducibility (R = 0.996). CLAHE algorithm showed the best correlation with the 10-step and 4-step subjective clinical grading scales together with high distinction power and reproducibility. CLAHE algorithm can be a useful for method for assessment of conjunctival injection.

A Wide Variety of Clostridium perfringens Type A Food-Borne Isolates That Carry a Chromosomal cpe Gene Belong to One Multilocus Sequence Typing Cluster

PubMed Central

Xiao, Yinghua; Wagendorp, Arjen; Moezelaar, Roy; Abee, Tjakko

2012-01-01

Of 98 suspected food-borne Clostridium perfringens isolates obtained from a nationwide survey by the Food and Consumer Product Safety Authority in The Netherlands, 59 strains were identified as C. perfringens type A. Using PCR-based techniques, the cpe gene encoding enterotoxin was detected in eight isolates, showing a chromosomal location for seven isolates and a plasmid location for one isolate. Further characterization of these strains by using (GTG)5 fingerprint repetitive sequence-based PCR analysis distinguished C. perfringens from other sulfite-reducing clostridia but did not allow for differentiation between various types of C. perfringens strains. To characterize the C. perfringens strains further, multilocus sequence typing (MLST) analysis was performed on eight housekeeping genes of both enterotoxic and non-cpe isolates, and the data were combined with a previous global survey covering strains associated with food poisoning, gas gangrene, and isolates from food or healthy individuals. This revealed that the chromosomal cpe strains (food strains and isolates from food poisoning cases) belong to a distinct cluster that is significantly distant from all the other cpe plasmid-carrying and cpe-negative strains. These results suggest that different groups of C. perfringens have undergone niche specialization and that a distinct group of food isolates has specific core genome sequences. Such findings have epidemiological and evolutionary significance. Better understanding of the origin and reservoir of enterotoxic C. perfringens may allow for improved control of this organism in foods. PMID:22865060

Hierarchical functional modularity in the resting-state human brain.

PubMed

Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

2009-07-01

Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

Nonredundant sparse feature extraction using autoencoders with receptive fields clustering.

PubMed

Ayinde, Babajide O; Zurada, Jacek M

2017-09-01

This paper proposes new techniques for data representation in the context of deep learning using agglomerative clustering. Existing autoencoder-based data representation techniques tend to produce a number of encoding and decoding receptive fields of layered autoencoders that are duplicative, thereby leading to extraction of similar features, thus resulting in filtering redundancy. We propose a way to address this problem and show that such redundancy can be eliminated. This yields smaller networks and produces unique receptive fields that extract distinct features. It is also shown that autoencoders with nonnegativity constraints on weights are capable of extracting fewer redundant features than conventional sparse autoencoders. The concept is illustrated using conventional sparse autoencoder and nonnegativity-constrained autoencoders with MNIST digits recognition, NORB normalized-uniform object data and Yale face dataset. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction (early recognition) of emerging flu strain clusters

NASA Astrophysics Data System (ADS)

Li, X.; Phillips, J. C.

2017-08-01

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

Multivalent Cation-Bridged PI(4,5)P2 Clusters Form at Very Low Concentrations.

PubMed

Wen, Yi; Vogt, Volker M; Feigenson, Gerald W

2018-06-05

Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P 2 or PIP2), is a key component of the inner leaflet of the plasma membrane in eukaryotic cells. In model membranes, PIP2 has been reported to form clusters, but whether these locally different conditions could give rise to distinct pools of unclustered and clustered PIP2 is unclear. By use of both fluorescence self-quenching and Förster resonance energy transfer assays, we have discovered that PIP2 self-associates at remarkably low concentrations starting below 0.05 mol% of total lipids. Formation of these clusters was dependent on physiological divalent metal ions, such as Ca 2+ , Mg 2+ , Zn 2+ , or trivalent ions Fe 3+ and Al 3+ . Formation of PIP2 clusters was also headgroup-specific, being largely independent of the type of acyl chain. The similarly labeled phospholipids phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, and phosphatidylinositol exhibited no such clustering. However, six phosphoinositide species coclustered with PIP2. The degree of PIP2 cation clustering was significantly influenced by the composition of the surrounding lipids, with cholesterol and phosphatidylinositol enhancing this behavior. We propose that PIP2 cation-bridged cluster formation, which might be similar to micelle formation, can be used as a physical model for what could be distinct pools of PIP2 in biological membranes. To our knowledge, this study provides the first evidence of PIP2 forming clusters at such low concentrations. The property of PIP2 to form such clusters at such extremely low concentrations in model membranes reveals, to our knowledge, a new behavior of PIP2 proposed to occur in cells, in which local multivalent metal ions, lipid compositions, and various binding proteins could greatly influence PIP2 properties. In turn, these different pools of PIP2 could further regulate cellular events. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Stratification of co-evolving genomic groups using ranked phylogenetic profiles

PubMed Central

Freilich, Shiri; Goldovsky, Leon; Gottlieb, Assaf; Blanc, Eric; Tsoka, Sophia; Ouzounis, Christos A

2009-01-01

Background Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present rank-BLAST, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database. Results The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples. Conclusion Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples. PMID:19860884

Genomic analysis of coxsackieviruses A1, A19, A22, enteroviruses 113 and 104: viruses representing two clades with distinct tropism within enterovirus C

PubMed Central

Haq, Saddef; Sameroff, Stephen; Howie, Stephen R. C.; Lipkin, W. Ian

2013-01-01

Coxsackieviruses (CV) A1, CV-A19 and CV-A22 have historically comprised a distinct phylogenetic clade within Enterovirus (EV) C. Several novel serotypes that are genetically similar to these three viruses have been recently discovered and characterized. Here, we report the coding sequence analysis of two genotypes of a previously uncharacterized serotype EV-C113 from Bangladesh and demonstrate that it is most similar to CV-A22 and EV-C116 within the capsid region. We sequenced novel genotypes of CV-A1, CV-A19 and CV-A22 from Bangladesh and observed a high rate of recombination within this group. We also report genomic analysis of the rarely reported EV-C104 circulating in the Gambia in 2009. All available EV-C104 sequences displayed a high degree of similarity within the structural genes but formed two clusters within the non-structural genes. One cluster included the recently reported EV-C117, suggesting an ancestral recombination between these two serotypes. Phylogenetic analysis of all available complete genome sequences indicated the existence of two subgroups within this distinct Enterovirus C clade: one has been exclusively recovered from gastrointestinal samples, while the other cluster has been implicated in respiratory disease. PMID:23761409

Identifying patterns of general practitioner service utilisation and their relationship with potentially preventable hospitalisations in people with diabetes: The utility of a cluster analysis approach.

PubMed

Ha, Ninh Thi; Harris, Mark; Preen, David; Robinson, Suzanne; Moorin, Rachael

2018-04-01

We aimed to characterise use of general practitioners (GP) simultaneously across multiple attributes in people with diabetes and examine its impact on diabetes related potentially preventable hospitalisations (PPHs). Five-years of panel data from 40,625 adults with diabetes were sourced from Western Australian administrative health records. Cluster analysis (CA) was used to group individuals with similar patterns of GP utilisation characterised by frequency and recency of services. The relationship between GP utilisation cluster and the risk of PPHs was examined using multivariable random-effects negative binomial regression. CA categorised GP utilisation into three clusters: moderate; high and very high usage, having distinct patient characteristics. After adjusting for potential confounders, the rate of PPHs was significantly lower across all GP usage clusters compared with those with no GP usage; IRR = 0.67 (95%CI: 0.62-0.71) among the moderate, IRR = 0.70 (95%CI 0.66-0.73) high and IRR = 0.76 (95%CI 0.72-0.80) very high GP usage clusters. Combination of temporal factors with measures of frequency of use of GP services revealed patterns of primary health care utilisation associated with different underlying patient characteristics. Incorporation of multiple attributes, that go beyond frequency-based approaches may better characterise the complex relationship between use of GP services and diabetes-related hospitalisation. Copyright © 2018 Elsevier B.V. All rights reserved.

Fluid intake patterns of children and adolescents: results of six Liq.In7 national cross-sectional surveys.

PubMed

Morin, C; Gandy, J; Brazeilles, R; Moreno, L A; Kavouras, S A; Martinez, H; Salas-Salvadó, J; Bottin, J; Guelinckx, Isabelle

2018-06-01

This study aimed to identify and characterize patterns of fluid intake in children and adolescents from six countries: Argentina, Brazil, China, Indonesia, Mexico and Uruguay. Data on fluid intake volume and type amongst children (4-9 years; N = 1400) and adolescents (10-17 years; N = 1781) were collected using the validated 7-day fluid-specific record (Liq.In 7 record). To identify relatively distinct clusters of subjects based on eight fluid types (water, milk and its derivatives, hot beverages, sugar-sweetened beverages (SSB), 100% fruit juices, artificial/non-nutritive sweetened beverages, alcoholic beverages, other beverages), a cluster analysis (partitioning around k-medoids algorithm) was used. Clusters were then characterized according to their socio-demographics and lifestyle indicators. The six interpretable clusters identified were: low drinkers-SSB (n 523), low drinkers-water and milk (n 615), medium mixed drinkers (n 914), high drinkers-SSB (n 513), high drinkers-water (n 352) and very high drinkers-water (n 264). Country of residence was the dominant characteristic, followed by socioeconomic level, in all six patterns. This analysis showed that consumption of water and SSB were the primary drivers of the clusters. In addition to country, socio-demographic and lifestyle factors played a role in determining the characteristics of each cluster. This information highlights the need to target interventions in particular populations aimed at changing fluid intake behavior and improving health in children and adolescents.

Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins.

PubMed

Kenn, Michael; Ribarics, Reiner; Ilieva, Nevena; Cibena, Michael; Karch, Rudolf; Schreiner, Wolfgang

2016-04-26

The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.

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

PubMed

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

2016-12-01

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

Off-road truck-related accidents in U.S. mines

PubMed Central

Dindarloo, Saeid R.; Pollard, Jonisha P.; Siami-Irdemoosa, Elnaz

2016-01-01

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. PMID:27620937

Off-road truck-related accidents in U.S. mines.

PubMed

Dindarloo, Saeid R; Pollard, Jonisha P; Siami-Irdemoosa, Elnaz

2016-09-01

Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Rigid-Cluster Models of Conformational Transitions in Macromolecular Machines and Assemblies

PubMed Central

Kim, Moon K.; Jernigan, Robert L.; Chirikjian, Gregory S.

2005-01-01

We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarse-grained elastic network interpolation (ENI) in which, for example, only Cα atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a Cα coarse-grained model is >(300,000)2. However, it reduces to (84)2 when we apply the rigid-cluster model with icosahedral symmetry constraints. The computational cost of the interpolation no longer scales heavily with the size of structures; instead, it depends strongly on the minimal number of rigid clusters into which the system can be decomposed. PMID:15833998

Maternal Smoking during Pregnancy and Offspring Overt and Covert Conduct Problems: A Longitudinal Study

ERIC Educational Resources Information Center

Monuteaux, Michael C.; Blacker, Deborah; Biederman, Joseph; Fitzmaurice, Garrett; Buka, Stephen L.

2006-01-01

Background: Empirical evidence demonstrates that conduct disorder (CD) symptoms tend to cluster into covert and overt domains. We hypothesized that overt and covert CD symptoms may be distinct constructs with distinct risk factors. An important risk factor for CD is maternal smoking during pregnancy. We further investigated this association,…

The Evolution of Globular Cluster Systems In Early-Type Galaxies

NASA Astrophysics Data System (ADS)

Grillmair, Carl

1999-07-01

We will measure structural parameters {core radii and concentrations} of globular clusters in three early-type galaxies using deep, four-point dithered observations. We have chosen globular cluster systems which have young, medium-age and old cluster populations, as indicated by cluster colors and luminosities. Our primary goal is to test the hypothesis that globular cluster luminosity functions evolve towards a ``universal'' form. Previous observations have shown that young cluster systems have exponential luminosity functions rather than the characteristic log-normal luminosity function of old cluster systems. We will test to see whether such young system exhibits a wider range of structural parameters than an old systems, and whether and at what rate plausible disruption mechanisms will cause the luminosity function to evolve towards a log-normal form. A simple observational comparison of structural parameters between different age cluster populations and between diff er ent sub-populations within the same galaxy will also provide clues concerning both the formation and destruction mechanisms of star clusters, the distinction between open and globular clusters, and the advisability of using globular cluster luminosity functions as distance indicators.

Muscle ischaemia associated with NXP2 autoantibodies: a severe subtype of juvenile dermatomyositis.

PubMed

Aouizerate, Jessie; De Antonio, Marie; Bader-Meunier, Brigitte; Barnerias, Christine; Bodemer, Christine; Isapof, Arnaud; Quartier, Pierre; Melki, Isabelle; Charuel, Jean-Luc; Bassez, Guillaume; Desguerre, Isabelle; Gherardi, Romain K; Authier, François-Jérôme; Gitiaux, Cyril

2018-05-01

Myositis-specific autoantibodies (MSAs) are increasingly used to delineate distinct subgroups of JDM. The aim of our study was to explore without a priori hypotheses whether MSAs are associated with distinct clinical-pathological changes and severity in a monocentric JDM cohort. Clinical, biological and histological findings from 23 JDM patients were assessed. Twenty-six histopathological parameters were subjected to multivariate analysis. Autoantibodies included anti-NXP2 (9/23), anti-TIF1γ (4/23), anti-MDA5 (2/23), no MSAs (8/23). Multivariate analysis yielded two histopathological clusters. Cluster 1 (n = 11) showed a more severe and ischaemic pattern than cluster 2 (n = 12) assessed by: total score severity ⩾ 20 (100.0% vs 25.0%); visual analogic score ⩾6 (100.0% vs 25.0%); the vascular domain score >1 (100.0% vs 41.7%); microinfarcts (100% vs 58.3%); ischaemic myofibrillary loss (focal punched-out vacuoles) (90.9 vs 25%); and obvious capillary loss (81.8% vs 16.7). Compared with cluster 2, patients in cluster 1 had strikingly more often anti-NXP2 antibodies (7/11 vs 2/12), more pronounced muscle weakness, more gastrointestinal involvement and required more aggressive treatment. Furthermore, patients with anti-NXP2 antibodies, mostly assigned in the first cluster, also displayed more severe muscular disease, requiring more aggressive treatment and having a lower remission rate during the follow-up period. Marked muscle ischaemic involvement and the presence of anti-NXP2 autoantibodies are associated with more severe forms of JDM.

Methanethiol chemistry on TiO 2-supported Ni clusters

NASA Astrophysics Data System (ADS)

Ozturk, O.; Park, J. B.; Black, T. J.; Rodriguez, J. A.; Hrbek, J.; Chen, D. A.

2008-10-01

The thermal decomposition of methanethiol on Ni clusters grown on TiO 2(1 1 0) was studied by temperature programmed desorption (TPD), X-ray photoelectron spectroscopy (XPS) and low energy ion scattering (LEIS). On all of the Ni surfaces investigated, methane and hydrogen were observed as gaseous products in the TPD experiments, and the only sulfur-containing species that desorbed from the surface was methanethiol itself at low temperatures. The two pathways for methanethiol reaction were hydrodesulfurization to produce methane and nonselective decomposition, which leaves atomic carbon and sulfur on the surface. From high resolution XPS studies, methyl thiolate was identified as the surface intermediate for reaction on TiO 2 and on all of the Ni surfaces investigated, similar to what is observed on single-crystal Ni surfaces. However, the binding sites for methyl thiolate on the 1 ML (monolayer) Ni clusters were different from those on the Ni clusters at coverages of 2.5 ML and higher, based on the S(2p) binding energies for methyl thiolate. No distinct changes in activity or selectivity were observed for the smaller Ni clusters grown at low coverage compared to the more film-like Ni surfaces other than what could be accounted for by changes in total surface area. Interactions between the Ni clusters and the TiO 2 support had two main effects on chemical activity. First, carbon was oxidized by oxygen from the TiO 2 lattice to produce CO at temperatures above 800 K. Second, annealing induced encapsulation of the Ni clusters by reduced TiO x and chemisorbed oxygen. At 800 K, the Ni clusters were totally encapsulated, resulting in a complete loss of methanethiol activity; partial encapsulation at 700 K caused a smaller decrease in activity accompanied by increased oxidation of carbon by lattice oxygen.

