Kawasaki syndrome: Cluster analysis of incident cases presenting to a pediatric tertiary care hospital in Texas from January 1, 2005 to December 31, 2009

Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^

Image analysis from TEM and AFM micrograph, Table S1, S2, S3, Figure S1, Figure S2

We report on metal enrichment along a natural pH gradient owing to increased CO2 degassing at cold, shal- low seeps of Vulcano Island in the Mediterranean Sea, off Sicily. We assessed composition of unfiltered and filtered seawater (b100 nm) along acidic zones ranging between ambient and pH 5, and showed that most seep derived elements are present as nanoclusters which then aggregate into larger colloids while mixing with ambient seawater along a pH gradient. Size and elemental composition of such naturally occurring nanoparticles assessed by modern characterisation methods were in good agreement with the results from conventional analytical methods. We provide analytical evidence for the presence in the water column of a large fraction of seep derived ele- ments (e.g. approximately 50% of iron, over 80% of Mn, 100% of Cr, S and Zn) in the form of nano sized par- ticles (e.g. b100 nm) even at typical open ocean pHs. We launch in situ sampling protocols and sample preparation procedures for multi-method suitable to obtain accurate measurements on nanoparticles from environmental samples. Based on our results a first insight to the formation of natural nanoparticles at cold CO2 seeps is presented and the persistence of such nano-clusters in the surrounding seawater is stipulated.

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.

Regional Cooperation of Small & Medium Firms in Japanese Industrial Clusters

This study examines the effects of intra-regional cooperation among firms and institutions on the growth of firms, using the unique data set of questionnaire survey collected in the three major industrial clusters in Japan. In contrast to the existing studies on regional innovations or agglomeration economies, this study explicitly focuses on the detailed contents of cooperative activities with two specific viewpoints: 1) the contents of regional cooperation in each of the three production stages of R&D, commercialization, and marketing, and 2) the detailed types of alliance partners. Our results demonstrate three points: 1) positive correlations are observed between the intensity of regional cooperation and the firm growth rate and R&D expenditure, 2) horizontal cooperation such as alliances with universities and cross-industry exchange organizations has positive significant effects on the growth rate of firms, which is in contrast with the previous studies that stressed only the role of vertically integrated inter-firm linkages in Japan, and 3) contents and partners of regional cooperation are different among the three clusters based on different dominant industries.

Chapter 7 Clusters of Modern and Local Industries in Vietnam

Since the introduction of the Doi Moi ('renovation') economic reform in 1986, Vietnam has experienced a transformation of its economic management, from a central planning economy to a market-oriented economy. High economic growth, created by the liberalization of activities in all sectors of the economy, has changed the economic structure of the country, and the once agriculture-based and poverty-stricken land now generates a midlevel income and possesses many industrial bases. Economic growth has also changed the landscape of the country. Business complexes have been built in metropolises like Ho Chi Minh City and Hanoi, and rice fields have been converted into industrial zones. As the number of enterprises increased, areas began to emerge where many enterprises agglomerated. Some of these 'clusters' were groups of cottage industry households, while many others were large-scale industrial clusters. As Porter [1998] argues, industrial clusters are the source of a nation's 'competitive advantage'. McCarty et al. [2005] indicate that in some key industries in Vietnam, some clusters of enterprises have been created, although the degree of agglomeration differs from one industry to another. Using industry census data from 2001, they include dot density maps for the 12 leading manufacturing industries in Vietnam. They show that most of the industries analyzed are clustered either in Hanoi or Ho Chi Minh City (or both). Among these 12 industries, the garments industry has the greatest tendency to cluster, followed by textile, rice, seafood, and paper industries. The fact that industrial clusters have begun to form in some areas could be a positive sign for Vietnam's future economic development. What is lacking in McCarty et al. [2005], however, is the identification of the participants in the industrial clusters. Some argue for the importance of small and medium enterprises (SMEs) in Vietnam's economic development (e.g. Nguyen Tri Thanh [2007], Tran Tien Cuong et al. [2008]), while others stress the impact of foreign direct investments (FDI) (for example, Tuan Bui [2009]). Adding information about the participants in the above cluster study (and in other studies of spatial patterns of location of enterprises) may broaden the scope for analysis of economic development in Vietnam. This study aims to reveal the characteristics of industrial clusters in terms of their participants and locations. The findings of the study may provide basic information for evaluating the effects of agglomeration and the robustness of the effects in the industrial clusters in Vietnam. Section 1 describes the characteristics of economic entities in Vietnam such as ownership, size of enterprise, and location. Section 2 examines qualitative aspects of industrial clusters identified in McCarty et al. [2005] and uses information on the size and ownership of clusters. Three key industries (garments, consumer electronics, and motor vehicle) are selected for the study. Section 3 identifies another type of cluster commonly seen in Vietnam, composed of local industries and called 'craft villages'. Many such villages have been developed since the early 1990s. The study points out that some of these villages have become industrialized (or are becoming industrialized) by introducing modern modes of production and by employing thousands of laborers.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Functional and expression analysis of the metal-inducible dmeRF system from Rhizobium legumionosarum bv. viciae

