936 resultados para Nonparametric discriminant analysis
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Members of the Chlamydiales order all share a biphasic lifecycle alternating between small infectious particles, the elementary bodies (EBs) and larger intracellular forms able to replicate, the reticulate bodies. Whereas the classical Chlamydia usually harbours round-shaped EBs, some members of the Chlamydia-related families display crescent and star-shaped morphologies by electron microscopy. To determine the impact of fixative methods on the shape of the bacterial cells, different buffer and fixative combinations were tested on purified EBs of Criblamydia sequanensis, Estrella lausannensis, Parachlamydia acanthamoebae, and Waddlia chondrophila. A linear discriminant analysis was performed on particle metrics extracted from electron microscopy images to recognize crescent, round, star and intermediary forms. Depending on the buffer and fixatives used, a mixture of alternative shapes were observed in varying proportions with stars and crescents being more frequent in C. sequanensis and P. acanthamoebae, respectively. No tested buffer and chemical fixative preserved ideally the round shape of a majority of bacteria and other methods such as deep-freezing and cryofixation should be applied. Although crescent and star shapes could represent a fixation artifact, they certainly point towards a diverse composition and organization of membrane proteins or intracellular structures rather than being a distinct developmental stage.
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BACKGROUND: Many factors affect survival in haemodialysis (HD) patients. Our aim was to study whether quality of clinical care may affect survival in this population, when adjusted for demographic characteristics and co-morbidities. METHODS: We studied survival in 553 patients treated by chronic HD during March 2001 in 21 dialysis facilities in western Switzerland. Indicators of quality of care were established for anaemia control, calcium and phosphate product, serum albumin, pre-dialysis blood pressure (BP), type of vascular access and dialysis adequacy (spKt/V) and their baseline values were related to 3-year survival. The modified Charlson co-morbidity index (including age) and transplantation status were also considered as a predictor of survival. RESULTS: Three-year survival was obtained for 96% of the patients; 39% (211/541) of these patients had died. The 3-year survival was 50, 62 and 69%, respectively, in patients who had 0-2, 3 and >or=4 fulfilled indicators of quality of care (test for linear trend, P < 0.001). In a Cox multivariate analysis model, the absence of transplantation, a higher modified Charlson's score, decreased fulfilment of indicators of good clinical care and low pre-dialysis systolic BP were independent predictors of death. CONCLUSION: Good clinical care improves survival in HD patients, even after adjustment for availability of transplantation and co-morbidities.
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Systematic pig slurry application to crop soils may lead to the accumulation of heavy metals in regions with intensive pig raising. The aim of this study was to evaluate the accumulation of Cu, Zn and Mn in soils under systematic pig slurry application. For this purpose, soil samples were collected from two of the most representative watersheds of Santa Catarina where the predominant activity is pig raising. In each watershed, 12 properties were chosen to evaluate the different systems of pig husbandry (complete cycle (CC), farrowing (FaU) and finishing units (FiU)). Based on information of the producers, soil samples were collected in areas with and without systematic manure application. To determine the total Cu, Zn and Mn content in soils and manure, a methodology proposed by the Environmental Protection Agency of the United States (USEPA), method nº 3050B, was used. For the available heavy metal content, Cu and Zn was extracted with HCl 0.1 mol L-1 and Mn with KCl 1 mol L-1. Data were subjected to multivariate analysis, using the canonical discriminant analysis to identify the metals that best differentiate the soils studied within each swine housing system. Successive pig slurry applications cause an increase in Cu, Zn and Mn availability in the soil and this indicates the need for monitoring of the metal concentrations over time. The critical values of Cu in the soil can be reached and exceeded more rapidly than Zn. The results showed that the soil type may be one of the attribute underlying the determination of public policies in pig raising and waste management because soils such as Inceptisols were shown to be more prone to possible contamination since they may more rapidly reach total critical Cu levels.
