895 resultados para discriminant analysis and cluster analysis
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RATIONALE: An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment. OBJECTIVES: To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes. METHODS: We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France. MEASUREMENTS: We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. MAIN RESULTS: The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were <or= 1.1% among patients in class I and <or= 1.9% among patients in class II. CONCLUSIONS: Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.
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The objective of this study was to identify gliadin band patterns and the extent of genetic diversity in durum wheat genotypes from Northwestern Iran and the Republic of Azerbaijan. Gliadins from 46 landraces and four cultivars were evaluated through acid PAGE analyses. Sixty-six polymorphic bands and 81 patterns were identified. Twenty-four different motility bands and 22 patterns were found in the ω gliadin region with 14 polymorph bands and 20 patterns for α and γ gliadins, and 14 bands and 19 different patterns for β gliadins. The combination of these patterns generated 38 and 39 combinations for Gli-1 and Gli-2 loci, respectively. The genetic diversity index (H) was higher for α gliadins (0.924), followed by ω and γ gliadins (0.899 and 0.878, respectively), and for β gliadin patterns (0.866). Extensive polymorphism (H = 0.875) was observed in four gliadin pattern regions, with higher genetic diversity in the Iranian landraces than in the Azerbaijani ones. Each genotype had special identifying patterns in the gliadin acid PAGE analysis, and cluster analysis based on Jaccard's similarity coefficients formed six groups. Gliadin has a simple, repeatable and economic analysis, and can be used in genetic studies
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AbstractThe purpose of this study was to evaluate the best operating conditions of ICP OES for the determination of Na, Ca, Mg, Sr and Fe in aqueous extract of crude oil obtained after hot extraction with organic solvents (ASTM D 6470-99 modified). Thus, the full factorial design and central composite design were used to optimize the best conditions for the flow of nebulization gas, the flow of auxiliary gas, and radio frequency power. After optimization of variables, a study to obtain correct classification of the 18 samples of aqueous extract of crude oils (E1 to E18) from three production and refining fields was carried out. Exploratory analysis of these extracts was performed by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), using the original variables as the concentration of the metals Na, Ca, Mg, Sr and Fe determined by ICP OES.
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The calyxes of Hibiscus sabdariffa are used in traditional medicine around the world. However, quality assurance protocols and chemical variability have not been previously analyzed. In the present study, chemical characterization of a set of samples of H. sabdariffa calyxes commercialized in Colombia was accomplished with the aim to explore the chemical variability among them. Chemometrics-based analyses on the data obtained from the HPLC-UV-DAD-derived profiles were then performed. Thus, the pre-processed single-wavelength data were subjected to principal component analysis (PCA). The PCA-derived results evidenced different groups which were well-correlated to the corresponding total phenolic and total anthocyanin contents. Multi-wavelength chromatographic (HPLC-UV-DAD surfaces) data were additionally examined via parallel factor analysis (PARAFAC) as data reduction method and the obtained loadings were subsequently submitted to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). Results were thus consistent with those from single-wavelength data. PCA loadings were employed to determine those chemical components responsible for the data variance and OPLS-DA model, constructed from PARAFAC loadings, and indicated differentiation according total anthocyanin contents among samples. The present chemometric analysis therefore demonstrated to be an excellent tool for differentiation of H. sabdariffacalyxes according to their chemical composition.
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Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.
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Nutritional status of eight 1.0 and 4.7 years old clones of Eucalyptus grandis, cultivated in a medium textured Ustults - US - and a Quartzipsamments - PS - soils, in Lençóis Paulista, São Paulo, were evaluated by the Diagnosis and Recommendation Integrated System (DRIS) and Critical Level (CL) methods. Based on multivariate discriminant analysis, the DRIS indices described the nutritional status of trees better in relation to tree age and soil type than in relation to nutrient composition. Spearman's correlation coefficients showed statistically significant relationships between volumetric tree growth and nutrients when applying DRIS indices or foliar nutrient concentrations. However, the DRIS indices indicated a lower number of trees with nutritional deficiencies, in relation to the CL method. According to the CL method, P, S, and Ca were deficient in the majority of the soils and tree age categories. By the DRIS method, Ca was the only deficient nutrient in PS soils, and appeared to be particularly limited in one-year-old trees. In conclusion, the DRIS method was more efficient than the CL method in evaluating the nutritional status of eucalyptus trees.
