990 resultados para DIFFERENTIAL IDENTIFICATION
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Two methods of differential isotopic coding of carboxylic groups have been developed to date. The first approach uses d0- or d3-methanol to convert carboxyl groups into the corresponding methyl esters. The second relies on the incorporation of two 18O atoms into the C-terminal carboxylic group during tryptic digestion of proteins in H(2)18O. However, both methods have limitations such as chromatographic separation of 1H and 2H derivatives or overlap of isotopic distributions of light and heavy forms due to small mass shifts. Here we present a new tagging approach based on the specific incorporation of sulfanilic acid into carboxylic groups. The reagent was synthesized in a heavy form (13C phenyl ring), showing no chromatographic shift and an optimal isotopic separation with a 6 Da mass shift. Moreover, sulfanilic acid allows for simplified fragmentation in matrix-assisted laser desorption/ionization (MALDI) due the charge fixation of the sulfonate group at the C-terminus of the peptide. The derivatization is simple, specific and minimizes the number of sample treatment steps that can strongly alter the sample composition. The quantification is reproducible within an order of magnitude and can be analyzed either by electrospray ionization (ESI) or MALDI. Finally, the method is able to specifically identify the C-terminal peptide of a protein by using GluC as the proteolytic enzyme.
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Differential protein labeling with 2-DE separation is an effective method for distinguishing differences in the protein composition of two or more protein samples. Here, we report on a sensitive infrared-based labeling procedure, adding a novel tool to the many labeling possibilities. Defined amounts of newborn and adult mouse brain proteins and tubulin were exposed to maleimide-conjugated infrared dyes DY-680 and DY-780 followed by 1- and 2-DE. The procedure allows amounts of less than 5 microg of cysteine-labeled protein mixtures to be detected (together with unlabeled proteins) in a single 2-DE step with an LOD of individual proteins in the femtogram range; however, co-migration of unlabeled proteins and subsequent general protein stains are necessary for a precise comparison. Nevertheless, the most abundant thiol-labeled proteins, such as tubulin, were identified by MS, with cysteine-containing peptides influencing the accuracy of the identification score. Unfortunately, some infrared-labeled proteins were no longer detectable by Western blots. In conclusion, differential thiol labeling with infrared dyes provides an additional tool for detection of low-abundant cysteine-containing proteins and for rapid identification of differences in the protein composition of two sets of protein samples.
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The objective of this work was to determine the transcript profile of tomato plants (Lycopersicon esculentum Mill.), during Fusarium oxysporum f. sp. lycopersici infection and after foliar application of salicylic acid. The suppression subtractive hybridization (SSH) technique was used to generate a cDNA library enriched for transcripts differentially expressed. A total of 307 clones was identified in two subtractive libraries, which allowed the isolation of several defense-related genes that play roles in different mechanisms of plant resistance to phytopathogens. Genes with unknown roles were also isolated from the two libraries, which indicates the possibility of identifying new genes not yet reported in studies of stress/defense response. The SSH technique is effective for identification of resistance genes activated by salicylic acid and F. oxysporum f. sp. lycopersici infection. Not only the application of this technique enables a cost effective isolation of differentially expressed sequences, but also it allows the identification of novel sequences in tomato from a relative small number of sequences.
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Access to new biological sources is a key element of natural product research. A particularly large number of biologically active molecules have been found to originate from microorganisms. Very recently, the use of fungal co-culture to activate the silent genes involved in metabolite biosynthesis was found to be a successful method for the induction of new compounds. However, the detection and identification of the induced metabolites in the confrontation zone where fungi interact remain very challenging. To tackle this issue, a high-throughput UHPLC-TOF-MS-based metabolomic approach has been developed for the screening of fungal co-cultures in solid media at the petri dish level. The metabolites that were overexpressed because of fungal interactions were highlighted by comparing the LC-MS data obtained from the co-cultures and their corresponding mono-cultures. This comparison was achieved by subjecting automatically generated peak lists to statistical treatments. This strategy has been applied to more than 600 co-culture experiments that mainly involved fungal strains from the Fusarium genera, although experiments were also completed with a selection of several other filamentous fungi. This strategy was found to provide satisfactory repeatability and was used to detect the biomarkers of fungal induction in a large panel of filamentous fungi. This study demonstrates that co-culture results in consistent induction of potentially new metabolites.
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The objective of this work was to identify genes that could be used as suitable markers for molecular recognition of phenological stages during coffee (Coffea arabica) fruit development. Four cultivars were evaluated as to their differential expression of genes associated to fruit development and maturation processes. Gene expression was characterized by both semi-quantitative and quantitative RT-PCR, in fruit harvested at seven different developmental stages, during three different seasons. No size polymorphisms or differential expression were observed among the cultivars for the evaluated genes; however, distinct expression profiles along fruit development were determined for each gene. Four out of the 28 evaluated genes exhibited a regular expression profile in all cultivars and harvest seasons, and, therefore, they were validated as candidate phenological markers of coffee fruit. The gene α-galactosidase can be used as a marker of green stage, caffeine synthase as a marker of transition to green and yellowish-green stages, and isocitrate lyase and ethylene receptor 3 as markers of late maturation.
