Xylella fastidiosa: An in vivo system to study possible survival strategies within citrus xylem vessels based on global gene expression analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Design and implementation of wireless sensor networks for impedance-based structural health monitoring using ZigBee and Global System for Mobile Communications

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Xylella fastidiosa: An in vivo system to study possible survival strategies within citrus xylem vessels based on global gene expression analysis

Xylella fastidiosa inhabits the plant xylem, a nutrient-poor environment, so that mechanisms to sense and respond to adverse environmental conditions are extremely important for bacterial survival in the plant host. Although the complete genome sequences of different Xylella strains have been determined, little is known about stress responses and gene regulation in these organisms. In this work, a DNA microarray was constructed containing 2,600 ORFs identified in the genome sequencing project of Xylella fastidiosa 9a5c strain, and used to check global gene expression differences in the bacteria when it is infecting a symptomatic and a tolerant citrus tree. Different patterns of expression were found in each variety, suggesting that bacteria are responding differentially according to each plant xylem environment. The global gene expression profile was determined and several genes related to bacterial survival in stressed conditions were found to be differentially expressed between varieties, suggesting the involvement of different strategies for adaptation to the environment. The expression pattern of some genes related to the heat shock response, toxin and detoxification processes, adaptation to atypical conditions, repair systems as well as some regulatory genes are discussed in this paper. DNA microarray proved to be a powerful technique for global transcriptome analyses. This is one of the first studies of Xylella fastidiosa gene expression in vivo which helped to increase insight into stress responses and possible bacterial survival mechanisms in the nutrient-poor environment of xylem vessels.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

Six-month evaluation of a resin/dentin interface created by methacrylate and silorane-based materials

Objectives: This study aimed to compare the micro-tensile bond strength of methacrylate resin systems to a silorane-based restorative system on dentin after 24 hours and six months water storage. Material and Methods: The restorative systems Adper Single Bond 2/Filtek Z350 (ASB), Clearfil SE Bond/Z350 (CF), Adper SE Plus/Z350 (ASEP) and P90 Adhesive System/Filtek P90 (P90) were applied on flat dentin surfaces of 20 third molars (n=5). The restored teeth were sectioned perpendicularly to the bonding interface to obtain sticks (0.8 mm2) to be tested after 24 hours (24 h) and 6 months (6 m) of water storage, in a universal testing machine at 0.5 mm/min. The data was analyzed via two-way Analysis of Variance/Bonferroni post hoc tests at 5% global significance. Results: Overall outcomes did not indicate a statistical difference for the resin systems (p=0.26) nor time (p=0.62). No interaction between material × time was detected (p=0.28). Mean standard-deviation in MPa at 24 h and 6 m were: ASB 31.38 (4.53) and 30.06 (1.95), CF 34.26 (3.47) and 32.75 (4.18), ASEP 29.54 (4.14) and 33.47 (2.47), P90 30.27 (2.03) and 31.34 (2.19). Conclusions: The silorane-based system showed a similar performance to methacrylate-based materials on dentin. All systems were stable in terms of bond strength up to 6 month of water storage.

Engineering knowledge-based variance-reduction simulation and G-dominance for structural frame robust optimization

[EN] This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variance reduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables.The simultaneous minimization of the constrained weight (adding structuralweight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including

A Functional-Based Distribution Diagnostic for a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed modesl and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. Linear functions or the resulting "rotated" residuals are used to construct an empirical cumulative distribution function (ECDF), whose stochastic limit is characterized. We describe a resampling technique that serves as a computationally efficient parametric bootstrap for generating representatives of the stochastic limit of the ECDF. Through functionals, such representatives are used to construct global tests for the hypothesis of normal margional errors. In addition, we demonstrate that the ECDF of the predicted random effects, as described by Lange and Ryan (1989), can be formulated as a special case of our approach. Thus, our method supports both omnibus and directed tests. Our method works well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series).

Appraising and selecting conservation measures to mitigate desertification and land degradation based on stakeholder participation and global best practices

Most desertification research focuses on degradation assessments without putting sufficient emphasis on prevention and mitigation strategies, although the concept of Sustainable Land Management (SLM) is increasingly being acknowledged. A variety of already applied conservation measures exist at the local level, but they are not adequately recognised, evaluated and shared, either by land users, technicians, researchers, or policy makers. Likewise, collaboration between research and implementation is often insufficient. The aim of this paper is to present a new methodology for a participatory process of appraising and selecting desertification mitigation strategies, and to present first experiences from its application in the EU-funded DESIRE project. The methodology combines a collective learning and decision approach with the use of evaluated global best practices. In three parts, it moves through a concise process, starting with identifying land degradation and locally applied solutions in a stakeholder workshop, leading to assessing local solutions with a standardised evaluation tool, and ending with jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology is currently being applied in 16 study sites. Preliminary analysis from the application of the first part of the methodology shows that the initial stakeholder workshop results in a good basis for stakeholder cooperation, and in promising land conservation practices for further assessment. Study site research teams appreciated the valuable results, as burning issues and promising options emerged from joint reflection. The methodology is suitable to initiate mutual learning among different stakeholder groups and to integrate local and scientific knowledge.