A spatial pattern analysis of beta-amyloid (Abeta) deposition in the temporal lobe in Alzheimer's disease

To determine the factors influencing the distribution of -amyloid (Abeta) deposits in Alzheimer's disease (AD), the spatial patterns of the diffuse, primitive, and classic A deposits were studied from the superior temporal gyrus (STG) to sector CA4 of the hippocampus in six sporadic cases of the disease. In cortical gyri and in the CA sectors of the hippocampus, the Abeta deposits were distributed either in clusters 200-6400 microm in diameter that were regularly distributed parallel to the tissue boundary or in larger clusters greater than 6400 microm in diameter. In some regions, smaller clusters of Abeta deposits were aggregated into larger 'superclusters'. In many cortical gyri, the density of Abeta deposits was positively correlated with distance below the gyral crest. In the majority of regions, clusters of the diffuse, primitive, and classic deposits were not spatially correlated with each other. In two cases, double immunolabelled to reveal the Abeta deposits and blood vessels, the classic Abeta deposits were clustered around the larger diameter vessels. These results suggest a complex pattern of Abeta deposition in the temporal lobe in sporadic AD. A regular distribution of Abeta deposit clusters may reflect the degeneration of specific cortico-cortical and cortico-hippocampal pathways and the influence of the cerebral blood vessels. Large-scale clustering may reflect the aggregation of deposits in the depths of the sulci and the coalescence of smaller clusters.

Phenotypic and genotypic analysis of intestinal spirochacies

Pulsed field gel electrophoresis of 82 intestinal spirochaete isolates showed specific differentiation of Serpulina pilosicoli and Serpulina hyodysenteriae although considerable heterogeneity was observed, especially amongst S. pilosicoli isolates. In several cases genotypically similar isolates originated from different animals suggesting that cross-species transmission may have occurred. The Caco-2 and Caco-21HT29 cell models have been proposed as potentially realistic models of intestinal infection. Quantitation of adhesion to the cells showed isolate 3 82/91 (from a bacteraemia) to adhere at significantly greater numbers than any other isolate tested. This isolate produced a PFGE profile which differed from other S. pilosicoli isolates and so would be of interest for further study. Comparison of bacteraemic and other S. pilosicoli isolates suggested that bacteraemic isolates were not more specifically adapted for adhesion to, or invasion of the epithelial cell layer than other S. pilosicoli isolates. Genotypically similar isolates from differing animal origins adhered to the Caco-2 model at similar levels. Generation of a random genomic library of S. pilosicoli and screening with species specific monoclonal antibody has enabled the identification of a gene sequence encoding a protein which showed significant homology with an ancestral form of the enzyme pyruvate oxidoreductase. Immunoscreening with polyclonal serum identified the sequences of two gene clusters and a probable arylsulphatase. One gene cluster represented a ribosomal gene cluster which has a similar molecular arrangement to Borrelia burgdorjeri, Treponema pallidum and Thermatoga maritima. The other gene cluster contained an ABC transporter protein, sorbitol dehydrogenase and phosphomannose isomerase. An ELISA type assay was used to demonstrate that isolates of S. pilosicoli could adhere to components of the extracellular matrix such as collagen (type 1), fibronectin, laminin, and porcine gastric mucin.

Proteomic analysis of a noninvasive human model of acute inflammation and its resolution:the twenty-one day gingivitis model

The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

Development of areolae and growth of the peripheral prothallus in the crustose lichen Rhizocarpon geographicum:an image analysis study