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PURPOSE Our purpose was development and assessment of a BRAF-mutant gene expression signature for colon cancer (CC) and the study of its prognostic implications. Materials and METHODS A set of 668 stage II and III CC samples from the PETACC-3 (Pan-European Trails in Alimentary Tract Cancers) clinical trial were used to assess differential gene expression between c.1799T>A (p.V600E) BRAF mutant and non-BRAF, non-KRAS mutant cancers (double wild type) and to construct a gene expression-based classifier for detecting BRAF mutant samples with high sensitivity. The classifier was validated in independent data sets, and survival rates were compared between classifier positive and negative tumors. Results A 64 gene-based classifier was developed with 96% sensitivity and 86% specificity for detecting BRAF mutant tumors in PETACC-3 and independent samples. A subpopulation of BRAF wild-type patients (30% of KRAS mutants, 13% of double wild type) showed a gene expression pattern and had poor overall survival and survival after relapse, similar to those observed in BRAF-mutant patients. Thus they form a distinct prognostic subgroup within their mutation class. CONCLUSION A characteristic pattern of gene expression is associated with and accurately predicts BRAF mutation status and, in addition, identifies a population of BRAF mutated-like KRAS mutants and double wild-type patients with similarly poor prognosis. This suggests a common biology between these tumors and provides a novel classification tool for cancers, adding prognostic and biologic information that is not captured by the mutation status alone. These results may guide therapeutic strategies for this patient segment and may help in population stratification for clinical trials.
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The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.
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NR2E3 encodes the photoreceptor-specific nuclear hormone receptor that acts as a repressor of cone-specific gene expression in rod photoreceptors, and as an activator of several rod-specific genes. Recessive variants located in the ligand-binding domain (LBD) of NR2E3 cause enhanced short wavelength sensitive- (S-) cone syndrome (ESCS), a retinal degeneration characterized by an excess of S-cones and non-functional rods. We analyzed the dimerization properties of NR2E3 and the effect of disease-causing LBD missense variants by bioluminescence resonance energy transfer (BRET(2) ) protein interaction assays. Homodimerization was not affected in presence of p.A256V, p.R039G, p.R311Q, and p.R334G variants, but abolished in presence of p.L263P, p.L336P, p.L353V, p.R385P, and p.M407K variants. Homology modeling predicted structural changes induced by NR2E3 LBD variants. NR2E3 LBD variants did not affect interaction with CRX, but with NRL and rev-erbα/NR1D1. CRX and NRL heterodimerized more efficiently together, than did either with NR2E3. NR2E3 did not heterodimerize with TLX/NR2E1 and RXRα/NR2C1. The identification of a new compound heterozygous patient with detectable rod function, who expressed solely the p.A256V variant protein, suggests a correlation between LBD variants able to form functional NR2E3 dimers and atypical mild forms of ESCS with residual rod function.
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Abstract Hyperechoic lesions are not a frequent finding at breasts ultrasonography, and most of times are associated with benign pathologies that do not require further evaluation. However, some neoplasms such as invasive breast carcinomas and metastases may present with hyperechogenicity. Thus, the knowledge about differential diagnoses and identification of signs of lesion aggressiveness are of great relevance to avoid unnecessary procedures or underdiagnosis, and to support the correct clinical/surgical approach. On the basis of such concepts, the present essay describes and illustrates the main features of hyperechoic lesions at breast ultrasonography in different cases, with anatomopathological correlation.
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Due to the increased importance of angular leaf spot of common bean (Phaseolus vulgaris) in Brazil, monitoring the pathogenic variability of its causal agent (Phaeoisariopsis griseola) is the best strategy for a breeding program aimed at developing resistant genotypes. Fifty one isolates of P. griseola collected in five Brazilian States were tested on a set of 12 international differential cultivars in the greenhouse. When inoculated plants showed symptoms but no sporulation was observed, they were transferred to a moist chamber for approximately 20-24 h. After this period of time, if no sporulation was observed, the plants were considered resistant; otherwise, they were considered susceptible. From the fifty-one tested isolates, seven different pathotypes were identified. No Andean pathotypes were identified; consequently, all isolates were classified as Middle American pathotypes. Pathotype 63-31 was the most widespread. Pathotype 63-63 overcame resistance genes present in all differential cultivars and also the resistance gene(s) present in the cultivar AND 277. This fact has important implications for breeding angular leaf spot resistance in beans, and suggests that searching for new resistance genes to angular leaf spot must be pursued.
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Twelve single-pustule isolates of Uromyces appendiculatus, the etiological agent of common bean rust, were collected in the state of Minas Gerais, Brazil, and classified according to the new international differential series and the binary nomenclature system proposed during the 3rd Bean Rust Workshop. These isolates have been used to select rust-resistant genotypes in a bean breeding program conducted by our group. The twelve isolates were classified into seven different physiological races: 21-3, 29-3, 53-3, 53-19, 61-3, 63-3 and 63-19. Races 61-3 and 63-3 were the most frequent in the area. They were represented by five and two isolates, respectively. The other races were represented by just one isolate. This is the first time the new international classification procedure has been used for U. appendiculatus physiological races in Brazil. The general adoption of this system will facilitate information exchange, allowing the cooperative use of the results obtained by different research groups throughout the world. The differential cultivars Mexico 309, Mexico 235 and PI 181996 showed resistance to all of the isolates that were characterized. It is suggested that these cultivars should be preferentially used as sources for resistance to rust in breeding programs targeting development lines adapted to the state of Minas Gerais.
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To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements, but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.
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Target of this book is to propose an approach for modelling drivetrain dynamics in order to design further a vibration control system of a hybrid bus. In this thesis two approaches are examined and compared. First model is obtained by theoretical means: drivetrain is represented as a system of rotating masses, which motion is described with differential equations. Second model is obtained using system identification method: mathematical description of the dynamic behavior of a system is formed based on measured input (torque) and output (speed) data. Then two models are compared and an optimal approach is suggested.
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Affiliation: Institut de recherche en immunologie et en cancérologie, Université de Montréal
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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal