959 resultados para generalized canonical correlation analysis


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Lychnophora pohlii Sch. Bip. (Asteraceae), known as "Arnica mineira", is widely used in folk medicine and very abundant in the altitude vegetation of rocky grassland. The aim of this work was to study the density of this species and its relationship with soil parameters in rocky grassland in Diamantina, in the Upper Jequitinhonha region, Minas Gerais. Ten contiguous 20 x 50 m plots were marked (total sampled area 10,000 m²) on the campus Juscelino Kubitschek of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM). The plants in these plots were evaluated for frequency, dominance and density. The relationship between the density of this species with nine soil physical and chemical properties was analyzed by means of canonical correspondence analysis (CCA). The highest plant abundance (I) of the species Lychnophora pohlii Sch. Bip. was found in the vegetation sampling areas: plot 6 with 255 plants, plot 7 with 173, plot 8 with 189, plot 9 with 159, and plot 1 with 151 plants. In these areas, the floristic soil characteristics were similar, resulting in spatial proximity in the ACC diagrams. The density of Lychnophora pohlii was higher in plots with higher pH, P-rem and base saturation, the variables most strongly correlated with the first axis of canonical correspondence analysis.

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Studies on water retention and availability are scarce for subtropical or humid temperate climate regions of the southern hemisphere. The aims of this study were to evaluate the relations of the soil physical, chemical, and mineralogical properties with water retention and availability for the generation and validation of continuous point pedotransfer functions (PTFs) for soils of the State of Santa Catarina (SC) in the South of Brazil. Horizons of 44 profiles were sampled in areas under different cover crops and regions of SC, to determine: field capacity (FC, 10 kPa), permanent wilting point (PWP, 1,500 kPa), available water content (AW, by difference), saturated hydraulic conductivity, bulk density, aggregate stability, particle size distribution (seven classes), organic matter content, and particle density. Chemical and mineralogical properties were obtained from the literature. Spearman's rank correlation analysis and path analysis were used in the statistical analyses. The point PTFs for estimation of FC, PWP and AW were generated for the soil surface and subsurface through multiple regression analysis, followed by robust regression analysis, using two sets of predictive variables. Soils with finer texture and/or greater organic matter content retain more moisture, and organic matter is the property that mainly controls the water availability to plants in soil surface horizons. Path analysis was useful in understanding the relationships between soil properties for FC, PWP and AW. The predictive power of the generated PTFs to estimate FC and PWP was good for all horizons, while AW was best estimated by more complex models with better prediction for the surface horizons of soils in Santa Catarina.

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Soil management influences the chemical and physical properties of soil. Chemical conditions have been thoroughly studied, while the role of soil physical conditions regarding crop yield has been neglected. This study aimed to analyze the wheat yield and its relationship with physical properties of an Oxisol under no-tillage (NT). The study was carried out between 2010 and 2011, in Reserva do Iguaçu, State of Paraná, Brazil, on the Campo Bonito farm, after 25 years of NT management. Based on harvest maps of barley (2006), wheat (2007) and maize (2009) of a plot (150 ha), zones with higher and lower yield potential (Z1 and Z2, respectively) were identified. Sampling grids with 16 units (50 x 50 m) and three sampling points per unit were established. The wheat grain yield (GY) and water infiltration capacity (WIC) were evaluated in 2010. Soil samples with disturbed and undisturbed structure were collected from the 0.00-0.10 and 0.10-0.20 m layers. The former were used to determine soil organic carbon (Corg) levels and the latter to determine soil bulk density (BD), total porosity (TP), macroporosity (Mac), and microporosity (Mic). Soil penetration resistance (PR) and water content (SWC) were also evaluated. The wheat GY of the whole plot was close to the regional average and the yield between the zones differed significantly, i.e. 22 % higher in Z1 than in Z2. No significant variation in Mic was observed between zones, but Z1 had higher Corg levels, SWC, TP and Mac and lower BD than Z2 in both soil layers, as well as a lower PR than Z2 in the 0.00-0.10 m layer. Therefore, soil physical conditions were more restrictive in Z2, in agreement with wheat yield and zone yield potential defined a priori, based on the harvest maps. Soil WIC in Z1 was significantly higher (30 %) than in Z2, in agreement with the results of TP and Mac which were also higher in Z1 in both soil layers. The correlation analysis of data of the two layers showed a positive relationship between wheat GY and the soil properties TP, SWC and WIC.

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Information underlying analyses of coffee fertilization systems should consider both the soil and the nutritional status of plants. This study investigated the spatial relationship between phosphorus (P) levels in coffee plant tissues and soil chemical and physical properties. The study was performed using two arabica and one canephora coffee variety. Sampling grids were established in the areas, and the points georeferenced. The assessed properties of the soil were levels of available phosphorus (P-Mehlich), remaining phosphorus (P-rem) and particle size, and of the plant tissue, phosphorus levels (foliar P). The data were subjected to descriptive statistical analysis, correlation analysis, cluster analysis, and probability tests. Geostatistical and trend analyses were only performed for pairs of variables with significant linear correlation. The spatial variability for foliar P content was high for the variety Catuai and medium for the other evaluated plants. Unlike P-Mehlich, the variability in P-rem of the soil indicated the nutritional status of this nutrient in the plant.

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The Brazilian savanna is a mosaic of phytophysiognomies influenced by edaphic and topographic factors that range from the occurrence of fires to anthropic disturbance. The goal of this study was a comparative analysis between two cerrado areas in southeastern Goiás, relating the floristic composition and structure of the vegetation to soil properties to better understand the physiognomic characteristics of the region. Twenty-five 20 × 20 m plots were used. All plants with circumference at breast height of more than 15 cm were measured. Soil samples collected at a depth of 0-20 cm were subjected to physical and chemical analyses. Canonical correspondence analysis (CCA) was used to detect possible correlations between the soil properties and species abundance and distribution. The density and total basal area were 1,647 ind/ha and 15.57 m2/ha, respectively, in Ouroana. At this site, 107 species were sampled. In Montes Claros de Goiás, the density and total basal area were 781 ind/ha and 17.62 m2/ha, and 120 species were sampled. The soil texture of Ouroana was sandy and significantly different from the medium to clayey texture of Montes Claros. The soils of both areas are dystrophic, however, more fertile in Montes Claros and aluminum-toxic in Ouroana. The species of vegetation were distributed according to soil fertility levels. The CCAs grouped species according to soil properties that defined location and abundance as well as the phytophysiognomies of the studied areas.

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A number of geophysical methods, such as ground-penetrating radar (GPR), have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, the stochastic inversion of such data within a coupled geophysical-hydrological framework may allow for the effective estimation of vadose zone hydraulic parameters and their corresponding uncertainties. A critical issue in stochastic inversion is choosing prior parameter probability distributions from which potential model configurations are drawn and tested against observed data. A well chosen prior should reflect as honestly as possible the initial state of knowledge regarding the parameters and be neither overly specific nor too conservative. In a Bayesian context, combining the prior with available data yields a posterior state of knowledge about the parameters, which can then be used statistically for predictions and risk assessment. Here we investigate the influence of prior information regarding the van Genuchten-Mualem (VGM) parameters, which describe vadose zone hydraulic properties, on the stochastic inversion of crosshole GPR data collected under steady state, natural-loading conditions. We do this using a Bayesian Markov chain Monte Carlo (MCMC) inversion approach, considering first noninformative uniform prior distributions and then more informative priors derived from soil property databases. For the informative priors, we further explore the effect of including information regarding parameter correlation. Analysis of both synthetic and field data indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when we combine these data with a realistic, informative prior.

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A statewide study was conducted to develop regression equations for estimating flood-frequency discharges for ungaged stream sites in Iowa. Thirty-eight selected basin characteristics were quantified and flood-frequency analyses were computed for 291 streamflow-gaging stations in Iowa and adjacent States. A generalized-skew-coefficient analysis was conducted to determine whether generalized skew coefficients could be improved for Iowa. Station skew coefficients were computed for 239 gaging stations in Iowa and adjacent States, and an isoline map of generalized-skew-coefficient values was developed for Iowa using variogram modeling and kriging methods. The skew map provided the lowest mean square error for the generalized-skew- coefficient analysis and was used to revise generalized skew coefficients for flood-frequency analyses for gaging stations in Iowa. Regional regression analysis, using generalized least-squares regression and data from 241 gaging stations, was used to develop equations for three hydrologic regions defined for the State. The regression equations can be used to estimate flood discharges that have recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years for ungaged stream sites in Iowa. One-variable equations were developed for each of the three regions and multi-variable equations were developed for two of the regions. Two sets of equations are presented for two of the regions because one-variable equations are considered easy for users to apply and the predictive accuracies of multi-variable equations are greater. Standard error of prediction for the one-variable equations ranges from about 34 to 45 percent and for the multi-variable equations range from about 31 to 42 percent. A region-of-influence regression method was also investigated for estimating flood-frequency discharges for ungaged stream sites in Iowa. A comparison of regional and region-of-influence regression methods, based on ease of application and root mean square errors, determined the regional regression method to be the better estimation method for Iowa. Techniques for estimating flood-frequency discharges for streams in Iowa are presented for determining ( 1) regional regression estimates for ungaged sites on ungaged streams; (2) weighted estimates for gaged sites; and (3) weighted estimates for ungaged sites on gaged streams. The technique for determining regional regression estimates for ungaged sites on ungaged streams requires determining which of four possible examples applies to the location of the stream site and its basin. Illustrations for determining which example applies to an ungaged stream site and for applying both the one-variable and multi-variable regression equations are provided for the estimation techniques.

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This tutorial review details some of the recent advances in signal analyses applied to event-related potential (ERP) data. These "electrical neuroimaging" analyses provide reference-independent measurements of response strength and response topography that circumvent statistical and interpretational caveats of canonical ERP analysis methods while also taking advantage of the greater information provided by high-density electrode montages. Electrical neuroimaging can be applied across scales ranging from group-averaged ERPs to single-subject and single-trial datasets. We illustrate these methods with a tutorial dataset and place particular emphasis on their suitability for studies of clinical and/or developmental populations.

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The aim of this work was to quantify low molecular weight organic acids in the rhizosphere of plants grown in a sewage sludge-treated media, and to assess the correlation between the release of the acids and the concentrations of trace-elements in the shoots of the plants. The species utilized in the experiment were cultivated in sand and sewage sludge-treated sand. The acetic, citric, lactic, and oxalic acids, were identified and quantified by high performance liquid chromatography in samples collected from a hydroponics system. Averages obtained from each treatment, concentration of trace elements in shoots and concentration of organic acids in the rhizosphere, were compared by Tukey test, at 5% of probability. Linear correlation analysis was applied to verify an association between the concentrations of organic acids and of trace elements. The average composition of organic acids for all plants was: 43.2, 31.1, 20.4 and 5.3% for acetic, citric, lactic, and oxalic acids, respectively. All organic acids evaluated, except for the citric acid, showed a close statistical agreement with the concentrations of Cd, Cu, Ni, and Zn found in the shoots. There is a positive relationship between organic acids present in the rhizosphere and trace element phytoavailability.

