Leishmania (Viannia) braziliensis identification by PCR in the state of Para, Brazil

The incidence of cutaneous leishmaniasis (CL) is increasing and there is limited surveillance of Leishmania species throughout the world. We identified the species associated with CL in a region of Amazonia, an area recognized for its Leishmania species variability. Clinical findings were analyzed and correlated with the species identified in 93 patients. PCR assays were based on small subunit ribosomal DNA (SSU-rDNA) and G6PD, and were performed in a laboratory located 3,500 km away. Leishmania (V.) braziliensis was identified in 53 patients (57%). The other 40 patients (43%) carried a different species (including six cases of L (L) amazonensis). Molecular methods can be employed, using special media, to allow transport to distant laboratories. L (V.) braziliensis is the most common species in the area of Para. The location of ulcers can suggest CL species (C) 2010 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

Modelling the distribution of stamp paper thickness via finite normal mixtures: The 1872 Hidalgo stamp issue of Mexico revisited

Izenman and Sommer (1988) used a non-parametric Kernel density estimation technique to fit a seven-component model to the paper thickness of the 1872 Hidalgo stamp issue of Mexico. They observed an apparent conflict when fitting a normal mixture model with three components with unequal variances. This conflict is examined further by investigating the most appropriate number of components when fitting a normal mixture of components with equal variances.

Separation and hedging results with state-contingent production

A state-contingent model of production under uncertainty is developed and compared with more traditional models of production under uncertainty. Producer behaviour with both production and price risk, in the presence and in the absence of futures and forward markets, is analysed in this state-contingent framework. Conditions for the optimal hedge to be positive or negative are derived. We also show that, under plausible conditions, a risk-averse producer facing price uncertainty and the ability to hedge price risk will never willingly adopt a nonstochastic technology. New separation results, which hold in the presence of both price and production risk, are then developed. These separation results generalize Townsend's spanning results by reducing the number of necessary forward markets by one.

Molecular motion in miscible polymer blends .1. Motion in blends of PEO and PVPh studied by solid-state C-13 T-1 rho measurements

Changes in molecular motion in blends of PEO-PVPh have been studied using measurements of C-13 T-1 rho relaxation times. C-13 T-1 rho relaxation has been confirmed as arising from spin-lattice interactions by observation of the variation in T-1 rho with rf field strength and temperature. In the pure homopolymers a minimum in T-1 rho is observed at ca. 50 K above the glass transition temperatures detected by DSC. After blending, the temperature of the minimum in T-1 rho for PEO increased, while that for PVPh decreased, however, the minima, which correspond to the temperatures where the average correlation times for reorientation are close to 3.1 mu s, are separated by 45 K (in a 45% PEO-PVPh blend). These phenomena are explained in terms of the local nature of T-1 rho measurements. The motions of the individual homopolymer chains are only partially coupled in the blend. A short T-1 rho has been observed for protonated aromatic carbons, and assigned to phenyl rings undergoing large-angle oscillatory motion, The effects of blending, and temperature, on the proportion of rings undergoing oscillatory motion are analyzed.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Finite element analysis of mechanical properties in discontinuously reinforced metal matrix composites with ultrafine microstructure

This investigation focused on the finite element analyses of elastic and plastic properties of aluminium/alumina composite materials with ultrafine microstructure. The commonly used unit cell model was used to predict the elastic properties. By combining the unit cell model with an indentation model, coupled with experimental indentation measurements, the plastic properties of the composites and the associated strengthening mechanism within the metal matrix material were investigated. The grain size of the matrix material was found to be an important factor influencing the mechanical properties of the composites studied. (C) 1997 Elsevier Science S.A.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Phase-dependent fluorescence linewidth narrowing in a three-level atom damped by a finite-bandwidth squeezed vacuum

We examine subnatural phase-dependent linewidths in the fluorescence spectrum of a three-level atom damped by a narrow-bandwidth squeezed vacuum in a cavity. Using the dressed-atom model approach of a strongly driven three-level cascade system, we derive the master equation of the system from which we obtain simple analytical expressions for the fluorescence spectrum. We show that the phase effects depend on the bandwidths of the squeezed vacuum and the cavity relative to the Rabi frequency of the driving fields. When the squeezing bandwidth is much larger than the Rabi frequency, the spectrum consists of five lines with only the central and outer sidebands dependent on the phase. For a squeezing bandwidth much smaller than the Rabi frequency the number of lines in the spectrum and their phase properties depend on the frequency at which the squeezing and cavity modes are centered. When the squeezing and cavity modes are centered on the inner Rabi sidebands, the spectrum exhibits five lines that are completely independent of the squeezing phase with only the inner Rabi sidebands dependent on the squeezing correlations. Matching the squeezing and cavity modes to the outer Rabi sidebands leads to the disappearance of the inner Rabi sidebands and a strong phase dependence of the central line and the outer Rabi sidebands. We find that in this case the system behaves as an individual two-level system that reveals exactly the noise distribution in the input squeezed vacuum. [S1050-2947(97)00111-X].

