Identification of an Operon, Pil-Chp, That Controls Twitching Motility and Virulence in Xylella fastidiosa

Xylella fastidiosa is an important phytopathogenic bacterium that causes many serious plant diseases, including Pierce`s disease of grapevines. Disease manifestation by X. fastidiosa is associated with the expression of several factors, including the type IV pili that are required for twitching motility. We provide evidence that an operon, named Pil-Chp, with genes homologous to those found in chemotaxis systems, regulates twitching motility. Transposon insertion into the pilL gene of the operon resulted in loss of twitching motility (pilL is homologous to cheA genes encoding kinases). The X. fastidiosa mutant maintained the type IV pili, indicating that the disrupted pilL or downstream operon genes are involved in pili function, and not biogenesis. The mutated X. fastidiosa produced less biofilm than wild-type cells, indicating that the operon contributes to biofilm formation. Finally, in planta the mutant produced delayed and less severe disease, indicating that the Pil-Chp operon contributes to the virulence of X. fastidiosa, presumably through its role in twitching motility.

TLC Separation and Identification of the Essential Oil Constituents from Aloysia gratissima

The present work had as objective the isolation of the five compounds by thin-layer Chromatography (TLC) from the essential oil of the Aloysia gratissima. For this, a number of systems of eluents were used for its separation, indicating that through the system acetone/hexane in proportions (v/v) 1:30 it was possible to isolate guaiol, elemol, pinocanphone (trans-3-pinanone), cis-pinocarvyl, and acorenone. The isolation of the compound acorenone from the other compounds was possible with the mixture of solvents hexane/dichloromethane in proportions (v/v) (1:1,3).

Identification of Staphylococcus saprophyticus isolated from patients with urinary tract infection using a simple set of biochemical tests correlating with 16S-23S interspace region molecular weight patterns

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of methods for the identification of coagulase-negative staphylococci

Coagulase-negative staphylococci (CNS) species identification is still difficult for most clinical laboratories. The scheme proposed by Kloos and Schleifer and modified by Bannerman is the reference method used for the identification of staphylococcal species and subspecies; however, this method is relatively laborious for routine use since it requires the utilization of a large number of biochemical tests. The objective of the present study was to compare four methods, i.e., the reference method, the API Staph system (bioMérieux) and two methods modified from the reference method in our laboratory (simplified method and disk method), in the identification of 100 CNS strains. Compared to the reference method, the simplified method and disk method correctly identified 100 and 99% of the CNS species, respectively, while this rate was 84% for the API Staph system. Inaccurate identification by the API Staph method was observed for Staphylococcus epidermidis (2.2%), S. hominis (25%), S. haemolyticus (37.5%), and S. warneri (47.1%). The simplified method using the simple identification scheme proposed in the present study was found to be efficient for all strains tested, with 100% sensitivity and specificity and proved to be available alternative for the identification of staphylococci, offering, higher reliability and lower cost than the currently available commercial systems. This method would be very useful in clinical microbiology laboratory, especially in places with limited resources.

A fuzzy inference system for identification of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

Identification of psoralen loaded PLGA microspheres in rat skin by light microscopy

Drug delivery systems involving the use of polymers are widely studied and discovery of biocompatible polymers has become the focus of research in this area. Psoralen loaded poly(DL-lactide-co-glycolide) (PLGA) microspheres to be used in PUVA therapy (psoralen and UVA irradiation (ultraviolet A, 320-400 nm) of psoriasis were identified in paraffin sections by histological analysis. The psoralen loaded PLGA microspheres were prepared using the solvent evaporation technique. They were spherical and possessed an external smooth surface as observed by scanning electron microscopy (SEM) analysis. This study describes a modification in the routine preparation of microsphere samples for examination by light microscopy. The changes involved fixative agents and/or stains allowing the identification of microspheres containing a non-fluorescent material. The preservation and identification of microspheres in tissues for histological processing in paraffin was greatly improved by these modifications as proven by our results. (c) 2007 Elsevicr Ltd. All rights reserved.

Expressed sequence tags from Atta laevigata and identification of candidate genes for the control of pest leaf-cutting ants.