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The histopathology of the liver is fundamental for the differential diagnosis between intra- and extrahepatic causes of neonatal cholestasis. However, histopathological findings may overlap and there is disagreement among authors concerning those which could discriminate between intra- and extrahepatic cholestasis. Forty-six liver biopsies (35 wedge biopsies and 11 percutaneous biopsies) and one specimen from a postmortem examination, all from patients hospitalized for neonatal cholestasis in the Pediatrics Service of Hospital de Clínicas de Porto Alegre, were prospectively studied using a specially designed histopathological protocol. At least 4 of 5 different stains were used, and 46 hepatic histopathological variables related to the differential diagnosis of neonatal cholestasis were studied. The findings were scored for severity on a scale from 0 to 4. Sections which showed less than 3 portal spaces were excluded from the study. Sections were examined by a pathologist who was unaware of the final diagnosis of each case. Bile tract permeability was defined by scintigraphy of the bile ducts and operative cholangiography. The F test and discriminant analysis were used as statistical methods for the study of the hepatic histopathological variables. The chi-square method with Yates correction was used to relate the age of the patients on the date of the histopathological study to the discriminatory variables between intra- and extrahepatic cholestasis selected by the discriminant function test. The most valuable hepatic histopathological variables for the discrimination between intra- and extrahepatic cholestasis, in decreasing order of importance, were periportal ductal proliferation, portal ductal proliferation, portal expansion, cholestasis in neoductules, foci of myeloid metaplasia, and portal-portal bridges. The only variable which pointed to the diagnosis of intrahepatic cholestasis was myeloid metaplasia. Due to the small number of patients who were younger than 60 days on the date of the histopathological study (N = 6), no variable discriminated between intra- and extrahepatic cholestasis before the age of 2 months and all of them, except for the portal expansion, were discriminatory after this age. In infants with cholestasis, foci of myeloid metaplasia, whenever present in the liver biopsy, suggested intrahepatic cholestasis. Periportal ductal proliferation, portal ductal proliferation, portal expansion, cholestasis in neoductules, portal cholestasis and portal-portal bridges suggested extrahepatic obstructive cholestasis.
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The predominant type of liver alteration in asymptomatic or oligosymptomatic chronic male alcoholics (N = 169) admitted to a psychiatric hospital for detoxification was classified by two independent methods: liver palpation and multiple quadratic discriminant analysis (QDA), the latter applied to two parameters reported by the patient (duration of alcoholism and daily amount ingested) and to the data obtained from eight biochemical blood determinations (total bilirubin, alkaline phosphatase, glycemia, potassium, aspartate aminotransferase, albumin, globulin, and sodium). All 11 soft and sensitive, and 13 firm and sensitive livers formed fully concordant groups as determined by QDA. Among the 22 soft and not sensitive livers, 95% were concordant by QDA grouping. Concordance rates were low (55%) in the 73 firm and not sensitive livers, and intermediate (76%) in the 50 not palpable livers. Prediction of the liver palpation characteristics by QDA was 95% correct for the firm and not sensitive livers and moderate for the other groups. On a preliminary basis, the variables considered to be most informative by QDA were the two anamnestic data and bilirubin levels, followed by alkaline phosphatase, glycemia and potassium, and then by aspartate aminotransferase and albumin. We conclude that, when biopsies would be too costly or potentially injurious to the patients to varying extents, clinical data could be considered valid to guide patient care, at least in the three groups (soft, not sensitive; soft, sensitive; firm, sensitive livers) in which the two noninvasive procedures were highly concordant in the present study.
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The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.
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In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.
