Differential gene expression by Paracoccidioides brasiliensis in host interaction conditions: Representational difference analysis identifies candidate genes associated with fungal pathogenesis

Paracoccidioides brasiliensis causes infection by the host inhalation of airborne propagules of the mycelia phase of the fungus. These particles reach the lungs, and disseminate to virtually all organs. Here we describe the identification of differentially expressed genes in studies of host-fungus interaction. We analyzed two cDNA populations of P. brasiliensis, one obtained from infected animals and the other an admixture of fungus and human blood thus mimicking the hematologic events of the fungal dissemination. Our analysis identified transcripts differentially expressed. Genes related to iron acquisition, melanin synthesis and cell defense were specially upregulated in the mouse model of infection. The upregulated transcripts of yeast cells during incubation with human blood were those predominantly related to cell wall remodeling/synthesis. The expression pattern of genes was independently confirmed in host conditions, revealing their potential role in the infection process. This work can facilitate functional studies of novel regulated genes that may be important for the survival and growth strategies of P. brasiliensis in humans. (c) 2006 Elsevier Masson SAS. All rights reserved.

Teores foliares de nutrientes, índice relativo de clorofila e teores de nitrato e de potássio na seiva do pecíolo na videira 'Niagara Rosada

A nutritional survey was carried out in 93 vineyards of the wine regions of Jundiai, Sao Miguel Arcanjo and Jales (state of São Paulo-Brazil), aiming to compare the nutrient concentration in leaf samples, the concentration of nitrate and potassium in the petiole sap and the relative chlorophyll index (IRC) of 'Niagara Rosada' vineyard. Leaves, blade and petiole in full bloom vines were sampled in 20 plants selected from each vineyard, and evaluations of the IRC in the leaf blade and the levels of NO3-and K in the petioles sap were realized. Macro and micronutrients concentrations were measured in leaf samples. The sampled vineyards were grouped by region of study, and each vineyard was considered as a replicate sample, totaling 45, 24 and 24 repetitions, in Jundiai, Sao Miguel Arcanjo and Jales, respectively. Sampled vineyards from the Jales region showed higher leaf concentrations of P, K, Ca, Mg, S, Fe and Mn, and also higher IRC and levels of nitrate and potassium in the petiole. These differences were related to the different rootstocks used, which were 'IAC 766', 'IAC 572' and 'Riparia of Traviu', respectively, for Jundiai, Jales and Sao Miguel Arcanjo. The differences highlight the need to adjust the concentration ranges of nutrients in leaf analysis, through regional trials, taking into account the rootstock and the region under study.

Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

Optimal placement of sensors/actuators in truss structures with known disturbances

An important stage in the solution of active vibration control in flexible structures is the optimal placement of sensors and actuators. In many works, the positioning of these devices in systems governed for parameter distributed is, mainly, based, in controllability approach or criteria of performance. The positions that enhance such parameters are considered optimal. These techniques do not take in account the space variation of disturbances. An way to enhance the robustness of the control design would be to locate the actuators considering the space distribution of the worst case of disturbances. This paper is addressed to include in the formulation of problem of optimal location of sensors and piezoelectric actuators the effect of external disturbances. The paper concludes with a numerical simulation in a truss structure considering that the disturbance is applied in a known point a priori. As objective function the C norm system is used. The LQR (Linear Quadratic Regulator) controller was used to quantify performance of different sensors/actuators configurations.

Experimental damage detection using system norms

Nowadays there is great interest in structural damage detection in systems using nondestructive tests. Once the failure is detected, as for instance a crack, it is possible to take providences. There are several different approaches that can be used to obtain information about the existence, location and extension of the fault in the system by non-destructive tests. Among these methodologies, one can mention different optimization techniques, as for instance classical methods, genetic algorithms, neural networks, etc. Most of these techniques, which are based on element-byelement adjustments of a finite element (FE) model, take advantage of the dynamic behavior of the model. However, in practical situations, usually, is almost impossible to obtain an accuracy model. In this paper, it is proposed an experimental technique for damage location. This technique is based on H: norm to obtain the damage location. The dynamic properties of the structure were identified using experimental data by eigensystem realization algorithm (ERA). The experimental test was carried out in a beam structure through varying the mass of an element. For the output signal was used a piezoelectric sensor. The signal of input of sine form was generated through SignalCalc® software.

