Deep sequencing of New World screw-worm transcripts to discover genes involved in insecticide resistance

Background: The New World screw-worm (NWS), Cochliomyia hominivorax, is one of the most important myiasis-causing flies, causing severe losses to the livestock industry. In its current geographical distribution, this species has been controlled by the application of insecticides, mainly organophosphate (OP) compounds, but a number of lineages have been identified that are resistant to such chemicals. Despite its economic importance, only limited genetic information is available for the NWS. Here, as a part of an effort to characterize the C. hominivorax genome and identify putative genes involved in insecticide resistance, we sampled its transcriptome by deep sequencing of polyadenylated transcripts using the 454 sequencing technology. Results: Deep sequencing on the 454 platform of three normalized libraries (larval, adult male and adult female) generated a total of 548,940 reads. Eighteen candidate genes coding for three metabolic detoxification enzyme families, cytochrome P450 monooxygenases, glutathione S transferases and carboxyl/cholinesterases were selected and gene expression levels were measured using quantitative real-time polymerase chain reaction (qRT-PCR). Of the investigated candidates, only one gene was expressed differently between control and resistant larvae with, at least, a 10-fold down-regulation in the resistant larvae. The presence of mutations in the acetylcholinesterase (target site) and carboxylesterase E3 genes was investigated and all of the resistant flies presented E3 mutations previously associated with insecticide resistance. Conclusions: Here, we provided the largest database of NWS expressed sequence tags that is an important resource, not only for further studies on the molecular basis of the OP resistance in NWS fly, but also for functional and comparative studies among Calliphoridae flies. Among our candidates, only one gene was found differentially expressed in resistant individuals, and its role on insecticide resistance should be further investigated. Furthermore, the absence of mutations in the OP target site and the high frequency of mutant carboxylesterase E3 indicate that metabolic resistance mechanisms have evolved predominantly in this species.

Searching supersymmetry at the LHCb with displaced vertices

Supersymmetric theories with bilinear R-parity violation can give rise to the observed neutrino masses and mixings. One important feature of such models is that the lightest supersymmetric particle might have a sufficiently large lifetime to produce detached vertices. Working in the framework of supergravity models, we analyze the potential of the LHCb experiment to search for supersymmetric models exhibiting bilinear R-parity violation. We show that the LHCb experiment can probe a large fraction of the m(0)circle times m(1/2), being able to explore gluino masses up to 1.3 TeV. The LHCb discover potential for these kinds of models is similar to the ATLAS and CMS ones in the low luminosity phase of operation of the LHC.

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Searching for Moniliophthora perniciosa pathogenicity genes

The basidiomycete Moniliophthora perniciosa is the causal agent of witches` broom disease of Theobroma cacao (cacao). Pathogenesis mechanisms of this hemibiotrophic fungus are largely unknown. An approach to identify putative pathogenicity genes is searching for sequences induced in mycelia grown under in vitro conditions. Using this approach, genes from M. perniciosa induced under limiting nitrogen and light were identified from a cDNA library enriched by suppression subtractive hybridization as potential putative pathogenicity genes. From the 159 identified unique sequences, 59 were annotated and classified by gene ontology. Two sequences were categorized as ""Defence genes, Virulence, and Cell response"" presumably coding for allergenic proteins, whose homologues from other fungi are inducers of animal or plant defences. Differential gene expression was evaluated by quantitative amplification of reversed transcripts (RT-qPCR) of the putative identified genes coding for the two allergenic proteins (Aspf13 and 88KD), and for the enzymes Arylsulfatase (AS); Aryl-Alcohol Oxidase; Aldo-Keto Reductase (AK); Cytochrome P450 (P450); Phenylalanine Ammonia-Lyase; and Peroxidase from mycelia grown under contrasting N concentrations. All genes were validated for differential expression, except for the putative Peroxidase. The same eight genes were analysed for expression in susceptible plants inoculated with M. perniciosa, and six were induced during the early asymptomatic stage of the disease. In infected host tissues, transcripts of 88KD and AS were found more abundant at the biotrophic phase, while those from Aspf13, AK, PAL, and P450 accumulated at the necrotrophic phase, enabling to suggest that mycelia transition from biotrophic to necrotrophic might occur earlier than currently considered. These sequences appeared to be virulence life-style genes, which encode factors or enzymes that enable invasion, colonization or intracellular survival, or manipulate host factors to benefit the pathogen`s own survival in the hostile environment. (C) 2010 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