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Identification of functional properties of wheat flour by specific tests allows genotypes with appropriate characteristics to be selected for specific industrial uses. The objective of wheat breeding programs is to improve the quality of germplasm bank in order to be able to develop wheat with suitable gluten strength and extensibility for bread making. The aim of this study was to evaluate 16 wheat genotypes by correlating both glutenin subunits of high and low molecular weight and gliadin subunits with the physicochemical characteristics of the grain. Protein content, sedimentation volume, sedimentation index, and falling number values were analyzed after the grains were milled. Hectoliter weight and mass of 1000 seeds were also determined. The glutenin and gliadin subunits were separated using polyacrylamide gel in the presence of sodium dodecyl sulfate. The data were evaluated using variance analysis, Pearson's correlation, principal component analysis, and cluster analysis. The IPR 85, IPR Catuara TM, T 091015, and T 091069 genotypes stood out from the others, which indicate their possibly superior grain quality with higher sedimentation volume, higher sedimentation index, and higher mass of 1000 seeds; these genotypes possessed the subunits 1 (Glu-A1), 5 + 10 (Glu-D1), c (Glu-A3), and b (Glu-B3), with exception of T 091069 genotype that possessed the g allele instead of b in the Glu-B3.
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Introduction: Numerous studies examined the associations between socio-demographic, economic and individual factors and chronic kidney disease (CKD) outcomes and observed that the associations were complex and multifactorial. Socioeconomic factors can be evaluated by a model of social vulnerability (SV). Objective: To analyze the impact of SV on the outcomes of predialysis patients. Methods: Demographic, clinical and laboratory data were collected from a cohort of patients with predialysis stage 3 to 5 who were treated by an interdisciplinary team (January 2002 and December 2009) in Minas Gerais, Brazil. Factor, cluster and discriminant analysis were performed in sequence to identify the most important variables and develop a model of SV that allowed for classification of the patients as vulnerable or non-vulnerable. Cox regression was performed to examine the impact of SV on the outcomes of mortality and need for renal replacement therapy (RRT). Results: Of the 209 patients examined, 29.4% were classified as vulnerable. No significance difference was found between the vulnerable and non-vulnerable groups regarding either mortality (log rank: 0.23) or need for RRT (log rank: 0.17). In the Cox regression model, the hazard ratios (HRs) for the unadjusted and adjusted impact of SV on mortality were found to be 1.87 (confidence interval [CI]: 0.64-5.41) and 1.47 (CI: 0.35-6.0), respectively, and the unadjusted and adjusted impact of need for RRT to be 1.85 (CI: 0.71-4.8) and 2.19 (CI: 0.50-9.6), respectively. Conclusion: These findings indicate that SV did not influence the outcomes of patients with predialysis CKD treated in an interdisciplinary center.
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Determinative common factors of currency and financial crisis. This paper identifies and evaluates determinative common factors of currency and financial crisis in relation to 86 crises episodes between 1970-2004, based on factor analysis, cluster and discriminant analysis. One evidenced that the rise of the ratios of domestic credit, fiscal deficit and residents bank deposits to the GDP is inherent to the different types of crises classified for economic literature. It was also identified as common factors to these episodes some indicators that capture the excessive monetary expansion of the economies and that reflect the fall in international reserves, represented by M2/Reserves and Imports/Reserves ratios and also the total volume of international reserves.
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I t was hypothesized that the freeze/thaw cycles endured by icewine grapes would change their chemical composition, resulting in unique chemical fingerprint and sensory properties, and would be affected by harvest date (HD) and crop level (CL). The objectives were: 1) to identify odour-active compounds using gas chromatographic and sensory analysis; 2) to determine the effect of CL and HD on these compounds; 3) to determine the icewine sensory profiles; 4) to correlate analytical and sensory results for an overall icewine profile. CharmAnalysis™ determined the Top 15 odour-potent compounds in Vidal and Riesling icewine and table wines; 24 and 23 compounds, respectively. The majority of the compounds had the highest concentrations in the icewines compared to table wines. These compounds were used as the foundation for assessing differences in icewine chemical profiles from different HD and CL. Vidal and Riesling icewine were made from grapes picked at different HD; HI : 19 December; H2: 29 December; H3: 18 January; H4: 11 February (Vidal only). HI wines differed from H3 and H4 wines in both Vidal and Riesling for aroma compounds and sensory profiles. - Three·CL [control (fully cropped), cluster thin at fruit set to one basal cluster/shoot (TFS), and cluster thin at veraison to one basal cluster/shoot (TV)] were evaluated for Riesling and Vidal cultivars over two seasons. Vidal icewines had the highest concentration of aroma compounds in the control and TV icewines in 2003 and in TFS icewines in 2004. In Riesling, most aroma compounds had the highest concentration in the TV icewines and the lowest concentration in the TFS wine for both years. The thinned treatments were associated with almost all of the sensory attributes in both cultivars, both years. HD and CL affected the chemical variables, aroma compounds and sensory properties of Vidal and Riesling icewines and freeze/thaw events changed their sensory profile. The most odour-potent compounds were p-damascenone, cis-rose oxide, 1- octen-3-ol, 4-vinylguaiacol, ethyl octanoate, and ethyl hexanoate. The role of Pdamascenone as a marker compound for icewine requires further investigation. This research provides a strong foundation for the understanding the odour-active volatiles and sensory profiles important to icewine.