Dyspnea descriptors developed in Brazil: application in obese patients and in patients with cardiorespiratory diseases.

PubMed

Teixeira, Christiane Aires; Rodrigues Júnior, Antonio Luiz; Straccia, Luciana Cristina; Vianna, Elcio Dos Santos Oliveira; Silva, Geruza Alves da; Martinez, José Antônio Baddini

2011-01-01

To develop a set of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors) for use in Brazil and to investigate the usefulness of these descriptors in four distinct clinical conditions that can be accompanied by dyspnea. We collected 111 dyspnea descriptors from 67 patients and 10 health professionals. These descriptors were analyzed and reduced to 15 based on their frequency of use, similarity of meaning, and potential pathophysiological value. Those 15 descriptors were applied in 50 asthma patients, 50 COPD patients, 30 patients with heart failure, and 50 patients with class II or III obesity. The three best descriptors, as selected by the patients, were studied by cluster analysis. Potential associations between the identified clusters and the four clinical conditions were also investigated. The use of this set of descriptors led to a solution with seven clusters, designated sufoco (suffocating), aperto (tight), rápido (rapid), fadiga (fatigue), abafado (stuffy), trabalho/inspiração (work/inhalation), and falta de ar (shortness of breath). Overlapping of descriptors was quite common among the patients, regardless of their clinical condition. Asthma was significantly associated with the sufoco and trabalho/inspiração clusters, whereas COPD and heart failure were associated with the sufoco, trabalho/inspiração, and falta de ar clusters. Obesity was associated only with the falta de ar cluster. In Brazil, patients who are accustomed to perceiving dyspnea employ various descriptors in order to describe the symptom, and these descriptors can be grouped into similar clusters. In our study sample, such clusters showed no usefulness in differentiating among the four clinical conditions evaluated.

Patterns of long-term and short-term responses in adult patients with attention-deficit/hyperactivity disorder in a completer cohort of 12 weeks or more with atomoxetine.

PubMed

Sobanski, E; Leppämäki, S; Bushe, C; Berggren, L; Casillas, M; Deberdt, W

2015-11-01

Atomoxetine is a well-established pharmacotherapy for adult ADHD. Long-term studies show incremental reductions in symptoms over time. However, clinical experience suggests that patients differ in their response patterns. From 13 Eli Lilly-sponsored studies, we pooled and analyzed data for adults with ADHD who completed atomoxetine treatment at long-term (24 weeks; n=1443) and/or short-term (12 weeks; n=2830) time-points, and had CAARS-Inv:SV total and CGI-S data up to or after these time-points and at Week 0 (i.e. at baseline, when patients first received atomoxetine). The goal was to identify and describe distinct trajectories of response to atomoxetine using hierarchical clustering methods and linear mixed modelling. Based on the homogeneity of changes in CAARS-Inv:SV total scores, 5 response clusters were identified for patients who completed long-term (24 weeks) treatment with atomoxetine, and 4 clusters were identified for patients who completed short-term (12 weeks) treatment. Four of the 5 long-term clusters (comprising 95% of completer patients) showed positive trajectories: 2 faster responding clusters (L1 and L2), and 2 more gradually responding clusters (L3 and L4). Responses (i.e.≥30% reduction in CAARS-Inv:SV total score, and CGI-S score≤3) were observed at 8 and 24 weeks in 80% and 95% of completers in Cluster L1, versus 5% and 48% in Cluster L4. While many adults with ADHD responded relatively rapidly to atomoxetine, others responded more gradually without a clear plateau at 24 weeks. Longer-term treatment may be associated with greater numbers of responders. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

[Acculturation orientations and psychosocial adaptation among adolescents with immigrant background].

PubMed

Goutaudier, N; Chauchard, E; Melioli, T; Valls, M; van Leeuwen, N; Chabrol, H

2015-09-01

The aim of the study was to explore the typology of adolescents with immigrant background based on the orientations of acculturation and to estimate the psychosocial adaptation of the various subtypes. A sample of 228 French high school students with an immigrant background completed a questionnaire assessing acculturation orientations (Immigrant Acculturation Scale; Barrette et al., 2004), antisocial behaviors, depressive symptoms and self-esteem. Cluster analysis based on acculturation orientations was performed using the k-means method. Cluster analysis produced four distinct acculturation profiles: bicultural (31%), separated (28%), marginalized (21%), and assimilated-individualistic (20%). Adolescents in the separated and marginalized clusters, both characterized by rejection of the host culture, reported higher levels of antisocial behavior. Depressive symptoms and self-esteem did not differ between clusters. Several hypotheses may explain the association between separation and delinquency. First, separation and rejection of the host culture may lead to rebellious behavior such as delinquency. Conversely, delinquent behavior may provoke rejection or discrimination by peers or school, or legal sanctions that induce a reciprocal process of rejection of the host culture and separation. The relationship between separation and antisocial behavior may be bidirectional, each one reinforcing the other, resulting in a negative spiral. This study confirms the interest of the study of the orientations of acculturation in the understanding of the antisocial behavior of adolescents with immigrant background. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Potential Environmental Justice (EJ) areas in Region 2 based on 2000 Census [EPA.EJAREAS_2000

EPA Pesticide Factsheets

Potential Environmental Justice (EJ) areas in Region 2 . This dataset was derived from 2000 census data and based on the criteria setforth in the Region 2 Interim Environmental Justice Policy. The two criteria for Region 2's EJ demographic analysis are percent poverty and percent minority. The percent minority and percent poverty numbers for each blockgroup are compared to the benchmark value for the state. Census blockgroups with percent poverty or percent minority higher than the state threshold are considered potential EJ areas. The cutoffs for each state were derived by using the statistical method - cluster analysis.Cluster analysis was chosen as the most objective way of evaluating the demographic data and determining cutoff values for minority and low income. With cluster analysis, data are divided into two distinct groups (e.g., minority and non-minority, and low income and non-low income). Cluster analysis examines natural breaks of the data. Separate analyses were conducted for minority and low income, respectively, for each State. All census block groups within a State were ranked in descending order according to the demographic factor under evaluation. This resulted in a ranking for percent minority by block group and a separate ranking for percent low income by block group. An iterative process was employed where the data were (1) split into two groups; (2) the means for each of the two groups were calculated; (3) the difference between the

CNO abundances in the quintuplet cluster M supergiant 5-7

NASA Technical Reports Server (NTRS)

Ramirez, S. V.; Sellgren, K.; Blum, R.; Terndrup, D. M.

2002-01-01

We present and analyze infrared spectra of the supergiant VR 5-7, in the Quintuplet cluster 30 pc from the Galactic center. Within the uncertainties, the [C/H],[N/H], and [O/H] abundances in this star are equal of Ori, a star which exhibits mixing of CNO processed elements, but distinct from the abundance patterns in IRS 7.

Theoretical prediction of novel ultrafine nanowires formed by Si12C12 cage-like clusters

NASA Astrophysics Data System (ADS)

Yong, Yongliang; Song, Bin; He, Pimo

2014-02-01

Using density functional theory calculations, we predict that novel SiC ultrafine nanowires can be produced via the coalescence of stable Si12C12 clusters. For the isolated Si12C12 clusters, we find that the cage-like structure with a distinct segregation between Si and C atoms is energetically more favourable than the fullerene-like structure with alternating Si-C bonds. Via the coalescence of Si12C12 clusters, three novel stable nanowires have been characterised. The band structure reveals that these nanowires are semiconductors with narrow gap, indicating that they may be used as infrared detectors and thermoelectrics.

Generalized clustering conditions of Jack polynomials at negative Jack parameter {alpha}

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

Bernevig, B. Andrei; Department of Physics, Princeton University, Princeton, New Jersey 08544; Haldane, F. D. M.

We present several conjectures on the behavior and clustering properties of Jack polynomials at a negative parameter {alpha}=-(k+1/r-1), with partitions that violate the (k,r,N)- admissibility rule of [Feigin et al. [Int. Math. Res. Notices 23, 1223 (2002)]. We find that the ''highest weight'' Jack polynomials of specific partitions represent the minimum degree polynomials in N variables that vanish when s distinct clusters of k+1 particles are formed, where s and k are positive integers. Explicit counting formulas are conjectured. The generalized clustering conditions are useful in a forthcoming description of fractional quantum Hall quasiparticles.

Growth of fluorescence gold clusters using photo-chemically activated ligands

NASA Astrophysics Data System (ADS)

Mishra, Dinesh; Aldeek, Fadi; Michael, Serge; Palui, Goutam; Mattoussi, Hedi

2016-03-01

Ligands made of lipoic acid (LA) appended with a polyethylene glycol (PEG) chain have been used in the aqueous phase growth of luminescent gold clusters with distinct emission from yellow to near-IR, using two different routes. In the first route, the gold-ligand complex was chemically reduced using sodium borohydride in alkaline medium, which gave near- IR luminescent gold clusters with maximum emission around 745 nm. In the second method, LA-PEG ligand was photochemically modified to a mixture of thiols, oligomers and oxygenated species under UV-irradiation, which was then used as both reducing agent and stabilizing ligand. By adjusting the pH, temperature, and time of the reaction, we were able to obtain clusters with two distinct emission properties. Refluxing the gold-ligand complex in alkaline medium in the presence of excess ligand gave yellow emission within the first two hours and the emission shifted to red after overnight reaction. Mass spectrometry and chemical assay were used to understand the photo-chemical transformation of Lipoic Acid (LA). Mass spectroscopic studies showed the photo-irradiated product contains thiols, oligomers (dimers, trimers and tetramers) as well as oxygenated species. The amount of thiol formed under different conditions of irradiation was estimated using Ellman's assay.

Mapping the Dark Matter Distribution of the Merging Galaxy Cluster Abell 115

NASA Astrophysics Data System (ADS)

Kim, Mincheol; Jee, Myungkook James; Forman, William; Golovich, Nathan; van Weeren, Reinout

2018-01-01

The colliding galaxy cluster Abell 115 shows a number of clear merging features including radio relics, double X-ray peaks, and offsets between the cluster member galaxies and the X-ray distributions. In order to constrain the merging scenario of this complex system, it is critical to know where the dark matter is. We present a high-fidelity weak-lensing analysis of the system using a state-of-the-art method that robustly models the detailed PSF variations. Our mass reconstruction reveals two distinct mass peaks. Through a careful bootstrapping analysis, we demonstrate that the positions of these two mass peaks are highly consistent with those of the cluster galaxies, although the comparison with the X-ray emission shows that the mass peaks lead the X-ray peaks. We obtain the first weak-lensing mass of each subcluster by simultaneously fitting two NFW profiles, as well as the total mass of the system. Interestingly, the total mass is a few factors lower than the published dynamical mass based on velocity dispersion. This large mass discrepancy may be attributed to a significant disruption of the cluster galaxy orbits due to the violent merger. Our preliminary analysis indicates that the two subclusters might have experienced a first off-axis collision a few Gyrs ago and might be now returning for a second collision.

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

PubMed

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

2018-05-01

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

Microbial species delineation using whole genome sequences

PubMed Central

Varghese, Neha J.; Mukherjee, Supratim; Ivanova, Natalia; Konstantinidis, Konstantinos T.; Mavrommatis, Kostas; Kyrpides, Nikos C.; Pati, Amrita

2015-01-01

Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness. In this work, we demonstrate that the combination of gANI and the alignment fraction (AF) between two genomes accurately reflects their genomic relatedness. We introduce an efficient implementation of AF,gANI and discuss its successful application to 86.5M genome pairs between 13,151 prokaryotic genomes assigned to 3032 species. Subsequently, by comparing the genome clusters obtained from complete linkage clustering of these pairs to existing taxonomy, we observed that nearly 18% of all prokaryotic species suffer from anomalies in species definition. Our results can be used to explore central questions such as whether microorganisms form a continuum of genetic diversity or distinct species represented by distinct genetic signatures. We propose that this precise and objective AF,gANI-based species definition: the MiSI (Microbial Species Identifier) method, be used to address previous inconsistencies in species classification and as the primary guide for new taxonomic species assignment, supplemented by the traditional polyphasic approach, as required. PMID:26150420

Anatomy of biocalcarenitic units in the Plio-Pleistocene record of the Northern Apennines (Italy)

NASA Astrophysics Data System (ADS)

Cau, Simone; Roveri, Marco; Taviani, Marco

2017-04-01

The Castell'Arquato Basin (CAB) in the foothills of the thrust-belt Northern Apennines is a foreland basin infilled by Plio-Quaternary sediments and a reference area for Plio-Pleistocene biostratigraphy. The CAB exposes plurimetric biodetrital carbonate units at discrete temporal intervals. Such shell-rich units are at places lithified, turning into conspicuous biodetritral carbonate rocks (biocalcarenites) that display a cyclical stacking motif highlighted by the regular alternation with finer-grained marine deposits. The cyclical nature of thick biocalcarenites has been hypothesized to be orbitally-controlled by obliquity and/or precession cyclicity. Furthermore, biocalcarenite-mudstone couplets form distinct clusters governed by 100-400 ka eccentricity maxima starting from 3.1 Ma at the inception of the Northern Hemisphere glaciation. They correlate with sapropels cycles formed at times of maximum insolation (precession minima). The CAB calcarenites are poorly known with respect to their environmental genetic context what motivated a detailed paleoecological analysis to unravel at best their formative context. Five distinct biofacies arranged in stacking patterns are identified through two-way cluster analysis based on the macrofossil content. Our quantitative and qualitative results suggest that these polytaxic shell concentrations and their bracketing marine mudstones developed in middle shelf settings being sensitive to climatically-driven changes.

Identification and DUS Testing of Rice Varieties through Microsatellite Markers

PubMed Central

Pourabed, Ehsan; Jazayeri Noushabadi, Mohammad Reza; Jamali, Seyed Hossein; Moheb Alipour, Naser; Zareyan, Abbas; Sadeghi, Leila

2015-01-01

Identification and registration of new rice varieties are very important to be free from environmental effects and using molecular markers that are more reliable. The objectives of this study were, first, the identification and distinction of 40 rice varieties consisting of local varieties of Iran, improved varieties, and IRRI varieties using PIC, and discriminating power, second, cluster analysis based on Dice similarity coefficient and UPGMA algorithm, and, third, determining the ability of microsatellite markers to separate varieties utilizing the best combination of markers. For this research, 12 microsatellite markers were used. In total, 83 polymorphic alleles (6.91 alleles per locus) were found. In addition, the variation of PIC was calculated from 0.52 to 0.9. The results of cluster analysis showed the complete discrimination of varieties from each other except for IR58025A and IR58025B. Moreover, cluster analysis could detect the most of the improved varieties from local varieties. Based on the best combination of markers analysis, five pair primers together have shown the same results of all markers for detection among all varieties. Considering the results of this research, we can propose that microsatellite markers can be used as a complementary tool for morphological characteristics in DUS tests. PMID:25755666

Size and shape variations of the bony components of sperm whale cochleae.

PubMed

Schnitzler, Joseph G; Frédérich, Bruno; Früchtnicht, Sven; Schaffeld, Tobias; Baltzer, Johannes; Ruser, Andreas; Siebert, Ursula

2017-04-25

Several mass strandings of sperm whales occurred in the North Sea during January and February 2016. Twelve animals were necropsied and sampled around 48 h after their discovery on German coasts of Schleswig Holstein. The present study aims to explore the morphological variation of the primary sensory organ of sperm whales, the left and right auditory system, using high-resolution computerised tomography imaging. We performed a quantitative analysis of size and shape of cochleae using landmark-based geometric morphometrics to reveal inter-individual anatomical variations. A hierarchical cluster analysis based on thirty-one external morphometric characters classified these 12 individuals in two stranding clusters. A relative amount of shape variation could be attributable to geographical differences among stranding locations and clusters. Our geometric data allowed the discrimination of distinct bachelor schools among sperm whales that stranded on German coasts. We argue that the cochleae are individually shaped, varying greatly in dimensions and that the intra-specific variation observed in the morphology of the cochleae may partially reflect their affiliation to their bachelor school. There are increasing concerns about the impact of noise on cetaceans and describing the auditory periphery of odontocetes is a key conservation issue to further assess the effect of noise pollution.

Prokaryotic diversity, distribution, and insights into their role in biogeochemical cycling in marine basalts

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

Mason, Olivia U.; Di Meo-Savoie, Carol A.; Van Nostrand, Joy D.

2008-09-30

We used molecular techniques to analyze basalts of varying ages that were collected from the East Pacific Rise, 9 oN, from the rift axis of the Juan de Fuca Ridge, and from neighboring seamounts. Cluster analysis of 16S rDNA Terminal Restriction Fragment Polymorphism data revealed that basalt endoliths are distinct from seawater and that communities clustered, to some degree, based on the age of the host rock. This age-based clustering suggests that alteration processes may affect community structure. Cloning and sequencing of bacterial and archaeal 16S rRNA genes revealed twelve different phyla and sub-phyla associated with basalts. These include themore » Gemmatimonadetes, Nitrospirae, the candidate phylum SBR1093 in the c, andin the Archaea Marine Benthic Group B, none of which have been previously reported in basalts. We delineated novel ocean crust clades in the gamma-Proteobacteria, Planctomycetes, and Actinobacteria that are composed entirely of basalt associated microflora, and may represent basalt ecotypes. Finally, microarray analysis of functional genes in basalt revealed that genes coding for previously unreported processes such as carbon fixation, methane-oxidation, methanogenesis, and nitrogen fixation are present, suggesting that basalts harbor previously unrecognized metabolic diversity. These novel processes could exert a profound influence on ocean chemistry.« less

Distinct differences in striatal dysmorphology between attention deficit hyperactivity disorder boys with and without a comorbid reading disability.

PubMed

Goradia, Dhruman D; Vogel, Sherry; Mohl, Brianne; Khatib, Dalal; Zajac-Benitez, Caroline; Rajan, Usha; Robin, Arthur; Rosenberg, David R; Stanley, Jeffrey A

2016-12-30

There is evidence of greater cognitive deficits in attention deficit hyperactivity disorder with a comorbid reading disability (ADHD/+RD) compared to ADHD alone (ADHD/-RD). Additionally, the striatum has been consistently implicated in ADHD. However, the extent of morphological alterations in the striatum of ADHD/+RD is poorly understood, which is the main purpose of this study. Based on structural MRI images, the surface deformation of the caudate and putamen was assessed in 59 boys matching in age and IQ [19 ADHD/-RD, 15 ADHD/+RD and 25 typically developing controls (TDC)]. A vertex based analysis with multiple comparison correction was conducted to compare ADHD/-RD and ADHD/+RD to TDC. Compared to TDC, ADHD/+RD showed multiple bilateral significant clusters of surface compression. In contrast, ADHD/-RD showed fewer significant clusters of surface compression and restricted to the left side. Regarding the putamen, only ADHD/-RD showed significant clusters of surface compression. Results demonstrate for the first time a greater extent of morphological alterations in the caudate of ADHD/+RD than ADHD/-RD compared to TDC, which may suggest greater implicated cortical areas projecting to the caudate that are associated with the greater neuropsychological impairments observed in ADHD/+RD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A new clustering algorithm applicable to multispectral and polarimetric SAR images

NASA Technical Reports Server (NTRS)

Wong, Yiu-Fai; Posner, Edward C.

1993-01-01

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

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

PubMed

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

2010-07-01

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

Redescription of Hepatozoon felis (Apicomplexa: Hepatozoidae) based on phylogenetic analysis, tissue and blood form morphology, and possible transplacental transmission.

PubMed

Baneth, Gad; Sheiner, Alina; Eyal, Osnat; Hahn, Shelley; Beaufils, Jean-Pierre; Anug, Yigal; Talmi-Frank, Dalit

2013-04-15

A Hepatozoon parasite was initially reported from a cat in India in 1908 and named Leucocytozoon felis domestici. Although domestic feline hepatozoonosis has since been recorded from Europe, Africa, Asia and America, its description, classification and pathogenesis have remained vague and the distinction between different species of Hepatozoon infecting domestic and wild carnivores has been unclear. The aim of this study was to carry out a survey on domestic feline hepatozoonosis and characterize it morphologically and genetically. Hepatozoon sp. DNA was amplified by PCR from the blood of 55 of 152 (36%) surveyed cats in Israel and from all blood samples of an additional 19 cats detected as parasitemic by microscopy during routine hematologic examinations. Hepatozoon sp. forms were also characterized from tissues of naturally infected cats. DNA sequencing determined that all cats were infected with Hepatozoon felis except for two infected by Hepatozoon canis. A significant association (p = 0.00001) was found between outdoor access and H. felis infection. H. felis meronts containing merozoites were characterized morphologically from skeletal muscles, myocardium and lungs of H. felis PCR-positive cat tissues and development from early to mature meront was described. Distinctly-shaped gamonts were observed and measured from the blood of these H. felis infected cats. Two fetuses from H. felis PCR-positive queens were positive by PCR from fetal tissue including the lung and amniotic fluid, suggesting possible transplacental transmission. Genetic analysis indicated that H. felis DNA sequences from Israeli cats clustered together with the H. felis Spain 1 and Spain 2 sequences. These cat H. felis sequences clustered separately from the feline H. canis sequences, which grouped with Israeli and foreign dog H. canis sequences. H. felis clustered distinctly from Hepatozoon spp. of other mammals. Feline hepatozoonosis caused by H. felis is mostly sub-clinical as a high proportion of the population is infected with no apparent overt clinical manifestations. This study aimed to integrate new histopathologic, hematologic, clinical, epidemiological and genetic findings on feline hepatozoonosis and promote the understanding of this infection. The results indicate that feline infection is primarily caused by a morphologically and genetically distinct species, H. felis, which has predilection to infecting muscular tissues, and is highly prevalent in the cat population studied. The lack of previous comprehensively integrated data merits the redescription of this parasite elucidating its parasitological characteristics.

Structural parameters from ground-based observations of newly discovered globular clusters in NGC 5128

NASA Astrophysics Data System (ADS)

Gómez, M.; Geisler, D.; Harris, W. E.; Richtler, T.; Harris, G. L. H.; Woodley, K. A.

2006-03-01

We have investigated a number of globular cluster candidates from a recent wide-field study by Harris et al. (2004a, AJ, 128, 712) of the giant elliptical galaxy NGC 5128. We used the Magellan I telescope + MagIC camera under excellent seeing conditions (0.3 arcsec-0.6 arcsec) and obtained very high resolution images for a sample of 44 candidates. Of these, 15 appear to be bonafide globular clusters in NGC 5128 while the rest are either foreground stars or background galaxies. We also serendipitously discovered 18 new cluster candidates in the same fields. Our images allow us to study the light profiles of the likely clusters, all of which are well resolved. This is the first ground-based study of structural parameters for globular clusters outside the Local Group. We compare the psf-deconvolved profiles with King models and derive structural parameters, ellipticities and surface brightnesses. We compare the derived structural properties with those of other well-studied globular cluster systems. In general, our clusters are similar in size, ellipticity, core radius and central surface brightness to their counterparts in other galaxies, in particular those in NGC 5128 observed with HST by Harris et al. (2002, AJ, 124, 1435). However, our clusters extend to higher ellipticities and larger half-light radii than their Galactic counterparts, as do the Harris et al. sample. Combining our results with those of Harris et al. fills in the gaps previously existing in rh - MV parameter space and indicates that any substantial difference between presumed distinct cluster types in this diagram, including for example the Faint Fuzzies of Larsen & Brodie (2000, AJ, 120, 2938) and the "extended, luminous" M 31 clusters of Huxor et al. (2005, MNRAS, 360, 1007) is now removed and that clusters form a continuum in this diagram. Indeed, this continuum now extends to the realm of the Ultra Compact Dwarfs. The metal-rich clusters in our sample have half-light radii that are almost twice as large in the mean as their metal-poor counterparts, at odds with the generally accepted trend. The possibility exists that this result could be due in part to contamination by background galaxies. We have carried out additional analysis to quantify this contamination. This shows that, although galaxies cannot be easily told apart from clusters in some of the structural diagrams, the combination of excellent image quality and Washington photometry should limit the contamination to roughly 10% of the population of cluster candidates. Finally, our discovery of a substantial number of new cluster candidates in the relatively distant regions of the NGC 5128 halo suggests that current values of the total number of globular clusters may be underestimates.

X-Ray Detection of the Cluster Containing the Cepheid S Mus

NASA Astrophysics Data System (ADS)

Evans, Nancy Remage; Pillitteri, Ignazio; Wolk, Scott; Guinan, Edward; Engle, Scott; Bond, Howard E.; Schaefer, Gail H.; Karovska, Margarita; DePasquale, Joseph; Tingle, Evan

2014-04-01

The galactic Cepheid S Muscae has recently been added to the important list of Cepheids linked to open clusters, in this case the sparse young cluster ASCC 69. Low-mass members of a young cluster are expected to have rapid rotation and X-ray activity, making X-ray emission an excellent way to discriminate them from old field stars. We have made an XMM-Newton observation centered on S Mus and identified a population of X-ray sources whose near-IR Two Micron All Sky Survey counterparts lie at locations in the J, (J - K) color-magnitude diagram consistent with cluster membership at the distance of S Mus. Their median energy and X-ray luminosity are consistent with young cluster members as distinct from field stars. These strengthen the association of S Mus with the young cluster, making it a potential Leavitt law (period-luminosity relation) calibrator.

The Hubble Space Telescope UV Legacy Survey of Galactic globular clusters - XIII. ACS/WFC parallel-field catalogues

NASA Astrophysics Data System (ADS)

Simioni, M.; Bedin, L. R.; Aparicio, A.; Piotto, G.; Milone, A. P.; Nardiello, D.; Anderson, J.; Bellini, A.; Brown, T. M.; Cassisi, S.; Cunial, A.; Granata, V.; Ortolani, S.; van der Marel, R. P.; Vesperini, E.

2018-05-01

As part of the Hubble Space Telescope UV Legacy Survey of Galactic globular clusters, 110 parallel fields were observed with the Wide Field Channel of the Advanced Camera for Surveys, in the outskirts of 48 globular clusters, plus the open cluster NGC 6791. Totalling about 0.3 deg2 of observed sky, this is the largest homogeneous Hubble Space Telescope photometric survey of Galalctic globular clusters outskirts to date. In particular, two distinct pointings have been obtained for each target on average, all centred at about 6.5 arcmin from the cluster centre, thus covering a mean area of about 23 arcmin2 for each globular cluster. For each field, at least one exposure in both F475W and F814W filters was collected. In this work, we publicly release the astrometric and photometric catalogues and the astrometrized atlases for each of these fields.

Self-concept differentiation and self-concept clarity across adulthood: associations with age and psychological well-being.

PubMed

Diehl, Manfred; Hay, Elizabeth L

2011-01-01

This study focused on the identification of conceptually meaningful groups of individuals based on their joint self-concept differentiation (SCD) and self-concept clarity (SCC) scores. Notably, we examined whether membership in different SCD-SCC groups differed by age and also was associated with differences in psychological well-being (PWB). Cluster analysis revealed five distinct SCD-SCC groups: a self-assured, unencumbered, fragmented-only, confused-only, and fragmented and confused group. Individuals in the self-assured group had the highest mean scores for positive PWB and the lowest mean scores for negative PWB, whereas individuals in the fragmented and confused group showed the inverse pattern. Findings showed that it was psychologically advantageous to belong to the self-assured group at all ages. As hypothesized, older adults were more likely than young adults to be in the self-assured cluster, whereas young adults were more likely to be in the fragmented and confused cluster. Thus, consistent with extant theorizing, age was positively associated with psychologically adaptive self-concept profiles.

Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2016-04-01

The proper functioning of multicellular organisms requires the robust establishment of precise proportions between distinct cell types. This developmental differentiation process typically involves intracellular regulatory and stochastic mechanisms to generate cell-fate diversity as well as intercellular signaling mechanisms to coordinate cell-fate decisions at tissue level. We thus surmise that key insights about the developmental regulation of cell-type proportion can be captured by the modeling study of clustering dynamics in population of inhibitory-coupled noisy bistable systems. This general class of dynamical system is shown to exhibit a very stable two-cluster state, but also metastability, collective oscillations or noise-induced state hopping, which can prevent from timely and reliably reaching a robust and well-proportioned clustered state. To circumvent these obstacles or to avoid fine-tuning, we highlight a general strategy based on dual-time positive feedback loops, such as mediated through transcriptional versus epigenetic mechanisms, which improves proportion regulation by coordinating early and flexible lineage priming with late and firm commitment. This result sheds new light on the respective and cooperative roles of multiple regulatory feedback, stochasticity and lateral inhibition in developmental dynamics.

Characteristics of foreshock activity inferred from the JMA earthquake catalog

NASA Astrophysics Data System (ADS)

Tamaribuchi, Koji; Yagi, Yuji; Enescu, Bogdan; Hirano, Shiro

2018-05-01

We investigated the foreshock activity characteristics using the Japan Meteorological Agency Unified Earthquake Catalog for the last 20 years. Using the nearest-neighbor distance approach, we systematically and objectively classified the earthquakes into clustered and background seismicity. We further categorized the clustered events into foreshocks, mainshocks, and aftershocks and analyzed their statistical features such as the b-value of the frequency-magnitude distribution. We found that the b-values of the foreshocks are lower than those of the aftershocks. This b-value difference suggested that not only the stochastic cascade effect but also the stress changes/aseismic processes may contribute to the mainshock-triggering process. However, forecasting the mainshock based on b-value analysis may be difficult. In addition, the rate of foreshock occurrence in all clusters (with two or more events) was nearly constant (30-40%) over a wide magnitude range. The difference in the magnitude, time, and epicentral distance between the mainshock and largest foreshock followed a power law. We inferred that the distinctive characteristics of foreshocks can be better revealed using the improved catalog, which includes the micro-earthquake information.

EEG Correlates of Ten Positive Emotions.

PubMed

Hu, Xin; Yu, Jianwen; Song, Mengdi; Yu, Chun; Wang, Fei; Sun, Pei; Wang, Daifa; Zhang, Dan

2017-01-01

Compared with the well documented neurophysiological findings on negative emotions, much less is known about positive emotions. In the present study, we explored the EEG correlates of ten different positive emotions (joy, gratitude, serenity, interest, hope, pride, amusement, inspiration, awe, and love). A group of 20 participants were invited to watch 30 short film clips with their EEGs simultaneously recorded. Distinct topographical patterns for different positive emotions were found for the correlation coefficients between the subjective ratings on the ten positive emotions per film clip and the corresponding EEG spectral powers in different frequency bands. Based on the similarities of the participants' ratings on the ten positive emotions, these emotions were further clustered into three representative clusters, as 'encouragement' for awe, gratitude, hope, inspiration, pride, 'playfulness' for amusement, joy, interest, and 'harmony' for love, serenity. Using the EEG spectral powers as features, both the binary classification on the higher and lower ratings on these positive emotions and the binary classification between the three positive emotion clusters, achieved accuracies of approximately 80% and above. To our knowledge, our study provides the first piece of evidence on the EEG correlates of different positive emotions.

Proton environment of reduced Rieske iron-sulfur cluster probed by two-dimensional ESEEM spectroscopy

PubMed Central

Kolling, Derrick R. J.; Samoilova, Rimma I.; Shubin, Alexander A.; Crofts, Antony R.; Dikanov, Sergei A.

