993 resultados para Spatial Clustering


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The aetiology of childhood cancers remains largely unknown. It has been hypothesized that infections may be involved and that mini-epidemics thereof could result in space-time clustering of incident cases. Most previous studies support spatio-temporal clustering for leukaemia, while results for other diagnostic groups remain mixed. Few studies have corrected for uneven regional population shifts which can lead to spurious detection of clustering. We examined whether there is space-time clustering of childhood cancers in Switzerland identifying cases diagnosed at age <16 years between 1985 and 2010 from the Swiss Childhood Cancer Registry. Knox tests were performed on geocoded residence at birth and diagnosis separately for leukaemia, acute lymphoid leukaemia (ALL), lymphomas, tumours of the central nervous system, neuroblastomas and soft tissue sarcomas. We used Baker's Max statistic to correct for multiple testing and randomly sampled time-, sex- and age-matched controls from the resident population to correct for uneven regional population shifts. We observed space-time clustering of childhood leukaemia at birth (Baker's Max p = 0.045) but not at diagnosis (p = 0.98). Clustering was strongest for a spatial lag of <1 km and a temporal lag of <2 years (Observed/expected close pairs: 124/98; p Knox test = 0.003). A similar clustering pattern was observed for ALL though overall evidence was weaker (Baker's Max p = 0.13). Little evidence of clustering was found for other diagnostic groups (p > 0.2). Our study suggests that childhood leukaemia tends to cluster in space-time due to an etiologic factor present in early life.

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This study subdivides the Potter Cove, King George Island, 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 includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. 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 and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 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.

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The Fractal Image Informatics toolbox (Oleschko et al., 2008 a; Torres-Argüelles et al., 2010) was applied to extract, classify and model the topological structure and dynamics of surface roughness in two highly eroded catchments of Mexico. Both areas are affected by gully erosion (Sidorchuk, 2005) and characterized by avalanche-like matter transport. Five contrasting morphological patterns were distinguished across the slope of the bare eroded surface of Faeozem (Queretaro State) while only one (apparently independent on the slope) roughness pattern was documented for Andosol (Michoacan State). We called these patterns ?the roughness clusters? and compared them in terms of metrizability, continuity, compactness, topological connectedness (global and local) and invariance, separability, and degree of ramification (Weyl, 1937). All mentioned topological measurands were correlated with the variance, skewness and kurtosis of the gray-level distribution of digital images. The morphology0 spatial dynamics of roughness clusters was measured and mapped with high precision in terms of fractal descriptors. The Hurst exponent was especially suitable to distinguish between the structure of ?turtle shell? and ?ramification? patterns (sediment producing zone A of the slope); as well as ?honeycomb? (sediment transport zone B) and ?dinosaur steps? and ?corals? (sediment deposition zone C) roughness clusters. Some other structural attributes of studied patterns were also statistically different and correlated with the variance, skewness and kurtosis of gray distribution of multiscale digital images. The scale invariance of classified roughness patterns was documented inside the range of five image resolutions. We conjectured that the geometrization of erosion patterns in terms of roughness clustering might benefit the most semi-quantitative models developed for erosion and sediment yield assessments (de Vente and Poesen, 2005).

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The Lofoten-Vesterålen marine shelf is one of the most geologically diverse coast and offshore margin areas in Norway. This leads to huge heterogeneity in marine environments, and often high biodiversity. However, little is known yet about the benthic communities in this region. Within the ARCTOS LoVe MarineEco project the epibenthic communities of the Hola trough (Vesterålen) are analysed to give a first description of their spatial distribution. In this trough both a complex hydrodynamic system and varied topographic submarine elements occur. Trawling samples were collected for two different approaches: one in a meso-scale and another in a small-scale. For the broad scale a transect consisting in three stations was developed, while for the fine scale a small area on a sand wave field, consisting in five stations called HolaBox, was sampled. All organisms were intended to be identified to species level and colonial fauna was discarded for the analysis. Different diversity indexes were assessed (Shannon index (H’) and Pielou’s eveness (J’)). Clustering and nMDS analyses identified four statistically significant groups in terms of abundance (ind./100m2). A total amount of 211 different taxa were found within all stations. The more outer part of the transect (close to the shelf edge) presented a huge abundance of organisms and was dominated by the hemi sessile tube-builder polychaetes Nothria conchylega and Eunice dubitata and the sea urchin Gacilechinus acutus, while the more inner parts presented less abundance of individuals. Probably some upwelling produced by the Norwegian Atlantic Current (NWAC) is influencing the shelf edge increasing the primary production and, therefore, enriching the seafloor in this region. The sand wave field presented two different groups with few amount of individuals. Small-scale variability could be produced by the high heterogeneity within the different types of sand waves, while the scarce abundance of animals can be produced by the permanent changing environment that movable sand waves produce. Here more active and mobile fauna was found such as brittle stars and hermit crabs (among others). Finally, a fourth group was found in the most inner station of the transect, laying on a ridge in the central part of the trough. This station, with coarse substrate, was mainly dominated again by brittle stars and sea urchins. We can conclude that this is a really heterogeneous trough in environments and therefore in communities (even in a local scale). More detailed studies that focus in the local environmental drivers have to be carried out to get an integrated understanding of the structure of benthic communities in this system.