Areolae of the crustose lichen Rhizocarpon geographicum (L.) DC., are present on the peripheral prothallus (marginal areolae) and also aggregate to form confluent masses in the centre of the thallus (central areolae). To determine the relationships between these areolae and whether growth of the peripheral prothallus is dependent on the marginal areolae, the density, morphology, and size frequency distributions of marginal areolae were measured in 23 thalli of R. geographicum in north Wales, UK using image analysis (Image J). Size and morphology of central areolae were also studied across the thallus. Marginal areolae were small, punctate, and occurred in clusters scattered over the peripheral prothallus while central areolae were larger and had a lobed structure. The size-class frequency distributions of the marginal and central areolae were fitted by power-law and log-normal models respectively. In 16 out of 23 thalli, central areolae close to the outer edge were larger and had a more complex lobed morphology than those towards the thallus centre. Neither mean width nor radial growth rate (RaGR) of the peripheral prothallus were correlated with density, diameter, or area fraction of marginal areolae. The data suggest central areolae may develop from marginal areolae as follows: (1) marginal areolae develop in clusters at the periphery and fuse to form central areolae, (2) central areolae grow exponentially, and (3) crowding of central areolae results in constriction and fragmentation. In addition, growth of the peripheral prothallus may be unrelated to the marginal areolae. © 2013 Springer Science+Business Media Dordrecht.

Psychophysiological responses to pain identify reproducible human clusters

Pain is a ubiquitous yet highly variable experience. The psychophysiological and genetic factors responsible for this variability remain unresolved. We hypothesised the existence of distinct human pain clusters (PCs) composed of distinct psychophysiological and genetic profiles coupled with differences in the perception and the brain processing of pain. We studied 120 healthy subjects in whom the baseline personality and anxiety traits and the serotonin transporter-linked polymorphic region (5-HTTLPR) genotype were measured. Real-time autonomic nervous system parameters and serum cortisol were measured at baseline and after standardised visceral and somatic pain stimuli. Brain processing reactions to visceral pain were studied in 29 subjects using functional magnetic resonance imaging (fMRI). The reproducibility of the psychophysiological responses to pain was assessed at 1 year. In group analysis, visceral and somatic pain caused an expected increase in sympathetic and cortisol responses and activated the pain matrix according to fMRI studies. However, using cluster analysis, we found 2 reproducible PCs: at baseline, PC1 had higher neuroticism/anxiety scores (P ≤ 0.01); greater sympathetic tone (P < 0.05); and higher cortisol levels (P ≤ 0.001). During pain, less stimulus was tolerated (P ≤ 0.01), and there was an increase in parasympathetic tone (P ≤ 0.05). The 5-HTTLPR short allele was over-represented (P ≤ 0.005). PC2 had the converse profile at baseline and during pain. Brain activity differed (P ≤ 0.001); greater activity occurred in the left frontal cortex in PC1, whereas PC2 showed greater activity in the right medial/frontal cortex and right anterior insula. In health, 2 distinct reproducible PCs exist in humans. In the future, PC characterization may help to identify subjects at risk for developing chronic pain and may reduce variability in brain imaging studies. © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

A Statistical Approach for Multilingual Document Clustering and Topic Extraction from Clusters

2000 Mathematics Subject Classification: 62H30

Analysis and Data Mining of Lead-Zinc Ore Data

This paper presents the results of our data mining study of Pb-Zn (lead-zinc) ore assay records from a mine enterprise in Bulgaria. We examined the dataset, cleaned outliers, visualized the data, and created dataset statistics. A Pb-Zn cluster data mining model was created for segmentation and prediction of Pb-Zn ore assay data. The Pb-Zn cluster data model consists of five clusters and DMX queries. We analyzed the Pb-Zn cluster content, size, structure, and characteristics. The set of the DMX queries allows for browsing and managing the clusters, as well as predicting ore assay records. A testing and validation of the Pb-Zn cluster data mining model was developed in order to show its reasonable accuracy before beingused in a production environment. The Pb-Zn cluster data mining model can be used for changes of the mine grinding and floatation processing parameters in almost real-time, which is important for the efficiency of the Pb-Zn ore beneficiation process. ACM Computing Classification System (1998): H.2.8, H.3.3.