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This thesis entitled “Studies on Nitrifying Microorganisms in Cochin Estuary and Adjacent Coastal Waters” reports for the first time the spatial andtemporal variations in the abundance and activity of nitrifiers (Ammonia oxidizingbacteria-AOB; Nitrite oxidizing bacteria- NOB and Ammonia oxidizing archaea-AOA) from the Cochin Estuary (CE), a monsoon driven, nutrient rich tropicalestuary along the southwest coast of India. To fulfil the above objectives, field observations were carried out for aperiod of one year (2011) in the CE. Surface (1 m below surface) and near-bottomwater samples were collected from four locations (stations 1 to 3 in estuary and 4 in coastal region), covering pre-monsoon, monsoon and post-monsoon seasons. Station 1 is a low saline station (salinity range 0-10) with high freshwater influx While stations 2 and 3 are intermediately saline stations (salinity ranges 10-25). Station 4 is located ~20 km away from station 3 with least influence of fresh water and is considered as high saline (salinity range 25- 35) station. Ambient physicochemical parameters like temperature, pH, salinity, dissolved oxygen (DO), Ammonium, nitrite, nitrate, phosphate and silicate of surface and bottom waters were measured using standard techniques. Abundance of Eubacteria, total Archaea and ammonia and nitrite oxidizing bacteria (AOB and NOB) were quantified using Fluorescent in situ Hybridization (FISH) with oligonucleotide probes labeled withCy3. Community structure of AOB and AOA was studied using PCR Denaturing Gradient Gel Electrophoresis (DGGE) technique. PCR products were cloned and sequenced to determine approximate phylogenetic affiliations. Nitrification rate in the water samples were analyzed using chemical NaClO3 (inhibitor of nitrite oxidation), and ATU (inhibitor of ammonium oxidation). Contribution of AOA and AOB in ammonia oxidation process was measured based on the recovered ammonia oxidation rate. The contribution of AOB and AOA were analyzed after inhibiting the activities of AOB and AOA separately using specific protein inhibitors. To understand the factors influencing or controlling nitrification, various statistical tools were used viz. Karl Pearson’s correlation (to find out the relationship between environmental parameters, bacterial abundance and activity), three-way ANOVA (to find out the significant variation between observations), Canonical Discriminant Analysis (CDA) (for the discrimination of stations based on observations), Multivariate statistics, Principal components analysis (PCA) and Step up multiple regression model (SMRM) (First order interaction effects were applied to determine the significantly contributing biological and environmental parameters to the numerical abundance of nitrifiers). In the CE, nitrification is modulated by the complex interplay between different nitrifiers and environmental variables which in turn is dictated by various hydrodynamic characteristics like fresh water discharge and seawater influx brought in by river water discharge and flushing. AOB in the CE are more adapted to varying environmental conditions compared to AOA though the diversity of AOA is higher than AOB. The abundance and seasonality of AOB and NOB is influenced by the concentration of ammonia in the water column. AOB are the major players in modulating ammonia oxidation process in the water column of CE. The distribution pattern and seasonality of AOB and NOB in the CE suggest that these organisms coexist, and are responsible for modulating the entire nitrification process in the estuary. This process is fuelled by the cross feeding among different nitrifiers, which in turn is dictated by nutrient levels especially ammonia. Though nitrification modulates the increasing anthropogenic ammonia concentration the anthropogenic inputs have to be controlled to prevent eutrophication and associated environmental changes.