Leafcutters are the highest evolved within Neotropical ants in the tribe Attini and model systems for studying caste formation, labor division and symbiosis with microorganisms. Some species of leafcutters are agricultural pests controlled by chemicals which affect other animals and accumulate in the environment. Aiming to provide genetic basis for the study of leafcutters and for the development of more specific and environmentally friendly methods for the control of pest leafcutters, we generated expressed sequence tag data from Atta laevigata, one of the pest ants with broad geographic distribution in South America. Results: The analysis of the expressed sequence tags allowed us to characterize 2,006 unique sequences in Atta laevigata. Sixteen of these genes had a high number of transcripts and are likely positively selected for high level of gene expression, being responsible for three basic biological functions: energy conservation through redox reactions in mitochondria; cytoskeleton and muscle structuring; regulation of gene expression and metabolism. Based on leafcutters lifestyle and reports of genes involved in key processes of other social insects, we identified 146 sequences potential targets for controlling pest leafcutters. The targets are responsible for antixenobiosis, development and longevity, immunity, resistance to pathogens, pheromone function, cell signaling, behavior, polysaccharide metabolism and arginine kynase activity. Conclusion: The generation and analysis of expressed sequence tags from Atta laevigata have provided important genetic basis for future studies on the biology of leaf-cutting ants and may contribute to the development of a more specific and environmentally friendly method for the control of agricultural pest leafcutters.

Application of HPLC-NMR coupling using C30 phase in the separation and identification of flavonoids of taxonomic relevance

The on-line separation and identification of two important taxonomic markers for plant species of the Paepalanthus genus, the flavonoids 6-methoxykaempferol-3-O-β-D-glucopyranoside and 6-methoxykaempferol-3-O-β-D-6″(p-coumaroyl)glucopyranoside, has been performed with an HPLC-NMR coupling using C30 phase. 1D spectra have been recorded in the stopped-flow mode for the two predominant chromatographic peaks. This is the first application of HPLC-NMR coupling using C30 phase to a taxonomic problem. The technique drastically reduces the required amount of sampling for structure determination. © Springer-Verlag 2000.

Modeling and identification of fertility maps using artificial neural networks

The application of agricultural fertilizers using variable rates along the field can be made through fertility maps previously elaborated or through real-time sensors. In most of the cases applies maps previously elaborated. These maps are identified from analyzes done in soil samples collected regularly (a sample for each field cell) or irregularly along the field. At the moment, mathematical interpolation methods such as nearest neighbor, local average, weighted inverse distance, contouring and kriging are used for predicting the variables involved with elaboration of fertility maps. However, some of these methods present deficiencies that can generate different fertility maps for a same data set. Moreover, such methods can generate inprecise maps to be used in precision farming. In this paper, artificial neural networks have been applied for elaboration and identification of precise fertility maps which can reduce the production costs and environmental impacts.

Identification of lattices from genus of compact surface

In this work we propose procedures for the identification of structure of group associate lattices from fundamental region F4g of regular tessellations {4g; 4g} in the Euclidian plane and hyperbolic plane, where g denote genus of compact surface. © 2006 SBrT.

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.

Optimization of algorithm to identification of duplicate tuples through similarity phonetic based on multithreading

Aiming to ensure greater reliability and consistency of data stored in the database, the data cleaning stage is set early in the process of Knowledge Discovery in Databases (KDD) and is responsible for eliminating problems and adjust the data for the later stages, especially for the stage of data mining. Such problems occur in the instance level and schema, namely, missing values, null values, duplicate tuples, values outside the domain, among others. Several algorithms were developed to perform the cleaning step in databases, some of them were developed specifically to work with the phonetics of words, since a word can be written in different ways. Within this perspective, this work presents as original contribution an optimization of algorithm for the detection of duplicate tuples in databases through phonetic based on multithreading without the need for trained data, as well as an independent environment of language to be supported for this. © 2011 IEEE.

Identification of Candida species in the clinical laboratory: A review of conventional, commercial, and molecular techniques

In healthy individuals, Candida species are considered commensal yeasts of the oral cavity. However, these microorganisms can also act as opportunist pathogens, particularly the so-called non-albicans Candida species that are increasingly recognized as important agents of human infection. Several surveys have documented increased rates of C. glabrata, C. tropicalis, C. guilliermondii, C. dubliniensis, C. parapsilosis, and C. krusei in local and systemic fungal infections. Some of these species are resistant to antifungal agents. Consequently, rapid and correct identification of species can play an important role in the management of candidiasis. Conventional methods for identification of Candida species are based on morphological and physiological attributes. However, accurate identification of all isolates from clinical samples is often complex and time-consuming. Hence, several manual and automated rapid commercial systems for identifying these organisms have been developed, some of which may have significant sensitivity issues. To overcome these limitations, newer molecular typing techniques have been developed that allow accurate and rapid identification of Candida species. This study reviewed the current state of identification methods for yeasts, particularly Candida species. © 2013 John Wiley & Sons A/S.

Identification of b-quark jets with the CMS experiment

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of nonlinear structures using discrete-time Volterra series

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)