Active control in flexible plates with piezoelectric actuators using linear matrix inequalities

The study of algorithms for active vibrations control in flexible structures became an area of enormous interest, mainly due to the countless demands of an optimal performance of mechanical systems as aircraft, aerospace and automotive structures. Smart structures, formed by a structure base, coupled with piezoelectric actuators and sensor are capable to guarantee the conditions demanded through the application of several types of controllers. The actuator/sensor materials are composed by piezoelectric ceramic (PZT - Lead Zirconate Titanate), commonly used as distributed actuators, and piezoelectric plastic films (PVDF-PolyVinyliDeno Floride), highly indicated for distributed sensors. The design process of such system encompasses three main phases: structural design; optimal placement of sensor/actuator (PVDF and PZT); and controller design. Consequently, for optimal design purposes, the structure, the sensor/actuator placement and the controller have to be considered simultaneously. This article addresses the optimal placement of actuators and sensors for design of controller for vibration attenuation in a flexible plate. Techniques involving linear matrix inequalities (LMI) to solve the Riccati's equation are used. The controller's gain is calculated using the linear quadratic regulator (LQR). The major advantage of LMI design is to enable specifications such as stability degree requirements, decay rate, input force limitation in the actuators and output peak bounder. It is also possible to assume that the model parameters involve uncertainties. LMI is a very useful tool for problems with constraints, where the parameters vary in a range of values. Once formulated in terms of LMI a problem can be solved efficiently by convex optimization algorithms.

Biodegradability of diesel and biodiesel blends

The biodegradability of pure diesel and biodiesel and blends with different proportions of biodiesel (2% (commercial); 5% and 20%) was evaluated employing the respirometric method and the redox indicator 2,6-dichlorophenol indophenol (DCPIP) test. In the former, experiments simulating the contamination of natural environments (soil from a petrol station or water from a river) were carried out in Bartha biometer flasks (250 ml), and used to measure the microbial CO 2 production. With the DCPIP test, the capability of three inocula to biodegrade the blends was tested. Results show that although biodiesel is more easily and faster biodegraded than diesel oil, among the blends evaluated (2%, 5% and 20%), only the blend with higher concentration of biodiesel presented biodegradability significantly different from diesel and it was not verified an improvement on the biodegradation of the diesel by means of co-metabolism. © 2008 Academic Journals.

Myotoxic phospholipases A2 isolated from Bothrops brazili snake venom and synthetic peptides derived from their C-terminal region: Cytotoxic effect on microorganism and tumor cells

This paper reports the purification and biochemical/pharmacological characterization of two myotoxic phospholipases A2 (PLA2s) from Bothrops brazili venom, a native snake from Brazil. Both myotoxins (MTX-I and II) were purified by a single chromatographic step on a CM-Sepharose ion-exchange column up to a high purity level, showing Mr ∼ 14,000 for the monomer and 28,000 Da for the dimer. The N-terminal and internal peptide amino acid sequences showed similarity with other myotoxic PLA2s from snake venoms, MTX-I belonging to Asp49 PLA2 class, enzymatically active, and MTX-II to Lys49 PLA2s, catalytically inactive. Treatment of MTX-I with BPB and EDTA reduced drastically its PLA2 and anticoagulant activities, corroborating the importance of residue His48 and Ca2+ ions for the enzymatic catalysis. Both PLA2s induced myotoxic activity and dose-time dependent edema similar to other isolated snake venom toxins from Bothrops and Crotalus genus. The results also demonstrated that MTXs and cationic synthetic peptides derived from their 115-129 C-terminal region displayed cytotoxic activity on human T-cell leukemia (JURKAT) lines and microbicidal effects against Escherichia coli, Candida albicans and Leishmania sp. Thus, these PLA2 proteins and C-terminal synthetic peptides present multifunctional properties that might be of interest in the development of therapeutic strategies against parasites, bacteria and cancer. © 2008 Elsevier Inc. All rights reserved.

Structural real time control using fluid magnetorheologic damper

In the last decades there was a great development in the study of control systems to attenuate the harmful effect of natural events in great structures, as buildings and bridges. Magnetorheological fluid (MR), that is an intelligent material, has been considered in many proposals of project for these controllers. This work presents the controller design using feedback of states through LMI (Linear Matrix Inequalities) approach. The experimental test were carried out in a structure with two degrees of freedom with a connected shock absorber MR. Experimental tests were realized in order to specify the features of this semi-active controller. In this case, there exist states that are not measurable, so the feedback of the states involves the project of an estimator. The coupling of the MR damper causes a variation in dynamics properties, so an identification methods, based on experimental input/output signal was used to compare with the numerical application. The identification method of Prediction Error Methods - (PEM) was used to find the physical characteristics of the system through realization in modal space of states. This proposal allows the project of a semi-active control, where the main characteristic is the possibility of the variation of the damping coefficient.

False alarms in damage detection approaches

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in structures in order to improve reliability and reduce life-cycle costs. The greatest challenge for designing a SHM system is knowing what changes to look for and how to classify them. Different approaches for SHM have been proposed for damage identification, each one with advantages and drawbacks. This paper presents a methodology for improvement in vibration signal analysis using statistics information involving the probability density. Generally, the presence of noises in input and output signals results in false alarms, then, it is important that the methodology can minimize this problem. In this paper, the proposed approach is experimentally tested in a flexible plate using a piezoelectric (PZT) actuator to provide the disturbance.

Estado físico do meio de cultura na propagação in vitro de bromeliaceae

The objective of this study was to evaluate the effect of the physical state of the culture medium on the behavior in vitro of the bromeliaceas Neoregelia cruenta, Tillandsia stricta, Vriesea gigantea, V. guttata e V. incun/ata. Micropropagated shoots had been cultivated in culture medium MS, with 30 g sucrose, 2,5 mg dm-3 BAP, and 0,5 mg dm-3 ANA, establishing the treatments: T1- half-solid with 7 g agar; T2- static liquid; T3- liquid under-agitation of 90 rpm; and T4-static liquid with bridge of paper filter. After 30 days, the use of static way of liquid culture presented better results in relation of proliferative average rate in all the species (9.4 shoots in N. cruenta, 5.6 in T. stricta, 11.5 in V. gigantea, 9.2 in V. guttata and 3.9 in V. incurvata). In relation the average height of the shoots, was distinguished for N. cruenta the liquid under-agitation (2.83 cm), T. stricta and V. incurvata the semisolid (1.76 cm and 2.02 cm, respectively) and V. gigantea and V. guttata the static liquid (0.61 cm and 1.48 cm, respectively). The use of medium MS static liquid was more suitable for in vitro culture of bromeliads species studied.

Qualidade fisiológica e sanitária de sementes de mamona submetidas a diferentes tratamentos químicos

The use of fungicides for treating seeds has become an essential measure in the control of pathogens. However, the effectiveness of many products is not well-known to some crops. The objective of this research was to evaluate the effect of different doses of carbendazin and carboxin + thiram fungicides for controlling pathogens and their interference on the physiologic quality of castor bean seeds. The test consisted of the following treatments (g i.a./100 kg of seeds): carbendazin (15, 30, and 60), carboxin + thiram (25 + 25, 50 + 50, and 100 + 100), formol 0.15% (v/v), and control (distilled water). The physiologic quality of the seeds was determined by germination, first counting, field emergence, speed emergence index, length, fresh and dry weight of the aerial part, and electrical conductivity. There were no statistical differences for germination and fresh and dry matter index. The treatment with formol provided lower values for first counting and field emergence. Seeds treated with fungicides presented higher values for electrical conductivity, but did not differ, statistically, among themselves. The fungi Cladosporium spp.; Bipolaris spp.; Curvularia spp.; Aspergillus flavus; Aspergillus niger; Rhizopus sp.; Penicillium sp.; Rhizoctonia sp.; Verticillium sp.; Fusarium sp.;Arthrobotrys sp.; and Epicocum sp. were identified. All tested products, independently of the dose, provided efficient control for pathogens.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Intrusion detection system using optimum-path forest

Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. Neural networks and Support Vector Machines have been also extensively applied to this task. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In this research, we introduce a new pattern classifier named Optimum-Path Forest (OPF) to this task, which has demonstrated to be similar to the state-of-the-art pattern recognition techniques, but extremely more efficient for training patterns. Experiments on public datasets showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, as well as allow the algorithm to learn new attacks faster than the other techniques. © 2011 IEEE.

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.