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This article presents an experimental study about the classification ability of several classifiers for multi-classclassification of cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland lawenforcement authorities regularly ask forensic laboratories to determinate the chemotype of a seized cannabisplant and then to conclude if the plantation is legal or not. This classification is mainly performed when theplant is mature as required by the EU official protocol and then the classification of cannabis seedlings is a timeconsuming and costly procedure. A previous study made by the authors has investigated this problematic [1]and showed that it is possible to differentiate between drug type (illegal) and fibre type (legal) cannabis at anearly stage of growth using gas chromatography interfaced with mass spectrometry (GC-MS) based on therelative proportions of eight major leaf compounds. The aims of the present work are on one hand to continueformer work and to optimize the methodology for the discrimination of drug- and fibre type cannabisdeveloped in the previous study and on the other hand to investigate the possibility to predict illegal cannabisvarieties. Seven classifiers for differentiating between cannabis seedlings are evaluated in this paper, namelyLinear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Nearest NeighbourClassification (NNC), Learning Vector Quantization (LVQ), Radial Basis Function Support Vector Machines(RBF SVMs), Random Forest (RF) and Artificial Neural Networks (ANN). The performance of each method wasassessed using the same analytical dataset that consists of 861 samples split into drug- and fibre type cannabiswith drug type cannabis being made up of 12 varieties (i.e. 12 classes). The results show that linear classifiersare not able to manage the distribution of classes in which some overlap areas exist for both classificationproblems. Unlike linear classifiers, NNC and RBF SVMs best differentiate cannabis samples both for 2-class and12-class classifications with average classification results up to 99% and 98%, respectively. Furthermore, RBFSVMs correctly classified into drug type cannabis the independent validation set, which consists of cannabisplants coming from police seizures. In forensic case work this study shows that the discrimination betweencannabis samples at an early stage of growth is possible with fairly high classification performance fordiscriminating between cannabis chemotypes or between drug type cannabis varieties.
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Assuming selective vulnerability of short association U-fibers in early Alzheimer's disease (AD), we quantified demyelination of the surface white matter (dSWM) with magnetization transfer ratio (MTR) in 15 patients (Clinical Dementia Rating Scale [CDR] 0.5-1; Functional Assessment Staging [FAST]: 3-4) compared with 15 controls. MTRs were computed for 39 areas in each hemisphere. We found a bilateral MTR decrease in the temporal, cingulate, parietal, and prefrontal areas. With linear discriminant analysis, we successfully classified all the participants with 3 variates including the cuneus, parahippocampal, and superior temporal regions of the left hemisphere. The pattern of dSWM changed with the age of AD onset. In early onset patients, we found bilateral posterior demyelination spreading to the temporal areas in the left hemisphere. The late onset patients showed a distributed bilateral pattern with the temporal and cingulate areas strongly affected. A correlation with Mini Mental State Examination (MMSE), Lexis, and memory tests revealed the dSWM impact on cognition. A specific landscape of dSWM in early AD shows the potential of MTR imaging as an in vivo biomarker superior to currently used techniques.
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Araucaria angustifolia (Bert.) O. Kuntze is the main component of the Mixed Ombrophilous forest and, in the State of São Paulo, it is associated with a high diversity of soil organisms, essential for the maintenance of soil quality, making the conservation of this ecosystem a major and pressing challenge. The objective of this study was to identify the physical and chemical properties that are most closely correlated with dehydrogenase enzyme activity, basal respiration and microbial biomass under native (NF) and replanted (RF) Araucaria angustifolia forests in three regions of the state of São Paulo, in winter and summer. The main differentiating factors between the areas were also determined. Each forest was represented by three true replications; at each site, from around the araucaria trees, 15 soil samples (0-20 cm) were collected to evaluate the soil physical, chemical and microbiological properties. At the same points, forest litter was sampled to assess mass and chemical properties. The following microbiological properties were evaluated: microbial biomass carbon (MBC), basal respiration (CO2-C), metabolic quotient (Q: CO2), dehydrogenase enzyme activity (DHA) as well as the physical properties (moisture, bulk density, macroporosity and total porosity), soil chemical properties [pH, organic carbon (org-C), P, Ca, K, Mg, Al, H+Al], litter dry mass, and C, N and S contents. The data were subjected to analysis of variance (TWO-WAY: ANOVA). A Canonical Discriminant Analysis (CDA) and a Canonical Correlation Analysis (CCA) were also performed. In the soil under NF, the values of K, P, soil macroporosity, and litter dry mass were higher and Q: CO2 and DHA lower, regardless of the sampling period, and DHA was lower in winter. In the RF areas, the levels of moisture, porosity and Q: CO2 were higher in both sampling periods, and DHA was higher in winter. The MBC was only higher under NF in the summer, while the litter contents of C, N and S were greater in winter. In winter, CCA showed a high correlation of DHA with CO2-C, pH and H+Al, while in the summer org-C, moisture, Mg, pH and litter C were more associated with DHA and CO2-C. The CDA indicated H+Al, available P, total porosity, litter S content, and soil moisture as the most discriminating variables between NF and RF, but moisture was the most relevant, in both seasons and CO2-C only in winter. The combined analysis of CCA and CDA showed that the contribution of the microbiological variables to a differentiation of the areas was small at both samplings, which may indicate that the period after reforestation was long enough to allow an almost complete recovery of the microbial activity.