2008-01-01

The proton environment of the reduced [2Fe-2S] cluster in the water-soluble head domain of the Rieske iron—sulfur protein (ISF) from the cytochrome bc1 complex of Rhodobacter sphaeroides has been studied by orientation-selected X-band 2D ESEEM. The 2D spectra show multiple cross-peaks from protons, with considerable overlap. Samples in which 1H2O water was replaced by 2H2O were used to determine which of the observed peaks belong to exchangeable protons, likely involved in hydrogen bonds in the neighborhood of the cluster. By correlating the cross-peaks from 2D spectra recorded at different parts of the EPR spectrum, lines from nine distinct proton signals were identified. Assignment of the proton signals was based on a point-dipole model for interaction with electrons of Fe(III) and Fe(II) ions, using the high-resolution structure of ISF from Rb. sphaeroides. Analysis of experimental and calculated tensors has led us to conclude that even 2D spectra do not completely resolve all contributions from nearby protons. Particularly, the seven resolved signals from non-exchangeable protons could be produced by at least thirteen protons. The contributions from exchangeable protons were resolved by difference spectra (1H2O minus 2H2O), and assigned to two groups of protons with distinct anisotropic hyperfine values. The largest measured coupling exceeded any calculated value. This discrepancy could result from limitations of the point dipole approximation in dealing with the distribution of spin density over the sulfur atoms of the cluster and the cysteine ligands, or from differences between the structure in solution and the crystallographic structure. The approach demonstrated here provides a paradigm for a wide range of studies in which hydrogen-bonding interactions with metallic centers has a crucial role in understanding of function. PMID:19099453

Self-aggregation in scaled principal component space

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

Ding, Chris H.Q.; He, Xiaofeng; Zha, Hongyuan

2001-10-05

Automatic grouping of voluminous data into meaningful structures is a challenging task frequently encountered in broad areas of science, engineering and information processing. These data clustering tasks are frequently performed in Euclidean space or a subspace chosen from principal component analysis (PCA). Here we describe a space obtained by a nonlinear scaling of PCA in which data objects self-aggregate automatically into clusters. Projection into this space gives sharp distinctions among clusters. Gene expression profiles of cancer tissue subtypes, Web hyperlink structure and Internet newsgroups are analyzed to illustrate interesting properties of the space.

Hierarchical structure and importance of patients' reasons for treatment choices in knee and hip osteoarthritis: a concept mapping study.

PubMed

Selten, Ellen M H; Geenen, Rinie; van der Laan, Willemijn H; van der Meulen-Dilling, Roelien G; Schers, Henk J; Nijhof, Marc W; van den Ende, Cornelia H M; Vriezekolk, Johanna E

2017-02-01

To improve patients' use of conservative treatment options of hip and knee OA, in-depth understanding of reasons underlying patients' treatment choices is required. The current study adopted a concept mapping method to thematically structure and prioritize reasons for treatment choice in knee and hip OA from a patients' perspective. Multiple reasons for treatment choices were previously identified using in-depth interviews. In consensus meetings, experts derived 51 representative reasons from the interviews. Thirty-six patients individually sorted the 51 reasons in two card-sorting tasks: one based on content similarity, and one based on importance of reasons. The individual sortings of the first card-sorting task provided input for a hierarchical cluster analysis (squared Euclidian distances, Ward's method). The importance of the reasons and clusters were examined using descriptive statistics. The hierarchical structure of reasons for treatment choices showed a core distinction between two categories of clusters: barriers [subdivided into context (e.g. the healthcare system) and disadvantages] and outcome (subdivided into treatment and personal life). At the lowest level, 15 clusters were identified of which the clusters Physical functioning, Risks and Prosthesis were considered most important when making a treatment decision for hip or knee OA. Patients' treatment choices in knee and hip OA are guided by contextual barriers, disadvantages of the treatment, outcomes of the treatment and consequences for personal life. The structured overview of reasons can be used to support shared decision-making. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A HYDRODYNAMICAL SOLUTION FOR THE ''TWIN-TAILED'' COLLIDING GALAXY CLUSTER ''EL GORDO''

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

Molnar, Sandor M.; Broadhurst, Tom, E-mail: sandor@phys.ntu.edu.tw

The distinctive cometary X-ray morphology of the recently discovered massive galaxy cluster ''El Gordo'' (ACT-CT J0102–4915; z = 0.87) indicates that an unusually high-speed collision is ongoing between two massive galaxy clusters. A bright X-ray ''bullet'' leads a ''twin-tailed'' wake, with the Sunyaev-Zel'dovich (SZ) centroid at the end of the northern tail. We show how the physical properties of this system can be determined using our FLASH-based, N-body/hydrodynamic model, constrained by detailed X-ray, SZ, and Hubble lensing and dynamical data. The X-ray morphology and the location of the two dark matter components and the SZ peak are accurately described by amore » simple binary collision viewed about 480 million years after the first core passage. We derive an impact parameter of ≅300 kpc, and a relative initial infall velocity of ≅2250 km s{sup –1} when separated by the sum of the two virial radii assuming an initial total mass of 2.15 × 10{sup 15} M {sub ☉} and a mass ratio of 1.9. Our model demonstrates that tidally stretched gas accounts for the northern X-ray tail along the collision axis between the mass peaks, and that the southern tail lies off axis, comprising compressed and shock heated gas generated as the less massive component plunges through the main cluster. The challenge for ΛCDM will be to find out if this physically extreme event can be plausibly accommodated when combined with the similarly massive, high-infall-velocity case of the Bullet cluster and other such cases being uncovered in new SZ based surveys.« less

Three-dimensional Magnetohydrodynamical Simulations of the Morphology of Head-Tail Radio Galaxies Based on the Magnetic Tower Jet Model

NASA Astrophysics Data System (ADS)

Gan, Zhaoming; Li, Hui; Li, Shengtai; Yuan, Feng

2017-04-01

The distinctive morphology of head-tail radio galaxies reveals strong interactions between the radio jets and their intra-cluster environment, the general consensus on the morphology origin of head-tail sources is that radio jets are bent by violent intra-cluster weather. We demonstrate in this paper that such strong interactions provide a great opportunity to study the jet properties and also the dynamics of the intra-cluster medium (ICM). By three-dimensional magnetohydrodynamical simulations, we analyze the detailed bending process of a magnetically dominated jet, based on the magnetic tower jet model. We use stratified atmospheres modulated by wind/shock to mimic the violent intra-cluster weather. Core sloshing is found to be inevitable during the wind-cluster core interaction, which induces significant shear motion and could finally drive ICM turbulence around the jet, making it difficult for the jet to survive. We perform a detailed comparison between the behavior of pure hydrodynamical jets and the magnetic tower jet and find that the jet-lobe morphology could not survive against the violent disruption in all of our pure hydrodynamical jet models. On the other hand, the head-tail morphology is well reproduced by using a magnetic tower jet model bent by wind, in which hydrodynamical instabilities are naturally suppressed and the jet could always keep its integrity under the protection of its internal magnetic fields. Finally, we also check the possibility for jet bending by shock only. We find that shock could not bend the jet significantly, and thus could not be expected to explain the observed long tails in head-tail radio galaxies.

Three-dimensional Magnetohydrodynamical Simulations of the Morphology of Head–Tail Radio Galaxies Based on the Magnetic Tower Jet Model

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

Gan, Zhaoming; Yuan, Feng; Li, Hui

The distinctive morphology of head–tail radio galaxies reveals strong interactions between the radio jets and their intra-cluster environment, the general consensus on the morphology origin of head–tail sources is that radio jets are bent by violent intra-cluster weather. We demonstrate in this paper that such strong interactions provide a great opportunity to study the jet properties and also the dynamics of the intra-cluster medium (ICM). By three-dimensional magnetohydrodynamical simulations, we analyze the detailed bending process of a magnetically dominated jet, based on the magnetic tower jet model. We use stratified atmospheres modulated by wind/shock to mimic the violent intra-cluster weather.more » Core sloshing is found to be inevitable during the wind-cluster core interaction, which induces significant shear motion and could finally drive ICM turbulence around the jet, making it difficult for the jet to survive. We perform a detailed comparison between the behavior of pure hydrodynamical jets and the magnetic tower jet and find that the jet-lobe morphology could not survive against the violent disruption in all of our pure hydrodynamical jet models. On the other hand, the head–tail morphology is well reproduced by using a magnetic tower jet model bent by wind, in which hydrodynamical instabilities are naturally suppressed and the jet could always keep its integrity under the protection of its internal magnetic fields. Finally, we also check the possibility for jet bending by shock only. We find that shock could not bend the jet significantly, and thus could not be expected to explain the observed long tails in head–tail radio galaxies.« less

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection.

PubMed

Liston, Adam D; De Munck, Jan C; Hamandi, Khalid; Laufs, Helmut; Ossenblok, Pauly; Duncan, John S; Lemieux, Louis

2006-07-01

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Allelic recombination between distinct genomic locations generates copy number diversity in human β-defensins

PubMed Central

Bakar, Suhaili Abu; Hollox, Edward J.; Armour, John A. L.

2009-01-01

β-Defensins are small secreted antimicrobial and signaling peptides involved in the innate immune response of vertebrates. In humans, a cluster of at least 7 of these genes shows extensive copy number variation, with a diploid copy number commonly ranging between 2 and 7. Using a genetic mapping approach, we show that this cluster is at not 1 but 2 distinct genomic loci ≈5 Mb apart on chromosome band 8p23.1, contradicting the most recent genome assembly. We also demonstrate that the predominant mechanism of change in β-defensin copy number is simple allelic recombination occurring in the interval between the 2 distinct genomic loci for these genes. In 416 meiotic transmissions, we observe 3 events creating a haplotype copy number not found in the parent, equivalent to a germ-line rate of copy number change of ≈0.7% per gamete. This places it among the fastest-changing copy number variants currently known. PMID:19131514

Cluster redshifts in five suspected superclusters

NASA Technical Reports Server (NTRS)

Ciardullo, R.; Ford, H.; Harms, R.

1985-01-01

Redshift surveys for rich superclusters were carried out in five regions of the sky containing surface-density enhancements of Abell clusters. While several superclusters are identified, projection effects dominate each field, and no system contains more than five rich clusters. Two systems are found to be especially interesting. The first, field 0136 10, is shown to contain a superposition of at least four distinct superclusters, with the richest system possessing a small velocity dispersion. The second system, 2206 - 22, though a region of exceedingly high Abell cluster surface density, appears to be a remarkable superposition of 23 rich clusters almost uniformly distributed in redshift space between 0.08 and 0.24. The new redshifts significantly increase the three-dimensional information available for the distance class 5 and 6 Abell clusters and allow the spatial correlation function around rich superclusters to be estimated.

Identification of the First Riboflavin Catabolic Gene Cluster Isolated from Microbacterium maritypicum G10*

PubMed Central

Xu, Hui; Chakrabarty, Yindrila; Philmus, Benjamin; Mehta, Angad P.; Bhandari, Dhananjay; Hohmann, Hans-Peter; Begley, Tadhg P.

2016-01-01

Riboflavin is a common cofactor, and its biosynthetic pathway is well characterized. However, its catabolic pathway, despite intriguing hints in a few distinct organisms, has never been established. This article describes the isolation of a Microbacterium maritypicum riboflavin catabolic strain, and the cloning of the riboflavin catabolic genes. RcaA, RcaB, RcaD, and RcaE were overexpressed and biochemically characterized as riboflavin kinase, riboflavin reductase, ribokinase, and riboflavin hydrolase, respectively. Based on these activities, a pathway for riboflavin catabolism is proposed. PMID:27590337

Globin gene structure in a reptile supports the transpositional model for amniote α- and β-globin gene evolution.

PubMed

Patel, Vidushi S; Ezaz, Tariq; Deakin, Janine E; Graves, Jennifer A Marshall

2010-12-01

The haemoglobin protein, required for oxygen transportation in the body, is encoded by α- and β-globin genes that are arranged in clusters. The transpositional model for the evolution of distinct α-globin and β-globin clusters in amniotes is much simpler than the previously proposed whole genome duplication model. According to this model, all jawed vertebrates share one ancient region containing α- and β-globin genes and several flanking genes in the order MPG-C16orf35-(α-β)-GBY-LUC7L that has been conserved for more than 410 million years, whereas amniotes evolved a distinct β-globin cluster by insertion of a transposed β-globin gene from this ancient region into a cluster of olfactory receptors flanked by CCKBR and RRM1. It could not be determined whether this organisation is conserved in all amniotes because of the paucity of information from non-avian reptiles. To fill in this gap, we examined globin gene organisation in a squamate reptile, the Australian bearded dragon lizard, Pogona vitticeps (Agamidae). We report here that the α-globin cluster (HBK, HBA) is flanked by C16orf35 and GBY and is located on a pair of microchromosomes, whereas the β-globin cluster is flanked by RRM1 on the 3' end and is located on the long arm of chromosome 3. However, the CCKBR gene that flanks the β-globin cluster on the 5' end in other amniotes is located on the short arm of chromosome 5 in P. vitticeps, indicating that a chromosomal break between the β-globin cluster and CCKBR occurred at least in the agamid lineage. Our data from a reptile species provide further evidence to support the transpositional model for the evolution of β-globin gene cluster in amniotes.

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

PubMed Central

2011-01-01

Background 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. Methods 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. Results 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. Conclusion 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. PMID:22044755

Clinical evaluation of a novel population-based regression analysis for detecting glaucomatous visual field progression.

PubMed

Kovalska, M P; Bürki, E; Schoetzau, A; Orguel, S F; Orguel, S; Grieshaber, M C

2011-04-01

The distinction of real progression from test variability in visual field (VF) series may be based on clinical judgment, on trend analysis based on follow-up of test parameters over time, or on identification of a significant change related to the mean of baseline exams (event analysis). The aim of this study was to compare a new population-based method (Octopus field analysis, OFA) with classic regression analyses and clinical judgment for detecting glaucomatous VF changes. 240 VF series of 240 patients with at least 9 consecutive examinations available were included into this study. They were independently classified by two experienced investigators. The results of such a classification served as a reference for comparison for the following statistical tests: (a) t-test global, (b) r-test global, (c) regression analysis of 10 VF clusters and (d) point-wise linear regression analysis. 32.5 % of the VF series were classified as progressive by the investigators. The sensitivity and specificity were 89.7 % and 92.0 % for r-test, and 73.1 % and 93.8 % for the t-test, respectively. In the point-wise linear regression analysis, the specificity was comparable (89.5 % versus 92 %), but the sensitivity was clearly lower than in the r-test (22.4 % versus 89.7 %) at a significance level of p = 0.01. A regression analysis for the 10 VF clusters showed a markedly higher sensitivity for the r-test (37.7 %) than the t-test (14.1 %) at a similar specificity (88.3 % versus 93.8 %) for a significant trend (p = 0.005). In regard to the cluster distribution, the paracentral clusters and the superior nasal hemifield progressed most frequently. The population-based regression analysis seems to be superior to the trend analysis in detecting VF progression in glaucoma, and may eliminate the drawbacks of the event analysis. Further, it may assist the clinician in the evaluation of VF series and may allow better visualization of the correlation between function and structure owing to VF clusters. © Georg Thieme Verlag KG Stuttgart · New York.

Screen-based media use clusters are related to other activity behaviours and health indicators in adolescents

PubMed Central

2013-01-01

Background Screen-based media (SBM) occupy a considerable portion of young peoples’ discretionary leisure time. The aim of this paper was to investigate whether distinct clusters of SBM use exist, and if so, to examine the relationship of any identified clusters with other activity/sedentary behaviours and physical and mental health indicators. Methods The data for this study come from 643 adolescents, aged 14 years, who were participating in the longitudinal Western Australian Pregnancy Cohort (Raine) Study through May 2003 to June 2006. Time spent on SBM, phone use and reading was assessed using the Multimedia Activity Recall for Children and Adults. Height, weight, muscle strength were measured at a clinic visit and the adolescents also completed questionnaires on their physical activity and psychosocial health. Latent class analysis (LCA) was used to analyse groupings of SBM use. Results Three clusters of SBM use were found; C1 ‘instrumental computer users’ (high email use, general computer use), C2 ‘multi-modal e-gamers’ (both high console and computer game use) and C3 ‘computer e-gamers’ (high computer game use only). Television viewing was moderately high amongst all the clusters. C2 males took fewer steps than their male peers in C1 and C3 (-13,787/week, 95% CI: -4619 to -22957, p = 0.003 and -14,806, 95% CI: -5,306 to -24,305, p = 0.002) and recorded less MVPA than the C1 males (-3.5 h, 95% CI: -1.0 to -5.9, p = 0.005). There was no difference in activity levels between females in clusters C1 and C3. Conclusion SBM use by adolescents did cluster and these clusters related differently to activity/sedentary behaviours and both physical and psychosocial health indicators. It is clear that SBM use is not a single construct and future research needs to take consideration of this if it intends to understand the impact SBM has on health. PMID:24330626

Spatial overlap links seemingly unconnected genotype-matched TB cases in rural Uganda

PubMed Central

Kato-Maeda, Midori; Emperador, Devy M.; Wandera, Bonnie; Mugagga, Olive; Crandall, John; Janes, Michael; Marquez, Carina; Kamya, Moses R.; Charlebois, Edwin D.; Havlir, Diane V.