A spatial pattern analysis of β-amyloid (Aβ) deposition in the temporal lobe in Alzheimer's disease

To determine the factors influencing the distribution of β-amyloid (Aβ) deposits in Alzheimer's disease (AD), the spatial patterns of the diffuse, primitive, and classic Aβ deposits were studied from the superior temporal gyrus (STG) to sector CA4 of the hippocampus in six sporadic cases of the disease. In cortical gyri and in the CA sectors of the hippocampus, the Aβ deposits were distributed either in clusters 200-6400 μm in diameter that were regularly distributed parallel to the tissue boundary or in larger clusters greater than 6400 μm in diameter. In some regions, smaller clusters of Aβ deposits were aggregated into larger 'superclusters'. In many cortical gyri, the density of Aβ deposits was positively correlated with distance below the gyral crest. In the majority of regions, clusters of the diffuse, primitive, and classic deposits were not spatially correlated with each other. In two cases, double immunolabelled to reveal the Aβ deposits and blood vessels, the classic Aβ deposits were clustered around the larger diameter vessels. These results suggest a complex pattern of Aβ deposition in the temporal lobe in sporadic AD. A regular distribution of Aβ deposit clusters may reflect the degeneration of specific cortico-cortical and cortico-hippocampal pathways and the influence of the cerebral blood vessels. Large-scale clustering may reflect the aggregation of deposits in the depths of the sulci and the coalescence of smaller clusters.

Az exportteljesítmények és a hátterükben álló vállalati jellemzők elemzése (Export performance clusters of the Hungarian enterprises)

A tanulmány célja a Magyarországon működő exportáló vállalatok jellemzőinek feltárása volt a 2009-es vállalati versenyképességi felmérés alapján. Több tanulmány vizsgálta a vállalatok exportteljesítményét vállalati méret és tulajdonosi szerkezet szerinti bontásban, az elemzésben a szerző viszont ettől eltérő szemléletmódot alkalmazott. A vállalatok exportteljesítménye áll (exportértékesítés volumene, aránya, exportárbevétel változása, jövedelmezőség), a vállalati csoportképzés, klaszterelemzés középpontjában. Három jól elkülöníthető klasztert sikerült azonosítani: a jelentős exporthányaddal és folyamatos növekedéssel jellemezhető sikeres exportáló vállalatok csoportját, a stagnálással, s gyakran csökkenő exportértékesítéssel jellemezhető vállalatcsoportot, s végül a harmadik klasztert azok a jelenleg még alacsony export-ár bevétellel és alacsony exportaránnyal jellemezhető vállalatok képezték, melyekre a növekedés és a kiugróan magas jövedelmezőség volt a jellemző. Az elemzés egyediségét az adja, hogy a vállalati versenyképességi felmérés adatbázisa lehetővé tette a különböző exportteljesítmények hátterében álló működési jellemzők vizsgálatát, amelynek eredményeit a cikk bemutatja. Fő következtetésként megállapítható, hogy a sikeres exportáló vállalatok csoportja mindegyik jellemző szerint jobb működési jellemzőkkel rendelkezik a másik két csoporthoz viszonyítva. / === / The purpose of the paper is to reveal the main characteristics of the Hungarian export oriented firms. It is based on the Hungarian Competitiveness Research Survey 2009. 85% of enterprises were small or medium size in the sample. The aim of the analysis was to identify main factors and tendencies of the overall export performance. Several papers discussed the export activities of firms according to their size and ownership structure in Hungary. A different method was used here. The overall export performance (measured by volume, change, and share of export revenues, and firm profitability ratios) was put in the centre of cluster analysis. Three different clusters were identified. Firms in the firstcluster had significant export performance and growth rate. The second cluster was the group of stagnating firms and the third one contained those whose export performance was low but signaled growth with excellent profitability ratios. The uniqueness of the paper derived from the Competitiveness Research Survey because it provided an opportunity to analyse the connection between export performance and other management and operational characteristics of enterprises. The paper may induce futher research in exploring main enterprise level factors of export performance of the Hungarian firms.

