Lack of Antilipoprotein Lipase Antibodies in Takayasu's Arteritis

Background. Antilipoprotein lipase (anti-LPL) antibodies were described in rheumatic diseases. In systemic lupus erythematosus they were highly associated with inflammatory markers and dyslipidemia, and may ultimately contribute to vascular damage. The relevance of this association in Takayasu's arteritis, which is characterized by major inflammatory process affecting vessels, has not been determined. Objectives. To analyze the presence of anti-LPL antibodies in patients with Takayasu's arteritis and its association with inflammatory markers and lipoprotein risk levels. Methods. Thirty sera from patients with Takayasu's arteritis, according to ACR criteria, were consecutively included. IgG anti-LPL was detected by a standard ELISA. Lipoprotein risk levels were evaluated according to NCEP/ATPIII. Inflammatory markers included ESR and CRP values. Results. Takayasu's arteritis patients had a mean age of 34 years old and all were females. Half of the patients presented high ESR and 60% elevated CRP. Lipoprotein NCEP risk levels were observed in approximately half of the patients: 53% for total cholesterol, 43% for triglycerides, 16% for HDL-c and 47% for LDL-c. In spite of the high frequency of dyslipidemia and inflammatory markers in these patients no anti-LPL were detected. Conclusions. The lack of anti-LPL antibodies in Takayasu's disease implies distinct mechanisms underlying dyslipidemia compared to systemic lupus erythematosus. Copyright (C) 2009 Jozelio Freire de Carvalho et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.

LIPSCHITZ CLASSIFICATION OF FUNCTIONS ON A HOLDER TRIANGLE

The problem of semialgebraic Lipschitz classification of quasihomogeneous polynomials on a Holder triangle is studied. For this problem, the ""moduli"" are described completely in certain combinatorial terms.

Definindo a arena política local: sistemas partidários municipais na federação brasileira

This article analyzes the Brazilian political system from the local perspective. Following Cox (1997), we review the problems with electoral coordination that emerge from a given institutional framework. Due to the characteristics of the Brazilian Federal system and its electoral rules, linkage between the three levels of government is not guaranteed a priori, but demands a coordinating effort by the parties' leadership. According to our hypothesis, the parties are capable of coordinating their election strategies at different levels in the party system. Regression models based on two-stage least squares (2SLS) and TOBIT, analyzing a panel of Brazilian municipalities with data from the 1994 and 2000 elections, show that the proportion of votes received by a party in a given election correlates closely with its previous votes in majoritarian elections. Despite institutional incentives, the Brazilian party system shows evidence that it is organized nationally to the extent that it links the competition for votes at the three levels of government (National, State, and Municipal).

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

DOES THE CHRONOTYPE CLASSIFICATION NEED TO BE UPDATED? PRELIMINARY FINDINGS

Traditionally, chronotype classification is based on the Morningness-Eveningness Questionnaire (MEQ). It is implicit in the classification that intermediate individuals get intermediate scores to most of the MEQ questions. However, a small group of individuals has a different pattern of answers. In some questions, they answer as ""morning-types"" and in some others they answer as ""evening-types,"" resulting in an intermediate total score. ""Evening-type"" and ""Morning-type"" answers were set as A(1) and A(4), respectively. Intermediate answers were set as A(2) and A(3). The following algorithm was applied: Bimodality Index = (Sigma A(1) x Sigma A(4))(2) - (Sigma A(2) x Sigma A(3))(2). Neither-types that had positive bimodality scores were classified as bimodal. If our hypothesis is validated by objective data, an update of chronotype classification will be required. (Author correspondence: brunojm@ymail.com)

Classification of normal swallowing and oropharyngeal dysphagia using wavelet

Oropharyngeal dysphagia is characterized by any alteration in swallowing dynamics which may lead to malnutrition and aspiration pneumonia. Early diagnosis is crucial for the prognosis of patients with dysphagia, and the best method for swallowing dynamics assessment is swallowing videofluoroscopy, an exam performed with X-rays. Because it exposes patients to radiation, videofluoroscopy should not be performed frequently nor should it be prolonged. This study presents a non-invasive method for the pre-diagnosis of dysphagia based on the analysis of the swallowing acoustics, where the discrete wavelet transform plays an important role to increase sensitivity and specificity in the identification of dysphagic patients. (C) 2008 Elsevier Inc. All rights reserved.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.