2018-01-01

Introduction Incomplete understanding of TB transmission dynamics in high HIV prevalence settings remains an obstacle for prevention. Understanding where transmission occurs could provide a platform for case finding and interrupting transmission. Methods From 2012–2015, we sought to recruit all adults starting TB treatment in a Ugandan community. Participants underwent household (HH) contact investigation, and provided names of social contacts, sites of work, healthcare and socializing, and two sputum samples. Mycobacterium tuberculosis culture-positive specimens underwent 24-loci MIRU-VNTR and spoligotyping. We sought to identify epidemiologic links between genotype-matched cases by analyzing social networks and mapping locations where cases reported spending ≥12 hours over the one-month pre-treatment. Sites of spatial overlap (≤100m) between genotype-matched cases were considered potential transmission sites. We analyzed social networks stratified by genotype clustering status, with cases linked by shared locations, and compared network density by location type between clustered vs. non-clustered cases. Results Of 173 adults with TB, 131 (76%) were enrolled, 108 provided sputum, and 84/131 (78%) were MTB culture-positive: 52% (66/131) tested HIV-positive. Of 118 adult HH contacts, 105 (89%) were screened and 3 (2.5%) diagnosed with active TB. Overall, 33 TB cases (39%) belonged to 15 distinct MTB genotype-matched clusters. Within each cluster, no cases shared a HH or reported shared non-HH contacts. In 6/15 (40%) clusters, potential epidemiologic links were identified by spatial overlap at specific locations: 5/6 involved health care settings. Genotype-clustered TB social networks had significantly greater network density based on shared clinics (p<0.001) and decreased density based on shared marketplaces (p<0.001), compared to non-clustered networks. Conclusions In this molecular epidemiologic study, links between MTB genotype-matched cases were only identifiable via shared locations, healthcare locations in particular, rather than named contacts. This suggests most transmission is occurring between casual contacts, and emphasizes the need for improved infection control in healthcare settings in rural Africa. PMID:29438413

Keeping the ball rolling: fullerene-like molecular clusters.

PubMed

Kong, Xiang-Jian; Long, La-Sheng; Zheng, Zhiping; Huang, Rong-Bin; Zheng, Lan-Sun

2010-02-16

The discovery of fullerenes in 1985 opened a new chapter in the chemistry of highly symmetric molecules. Fullerene-like metal clusters, characterized by (multi)shell-like structures, are one rapidly developing class of molecules that share this shape. In addition to creating aesthetically pleasing molecular structures, the ordered arrangement of metal atoms within such frameworks provides the opportunity to develop materials with properties not readily achieved in corresponding mononuclear or lower-nuclearity complexes. In this Account, we survey the great variety of fullerene-like metal-containing clusters with an emphasis on their synthetic and structural chemistry, a first step in the discussion of this fascinating field of cluster chemistry. We group the compounds of interest into three categories based on the atomic composition of the cluster core: those with formal metal-metal bonding, those characterized by ligand participation, and those supported by polyoxometalate building blocks. The number of clusters in the first group, containing metal-metal bonds, is relatively small. However, because of the unique and complex bonding scenarios observed for some of these species, these metalloid clusters present a number of research questions with significant ramifications. Because these cores contain molecular clusters of precious metals at the nanoscale, they offer an opportunity to study chemical properties at size ranges from the molecular to nanoscale and to gain insights into the electronic structures and properties of nanomaterials of similar chemical compositions. Clusters of the second type, whose core structures are facilitated by ligand participation, could aid in the development of functional materials. Of particular interest are the magnetic clusters containing both transition and lanthanide elements. A series of such heterometallic clusters that we prepared demonstrates diverse magnetic properties including antiferromagnetism, ferrimagnetism, and ferromagnetism. Considering the diversity of their composition, their distinct electronic structures, and the disparate coordination behaviors of the different metal elements, these materials suggest abundant opportunities for designing multifunctional materials with varied structures. The third type of clusters that we discuss are based on polyoxometalates, in particular those containing pentagonal units. However, unlike in fullerene chemistry, which does not allow the use of discrete pentagonal building blocks, the metal oxide-based pentagonal units can be used as fundamental building blocks for constructing various Keplerate structures. These structures also have a variety of functions, including intriguing magnetic properties in some cases. Coupled with different linking groups, such pentagonal units can be used for the assembly of a large number of spherical molecules whose properties can be tuned and optimized. Although this Account focuses on the topological aspects of fullerene-like metal clusters, we hope that this topical review will stimulate more efforts in the exploratory synthesis of new fullerene-like clusters. More importantly, we hope that further study of the bonding interactions and properties of these molecules will lead to the development of new functional materials.

UV laser photoactivation of hexachloroplatinate bound to individual nucleobases in vacuo as molecular level probes of a model photopharmaceutical.

PubMed

Matthews, Edward; Sen, Ananya; Yoshikawa, Naruo; Bergström, Ed; Dessent, Caroline E H

2016-06-01

Isolated molecular clusters of adenine, cytosine, thymine and uracil bound to hexachloroplatinate, PtCl6(2-), have been studied using laser electronic photodissociation spectroscopy to investigate photoactivation of a platinum complex in the vicinity of a nucleobase. These metal complex-nucleobase clusters represent model systems for identifying the fundamental photochemical processes occurring in photodynamic platinum drug therapies that target DNA. This is the first study to explore the specific role of a strongly photoactive platinum compound in the aggregate complex. Each of the clusters studied displays a broadly similar absorption spectra, with a strong λmax ∼ 4.6 eV absorption band and a subsequent increase in the absorption intensity towards higher spectral-energy. The absorption bands are traced to ligand-to-metal-charge-transfer excitations on the PtCl6(2-) moiety within the cluster, and result in Cl(-)·nucleobase and PtCl5(-) as primary photofragments. These results demonstrate how selective photoexcitation can drive distinctive photodecay channels for a model photo-pharmaceutical. In addition, cluster absorption due to excitation of nucleobase-centred chromophores is observed in the region around 5 eV. For the uracil cluster, photofragments consistent with ultrafast decay of the excited state and vibrational predissociation on the ground-state surface are observed. However, this decay channel becomes successively weaker on going from thymine to cytosine to adenine, due to differential coupling of the excited states to the electron detachment continuum. These effects demonstrate the distinctive photophysical characteristics of the different nucleobases, and are discussed in the context of the recently recorded photoelectron spectra of theses clusters.

Dyspnea descriptors translated from English to Portuguese: application in obese patients and in patients with cardiorespiratory diseases.

PubMed

Teixeira, Christiane Aires; Rodrigues Júnior, Antonio Luiz; Straccia, Luciana Cristina; Vianna, Elcio Dos Santos Oliveira; Silva, Geruza Alves da; Martinez, José Antônio Baddini

2011-01-01

To investigate the usefulness of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors) that were developed in English and translated to Brazilian Portuguese in patients with four distinct clinical conditions that can be accompanied by dyspnea. We translated, from English to Brazilian Portuguese, a list of 15 dyspnea descriptors reported in a study conducted in the USA. Those 15 descriptors were applied in 50 asthma patients, 50 COPD patients, 30 patients with heart failure, and 50 patients with class II or III obesity. The three best descriptors, as selected by the patients, were studied by cluster analysis. Potential associations between the identified clusters and the four clinical conditions were also investigated. The use of this set of descriptors led to a solution with nine clusters, designated expiração (exhalation), fome de ar (air hunger), sufoco (suffocating), superficial (shallow), rápido (rapid), aperto (tight), falta de ar (shortness of breath), trabalho (work), and inspiração (inhalation). Overlapping of the descriptors was quite common among the patients, regardless of their clinical condition. Asthma, COPD, and heart failure were significantly associated with the inspiração cluster. Heart failure was also associated with the trabalho cluster, whereas obesity was not associated with any of the clusters. In our study sample, the application of dyspnea descriptors translated from English to Portuguese led to the identification of distinct clusters, some of which were similar to those identified in a study conducted in the USA. The translated descriptors were less useful than were those developed in Brazil regarding their ability to generate significant associations among the clinical conditions investigated here.

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

PubMed Central

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

2015-01-01

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

Pain Sensitivity Subgroups in Individuals With Spine Pain: Potential Relevance to Short-Term Clinical Outcome

PubMed Central

Bialosky, Joel E.; Robinson, Michael E.

2014-01-01

Background Cluster analysis can be used to identify individuals similar in profile based on response to multiple pain sensitivity measures. There are limited investigations into how empirically derived pain sensitivity subgroups influence clinical outcomes for individuals with spine pain. Objective The purposes of this study were: (1) to investigate empirically derived subgroups based on pressure and thermal pain sensitivity in individuals with spine pain and (2) to examine subgroup influence on 2-week clinical pain intensity and disability outcomes. Design A secondary analysis of data from 2 randomized trials was conducted. Methods Baseline and 2-week outcome data from 157 participants with low back pain (n=110) and neck pain (n=47) were examined. Participants completed demographic, psychological, and clinical information and were assessed using pain sensitivity protocols, including pressure (suprathreshold pressure pain) and thermal pain sensitivity (thermal heat threshold and tolerance, suprathreshold heat pain, temporal summation). A hierarchical agglomerative cluster analysis was used to create subgroups based on pain sensitivity responses. Differences in data for baseline variables, clinical pain intensity, and disability were examined. Results Three pain sensitivity cluster groups were derived: low pain sensitivity, high thermal static sensitivity, and high pressure and thermal dynamic sensitivity. There were differences in the proportion of individuals meeting a 30% change in pain intensity, where fewer individuals within the high pressure and thermal dynamic sensitivity group (adjusted odds ratio=0.3; 95% confidence interval=0.1, 0.8) achieved successful outcomes. Limitations Only 2-week outcomes are reported. Conclusions Distinct pain sensitivity cluster groups for individuals with spine pain were identified, with the high pressure and thermal dynamic sensitivity group showing worse clinical outcome for pain intensity. Future studies should aim to confirm these findings. PMID:24764070

History, geography and host use shape genomewide patterns of genetic variation in the redheaded pine sawfly (Neodiprion lecontei).

PubMed

Bagley, Robin K; Sousa, Vitor C; Niemiller, Matthew L; Linnen, Catherine R

2017-02-01

Divergent host use has long been suspected to drive population differentiation and speciation in plant-feeding insects. Evaluating the contribution of divergent host use to genetic differentiation can be difficult, however, as dispersal limitation and population structure may also influence patterns of genetic variation. In this study, we use double-digest restriction-associated DNA (ddRAD) sequencing to test the hypothesis that divergent host use contributes to genetic differentiation among populations of the redheaded pine sawfly (Neodiprion lecontei), a widespread pest that uses multiple Pinus hosts throughout its range in eastern North America. Because this species has a broad range and specializes on host plants known to have migrated extensively during the Pleistocene, we first assess overall genetic structure using model-based and model-free clustering methods and identify three geographically distinct genetic clusters. Next, using a composite-likelihood approach based on the site frequency spectrum and a novel strategy for maximizing the utility of linked RAD markers, we infer the population topology and date divergence to the Pleistocene. Based on existing knowledge of Pinus refugia, estimated demographic parameters and patterns of diversity among sawfly populations, we propose a Pleistocene divergence scenario for N. lecontei. Finally, using Mantel and partial Mantel tests, we identify a significant relationship between genetic distance and geography in all clusters, and between genetic distance and host use in two of three clusters. Overall, our results indicate that Pleistocene isolation, dispersal limitation and ecological divergence all contribute to genomewide differentiation in this species and support the hypothesis that host use is a common driver of population divergence in host-specialized insects. © 2016 John Wiley & Sons Ltd.

Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data.

PubMed

Menon, Vilas

2017-12-11

Advances in single-cell RNA-sequencing technology have resulted in a wealth of studies aiming to identify transcriptomic cell types in various biological systems. There are multiple experimental approaches to isolate and profile single cells, which provide different levels of cellular and tissue coverage. In addition, multiple computational strategies have been proposed to identify putative cell types from single-cell data. From a data generation perspective, recent single-cell studies can be classified into two groups: those that distribute reads shallowly over large numbers of cells and those that distribute reads more deeply over a smaller cell population. Although there are advantages to both approaches in terms of cellular and tissue coverage, it is unclear whether different computational cell type identification methods are better suited to one or the other experimental paradigm. This study reviews three cell type clustering algorithms, each representing one of three broad approaches, and finds that PCA-based algorithms appear most suited to low read depth data sets, whereas gene clustering-based and biclustering algorithms perform better on high read depth data sets. In addition, highly related cell classes are better distinguished by higher-depth data, given the same total number of reads; however, simultaneous discovery of distinct and similar types is better served by lower-depth, higher cell number data. Overall, this study suggests that the depth of profiling should be determined by initial assumptions about the diversity of cells in the population, and that the selection of clustering algorithm(s) is subsequently based on the depth of profiling will allow for better identification of putative transcriptomic cell types. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The Everyday Moral Judge - Autobiographical Recollections of Moral Emotions.

PubMed

Körner, André; Tscharaktschiew, Nadine; Schindler, Rose; Schulz, Katrin; Rudolph, Udo

2016-01-01

Moral emotions are typically elicited in everyday social interactions and regulate social behavior. Previous research in the field of attribution theory identified ought (the moral standard of a given situation or intended goal), goal-attainment (a goal can be attained vs. not attained) and effort (high vs. low effort expenditure) as cognitive antecedents of moral emotions. In contrast to earlier studies, mainly relying on thought experiments, we investigated autobiographical recollections of N = 312 participants by means of an online study. We analyzed a diverse range of moral emotions, i.e., admiration, anger, contempt, indignation, pride, respect, schadenfreude, and sympathy, by using a mixed-method approach. Qualitative and quantitative methods clearly corroborate the important role of ought, goal-attainment, and effort as eliciting conditions of moral emotions. Furthermore, we built categorical systems based on our participants' descriptions of real-life situations, allowing for more fine-grained distinctions between seemingly similar moral emotions. We thus identify additional prerequisites explaining more subtle differences between moral emotion clusters as they emerge from our analyses (i.e., cluster 1: admiration, pride, and respect; cluster 2: anger, contempt, and indignation; cluster 3: schadenfreude and sympathy). Results are discussed in the light of attributional theories of moral emotions, and implications for future research are derived.

Internal working models and adjustment of physically abused children: the mediating role of self-regulatory abilities.

PubMed

Hawkins, Amy L; Haskett, Mary E

2014-01-01

Abused children's internal working models (IWM) of relationships are known to relate to their socioemotional adjustment, but mechanisms through which negative representations increase vulnerability to maladjustment have not been explored. We sought to expand the understanding of individual differences in IWM of abused children and investigate the mediating role of self-regulation in links between IWM and adjustment. Cluster analysis was used to subgroup 74 physically abused children based on their IWM. Internal working models were identified by children's representations, as measured by a narrative story stem task. Self-regulation was assessed by teacher report and a behavioral task, and adjustment was measured by teacher report. Cluster analyses indicated two subgroups of abused children with distinct patterns of IWMs. Cluster membership predicted internalizing and externalizing problems. Associations between cluster membership and adjustment were mediated by children's regulation, as measured by teacher reports of many aspects of regulation. There was no support for mediation when regulation was measured by a behavioral task that tapped more narrow facets of regulation. Abused children exhibit clinically relevant individual differences in their IWMs; these models are linked to adjustment in the school setting, possibly through children's self-regulation. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Clustering of trauma and associations with single and co-occurring depression and panic attack over twenty years.

PubMed

McCutcheon, Vivia V; Heath, Andrew C; Nelson, Elliot C; Bucholz, Kathleen K; Madden, Pamela A F; Martin, Nicholas G

2010-02-01

Individuals who experience one type of trauma often experience other types, yet few studies have examined the clustering of trauma. This study examines the clustering of traumatic events and associations of trauma with risk for single and co-occurring major depressive disorder (MDD) and panic attack for 20 years after first trauma. Lifetime histories of MDD, panic attack, and traumatic events were obtained from participants in an Australian twin sample. Latent class analysis was used to derive trauma classes based on each respondent's trauma history. Associations of the resulting classes and of parental alcohol problems and familial effects with risk for a first onset of single and co-occurring MDD and panic attack were examined from the year of first trauma to 20 years later. Traumatic events clustered into three distinct classes characterized by endorsement of little or no trauma, primarily nonassaultive, and primarily assaultive events. Individuals in the assaultive class were characterized by a younger age at first trauma, a greater number of traumatic events, and high rates of parental alcohol problems. Members of the assaultive trauma class had the strongest and most enduring risk for single and co-occurring lifetime MDD and panic attack. Assaultive trauma outweighed associations of familial effects and nonassaultive trauma with risk for 10 years following first trauma.

The Everyday Moral Judge – Autobiographical Recollections of Moral Emotions

PubMed Central

Tscharaktschiew, Nadine; Schindler, Rose; Schulz, Katrin; Rudolph, Udo

2016-01-01

Moral emotions are typically elicited in everyday social interactions and regulate social behavior. Previous research in the field of attribution theory identified ought (the moral standard of a given situation or intended goal), goal-attainment (a goal can be attained vs. not attained) and effort (high vs. low effort expenditure) as cognitive antecedents of moral emotions. In contrast to earlier studies, mainly relying on thought experiments, we investigated autobiographical recollections of N = 312 participants by means of an online study. We analyzed a diverse range of moral emotions, i.e., admiration, anger, contempt, indignation, pride, respect, schadenfreude, and sympathy, by using a mixed-method approach. Qualitative and quantitative methods clearly corroborate the important role of ought, goal-attainment, and effort as eliciting conditions of moral emotions. Furthermore, we built categorical systems based on our participants’ descriptions of real-life situations, allowing for more fine-grained distinctions between seemingly similar moral emotions. We thus identify additional prerequisites explaining more subtle differences between moral emotion clusters as they emerge from our analyses (i.e., cluster 1: admiration, pride, and respect; cluster 2: anger, contempt, and indignation; cluster 3: schadenfreude and sympathy). Results are discussed in the light of attributional theories of moral emotions, and implications for future research are derived. PMID:27977699

Morphology of size-selected Ptn clusters on CeO2(111)

NASA Astrophysics Data System (ADS)

Shahed, Syed Mohammad Fakruddin; Beniya, Atsushi; Hirata, Hirohito; Watanabe, Yoshihide

2018-03-01

Supported Pt catalysts and ceria are well known for their application in automotive exhaust catalysts. Size-selected Pt clusters supported on a CeO2(111) surface exhibit distinct physical and chemical properties. We investigated the morphology of the size-selected Ptn (n = 5-13) clusters on a CeO2(111) surface using scanning tunneling microscopy at room temperature. Ptn clusters prefer a two-dimensional morphology for n = 5 and a three-dimensional (3D) morphology for n ≥ 6. We further observed the preference for a 3D tri-layer structure when n ≥ 10. For each cluster size, we quantitatively estimated the relative fraction of the clusters for each type of morphology. Size-dependent morphology of the Ptn clusters on the CeO2(111) surface was attributed to the Pt-Pt interaction in the cluster and the Pt-O interaction between the cluster and CeO2(111) surface. The results obtained herein provide a clear understanding of the size-dependent morphology of the Ptn clusters on a CeO2(111) surface.

Morphology of size-selected Ptn clusters on CeO2(111).

PubMed

Shahed, Syed Mohammad Fakruddin; Beniya, Atsushi; Hirata, Hirohito; Watanabe, Yoshihide

2018-03-21

Supported Pt catalysts and ceria are well known for their application in automotive exhaust catalysts. Size-selected Pt clusters supported on a CeO 2 (111) surface exhibit distinct physical and chemical properties. We investigated the morphology of the size-selected Pt n (n = 5-13) clusters on a CeO 2 (111) surface using scanning tunneling microscopy at room temperature. Pt n clusters prefer a two-dimensional morphology for n = 5 and a three-dimensional (3D) morphology for n ≥ 6. We further observed the preference for a 3D tri-layer structure when n ≥ 10. For each cluster size, we quantitatively estimated the relative fraction of the clusters for each type of morphology. Size-dependent morphology of the Pt n clusters on the CeO 2 (111) surface was attributed to the Pt-Pt interaction in the cluster and the Pt-O interaction between the cluster and CeO 2 (111) surface. The results obtained herein provide a clear understanding of the size-dependent morphology of the Pt n clusters on a CeO 2 (111) surface.

A measurement of CMB cluster lensing with SPT and DES year 1 data

NASA Astrophysics Data System (ADS)

Baxter, E. J.; Raghunathan, S.; Crawford, T. M.; Fosalba, P.; Hou, Z.; Holder, G. P.; Omori, Y.; Patil, S.; Rozo, E.; Abbott, T. M. C.; Annis, J.; Aylor, K.; Benoit-Lévy, A.; Benson, B. A.; Bertin, E.; Bleem, L.; Buckley-Geer, E.; Burke, D. L.; Carlstrom, J.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Chang, C. L.; Cho, H.-M.; Crites, A. T.; Crocce, M.; Cunha, C. E.; da Costa, L. N.; D'Andrea, C. B.; Davis, C.; de Haan, T.; Desai, S.; Dietrich, J. P.; Dobbs, M. A.; Dodelson, S.; Doel, P.; Drlica-Wagner, A.; Estrada, J.; Everett, W. B.; Fausti Neto, A.; Flaugher, B.; Frieman, J.; García-Bellido, J.; George, E. M.; Gaztanaga, E.; Giannantonio, T.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Halverson, N. W.; Harrington, N. L.; Hartley, W. G.; Holzapfel, W. L.; Honscheid, K.; Hrubes, J. D.; Jain, B.; James, D. J.; Jarvis, M.; Jeltema, T.; Knox, L.; Krause, E.; Kuehn, K.; Kuhlmann, S.; Kuropatkin, N.; Lahav, O.; Lee, A. T.; Leitch, E. M.; Li, T. S.; Lima, M.; Luong-Van, D.; Manzotti, A.; March, M.; Marrone, D. P.; Marshall, J. L.; Martini, P.; McMahon, J. J.; Melchior, P.; Menanteau, F.; Meyer, S. S.; Miller, C. J.; Miquel, R.; Mocanu, L. M.; Mohr, J. J.; Natoli, T.; Nord, B.; Ogando, R. L. C.; Padin, S.; Plazas, A. A.; Pryke, C.; Rapetti, D.; Reichardt, C. L.; Romer, A. K.; Roodman, A.; Ruhl, J. E.; Rykoff, E.; Sako, M.; Sanchez, E.; Sayre, J. T.; Scarpine, V.; Schaffer, K. K.; Schindler, R.; Schubnell, M.; Sevilla-Noarbe, I.; Shirokoff, E.; Smith, M.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Staniszewski, Z.; Stark, A.; Story, K.; Suchyta, E.; Tarle, G.; Thomas, D.; Troxel, M. A.; Vanderlinde, K.; Vieira, J. D.; Walker, A. R.; Williamson, R.; Zhang, Y.; Zuntz, J.

2018-05-01

Clusters of galaxies gravitationally lens the cosmic microwave background (CMB) radiation, resulting in a distinct imprint in the CMB on arcminute scales. Measurement of this effect offers a promising way to constrain the masses of galaxy clusters, particularly those at high redshift. We use CMB maps from the South Pole Telescope Sunyaev-Zel'dovich (SZ) survey to measure the CMB lensing signal around galaxy clusters identified in optical imaging from first year observations of the Dark Energy Survey. The cluster catalogue used in this analysis contains 3697 members with mean redshift of \\bar{z} = 0.45. We detect lensing of the CMB by the galaxy clusters at 8.1σ significance. Using the measured lensing signal, we constrain the amplitude of the relation between cluster mass and optical richness to roughly 17 {per cent} precision, finding good agreement with recent constraints obtained with galaxy lensing. The error budget is dominated by statistical noise but includes significant contributions from systematic biases due to the thermal SZ effect and cluster miscentring.

Ab initio investigation on hydrogen adsorption capability in Zn and Cu-based metal organic frameworks

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

Tanuwijaya, V. V., E-mail: viny.veronika@gmail.com; Hidayat, N. N., E-mail: avantgarde.vee@gmail.com; Agusta, M. K., E-mail: kemal@fti.itb.ac.id

2015-09-30

One of the biggest challenge in material technology for hydrogen storage application is to increase hydrogen uptake in room temperature and pressure. As a class of highly porous material, Metal-Organic Frameworks (MOF) holds great potential with its tunable structure. However, little is known about the effect of metal cluster to its hydrogen storage capability. Investigation on this matter has been carried out carefully on small cluster of Zn and Cu-based MOF using first principles method. The calculation of two distinct building units of MOFs, namely octahedral and paddle-wheel models, have been done with B3LYP density functional method using 6-31G(d,p) andmore » LANL2DZ basis sets. From geometry optimization of Zn-based MOF linked by benzene-dicarboxylate (MOF-5), it is found that hydrogen tends to keep distance from metal cluster group and stays above benzene ring. In the other hand, hydrogen molecule prefers to stay atop of the exposed Cu atom in Cu-based MOF system linked by the same linker group (Cu-bdc). Calculated hydrogen binding enthalpies for Zn and Cu octahedral cages at ZnO{sub 3} sites are 1.64kJ/mol and 2.73kJ/mol respectively, while hydrogen binding enthalpies for Zn and Cu paddle-wheel cages calculated on top of metal atoms are found to be at 6.05kJ/mol and 6.10kJ/mol respectively. Major difference between Zn-MOF-5 and Cu-bdc hydrogen uptake performance might be caused by unsaturated metal sites present in Cu-bdc system and the influence of their geometric structures, although a small difference on binding energy in the type of transition metal used is also observed. The comparison between Zn and Cu-based MOF may contribute to a comprehensive understanding of metal clusters and the importance of selecting best transition metal for design and synthesis of metal-organic frameworks.« less

Metabolite profiling approach reveals the interface of primary and secondary metabolism in colored cauliflowers (Brassica oleracea L. ssp. botrytis).

PubMed

Park, Soo-Yun; Lim, Sun-Hyung; Ha, Sun-Hwa; Yeo, Yunsoo; Park, Woo Tae; Kwon, Do Yeon; Park, Sang Un; Kim, Jae Kwang

2013-07-17

In the present study, carotenoids, anthocyanins, and phenolic acids of cauliflowers ( Brassica oleracea L. ssp. botrytis) with various colored florets (white, yellow, green, and purple) were characterized to determine their phytochemical diversity. Additionally, 48 metabolites comprising amino acids, organic acids, sugars, and sugar alcohols were identified using gas chromatography-time-of-flight mass spectrometry (GC-TOFMS). Carotenoid content was considerably higher in green cauliflower; anthocyanins were detected only in purple cauliflower. Phenolic acids were higher in both green and purple cauliflower. Results of partial least-squares discriminant, Pearson correlation, and hierarchical clustering analyses showed that green cauliflower is distinct on the basis of the high levels of amino acids and clusters derived from common or closely related biochemical pathways. These results suggest that GC-TOFMS-based metabolite profiling, combined with chemometrics, is a useful tool for determining phenotypic variation and identifying metabolic networks connecting primary and secondary metabolism.

Molecular phylogeny of edge hill virus supports its position in the yellow Fever virus group and identifies a new genetic variant.

PubMed

Macdonald, Joanne; Poidinger, Michael; Mackenzie, John S; Russell, Richard C; Doggett, Stephen; Broom, Annette K; Phillips, Debra; Potamski, Joseph; Gard, Geoff; Whelan, Peter; Weir, Richard; Young, Paul R; Gendle, Debra; Maher, Sheryl; Barnard, Ross T; Hall, Roy A

2010-06-15

Edge Hill virus (EHV) is a mosquito-borne flavivirus isolated throughout Australia during mosquito surveillance programs. While not posing an immediate threat to the human population, EHV is a taxonomically interesting flavivirus since it remains the only member of the yellow fever virus (YFV) sub-group to be detected within Australia. Here we present both an antigenic and genetic investigation of collected isolates, and confirm taxonomic classification of the virus within the YFV-group. Isolates were not clustered based on geographical origin or time of isolation, suggesting that minimal genetic evolution of EHV has occurred over geographic distance or time within the EHV cluster. However, two isolates showed significant differences in antigenic reactivity patterns, and had a much larger divergence from the EHV prototype (19% nucleotide and 6% amino acid divergence), indicating a distinct subtype or variant within the EHV subgroup.

Level crossings and zero-field splitting in the {Cr8}-cubane spin cluster studied using inelastic neutron scattering and magnetization

NASA Astrophysics Data System (ADS)

Vaknin, D.; Garlea, V. O.; Demmel, F.; Mamontov, E.; Nojiri, H.; Martin, C.; Chiorescu, I.; Qiu, Y.; Kögerler, P.; Fielden, J.; Engelhardt, L.; Rainey, C.; Luban, M.

2010-11-01

Inelastic neutron scattering (INS) in variable magnetic field and high-field magnetization measurements in the millikelvin temperature range were performed to gain insight into the low-energy magnetic excitation spectrum and the field-induced level crossings in the molecular spin cluster {Cr8}-cubane. These complementary techniques provide consistent estimates of the lowest level-crossing field. The overall features of the experimental data are explained using an isotropic Heisenberg model, based on three distinct exchange interactions linking the eight CrIII paramagnetic centers (spins s = 3/2), that is supplemented with a relatively large molecular magnetic anisotropy term for the lowest S = 1 multiplet. It is noted that the existence of the anisotropy is clearly evident from the magnetic field dependence of the excitations in the INS measurements, while the magnetization measurements are not sensitive to its effects.

Level crossings and zero-field splitting in the {Cr8}-cubane spin-cluster studied using inelastic neutron scattering and magnetization

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

Vaknin, D.; Garlea, Vasile O; Demmel, F.

Inelastic neutron scattering (INS) in variable magnetic field and high-field magnetization measurements in the millikelvin temperature range were performed to gain insight into the low-energy magnetic excitation spectrum and the field-induced level crossings in the molecular spin cluster {Cr8}-cubane. These complementary techniques provide consistent estimates of the lowest level-crossing field. The overall features of the experimental data are explained using an isotropic Heisenberg model, based on three distinct exchange interactions linking the eight CrIII paramagnetic centers (spins s = 3/2), that is supplemented with a relatively large molecular magnetic anisotropy term for the lowest S = 1 multiplet. It ismore » noted that the existence of the anisotropy is clearly evident from the magnetic field dependence of the excitations in the INS measurements, while the magnetization measurements are not sensitive to its effects.« less

Weak-lensing mass calibration of redMaPPer galaxy clusters in Dark Energy Survey Science Verification data

DOE PAGES

Melchior, P.; Gruen, D.; McClintock, T.; ...

2017-05-16

Here, we use weak-lensing shear measurements to determine the mean mass of optically selected galaxy clusters in Dark Energy Survey Science Verification data. In a blinded analysis, we split the sample of more than 8000 redMaPPer clusters into 15 subsets, spanning ranges in the richness parameter 5 ≤ λ ≤ 180 and redshift 0.2 ≤ z ≤ 0.8, and fit the averaged mass density contrast profiles with a model that accounts for seven distinct sources of systematic uncertainty: shear measurement and photometric redshift errors; cluster-member contamination; miscentring; deviations from the NFW halo profile; halo triaxiality and line-of-sight projections.

Weak-lensing mass calibration of redMaPPer galaxy clusters in Dark Energy Survey Science Verification data

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

Melchior, P.; Gruen, D.; McClintock, T.

Here, we use weak-lensing shear measurements to determine the mean mass of optically selected galaxy clusters in Dark Energy Survey Science Verification data. In a blinded analysis, we split the sample of more than 8000 redMaPPer clusters into 15 subsets, spanning ranges in the richness parameter 5 ≤ λ ≤ 180 and redshift 0.2 ≤ z ≤ 0.8, and fit the averaged mass density contrast profiles with a model that accounts for seven distinct sources of systematic uncertainty: shear measurement and photometric redshift errors; cluster-member contamination; miscentring; deviations from the NFW halo profile; halo triaxiality and line-of-sight projections.

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

PubMed

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

2014-12-09

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

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

PubMed

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

2015-11-05

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

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®

Composition formulas of binary eutectics

PubMed Central

Ma, Y. P.; Dong, D. D.; Dong, C.; Luo, L. J.; Wang, Q.; Qiang, J. B.; Wang, Y. M.

2015-01-01

The present paper addresses the long-standing composition puzzle of eutectic points by introducing a new structural tool for the description of short-range-order structural unit, the cluster-plus-glue-atom model. In this model, any structure is dissociated into a 1st-neighbor cluster and a few glue atoms between the clusters, expressed by a cluster formula [cluster]gluex. This model is applied here to establish the structural model for eutectic liquids, assuming that a eutectic liquid consist of two subunits issued from the relevant eutectic phases, each being expressed by the cluster formula for ideal metallic glasses, i.e., [cluster](glue atom)1 or 3. A structural unit is then composed of two clusters from the relevant eutectic phases plus 2, 4, or 6 glue atoms. Such a dual cluster formulism is well validated in all boron-containing (except those located by the extreme phase diagram ends) and in some commonly-encountered binary eutectics, within accuracies below 1 at.%. The dual cluster formulas vary extensively and are rarely identical even for eutectics of close compositions. They are generally formed with two distinctly different cluster types, with special cluster matching rules such as cuboctahedron plus capped trigonal prism and rhombidodecahedron plus octahedral antiprism. PMID:26658618

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

PubMed

Kanchanatawan, Buranee; Sriswasdi, Sira; Thika, Supaksorn; Stoyanov, Drozdstoy; Sirivichayakul, Sunee; Carvalho, André F; Geffard, Michel; Maes, Michael

2018-05-23

Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate classifications should be based on supervised and unsupervised learning rather than on consensus criteria. This study used machine learning as means to provide a more accurate classification of patients with stable phase schizophrenia. We found that using negative symptoms as discriminatory variables, schizophrenia patients may be divided into two distinct classes modelled by (A) impairments in IgA/IgM responses to noxious and generally more protective tryptophan catabolites, (B) impairments in episodic and semantic memory, paired associative learning and false memory creation, and (C) psychotic, excitation, hostility, mannerism, negative, and affective symptoms. The first cluster shows increased negative, psychotic, excitation, hostility, mannerism, depression and anxiety symptoms, and more neuroimmune and cognitive disorders and is therefore called "major neurocognitive psychosis" (MNP). The second cluster, called "simple neurocognitive psychosis" (SNP) is discriminated from normal controls by the same features although the impairments are less well developed than in MNP. The latter is additionally externally validated by lowered quality of life, body mass (reflecting a leptosome body type), and education (reflecting lower cognitive reserve). Previous distinctions including "type 1" (positive)/"type 2" (negative) and DSM-IV-TR (eg, paranoid) schizophrenia could not be validated using machine learning techniques. Previous names of the illness, including schizophrenia, are not very adequate because they do not describe the features of the illness, namely, interrelated neuroimmune, cognitive, and clinical features. Stable-phase schizophrenia consists of 2 relevant qualitatively distinct categories or nosological entities with SNP being a less well-developed phenotype, while MNP is the full blown phenotype or core illness. Major neurocognitive psychosis and SNP should be added to the DSM-5 and incorporated into the Research Domain Criteria project. © 2018 John Wiley & Sons, Ltd.

Design of double fuzzy clustering-driven context neural networks.

PubMed

Kim, Eun-Hu; Oh, Sung-Kwun; Pedrycz, Witold

2018-08-01

In this study, we introduce a novel category of double fuzzy clustering-driven context neural networks (DFCCNNs). The study is focused on the development of advanced design methodologies for redesigning the structure of conventional fuzzy clustering-based neural networks. The conventional fuzzy clustering-based neural networks typically focus on dividing the input space into several local spaces (implied by clusters). In contrast, the proposed DFCCNNs take into account two distinct local spaces called context and cluster spaces, respectively. Cluster space refers to the local space positioned in the input space whereas context space concerns a local space formed in the output space. Through partitioning the output space into several local spaces, each context space is used as the desired (target) local output to construct local models. To complete this, the proposed network includes a new context layer for reasoning about context space in the output space. In this sense, Fuzzy C-Means (FCM) clustering is useful to form local spaces in both input and output spaces. The first one is used in order to form clusters and train weights positioned between the input and hidden layer, whereas the other one is applied to the output space to form context spaces. The key features of the proposed DFCCNNs can be enumerated as follows: (i) the parameters between the input layer and hidden layer are built through FCM clustering. The connections (weights) are specified as constant terms being in fact the centers of the clusters. The membership functions (represented through the partition matrix) produced by the FCM are used as activation functions located at the hidden layer of the "conventional" neural networks. (ii) Following the hidden layer, a context layer is formed to approximate the context space of the output variable and each node in context layer means individual local model. The outputs of the context layer are specified as a combination of both weights formed as linear function and the outputs of the hidden layer. The weights are updated using the least square estimation (LSE)-based method. (iii) At the output layer, the outputs of context layer are decoded to produce the corresponding numeric output. At this time, the weighted average is used and the weights are also adjusted with the use of the LSE scheme. From the viewpoint of performance improvement, the proposed design methodologies are discussed and experimented with the aid of benchmark machine learning datasets. Through the experiments, it is shown that the generalization abilities of the proposed DFCCNNs are better than those of the conventional FCNNs reported in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characteristics of Brazilian Offenders and Victims of Interpersonal Violence: An Exploratory Study.

PubMed

d'Avila, Sérgio; Campos, Ana Cristina; Bernardino, Ítalo de Macedo; Cavalcante, Gigliana Maria Sobral; Nóbrega, Lorena Marques da; Ferreira, Efigênia Ferreira E

2016-10-01

The aim of this study was to characterize the profile of Brazilian offenders and victims of interpersonal violence, following a medicolegal and forensic perspective. A cross-sectional and exploratory study was performed in a Center of Forensic Medicine and Dentistry. The sample was made up of 1,704 victims of nonlethal interpersonal violence with some type of trauma. The victims were subject to forensic examinations by a criminal investigative team that identified and recorded the extent of the injuries. For data collection, a specific form was designed consisting of four parts according to the information provided in the medicolegal and social records: sociodemographic data of the victims, offender's characteristics, aggression characteristics, and types of injuries. Descriptive and multivariate statistics using cluster analysis (CA) were performed. The two-step cluster method was used to characterize the profile of the victims and offenders. Most of the events occurred during the nighttime (50.9%) and on weekdays (66.3%). Soft tissue injuries were the most prevalent type (94.6%). Based on the CA results, two clusters for the victims and two for the offenders were identified. Victims: Cluster 1 was formed typically by women, aged 30 to 59 years, and married; Cluster 2 was composed of men, aged 20 to 29 years, and unmarried. Offenders: Cluster 1 was characterized by men, who perpetrated violence in a community environment. Cluster 2 was formed by men, who perpetrated violence in the familiar environment. These findings revealed different risk groups with distinct characteristics for both victims and offenders, allowing the planning of targeted measures of care, prevention, and health promotion. This study assesses the profile of violence through morbidity data and significantly contributes to building an integrated system of health surveillance in Brazil, as well as linking police stations, forensic services, and emergency hospitals.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox.

PubMed

Basto, Mafalda P; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation.

Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003-2015): Implications for Prevention and Control Policies.

PubMed

Zhu, Bin; Liu, Jinlin; Fu, Yang; Zhang, Bo; Mao, Ying

2018-04-02

Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study aims to explore, visualize and compare the epidemiologic trends and spatial changing patterns of different types of viral hepatitis (A, B, C, E and unspecified, based on the classification of CDC) at the provincial level in China. The growth rates of incidence are used and converted to box plots to visualize the epidemiologic trends, with the linear trend being tested by chi-square linear by linear association test. Two complementary spatial cluster methods are used to explore the overall agglomeration level and identify spatial clusters: spatial autocorrelation analysis (measured by global and local Moran's I) and space-time scan analysis. Based on the spatial autocorrelation analysis, the hotspots of hepatitis A remain relatively stable and gradually shrunk, with Yunnan and Sichuan successively moving out the high-high (HH) cluster area. The HH clustering feature of hepatitis B in China gradually disappeared with time. However, the HH cluster area of hepatitis C has gradually moved towards the west, while for hepatitis E, the provincial units around the Yangtze River Delta region have been revealing HH cluster features since 2005. The space-time scan analysis also indicates the distinct spatial changing patterns of different types of viral hepatitis in China. It is easy to conclude that there is no one-size-fits-all plan for the prevention and control of viral hepatitis in all the provincial units. An effective response requires a package of coordinated actions, which should vary across localities regarding the spatial-temporal epidemic dynamics of each type of virus and the specific conditions of each provincial unit.

Successful ageing: A study of the literature using citation network analysis.

PubMed

Kusumastuti, Sasmita; Derks, Marloes G M; Tellier, Siri; Di Nucci, Ezio; Lund, Rikke; Mortensen, Erik Lykke; Westendorp, Rudi G J

2016-11-01

Ageing is accompanied by an increased risk of disease and a loss of functioning on several bodily and mental domains and some argue that maintaining health and functioning is essential for a successful old age. Paradoxically, studies have shown that overall wellbeing follows a curvilinear pattern with the lowest point at middle age but increases thereafter up to very old age. To shed further light on this paradox, we reviewed the existing literature on how scholars define successful ageing and how they weigh the contribution of health and functioning to define success. We performed a novel, hypothesis-free and quantitative analysis of citation networks exploring the literature on successful ageing that exists in the Web of Science Core Collection Database using the CitNetExplorer software. Outcomes were visualized using timeline-based citation patterns. The clusters and sub-clusters of citation networks identified were starting points for in-depth qualitative analysis. Within the literature from 1902 through 2015, two distinct citation networks were identified. The first cluster had 1146 publications and 3946 citation links. It focused on successful ageing from the perspective of older persons themselves. Analysis of the various sub-clusters emphasized the importance of coping strategies, psycho-social engagement, and cultural differences. The second cluster had 609 publications and 1682 citation links and viewed successful ageing based on the objective measurements as determined by researchers. Subsequent sub-clustering analysis pointed to different domains of functioning and various ways of assessment. In the current literature two mutually exclusive concepts of successful ageing are circulating that depend on whether the individual himself or an outsider judges the situation. These different points of view help to explain the disability paradox, as successful ageing lies in the eyes of the beholder. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox

PubMed Central

Basto, Mafalda P.; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W.; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation. PMID:26727497

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.

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Metabotyping for the development of tailored dietary advice solutions in a European population: the Food4Me study.

PubMed

O'Donovan, Clare B; Walsh, Marianne C; Woolhead, Clara; Forster, Hannah; Celis-Morales, Carlos; Fallaize, Rosalind; Macready, Anna L; Marsaux, Cyril F M; Navas-Carretero, Santiago; Rodrigo San-Cristobal, S; Kolossa, Silvia; Tsirigoti, Lydia; Mvrogianni, Christina; Lambrinou, Christina P; Moschonis, George; Godlewska, Magdalena; Surwillo, Agnieszka; Traczyk, Iwona; Drevon, Christian A; Daniel, Hannelore; Manios, Yannis; Martinez, J Alfredo; Saris, Wim H M; Lovegrove, Julie A; Mathers, John C; Gibney, Michael J; Gibney, Eileen R; Brennan, Lorraine

2017-10-01

Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.

Microsolvation of the potassium ion with aromatic rings: comparison between hexafluorobenzene and benzene.

PubMed

Marques, J M C; Llanio-Trujillo, J L; Albertí, M; Aguilar, A; Pirani, F

2013-08-22

We employ a recently developed methodology to study structural and energetic properties of the first solvation shells of the potassium ion in nonpolar environments due to aromatic rings, which is important to understand the selectivity of several biochemical phenomena. Our evolutionary algorithm is used in the global optimization study of clusters formed of K(+) solvated with hexafluorobenzene (HFBz) molecules. The global intermolecular interaction for these clusters has been decomposed in HFBz-HFBz and in K(+)-HFBz contributions, using a potential model based on different decompositions of the molecular polarizability of hexafluorobenzene. Putative global minimum structures of microsolvation clusters up to 21 hexafluorobenzene molecules were obtained and compared with the analogous K(+)-benzene clusters reported in our previous work (J. Phys. Chem. A 2012, 116, 4947-4956). We have found that both K(+)-(Bz)n and K(+)-(HFBz)n clusters show a strong magic number around the closure of the first solvation shell. Nonetheless, all K(+)-benzene clusters have essentially the same first solvation shell geometry with four solvent molecules around the ion, whereas the corresponding one for K(+)-(HFBz)n is completed with nine HFBz species, and its structural motif varies as n increases. This is attributed to the ion-solvent interaction that has a larger magnitude for K(+)-Bz than in the case of K(+)-HFBz. In addition, the ability of having more HFBz than Bz molecules around K(+) in the first solvation shell is intimately related to the inversion in the sign of the quadrupole moment of the two solvent species, which leads to a distinct ion-solvent geometry of approach.

Tumour-associated and non-tumour-associated microbiota in colorectal cancer

PubMed Central

Flemer, Burkhardt; Lynch, Denise B; Brown, Jillian M R; Jeffery, Ian B; Ryan, Feargal J; Claesson, Marcus J; O'Riordain, Micheal; Shanahan, Fergus; O'Toole, Paul W

2017-01-01

Objective A signature that unifies the colorectal cancer (CRC) microbiota across multiple studies has not been identified. In addition to methodological variance, heterogeneity may be caused by both microbial and host response differences, which was addressed in this study. Design We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR. Results The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes. Conclusions CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers. PMID:26992426

Influence of HLA-DR and -DQ alleles on autoantibody recognition of distinct epitopes within the juxtamembrane domain of the IA-2 autoantigen in type 1 diabetes.

PubMed

Richardson, Carolyn C; McLaughlin, Kerry A; Morgan, Diana; Feltbower, Richard G; Christie, Michael R

2016-02-01

Insulinoma-associated protein 2 (IA-2) is a major target of autoimmunity in type 1 diabetes. When first detected, IA-2-autoantibodies commonly bind epitopes in the juxtamembrane (JM) domain of IA-2 and antibody responses subsequently spread to the tyrosine phosphatase domain. Definition of structures of epitopes in the JM domain, and genetic requirements for autoimmunity to these epitopes, is important for our understanding of initiation and progression of autoimmunity. The aims of this study were to investigate the contribution of individual amino acids in the IA-2 JM domain to antibody binding to these epitopes and the role of HLA genotypes in determining epitope specificity. Regions of the JM domain recognised by autoantibodies were identified by peptide competition and inhibitory effects of alanine substitutions of residues within the JM region. Antibody binding was determined by radioligand binding assays using sera from patients genotyped for HLA-DRB1 and -DQB1 alleles. Patients were categorised into two distinct groups of JM antibody reactivity according to peptide inhibition. Inhibition by substitutions of individual amino acids within the JM domain differed between patients, indicating heterogeneity in epitope recognition. Cluster analysis defined six groups of residues having similar inhibitory effects on antibody binding, with three clusters showing differences in patients affected or unaffected by peptide. One cluster demonstrated significant differences in antibody binding between HLA-DRB1*04 and HLA-DRB1*07 patients and within DRB1*04 individuals; antibody recognition of a second cluster depended on expression of HLA-DQB1*0302. The results identify amino acids contributing to distinct epitopes on IA-2, with both HLA-DR and HLA-DQ alleles influencing epitope specificity.

Mapping disease-related missense mutations in the immunoglobulin-like fold domain of lamin A/C reveals novel genotype-phenotype associations for laminopathies.

PubMed

Scharner, Juergen; Lu, Hui-Chun; Fraternali, Franca; Ellis, Juliet A; Zammit, Peter S

2014-06-01

Mutations in A-type nuclear lamins cause laminopathies. However, genotype-phenotype correlations using the 340 missense mutations within the LMNA gene are unclear: partially due to the limited availability of three-dimensional structure. The immunoglobulin (Ig)-like fold domain has been solved, and using bioinformatics tools (including Polyphen-2, Fold X, Parameter OPtimized Surfaces, and PocketPicker) we characterized 56 missense mutations for position, surface exposure, change in charge and effect on Ig-like fold stability. We find that 21 of the 27 mutations associated with a skeletal muscle phenotype are distributed throughout the Ig-like fold, are nonsurface exposed and predicted to disrupt overall stability of the Ig-like fold domain. Intriguingly, the remaining 6 mutations clustered, had higher surface exposure, and did not affect stability. The majority of 9 lipodystrophy or 10 premature aging syndrome mutations also did not disrupt Ig-like fold domain stability and were surface exposed and clustered in distinct regions that overlap predicted binding pockets. Although buried, the 10 cardiac mutations had no other consistent properties. Finally, most lipodystrophy and premature aging mutations resulted in a -1 net charge change, whereas skeletal muscle mutations caused no consistent net charge changes. Since premature aging, lipodystrophy and the subset of 6 skeletal muscle mutations cluster tightly in distinct, charged regions, they likely affect lamin A/C -protein/DNA/RNA interactions: providing a consistent genotype-phenotype relationship for mutations in this domain. Thus, this subgroup of skeletal muscle laminopathies that we term the 'Skeletal muscle cluster', may have a distinct pathological mechanism. These novel associations refine the ability to predict clinical features caused by certain LMNA missense mutations. © 2013 Wiley Periodicals, Inc.

Cluster analysis reveals seasonal variation of sperm subpopulations in extended boar semen

PubMed Central

IBĂNESCU, Iulian; LEIDING, Claus; BOLLWEIN, Heinrich

2017-01-01

This study aimed to identify motile sperm subpopulations in extended boar semen and to observe the presumptive seasonal variation in their distribution. Data from 4837 boar ejaculates collected over a two-year period were analyzed in terms of kinematic parameters by Computer Assisted Sperm Analysis (CASA). Individual sperm data were used to determine subgroups of motile sperm within the ejaculates using cluster analysis. Four motile sperm subpopulations (SP) were identified, with distinct movement patterns: SP1 sperm with high velocity and high linearity; SP2 sperm with high velocity but low linearity; SP3 sperm with low velocity but high linearity; and SP4 sperm with low velocity and low linearity. SP1 constituted the least overall proportion within the ejaculates (P < 0.05). Season of semen collection significantly influenced the different proportions of sperm subpopulations. Spring was characterized by similar proportions of SP1 and SP4 (NS) and higher proportions of SP3. Summer brought a decrease in both subgroups containing fast sperm (SP1 and SP2) (P < 0.05). During autumn, increases in SP2 and SP4 were recorded. Winter substantially affected the proportions of all sperm subpopulations (P < 0.05) and SP2 became the most represented subgroup, while SP1 (fast and linear) reached its highest proportion compared to other seasons. In conclusion, extended boar semen is structured in distinct motile sperm subpopulations whose proportions vary according to the season of collection. Summer and autumn seem to have a negative impact on the fast and linear subpopulation. Cluster analysis can be useful in revealing differences in semen quality that are not normally detected by classical evaluation based on mean values. PMID:29081440

Unexpected nondenitrifier nitrous oxide reductase gene diversity and abundance in soils

PubMed Central

Sanford, Robert A.; Wagner, Darlene D.; Wu, Qingzhong; Chee-Sanford, Joanne C.; Thomas, Sara H.; Cruz-García, Claribel; Rodríguez, Gina; Massol-Deyá, Arturo; Krishnani, Kishore K.; Ritalahti, Kirsti M.; Nissen, Silke; Konstantinidis, Konstantinos T.; Löffler, Frank E.

2012-01-01

Agricultural and industrial practices more than doubled the intrinsic rate of terrestrial N fixation over the past century with drastic consequences, including increased atmospheric nitrous oxide (N2O) concentrations. N2O is a potent greenhouse gas and contributor to ozone layer destruction, and its release from fixed N is almost entirely controlled by microbial activities. Mitigation of N2O emissions to the atmosphere has been attributed exclusively to denitrifiers possessing NosZ, the enzyme system catalyzing N2O to N2 reduction. We demonstrate that diverse microbial taxa possess divergent nos clusters with genes that are related yet evolutionarily distinct from the typical nos genes of denitirifers. nos clusters with atypical nosZ occur in Bacteria and Archaea that denitrify (44% of genomes), do not possess other denitrification genes (56%), or perform dissimilatory nitrate reduction to ammonium (DNRA; (31%). Experiments with the DNRA soil bacterium Anaeromyxobacter dehalogenans demonstrated that the atypical NosZ is an effective N2O reductase, and PCR-based surveys suggested that atypical nosZ are abundant in terrestrial environments. Bioinformatic analyses revealed that atypical nos clusters possess distinctive regulatory and functional components (e.g., Sec vs. Tat secretion pathway in typical nos), and that previous nosZ-targeted PCR primers do not capture the atypical nosZ diversity. Collectively, our results suggest that nondenitrifying populations with a broad range of metabolisms and habitats are potentially significant contributors to N2O consumption. Apparently, a large, previously unrecognized group of environmental nosZ has not been accounted for, and characterizing their contributions to N2O consumption will advance understanding of the ecological controls on N2O emissions and lead to refined greenhouse gas flux models. PMID:23150571

Population structure and phylogeography of Toda buffalo in Nilgiris throw light on possible origin of aboriginal Toda tribe of South India.

PubMed

Kathiravan, P; Kataria, R S; Mishra, B P; Dubey, P K; Sadana, D K; Joshi, B K

2011-08-01

We report the genetic structure and evolutionary relationship of the endangered Toda buffalo of Nilgiris in South India with Kanarese and two other riverine buffalo breeds. The upgma phylogeny drawn using Nei's distance grouped South Kanara and Toda buffaloes at a single node while Marathwada and Murrah together formed a separate node. Principal component analysis was performed with pairwise interindividual chord distances which revealed clustering of Murrah and Marathwada buffaloes distinctly, while individuals of Toda and South Kanara breeds completely intermingled with each other. Furthermore, there were highly significant group variances (p < 0.01) when the breeds were grouped based on phylogeny, thus revealing the existence of cryptic genetic structure within these buffalo breeds. To know the evolutionary relationship among these breeds, 537-bp D-loop region of mitochondrial DNA was analysed. The phylogenetic analysis of mtDNA haplotypes following NJ algorithm with Chinese swamp buffalo as outgroup revealed a major cluster that included haplotypes from all the four investigated breeds and two minor clusters formed by South Kanara and Toda haplotypes. Reduced median network analysis revealed haplotypes of South Kanara and Toda to be quite distinct from the commonly found haplotypes indicating that these might have been ancestral to all the present-day haplotypes. Few mutations in two of the haplotypes of South Kanara buffalo were found to have contributed to ancestral haplotypes of Toda buffalo suggesting the possible migration of buffaloes from Kanarese region towards Nilgiris along the Western Ghats. Considering the close social, economic and cultural association of Todas with their buffaloes, the present study supports the theory of migration of Toda tribe from Kanarese/Mysore region along with their buffaloes. © 2011 Blackwell Verlag GmbH.

Aggregates and Superaggregates of Soot with Four Distinct Fractal Morphologies

NASA Technical Reports Server (NTRS)

Sorensen, C. M.; Kim, W.; Fry, D.; Chakrabarti, A.

2004-01-01

Soot formed in laminar diffusion flames of heavily sooting fuels evolves through four distinct growth stages which give rise to four distinct aggregate fractal morphologies. These results were inferred from large and small angle static light scattering from the flames, microphotography of the flames, and analysis of soot sampled from the flames. The growth stages occur approximately over four successive orders of magnitude in aggregate size. Comparison to computer simulations suggests that these four growth stages involve either diffusion limited cluster aggregation or percolation in either three or two dimensions.

Automated classification of dolphin echolocation click types from the Gulf of Mexico.

PubMed

Frasier, Kaitlin E; Roch, Marie A; Soldevilla, Melissa S; Wiggins, Sean M; Garrison, Lance P; Hildebrand, John A

2017-12-01

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso's dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori.

Automated classification of dolphin echolocation click types from the Gulf of Mexico

PubMed Central

Roch, Marie A.; Soldevilla, Melissa S.; Wiggins, Sean M.; Garrison, Lance P.; Hildebrand, John A.

2017-01-01

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso’s dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori. PMID:29216184

Trace Element Study of H Chondrites: Evidence for Meteoroid Streams.

NASA Astrophysics Data System (ADS)

Wolf, Stephen Frederic

1993-01-01

Multivariate statistical analyses, both linear discriminant analysis and logistic regression, of the volatile trace elemental concentrations in H4-6 chondrites reveal compositionally distinguishable subpopulations. Observed difference in volatile trace element composition between Antarctic and non-Antarctic H4-6 chondrites (Lipschutz and Samuels, 1991) can be explained by a compositionaily distinct subpopulation found in Victoria Land, Antarctica. This population of H4-6 chondrites is compositionally distinct from non-Antarctic H4-6 chondrites and from Antarctic H4 -6 chondrites from Queen Maud Land. Comparisons of Queen Maud Land H4-6 chondrites with non-Antarctic H4-6 chondrites do not give reason to believe that these two populations are distinguishable from each other on the basis of the ten volatile trace element concentrations measured. ANOVA indicates that these differences are not the result of trivial causes such as weathering and analytical bias. Thermoluminescence properties of these populations parallels the results of volatile trace element comparisons. Given the differences in terrestrial age between Victoria Land, Queen Maud Land, and modern H4-6 chondrite falls, these results are consistent with a variation in H4-6 chondrite flux on a 300 ky timescale. This conclusion requires the existence of co-orbital meteoroid streams. Statistical analyses of the volatile trace elemental concentrations in non-Antarctic modern falls of H4-6 chondrites also demonstrate that a group of 13 H4-6 chondrites, Cluster 1, selected exclusively for their distinct fall parameters (Dodd, 1992) is compositionally distinguishable from a control group of 45 non-Antarctic modern H4-6 chondrites on the basis of the ten volatile trace element concentrations measured. Model-independent randomization-simulations based on both linear discriminant analysis and logistic regression verify these results. While ANOVA identifies two possible causes for this difference, analytical bias and group classification, a test validation experiment verifies that group classification is the more significant cause of compositional difference between Cluster 1 and non-Cluster 1 modern H4-6 chondrite falls. Thermoluminescence properties of these populations parallels the results of volatile trace element comparisons. This suggests that these meteorites are fragments of a co-orbital meteorite stream derived from a single parent body.

Market segmentation for multiple option healthcare delivery systems--an application of cluster analysis.

PubMed

Jarboe, G R; Gates, R H; McDaniel, C D

1990-01-01

Healthcare providers of multiple option plans may be confronted with special market segmentation problems. This study demonstrates how cluster analysis may be used for discovering distinct patterns of preference for multiple option plans. The availability of metric, as opposed to categorical or ordinal, data provides the ability to use sophisticated analysis techniques which may be superior to frequency distributions and cross-tabulations in revealing preference patterns.

Primordial random motions and angular momenta of galaxies and galaxy clusters.

NASA Technical Reports Server (NTRS)

Silk, J.; Lea, S.

1973-01-01

We study the decay of primordial random motions of galaxies and galaxy clusters in an expanding universe by solving a kinetic equation for the relaxation of differential energy spectra N(E, t). Systematic dissipative energy losses are included, involving gravitational drag by, and accretion of, intergalactic matter, as well as the effect of collisions with other systems. Formal and numerical solutions are described for two distinct modes of galaxy formation in a turbulent medium, corresponding to formation at a distinct epoch and to continuous formation of galaxies. We show that any primordial random motions of galaxies at the present epoch can amount to at most a few km/sec, and that collisions at early epochs can lead to the acquisition of significant amounts of primordial angular momentum.

Random whole metagenomic sequencing for forensic discrimination of soils.

PubMed

Khodakova, Anastasia S; Smith, Renee J; Burgoyne, Leigh; Abarno, Damien; Linacre, Adrian

2014-01-01

Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

Molecular characterizations of somatic hybrids developed between Pleurotus florida and Lentinus squarrosulus through inter-simple sequence repeat markers and sequencing of ribosomal RNA-ITS gene.

PubMed

Mallick, Pijush; Chattaraj, Shruti; Sikdar, Samir Ranjan

2017-10-01

The 12 pfls somatic hybrids and 2 parents of Pleurotus florida and Lentinus s quarrosulus were characterized by ISSR and sequencing of rRNA-ITS genes. Five ISSR primers were used and amplified a total of 54 reproducible fragments with 98.14% polymorphism among all the pfls hybrid populations and parental strains. UPGMA-based cluster exhibited a dendrogram with three major groups between the parents and pfls hybrids. Parent P . florida and L . squarrosulus showed different degrees of genetic distance with all the hybrid lines and they showed closeness to hybrid pfls 1m and pfls 1h , respectively. ITS1(F) and ITS4(R) amplified the rRNA-ITS gene with 611-867 bp sequence length. The nucleotide polymorphisms were found in the ITS1, ITS2 and 5.8S rRNA region with different number of bases. Based on rRNA-ITS sequence, UPGMA cluster exhibited three distinct groups between L. squarrosulus and pfls 1p , pfls 1m and pfls 1s , and pfls 1e and P. florida .

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

NASA Astrophysics Data System (ADS)

Harper, Bryan; Thomas, Dennis; Chikkagoudar, Satish; Baker, Nathan; Tang, Kaizhi; Heredia-Langner, Alejandro; Lins, Roberto; Harper, Stacey

2015-06-01

The integration of rapid assays, large datasets, informatics, and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here, we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality in developing embryonic zebrafish, were established at realistic exposure levels and used to develop a hazard ranking of diverse nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both the core composition and outermost surface chemistry of nanomaterials. The resulting clusters guided the development of a surface chemistry-based model of gold nanoparticle toxicity. Our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. Research should continue to focus on methodologies for determining nanomaterial hazard based on multiple sub-lethal responses following realistic, low-dose exposures, thus increasing the availability of quantitative measures of nanomaterial hazard to support the development of nanoparticle structure-activity relationships.

Who are the obese? A cluster analysis exploring subgroups of the obese.

PubMed

Green, M A; Strong, M; Razak, F; Subramanian, S V; Relton, C; Bissell, P

2016-06-01

Body mass index (BMI) can be used to group individuals in terms of their height and weight as obese. However, such a distinction fails to account for the variation within this group across other factors such as health, demographic and behavioural characteristics. The study aims to examine the existence of subgroups of obese individuals. Data were taken from the Yorkshire Health Study (2010-12) including information on demographic, health and behavioural characteristics. Individuals with a BMI of ≥30 were included. A two-step cluster analysis was used to define groups of individuals who shared common characteristics. The cluster analysis found six distinct groups of individuals whose BMI was ≥30. These subgroups were heavy drinking males, young healthy females; the affluent and healthy elderly; the physically sick but happy elderly; the unhappy and anxious middle aged and a cluster with the poorest health. It is important to account for the important heterogeneity within individuals who are obese. Interventions introduced by clinicians and policymakers should not target obese individuals as a whole but tailor strategies depending upon the subgroups that individuals belong to. © The Author 2015. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.