A gene encoding a homolog to the cation diffusion facilitator protein DmeF from Cupriavidus metallidurans has been identified in the genome of Rhizobium leguminosarum UPM791. The R. leguminosarum dmeF gene is located downstream of an open reading frame (designated dmeR) encoding a protein homologous to the nickel- and cobalt-responsive transcriptional regulator RcnR from Escherichia coli. Analysis of gene expression showed that the R. leguminosarum dmeRF genes are organized as a transcriptional unit whose expression is strongly induced by nickel and cobalt ions, likely by alleviating the repressor activity of DmeR on dmeRF transcription. An R. leguminosarum dmeRF mutant strain displayed increased sensitivity to Co(II) and Ni(II), whereas no alterations of its resistance to Cd(II), Cu(II), or Zn(II) were observed. A decrease of symbiotic performance was observed when pea plants inoculated with an R. leguminosarum dmeRF deletion mutant strain were grown in the presence of high concentrations of nickel and cobalt. The same mutant induced significantly lower activity levels of NiFe hydrogenase in microaerobic cultures. These results indicate that the R. leguminosarum DmeRF system is a metal-responsive efflux mechanism acting as a key element for metal homeostasis in R. leguminosarum under free-living and symbiotic conditions. The presence of similar dmeRF gene clusters in other Rhizobiaceae suggests that the dmeRF system is a conserved mechanism for metal tolerance in legume endosymbiotic bacteria.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

From calcium blips to calcium puffs: Theoretical analysis of the requirements for interchannel communication

In the cytoplasm of cells of different types, discrete clusters of inositol 1,4,5-trisphosphate-sensitive Ca2+ channels generate Ca2+ signals of graded size, ranging from blips, which involve the opening of only one channel, to moderately larger puffs, which result from the concerted opening of a few channels in the same cluster. These channel clusters are of unknown size or geometrical characteristics. The aim of this study was to estimate the number of channels and the interchannel distance within such a cluster. Because these characteristics are not attainable experimentally, we performed computer stochastic simulations of Ca2+ release events. We conclude that, to ensure efficient interchannel communication, as experimentally observed, a typical cluster should contain two or three tens of inositol 1,4,5-trisphosphate-sensitive Ca2+ channels in close contact.

Ultrastructural Analysis of Transcription and Splicing in the Cell Nucleus after Bromo-UTP Microinjection

In this study we demonstrate, at an ultrastructural level, the in situ distribution of heterogeneous nuclear RNA transcription sites after microinjection of 5-bromo-UTP (BrUTP) into the cytoplasm of living cells and subsequent postembedding immunoelectron microscopic visualization after different labeling periods. Moreover, immunocytochemical localization of several pre-mRNA transcription and processing factors has been carried out in the same cells. This high-resolution approach allowed us to reveal perichromatin regions as the most important sites of nucleoplasmic RNA transcription and the perichromatin fibrils (PFs) as in situ forms of nascent transcripts. Furthermore, we show that transcription takes place in a rather diffuse pattern, without notable local accumulation of transcription sites. RNA polymerase II, heterogeneous nuclear ribonucleoprotein (hnRNP) core proteins, general transcription factor TFIIH, poly(A) polymerase, splicing factor SC-35, and Sm complex of small nuclear ribonucleoproteins (snRNPs) are associated with PFs. This strongly supports the idea that PFs are also sites of major pre-mRNA processing events. The absence of nascent transcripts, RNA polymerase II, poly(A) polymerase, and hnRNPs within the clusters of interchromatin granules rules out the possibility that this domain plays a role in pre-mRNA transcription and polyadenylation; however, interchromatin granule-associated zones contain RNA polymerase II, TFIIH, and Sm complex of snRNPs and, after longer periods of BrUTP incubation, also Br-labeled RNA. Their role in nuclear functions still remains enigmatic. In the nucleolus, transcription sites occur in the dense fibrillar component. Our fine structural results show that PFs represent the major nucleoplasmic structural domain involved in active pre-mRNA transcriptional and processing events.

CluSTr: a database of clusters of SWISS-PROT+TrEMBL proteins

The CluSTr (Clusters of SWISS-PROT and TrEMBL proteins) database offers an automatic classification of SWISS-PROT and TrEMBL proteins into groups of related proteins. The clustering is based on analysis of all pairwise comparisons between protein sequences. Analysis has been carried out for different levels of protein similarity, yielding a hierarchical organisation of clusters. The database provides links to InterPro, which integrates information on protein families, domains and functional sites from PROSITE, PRINTS, Pfam and ProDom. Links to the InterPro graphical interface allow users to see at a glance whether proteins from the cluster share particular functional sites. CluSTr also provides cross-references to HSSP and PDB. The database is available for querying and browsing at http://www.ebi.ac.uk/clustr.

Differential fluorescence labeling of cysteinyl clusters uncovers high tissue levels of thionein

The isolation of thionein (T) from tissues has not been reported heretofore. T contains 20 cysteinyl residues that react with 7-fluorobenz-2-oxa-1,3-diazole-4-sulfonamide to form fluorescent adducts. In metallothionein (MT) the cysteinyl residues, which are bound to zinc, do not react. However, they do react in the presence of a chelating agent such as EDTA. The resultant difference in chemical reactivity provides a means to measure T in the absence of EDTA, (MT + T) in its presence, and, of course, MT by difference. The 7-fluorobenz-2-oxa-1,3-diazole-4-sulfonamide derivative of T can be isolated from tissue homogenates by HPLC and quantified fluorimetrically with a detection limit in the femtomolar range and a linear response over 3 orders of magnitude. Analysis of liver, kidney, and brain of rats reveals almost as much T as MT. Moreover, in contrast to earlier views, MT in tissue extracts appears to be less stable than T. The existence of T in tissues under normal physiological conditions has important implications for its function both in zinc metabolism and the redox balance of the cell.