A TR beta-selective agonist confers resistance to diet-induced obesity

Thyroid hormone receptor beta (TR beta also listed as THRB oil the MGI Database)-selective agonists activate brown adipose tissue (BAT) thermogenesis, while only minimally affecting cardiac activity or lean body mass. Here, we tested the hypothesis that daily administration of the TR beta agonist GC-24 prevents the metabolic alterations associated with a hypercaloric diet. Rats were placed on a high-fat diet and after a month exhibited increased body weight (BW) and adiposity, fasting hyperglycemia and glucose intolerance, increased plasma levels of triglycerides, cholesterol, nonesterified Fatty acids and interleukin-6. While GC-24 administration to these animals did not affect food ingestion or modified the progression of BW gain, it did increase energy, g the increase in adiposity Without expenditure, eliminating causing cardiac hypertrophy Fasting hyperglycemia remained unchanged, but treatment with GC-24 improved glucose I tolerance by increasing insulin Sensitivity and also normalized plasma triglyceride levels. plasma cholesterol levels were only Partially normalized and liver cholesterol content remained high in the GC-24-treated animals. Gene expression in liver, skeletal muscle, and white adipose tissue was only minimally affected by treatment with GC-24, with the main target being BAT In conclusion, during high-fat feeding treatment with the TR beta-selective agonist, GC-24 only partially improves metabolic control probably as a result Of accelerating the resting metabolic rate. Journal of Endocrinology (2009) 203, 291-299

Online Mammographic Images Database for Development and Comparison of CAD Schemes

Considering the difficulties in finding good-quality images for the development and test of computer-aided diagnosis (CAD), this paper presents a public online mammographic images database free for all interested viewers and aimed to help develop and evaluate CAD schemes. The digitalization of the mammographic images is made with suitable contrast and spatial resolution for processing purposes. The broad recuperation system allows the user to search for different images, exams, or patient characteristics. Comparison with other databases currently available has shown that the presented database has a sufficient number of images, is of high quality, and is the only one to include a functional search system.

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

Parametrical study of masonry walls subjected to in-plane loading through numerical modeling

This paper deals with the numerical assessment of the influence of parameters such as pre-compression level, aspect ratio, vertical and horizontal reinforcement ratios and boundary conditions on the lateral strength of masonry walls under in-plane loading. The numerical study is performed through the software DIANA (R) based on the Finite Element Method. The validation of the numerical model is carried out from a database of available experimental results on masonry walls tested under cyclic lateral loading. Numerical results revealed that boundary conditions play a central role on the lateral behavior of masonry walls under in-plane loading and determine the influence of level of pre-compression as well as the reinforcement ratio on the wall strength. The lateral capacity of walls decreases with the increase of aspect ratio and with the decrease of pre-compression. Vertical steel bars appear to have almost no influence in the shear strength of masonry walls and horizontal reinforcement only increases the lateral strength of masonry walls if the shear response of the walls is determinant for failure, which is directly related to the boundary conditions. (C) 2011 Elsevier Ltd. All rights reserved.

GIS applied to geotechnical and environmental risk management in a Brazilian oil pipeline

The paper presents the development of a decision support system for the management of geotechnical and environmental risks in oil pipelines using a geographical information system. The system covers a 48.5 km long section of the So Paulo to Brasilia (OSBRA) oil pipeline, which crosses three municipalities in the northeast region of the So Paulo state (Brazil) and represents an area of 205.8 km(2). The spatial database was created using geo-processing procedures, surface and intrusive investigations and geotechnical reports. The risk assessment was based mainly on qualitative models (relative numeric weights and multicriteria decision analysis) and considered pluvial erosion, slope movements, soil corrosion and third party activities. The maps were produced at a scale of 1:10,000.

Rotation-discriminating template matching based on Fourier coefficients of radial projections with robustness to scaling and partial occlusion

We consider brightness/contrast-invariant and rotation-discriminating template matching that searches an image to analyze A for a query image Q We propose to use the complex coefficients of the discrete Fourier transform of the radial projections to compute new rotation-invariant local features. These coefficients can be efficiently obtained via FFT. We classify templates in ""stable"" and ""unstable"" ones and argue that any local feature-based template matching may fail to find unstable templates. We extract several stable sub-templates of Q and find them in A by comparing the features. The matchings of the sub-templates are combined using the Hough transform. As the features of A are computed only once, the algorithm can find quickly many different sub-templates in A, and it is Suitable for finding many query images in A, multi-scale searching and partial occlusion-robust template matching. (C) 2009 Elsevier Ltd. All rights reserved.