On the classification of mixed construction and demolition waste aggregate by porosity and its impact on the mechanical performance of concrete

The properties of recycled aggregate produced from mixed (masonry and concrete) construction and demolition (C&D) waste are highly variable, and this restricts the use of such aggregate in structural concrete production. The development of classification techniques capable of reducing this variability is instrumental for quality control purposes and the production of high quality C&D aggregate. This paper investigates how the classification of C&D mixed coarse aggregate according to porosity influences the mechanical performance of concrete. Concretes using a variety of C&D aggregate porosity classes and different water/cement ratios were produced and the mechanical properties measured. For concretes produced with constant volume fractions of water, cement, natural sand and coarse aggregate from recycled mixed C&D waste, the compressive strength and Young modulus are direct exponential functions of the aggregate porosity. Sink and float technique is a simple laboratory density separation tool that facilitates the separation of cement particles with lower porosity, a difficult task when done only by visual sorting. For this experiment, separation using a 2.2 kg/dmA(3) suspension produced recycled aggregate (porosity less than 17%) which yielded good performance in concrete production. Industrial gravity separators may lead to the production of high quality recycled aggregate from mixed C&D waste for structural concrete applications.

Spatial-temporal variation in coiled and straight morphotypes of Cylindrospermopsis raciborskii (Wolsz) Seenayya et Subba Raju (Cyanobacteria)

(Spatial-temporal variation in coiled and straight morphotypes of Cylindrospermopsis raciborskii (Wolsz) Seenayya et Subba Raju (Cyanobacteria)). This study reports the spatial and temporal behavior of straight and coiled morphotypes of C. raciborskii in a reservoir in Brazil`s semiarid region as well as the main factors responsible for the variability. Two set of samples were collected from the subsurface and bottom in the central region of a reservoir in two seasonal periods (dry January 2005; rainy June 2005) over 20-hour sampling periods during daylight (8 am, 12 pm and 4 pm) and dark (8 pm, 12 am and 4 am) hours. Measurements of abiotic parameters were determined concurrently to the sampling of biotic variables. Two C. raciborskii morphotypes were found in the reservoir: straight and coiled. There was no difference in density of the straight and coiled C. raciborskii morphotypes between the different sampling times for either season. Vertical differences were found in the distribution of both morphotypes in both seasons, with greater densities recorded at the subsurface. Densities of the two C. raciborskii morphotypes were greater in the dry season, with the density of the coiled morphotype at the surface two-fold greater than that of the straight morphotype and that found in the rainy season. The ecological success of the coiled morphotype was due to thermal stratification, whereas a mixed condition was determinant in the success of the straight morphotype.

A Brazilian registry of juvenile dermatomyositis: onset features and classification of 189 cases