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This paper develops an Internet geographical information system (GIS) and spatial model application that provides socio-economic information and exploratory spatial data analysis for local government authorities (LGAs) in Queensland, Australia. The application aims to improve the means by which large quantities of data may be analysed, manipulated and displayed in order to highlight trends and patterns as well as provide performance benchmarking that is readily understandable and easily accessible for decision-makers. Measures of attribute similarity and spatial proximity are combined in a clustering model with a spatial autocorrelation index for exploratory spatial data analysis to support the identification of spatial patterns of change. Analysis of socio-economic changes in Queensland is presented. The results demonstrate the usefulness and potential appeal of the Internet GIS applications as a tool to inform the process of regional analysis, planning and policy.

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In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

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A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

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The development of abnormal protein aggregates in the form of extracellular plaques and intracellular inclusions is a characteristic feature of many neurodegenerative diseases such as Alzheimer's disease (AD), Creutzfeldt-Jakob disease (CJD) and the fronto-temporal dementias (FTD). An important aspect of a pathological protein aggregate is its spatial topography in the tissue. Lesions may not be randomly distributed within a histological section but exhibit spatial pattern, a departure from randomness either towards regularity or clustering. Information on the spatial pattern of a lesion may be useful in elucidating its pathogenesis and in studying the relationships between different lesions. This article reviews the methods that have been used to study the spatial topography of lesions. These include simple tests of whether the distribution of a lesion departs significantly from random using randomized points or sample fields, and more complex methods that employ grids or transects of contiguous fields and which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters. The usefulness of these methods in elucidating the pathogenesis of protein aggregates in neurodegenerative disease is discussed.

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Discrete pathological lesions, which include extracellular protein deposits, intracellular inclusions and changes in cell morphology, occur in the brain in the majority of neurodegenerative disorders. These lesions are not randomly distributed in the brain but exhibit a spatial pattern, that is, a departure from randomness towards regularity or clustering. The spatial pattern of a lesion may reflect pathological processes affecting particular neuroanatomical structures and, therefore, studies of spatial pattern may help to elucidate the pathogenesis of a lesion and of the disorders themselves. The present article reviews first, the statistical methods used to detect spatial patterns and second, the types of spatial patterns exhibited by pathological lesions in a variety of disorders which include Alzheimer's disease, Down syndrome, dementia with Lewy bodies, Creutzfeldt-Jakob disease, Pick's disease and corticobasal degeneration. These studies suggest that despite the morphological and molecular diversity of brain lesions, they often exhibit a common type of spatial pattern (i.e. aggregation into clusters that are regularly distributed in the tissue). The pathogenic implications of spatial pattern analysis are discussed with reference to the individual disorders and to studies of neurodegeneration as a whole.

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In patients with Pick's disease (PD), high densities of tau positive Pick bodies (PB) have been observed within the granule cell layer of the dentate gyrus. This study investigated the spatial patterns of PB along the granule cell layer in coronal sections of the hippocampus in eight patients with PD. In all patients, there was evidence of clustering of PB within the granule cell layer; however, there was considerable variation in the pattern of clustering. In five patients, the clusters of PB were regularly distributed along the dentate gyms, and in two of these patients, the smaller clusters were aggregated into larger superclusters. In three patients, a single large cluster of PB, more than 1200 μm in diameter, was present. Clustering of PB may reflect a primary degenerative process within the granule cells or the degeneration of pathways that project to the dentate gyrus.

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In Alzheimer's disease (AD), neurofibrillary tangles (NFT) occur within neurons in both the upper and lower cortical laminae. Using a statistical method that estimates the size and spacing of NFT clusters along the cortex parallel to the pia mater, two hypotheses were tested: 1) that the cluster size and distribution of the NFT in gyri of the temporal lobe reflect degeneration of the feedforward (FF) and feedback (FB) cortico-cortical pathways, and 2) that there is a spatial relationship between the clusters of NFT in the upper and lower laminae. In 16 temporal lobe gyri from 10 cases of sporadic AD, NFT were present in both the upper and lower laminae in 11/16 (69%) gyri and in either the upper or lower laminae in 5/16 (31%) gyri. Clustering of the NFT was observed in all gyri. A significant peak-to-peak distance was observed in the upper laminae in 13/15 (87%) gyri and in the lower laminae in 8/ 12 (67%) gyri, suggesting a regularly repeating pattern of NFT clusters along the cortex. The regularly distributed clusters of NFT were between 500 and 800 μm in size, the estimated size of the cells of origin of the FF and FB cortico-cortical projections, in the upper laminae of 6/13 (46%) gyri and in the lower laminae of 2/8 (25%) gyri. Clusters of NFT in the upper laminae were spatially correlated (in phase) with those in the lower laminae in 5/16 (31%) gyri. The clustering patterns of the NFT are consistent with their formation in relation to the FF and FB cortico-cortical pathways. In most gyri, NFT clusters appeared to develop independently in the upper and lower laminae.