The Potential Impact of Using Donations After Cardiac Death on the Liver Transplantation Program and Waiting List in the State of Sao Paulo, Brazil

Liver transplantation was first performed at the University of Sao Paulo School of Medicine in 1968. Since then, the patient waiting list for liver transplantation has increased at a rate of 150 new cases per month. Liver transplantation itself rose 1.84-fold (from 160 to 295) from 1988 to 2004. However, the number of patients on the liver waiting list jumped 2.71-fold (from 553 to 1500). Consequently, the number of deaths on the liver waiting list moved to a higher level, from 321 to 671, increasing 2.09-fold. We have applied a mathematical model to analyze the potential impact of using a donation after cardiac death (DCD) policy on our liver transplantation program and on the waiting list. Five thousand one hundred people died because of accidents and other violent causes in our state in 2004; of these, only 295 were donors of liver grafts that were transplanted. The model assumed that 5% of these grafts would have been DCD. We found a relative reduction of 27% in the size of the liver transplantation waiting list if DCD had been used by assuming that 248 additional liver transplants would have been performed annually. In conclusion, the use of DCD in our transplantation program would reduce the pressure on our liver transplantation waiting list, reducing it by at least 27%. On the basis of this model, the projected number of averted deaths is about 41,487 in the next 20 years. Liver Transpl 14:1732-1736, 2008. (C) 2008 AASLD.

State-dependent microstructural white matter changes in bipolar I depression

Abnormalities in fronto-limbic-striatal white matter (WM) have been reported in bipolar disorder (BD), but results have been inconsistent across studies. Furthermore, there have been no detailed investigations as to whether acute mood states contribute to microstructural changes in WM tracts. In order to compare fiber density and structural integrity within WM tracts between BD depression and remission, whole-brain fractional anisotropy (FA) and mean diffusivity (MD) were assessed in 37 bipolar I disorder (BD-I) patients (16 depressed and 21 remitted), and 26 healthy individuals with diffusion tensor imaging. Significantly decreased FA and increased MD in bilateral prefronto-limbic-striatal white matter and right inferior fronto-occipital, superior and inferior longitudinal fasciculi were shown in all BD-I patients versus controls, as well as in depressed BD-I patients compared to both controls and remitted BD-I patients. Depressed BD-I patients also exhibited increased FA in the ventromedial prefrontal cortex. Remitted BD-I patients did not differ from controls in FA or MD. These findings suggest that BD-I depression may be associated with acute microstructural WM changes.

Limitations of the Mini-Mental State Examination for screening dementia in a community with low socioeconomic status

The Mini-Mental State Examination (MMSE) is the most widely used instrument for the screening of cognitive impairment worldwide, but its ability to produce valid estimates of dementia in populations of low socioeconomic status and minimal literacy skills has not been adequately established. The authors investigated the psychometric properties of the MMSE in a community-based sample of older Brazilians. Cross-sectional one-phase population-based study of all residents of pre-defined areas of the city of Sao Paulo, aged 65 years or over. The Brazilian version of the MMSE was compared with DSM-IV diagnosis of dementia assessed with a harmonized one-phase procedure developed by the 10/66 Dementia Research Group. Analyses were performed with 1,933 participants of the SPAH study. Receiver operating characteristic analysis showed that the MMSE cut-point of 14/15 was associated with 78.7% sensitivity and 77.8% specificity for the diagnosis of dementia amongst participants with no formal education, and the cut-point 17/18 with 91.9% sensitivity and 89.5% specificity for those with at least 1 year of formal education (areas under the curves 0.87 and 0.94, respectively; P = 0.03). Even with these best fitting cut-points, the MMSE estimate of the prevalence of dementia was four times higher than determined by the DSM-IV criteria. Education, age, sex and income influenced MMSE scores, independently of dementia caseness. The MMSE is an adequate tool for screening dementia in older adults with minimum literacy skills, but misclassification is unacceptably high for older adults who are illiterate, which has serious consequences for research and clinical practice in low and middle income countries, where the proportion of illiteracy among older adults is high.