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Anti-doping authorities have high expectations of the athlete steroidal passport (ASP) for anabolic-androgenic steroids misuse detection. However, it is still limited to the monitoring of known well-established compounds and might greatly benefit from the discovery of new relevant biomarkers candidates. In this context, steroidomics opens the way to the untargeted simultaneous evaluation of a high number of compounds. Analytical platforms associating the performance of ultra-high pressure liquid chromatography (UHPLC) and the high mass-resolving power of quadrupole time-of-flight (QTOF) mass spectrometers are particularly adapted for such purpose. An untargeted steroidomic approach was proposed to analyse urine samples from a clinical trial for the discovery of relevant biomarkers of testosterone undecanoate oral intake. Automatic peak detection was performed and a filter of reference steroid metabolites mass-to-charge ratio (m/z) values was applied to the raw data to ensure the selection of a subset of steroid-related features. Chemometric tools were applied for the filtering and the analysis of UHPLC-QTOF-MS(E) data. Time kinetics could be assessed with N-way projections to latent structures discriminant analysis (N-PLS-DA) and a detection window was confirmed. Orthogonal projections to latent structures discriminant analysis (O-PLS-DA) classification models were evaluated in a second step to assess the predictive power of both known metabolites and unknown compounds. A shared and unique structure plot (SUS-plot) analysis was performed to select the most promising unknown candidates and receiver operating characteristic (ROC) curves were computed to assess specificity criteria applied in routine doping control. This approach underlined the pertinence to monitor both glucuronide and sulphate steroid conjugates and include them in the athletes passport, while promising biomarkers were also highlighted.
The 5th anniversary of "Patient Safety in Surgery" - from the Journal's origin to its future vision.
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A prospective study was undertaken to determine prognostic markers for patients with obstructive jaundice. Along with routine liver function tests, antipyrine clearance was determined in 20 patients. Four patients died after basal investigations. Five patients underwent definitive surgery. The remaining 11 patients were subjected to percutaneous transhepatic biliary decompression. Four patients died during the drainage period, while surgery was carried out for seven patients within 1-3 weeks of drainage. Of 20 patients, only six patients survived. Basal liver function tests were comparable in survivors and nonsurvivors. Discriminant analysis of the basal data revealed that plasma bilirubin, proteins and antipyrine half-life taken together had a strong association with mortality. A mathematical equation was derived using these variables and a score was computed for each patient. It was observed that a score value greater than or equal to 0.84 indicated survival. Omission of antipyrine half-life from the data, however, resulted in prediction of false security in 55% of patients. This study highlights the importance of addition of antipyrine elimination test to the routine liver function tests for precise identification of high risk patients.