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The objective of this work was to elevate gradient effect on diversity of Collembola, in a temperate forest on the northeast slope of Iztaccíhuatl Volcano, Mexico. Four expeditions were organized from November 2003 to August 2004, at four altitudes (2,753, 3,015, 3,250 and 3,687 m a.s.l.). In each site, air temperature, CO2 concentration, humidity, and terrain inclination were measured. The influence of abiotic factors on faunal composition was evaluated, at the four collecting sites, with canonical correspondence analyses (CCA). A total of 24,028 specimens were obtained, representing 12 families, 44 genera and 76 species. Mesaphorura phlorae, Proisotoma ca. tenella and Parisotoma ca. notabilis were the most abundant species. The highest diversity and evenness were recorded at 3,250 m (H' = 2.85; J' = 0.73). Canonical analyses axes 1 and 2 of the CCA explained 67.4% of the variance in species composition, with CO2 and altitude best explaining axis 1, while slope and humidity were better correlated to axis 2. The results showed that CO2 is an important factor to explain Collembola species assemblage, together with slope and humidity.

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We tested the performance of transcutaneous oxygen monitoring (TcPO2) and pulse oximetry (tcSaO2) in detecting hypoxia in critically ill neonatal and pediatric patients. In 54 patients (178 data sets) with a mean age of 2.4 years (range 1 to 19 years), arterial saturation (SaO2) ranged from 9.5 to 100%, and arterial oxygen tension (PaO2) from 16.4 to 128 mmHg. Linear correlation analysis of pulse oximetry vs measured SaO2 revealed an r value of 0.95 (p less than 0.001) with an equation of y = 21.1 + 0.749x, while PaO2 vs tcPO2 showed a correlation coefficient of r = 0.95 (p less than 0.001) with an equation of y = -1.04 + 0.876x. The mean difference between measured SaO2 and tcSaO2 was -2.74 +/- 7.69% (range +14 to - 29%) and the mean difference between PaO2 and tcPO2 was +7.43 +/- 8.57 mmHg (range -14 to +49 mmHg). Pulse oximetry was reliable at values above 65%, but was inaccurate and overestimated the arterial SaO2 at lower values. TcPO2 tended to underestimate the arterial value with increasing PaO2. Pulse oximetry had the best sensitivity to specificity ratio for hypoxia between 65 and 90% SaO2; for tcPO2 the best results were obtained between 35 and 55 mmHg PaO2.

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The objectives of this work were to evaluate the richness and diversity of the Poduromorpha fauna in two biotopes in Restinga de Maricá, RJ, Brazil, to identify the characteristic species of each biotope and to determine the relationships between the community structure and the abiotic environmental parameters. Representatives of the Poduromorpha (Collembola) order were studied under an ecological viewpoint in halophyte-psammophyte vegetation and foredune zone in preserved areas of Restinga de Maricá, a sand dune environment in the state of Rio de Janeiro, Brazil. The foredune zone showed the highest diversity, richness and equitability of springtail species. Differences in the fundamental, accessory and accidental species in each environment were encountered. Paraxenylla piloua was found to be an indicator species of the halophyte-psammophyte vegetation, while Friesea reducta, Pseudachorutes difficilis and Xenylla maritima were indicators of the foredune zone. The canonical correspondence analysis indicated pH, organic matter content and soil humidity as the most important factors influencing the spatiotemporal distribution of the species.

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BACKGROUND: The diagnosis of malignant hematologic diseases has become increasingly complex during the last decade. It is based on the interpretation of results from different laboratory analyses, which range from microscopy to gene expression profiling. Recently, a method for the analysis of RNA phenotypes has been developed, the nCounter technology (Nanostring® Technologies), which allows for simultaneous quantification of hundreds of RNA molecules in biological samples. We evaluated this technique in a Swiss multi-center study on eighty-six samples from acute leukemia patients. METHODS: mRNA and protein profiles were established for normal peripheral blood and bone marrow samples. Signal intensities of the various tested antigens with surface expression were similar to those found in previously performed Affymetrix microarray analyses. Acute leukemia samples were analyzed for a set of twenty-two validated antigens and the Pearson Correlation Coefficient for nCounter and flow cytometry results was calculated. RESULTS: Highly significant values between 0.40 and 0.97 were found for the twenty-two antigens tested. A second correlation analysis performed on a per sample basis resulted in concordant results between flow cytometry and nCounter in 44-100% of the antigens tested (mean = 76%), depending on the number of blasts present in a sample, the homogeneity of the blast population, and the type of leukemia (AML or ALL). CONCLUSIONS: The nCounter technology allows for fast and easy depiction of a mRNA profile from hematologic samples. This technology has the potential to become a valuable tool for the diagnosis of acute leukemias, in addition to multi-color flow cytometry.