The network structure of Hungarian business clusters

This article investigates the attitudes to inter-firm co-operation in Hungary by analysing a special group of business networks: the business clusters. Following an overview of cluster policy, a wide range of selfproclaimed business clusters are identified. A small elite of these business networks evolves into successful, sustainable innovative business clusters. However, in the majority of cases, these consortia of interfirm co-operation are not based on a mutually satisfactory model, and as a consequence, many clusters do not survive in the longer term. The paper uses the concepts and models of social network theory in order to explain, why and under what circumstances inter-firm co-operation in clusters enhances the competitiveness of the network as a whole, or alternatively, under what circumstances the cluster remains dependent on Government subsidies. The empirical basis of the study is a thorough internet research about the Hungarian cluster movement; a questionnaire based expert survey among managers of clusters and member companies and a set of in-depth interviews among managers of self-proclaimed clusters. The last chapter analyises the applicability of social network theory in the analysis of business networks and a model involving the value chain is recommended.

Ionized cluster beam deposition, and thin film analysis

In 1972 the ionized cluster beam (ICB) deposition technique was introduced as a new method for thin film deposition. At that time the use of clusters was postulated to be able to enhance film nucleation and adatom surface mobility, resulting in high quality films. Although a few researchers reported singly ionized clusters containing 10$\sp2$-10$\sp3$ atoms, others were unable to repeat their work. The consensus now is that film effects in the early investigations were due to self-ion bombardment rather than clusters. Subsequently in recent work (early 1992) synthesis of large clusters of zinc without the use of a carrier gas was demonstrated by Gspann and repeated in our laboratory. Clusters resulted from very significant changes in two source parameters. Crucible pressure was increased from the earlier 2 Torr to several thousand Torr and a converging-diverging nozzle 18 mm long and 0.4 mm in diameter at the throat was used in place of the 1 mm x 1 mm nozzle used in the early work. While this is practical for zinc and other high vapor pressure materials it remains impractical for many materials of industrial interest such as gold, silver, and aluminum. The work presented here describes results using gold and silver at pressures of around 1 and 50 Torr in order to study the effect of the pressure and nozzle shape. Significant numbers of large clusters were not detected. Deposited films were studied by atomic force microscopy (AFM) for roughness analysis, and X-ray diffraction.^ Nanometer size islands of zinc deposited on flat silicon substrates by ICB were also studied by atomic force microscopy and the number of atoms/cm$\sp2$ was calculated and compared to data from Rutherford backscattering spectrometry (RBS). To improve the agreement between data from AFM and RBS, convolution and deconvolution algorithms were implemented to study and simulate the interaction between tip and sample in atomic force microscopy. The deconvolution algorithm takes into account the physical volume occupied by the tip resulting in an image that is a more accurate representation of the surface.^ One method increasingly used to study the deposited films both during the growth process and following, is ellipsometry. Ellipsometry is a surface analytical technique used to determine the optical properties and thickness of thin films. In situ measurements can be made through the windows of a deposition chamber. A method for determining the optical properties of a film, that is sensitive only to the growing film and accommodates underlying interfacial layers, multiple unknown underlayers, and other unknown substrates was developed. This method is carried out by making an initial ellipsometry measurement well past the real interface and by defining a virtual interface in the vicinity of this measurement. ^

Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

The Excess Burden of Cytomegalovirus in African American Communities: A Geospatial Analysis.

Background.  Cytomegalovirus (CMV) is a common cause of birth defects and hearing loss in infants and opportunistic infections in the immunocompromised. Previous studies have found higher CMV seroprevalence rates among minorities and among persons with lower socioeconomic status. No studies have investigated the geographic distribution of CMV and its relationship to age, race, and poverty in the community. Methods.  We identified patients from 6 North Carolina counties who were tested in the Duke University Health System for CMV immunoglobulin G. We performed spatial statistical analyses to analyze the distributions of seropositive and seronegative individuals. Results.  Of 1884 subjects, 90% were either white or African American. Cytomegalovirus seropositivity was significantly more common among African Americans (73% vs 42%; odds ratio, 3.31; 95% confidence interval, 2.7-4.1), and this disparity persisted across the life span. We identified clusters of high and low CMV odds, both of which were largely explained by race. Clusters of high CMV odds were found in communities with high proportions of African Americans. Conclusions.  Cytomegalovirus seropositivity is geographically clustered, and its distribution is strongly determined by a community's racial composition. African American communities have high prevalence rates of CMV infection, and there may be a disparate burden of CMV-associated morbidity in these communities.