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Despite numerous studies conducted on the lower limit of soil and its contact with saprolite layers, a great deal of work is left to standardize identification and annotation of these variables in the field. In shallow soils, the appropriately noting these limits or contacts is essential for determining their behavior and potential use. The aims of this study were to identify and define the field contact and/or transition zone between soil and saprolite in profiles of an Alisol derived from fine sandstone and siltstone/claystone in subtropical southern Brazil and to subsequently validate the field observations through a multivariate analysis of laboratory analytical data. In the six Alisol profiles evaluated, the sequence of horizons found was A, Bt, C, and Cr, where C was considered part of the soil due to its pedogenetic structure, and Cr was considered saprolite due to its rock structure. The morphological properties that were determined in the field and that were different between the B and C horizons and the Cr layer were color, structure, texture, and fragments of saprolite. According to the test of means, the properties that support the inclusion of the C horizon as part of the soil are sand, clay, water-dispersible clay, silt/clay ratio, macroporosity, total porosity, resistance to penetration, cation exchange capacity, Fe extracted by DCB, Al, H+Al, and cation exchange capacity of clay. The properties that support the C horizon as a transition zone are silt, Ca, total organic C, and Fe extracted by ammonium oxalate. Discriminant analysis indicated differences among the three horizons evaluated.
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Cova del Gegant is located near the city of Sitges (Barcelona, Spain). The cave is a small karst system which contains Upper Pleistocene archaeological and paleontological material (DauRa et al., 2005). The site was first excavated in 1954 and then in 1972 and 1974- (Viñas, 1972; Viñas & Villalta, 1975) and in 1985 and 1989 (maRtínez et al., 1985; moRa, 1988; maRtínez et al., 1990). Finally, in 2007, Grup de Recerca del Quaternari has restarted the archaeological research at Cova del Gegant (DauRa, 2008; DauRa et al., 2010). A human mandible was recovered during the first field season in 1954 and was recently published by DauRa et al. (2005). In the present study, we describe a new human tooth (left I2) that appeared, like the mandible, in a revision of the faunal material recovered from the site in 1974-1975. The specimen preserves the entire crown and the cervical two thirds of the root (Figure 1). The lack of the root apex makes it difficult to determine if the tooth was fully developed at the time of death. However, CT analysis reveals a pulp cavity that could be still open, suggesting root formation was incomplete. The specimen shows only slight dental wear corresponding to stage 2 of Molnar (1971 en Hillson, 1996). Morphologically, the crown shows slight shovelling and a lingual tubercle and appears similar to Neandertal incisors. Standard crown measurements (buccolingual diameter=7.7 mm; mesiodistal diameter= 7.3 mm) (Figure 2) suggest a fairly large tooth, particularly in the BL dimension, again resembling Neandertals in this regard. Discriminant analysis classified the Gegant incisor as Neandertal with a 99.8% posterior probability (Table 2). Association of this tooth with the previously described mandible is considered unlikely given the different ages at death estimated for each. Thus, there appear to be two individuals preserved in the sediments of the Gegant cave, one adult and one subadult (around 8-10 years old).
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Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.
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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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Metastatic melanomas are frequently refractory to most adjuvant therapies such as chemotherapies and radiotherapies. Recently, immunotherapies have shown good results in the treatment of some metastatic melanomas. Immune cell infiltration in the tumor has been associated with successful immunotherapy. More generally, tumor infiltrating lymphocytes (TILs) in the primary tumor and in metastases of melanoma patients have been demonstrated to correlate positively with favorable clinical outcomes. Altogether, these findings suggest the importance of being able to identify, quantify and characterize immune infiltration at the tumor site for a better diagnostic and treatment choice. In this paper, we used Fourier Transform Infrared (FTIR) imaging to identify and quantify different subpopulations of T cells: the cytotoxic T cells (CD8+), the helper T cells (CD4+) and the regulatory T cells (T reg). As a proof of concept, we investigated pure populations isolated from human peripheral blood from 6 healthy donors. These subpopulations were isolated from blood samples by magnetic labeling and purities were assessed by Fluorescence Activated Cell Sorting (FACS). The results presented here show that Fourier Transform Infrared (FTIR) imaging followed by supervised Partial Least Square Discriminant Analysis (PLS-DA) allows an accurate identification of CD4+ T cells and CD8+ T cells (>86%). We then developed a PLS regression allowing the quantification of T reg in a different mix of immune cells (e.g. Peripheral Blood Mononuclear Cells (PBMCs)). Altogether, these results demonstrate the sensitivity of infrared imaging to detect the low biological variability observed in T cell subpopulations.
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Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.
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In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.