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Neuronal intermediate filament inclusion disease (NIFID) is a new neurodegenerative disease characterized histologically by the presence of neuronal cytoplasmic inclusions (NI) immunopositive for intermediate filament proteins, neuronal loss, swollen achromatic neurons (SN), and gliosis. We studied the spatial patterns of these pathological changes parallel to the pia mater in gyri of the temporal lobe in four cases of NIFID. Both the NI and SN occurred in clusters that were regularly distributed parallel to the pia mater, the cluster sizes of the SN being significantly greater than those of the NI. In a significant proportion of areas studied, there was a spatial correlation between the clusters of NI and those of the SN and with the density of the surviving neurons. In addition, the clusters of surviving neurons were negatively correlated (out of phase) with the clusters of glial cell nuclei. The pattern of clustering of these histological features suggests that there is degeneration of the cortico-cortical projections in NIFID leading to the formation of NI and SN within the same vertical columns of cells. The glial cell reaction may be a response to the loss of neurons rather than to the appearance of the NI or SN.

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The spatial patterns of the vacuolation ("spongiform change"), surviving cells, and prion protein (PrP) deposition were studied in the various cell laminae of the cerebellar cortex in 11 cases of sporadic Creutzfeldt-Jakob disease (sCJD). Clustering of the histological features, with the clusters regularly distributed along the folia, was evident in all cell laminae. In the molecular layer, clusters of vacuoles coincided with the surviving Purkinje cells. In the granule cell layer, however, the spatial relationship between the vacuoles and surviving cells was more complex and varied between cases. PrP deposition was not spatially correlated with either the vacuoles or the surviving cells in any of the cerebellar laminae in the majority of cases. In some cases, there were spatial relationships between th histological features in the molecular and granule cell layers. The data suggest that degeneration of the cerebellar cortex in sCJD may occur in a topographic pattern consistent with the spread of prion pathology along anatomical pathways. The development of the vacuolation may be an early stage of the pathology in the cerebellum preceding the appearance of the PrP deposits. In addition, there is evidence that the pathological changes may spread across the different laminae of the cerebellar cortex.

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Dementia with neurofilament inclusions (DNI) is a new disorder characterized clinically by early-onset dementia and histologically by the presence of intraneural inclusions immunopositive for neurofilament antigens but lacking tau and α-synuclein reactivity. We studied the clustering patterns of the neurofilament inclusions (NI) in regions of the temporal lobe in three cases of DNI to determine whether they have the same spatial patterns as inclusions in the tauopathies and α-synucleinopathies. The NI exhibited a clustered distribution (mean size of clusters 400 μm, range 50-800 μm, SD 687.8) in 24/28 of the areas studied. In 22 of these areas, the clusters exhibited a regular distribution along the tissue parallel to the pia mater or alveus. In 3 cortical areas, there was evidence of a more complex pattern in which the NI clusters were aggregated into larger superclusters. In 6 cortical areas, the size of the clusters approximated to those of the cells of origin of the cortico-cortical pathways but in the remaining areas cluster size was smaller than 400 μm. Despite the unique molecular profile of the NI, their spatial patterns are similar to those shown by filamentous neuronal inclusions in the tauopathies and α-synucleinopathies.

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The spatial patterns of the prion protein (PrP) deposits were studied in immunostained sections of areas of the cerebral cortex, hippocampus, dentate gyrus, and the molecular layer of the cerebellum in 11 cases of variant Creutzfeldt-Jakob disease (vCJD). Clustering of PrP deposits, with a regular distribution of the clusters parallel to the tissue boundary, was the most common spatial pattern observed. Two morphological types of PrP deposit were recognised, those consisting of a condensed core (florid deposits) and those deposits lacking a condensed core (non-florid deposits). The florid and non-florid PrP deposits exhibited a different profile of spatial patterns. First, the florid deposits exhibited a regularly distributed pattern of clusters more frequently than the non-florid deposits. Second, the florid deposits formed larger clusters (greater than1,600 µm in diameter) less frequently than the non-florid deposits. In the areas of the cerebral cortex that exhibited a regular distribution of PrP deposit clusters, the cluster size of the deposits approximated that of the groups of cells of the cortico-cortical pathway origin in only 12% of analyses. No significant differences in the frequency of the different types of spatial pattern were observed in different brain regions, or in the cerebral cortex between the upper and lower laminae. It was concluded that the spatial patterns of the PrP deposits in the cerebral cortex in vCJD are unlikely to reflect the degeneration of the cortico-cortical pathways as has been reported in sporadic CJD (sCJD). In addition, different factors could be involved in the development of the deposits with and without a condensed core.