Brazilian flavonoid database: Application of quality evaluation system

Much information on flavonoid content of Brazilian foods has already been obtained; however, this information is spread in scientific publications and non-published data. The objectives of this work were to compile and evaluate the quality of national flavonoid data according to the United States Department of Agriculture`s Data Quality Evaluation System (USDA-DQES) with few modifications, for future dissemination in the TBCA-USP (Brazilian Food Composition Database). For the compilation, the most abundant compounds in the flavonoid subclasses were considered (flavonols, flavones, isoflavones, flavanones, flavan-3-ols, and anthocyanidins) and the analysis of the compounds by HPLC was adopted as criteria for data inclusion. The evaluation system considers five categories, and the maximum score assigned to each category is 20. For each data, a confidence code (CC) was attributed (A, B, C and D), indicating the quality and reliability of the information. Flavonoid data (773) present in 197 Brazilian foods were evaluated. The CC ""C"" (as average) was attributed to 99% of the data and ""B"" (above average) to 1%. The main categories assigned low average scores were: number of samples; sampling plan and analytical quality control (average scores 2, 5 and 4, respectively). The analytical method category received an average score of 9. The category assigned the highest score was the sample handling (20 average). These results show that researchers need to be conscious about the importance of the number and plan of evaluated samples and the complete description and documentation of all the processes of methodology execution and analytical quality control. (C) 2010 Elsevier Inc. All rights reserved.

New information on carbohydrates in the Brazilian Food Composition Database

Foods that contain unavailable carbohydrates may lower the risks for some non-transmissible chronic diseases because of the potential benefits provided by the products of colonic fermentation. On the other hand, foods that are sources of available carbohydrates may have higher energy value and increase the post-prandial glycemic response. The biomarker glycemic index and the resulting glycemic load may be used to classify foods according to their potential to increase blood glucose. Information about glycemic index and glycemic load may be useful in diet therapy. Currently, food composition tables in Brazil do not provide data for individually analyzed carbohydrates even though some quality data are available in scientific publications. The objectives of this work were to produce and compile information about the concentration of individual carbohydrates in foods and their glycemic responses and to disseminate this information through the Brazilian Food Composition Database (TBCA-USP). The glycemic index and glycemic load of foods were evaluated in healthy individuals. Concentrations of available carbohydrates (soluble sugars and available starch) and unavailable carbohydrates (dietary fiber, resistant starch, beta-glucans, fructans) were quantified by official methods, and other national data were compiled. TBCA-USP (http://www.fcf.usp.br/tabela), which is used by professionals and the population in general, now offers both chemical and biological information for carbohydrates. (C) 2009 Elsevier Inc. All rights reserved.

Profiling the Proteome of the Venom from the Social Wasp Polybia paulista: A Clue to Understand the Envenoming Mechanism

The study reported here is a classical bottom-up proteomic approach where proteins from wasp venom were extracted and separated by 2-DE; the individual protein spots were proteolytically digested and subsequently identified by using tandem mass spectrometry and database query with the protein search engine MASCOT. Eighty-four venom proteins belonging to 12 different molecular functions were identified. These proteins were classified into three groups; the first is constituted of typical venom proteins: antigens-5, hyaluronidases, phospholipases, heat shock proteins, metalloproteinases, metalloproteinase-desintegrin like proteins, serine proteinases, proteinase inhibitors, vascular endothelial growth factor-related protein, arginine kinases, Sol i-II and -II like proteins, alpha-glucosidase, and superoxide dismutases. The second contained proteins structurally related to the muscles that involves the venom reservoir. The third group, associated with the housekeeping of cells from venom glands, was composed of enzymes, membrane proteins of different types, and transcriptional factors. The composition of P. paulista venom permits us to hypothesize about a general envenoming mechanism based on five actions: (i) diffusion of venom through the tissues and to the blood, (ii) tissue, (iii) hemolysis, (iv) inflammation, and (v) allergy-played by antigen-5, PLA1, hyaluronidase, HSP 60, HSP 90, and arginine kinases.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

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.