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Huntington's disease is an incurable neurodegenerative disease caused by inheritance of an expanded cytosine-adenine-guanine (CAG) trinucleotide repeat within the Huntingtin gene. Extensive volume loss and altered diffusion metrics in the basal ganglia, cortex and white matter are seen when patients with Huntington's disease (HD) undergo structural imaging, suggesting that changes in basal ganglia-cortical structural connectivity occur. The aims of this study were to characterise altered patterns of basal ganglia-cortical structural connectivity with high anatomical precision in premanifest and early manifest HD, and to identify associations between structural connectivity and genetic or clinical markers of HD. 3-Tesla diffusion tensor magnetic resonance images were acquired from 14 early manifest HD subjects, 17 premanifest HD subjects and 18 controls. Voxel-based analyses of probabilistic tractography were used to quantify basal ganglia-cortical structural connections. Canonical variate analysis was used to demonstrate disease-associated patterns of altered connectivity and to test for associations between connectivity and genetic and clinical markers of HD; this is the first study in which such analyses have been used. Widespread changes were seen in basal ganglia-cortical structural connectivity in early manifest HD subjects; this has relevance for development of therapies targeting the striatum. Premanifest HD subjects had a pattern of connectivity more similar to that of controls, suggesting progressive change in connections over time. Associations between structural connectivity patterns and motor and cognitive markers of disease severity were present in early manifest subjects. Our data suggest the clinical phenotype in manifest HD may be at least partly a result of altered connectivity. Hum Brain Mapp 36:1728-1740, 2015. © 2015 Wiley Periodicals, Inc.

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Background MicroRNAs (miRNAs) are short non-coding regulatory RNAs that control gene expression usually producing translational repression and gene silencing. High-throughput sequencing technologies have revealed heterogeneity at length and sequence level for the majority of mature miRNAs (IsomiRs). Most isomiRs can be explained by variability in either Dicer1 or Drosha cleavage during miRNA biogenesis at 5" or 3" of the miRNA (trimming variants). Although isomiRs have been described in different tissues and organisms, their functional validation as modulators of gene expression remains elusive. Here we have characterized the expression and function of a highly abundant miR-101 5"-trimming variant (5"-isomiR-101). Results The analysis of small RNA sequencing data in several human tissues and cell lines indicates that 5"-isomiR-101 is ubiquitously detected and a highly abundant, especially in the brain. 5"- isomiR-101 was found in Ago-2 immunocomplexes and complementary approaches showed that 5"-isomiR-101 interacted with different members of the silencing (RISC) complex. In addition, 5"-isomiR-101 decreased the expression of five validated miR-101 targets, suggesting that it is a functional variant. Both the binding to RISC members and the degree of silencing were less efficient for 5"-isomiR-101 compared with miR-101. For some targets, both miR-101 and 5"-isomiR-101 significantly decreased protein expression with no changes in the respective mRNA levels. Although a high number of overlapping predicted targets suggest similar targeted biological pathways, a correlation analysis of the expression profiles of miR-101 variants and predicted mRNA targets in human brains at different ages, suggest specific functions for miR-101- and 5"-isomiR-101. Conclusions These results suggest that isomiRs are functional variants and further indicate that for a given miRNA, the different isomiRs may contribute to the overall effect as quantitative and qualitative fine-tuners of gene expression.