Objective To describe onset features, classification and treatment of juvenile dermatomyositis (JDM) and juvenile polymyositis (JPM) from a multicentre registry. Methods Inclusion criteria were onset age lower than 18 years and a diagnosis of any idiopathic inflammatory myopathy (IIM) by attending physician. Bohan & Peter (1975) criteria categorisation was established by a scoring algorithm to define JDM and JPM based oil clinical protocol data. Results Of the 189 cases included, 178 were classified as JDM, 9 as JPM (19.8: 1) and 2 did not fit the criteria; 6.9% had features of chronic arthritis and connective tissue disease overlap. Diagnosis classification agreement occurred in 66.1%. Medial? onset age was 7 years, median follow-up duration was 3.6 years. Malignancy was described in 2 (1.1%) cases. Muscle weakness occurred in 95.8%; heliotrope rash 83.5%; Gottron plaques 83.1%; 92% had at least one abnormal muscle enzyme result. Muscle biopsy performed in 74.6% was abnormal in 91.5% and electromyogram performed in 39.2% resulted abnormal in 93.2%. Logistic regression analysis was done in 66 cases with all parameters assessed and only aldolase resulted significant, as independent variable for definite JDM (OR=5.4, 95%CI 1.2-24.4, p=0.03). Regarding treatment, 97.9% received steroids; 72% had in addition at least one: methotrexate (75.7%), hydroxychloroquine (64.7%), cyclosporine A (20.6%), IV immunoglobulin (20.6%), azathioprine (10.3%) or cyclophosphamide (9.6%). In this series 24.3% developed calcinosis and mortality rate was 4.2%. Conclusion Evaluation of predefined criteria set for a valid diagnosis indicated aldolase as the most important parameter associated with de, methotrexate combination, was the most indicated treatment.

Characterization of tree-rings of Pinus caribaea var. hondurensis Barr. et Golf. trees by X ray densitometry

This work aimed to determining the anatomical structure of wood, through methodology of histology and X-ray densitometry, of resin-tapped and not resin-tapped Pinus caribaea var. hondurensis trees samples, of three diameter classes. Pine trees, in forest plantation established in 1969, in the Ecological Experimental Station of Itirapina, from the Forestry Institute of Sao Paulo State, were measured and stratified into three classes of trunk diameter. The pine trees were resin-tapped since 2004, with the opening of two simultaneous and opposing panels. Sixty samples of pine wood trees were extracted from the tree trunk through a non-destructive method and in the laboratory. Tree rings were determined in the laboratory and wood apparent density by X-ray densitometry. The test results showed that: (i) false tree rings occur in the early wood and late wood of the tree rings due to climate change; (ii) the X-ray densitometry allowed the demarcation of the tree rings limits; (iii) the wood apparent density average was significantly different between the trees in high class diameter and in the medium-low class; (iv) the wood characteristics from the resin-tapped and non resin-tapped faces did not show significant differences.

WINE GRAPE QUALITY OF GRAPEVINES GROWN IN THE CERRADO ECOREGION OF BRAZIL

Aims: Geographical indication plays an important role in the improvement of wine quality. In this context, the search for new grape growing areas has been constant. The Sao Francisco River Valley in the cerrado of Minas Gerais State (Brazil) has been pointed out in the Geoviticulture Multicriteria Climatic Classification System (MCC System) as a potentially winegrowing region, especially considering the autumn-winter period when night temperatures are favorable to grape ripening. In this work, we studied the maturation curves and fruit composition of four wine grape varieties (Syrah, Merlot, Cabernet-Sauvignon and Cabernet Franc) in two growing seasons in order to validate the state of Minas Gerais as a new winegrowing region in Brazil. Methods and results: Quality parameters (berry weight, pH, titratable acidity and total soluble solids) were measured weekly from veraison to harvest, and sugar, organic acid, anthocyanin and phenolic concentrations were determined in must and berry skins and seeds at harvest. Syrah berries showed the highest weight throughout maturation which contributed to higher yield (8.92 ton ha(-1)), followed closely by Merlot (8.07 ton ha(-1)). Bern, sugar concentrations were higher and malic acid levels were lower than the values usually observed in wine grapes harvested during summer in traditional winegrowing regions in Brazil. Cabernet Franc showed lower levels of anthocyanins and skin phenolics per kg berries and the highest values of seed phenolics, which were not affected by growing season. Conclusion: Weather conditions of the cerrado of Minas Gerais State in Brazil during winter allowed complete maturation of Cabernet-Sauvignon, Cabernet Franc, Merlot and Syrah cultivars as revealed by the satisfactory sugar, anthocyanin and skin phenolic accumulation. Significance and impact of the study: This study revealed the potential of the cerrado ecoregion in the northeast of Minas Gerais to become a new winemaking region in Brazil.