Interactions protéiques et relation dynamique entre phosphorylation / sumoylation / ubiquitination des protéines TIF1α, β et PML: détection in vivo par BRET

Trois protéines de la famille TRIM (Motif TRIpartite), TIF1α, β (Transcriptional Intermediary Factor 1) et PML (ProMyelocytic Leukaemia¬), font l’objet de cette étude. TIF1α est connu comme un coactivateur des récepteurs nucléaires et TIF1β comme le corépresseur universel des protéines KRAB-multidoigt de zinc dont le prototype étudié ici est ZNF74. PML possède divers rôles dont le plus caractérisé est celui d’être l’organisateur principal et essentiel des PML-NBs (PML-Nuclear Bodies), des macrostructures nucléaires très dynamiques regroupant et coordonnant plus de 40 protéines. Il est à noter que la fonction de TIF1α, β et PML est régulée par une modification post-traductionnelle, la sumoylation, qui implique le couplage covalent de la petite protéine SUMO (Small Ubiquitin like MOdifier) à des lysines de ces trois protéines cibles. Cette thèse propose de développer des méthodes utilisant le BRET (Bioluminescence Resonance Energy Transfert) afin de détecter dans des cellules vivantes et en temps réel des interactions non-covalentes de protéines nucléaires mais aussi leur couplage covalent à SUMO. En effet, le BRET n’a jamais été exploré jusqu’alors pour étudier les interactions non-covalentes et covalentes de protéines nucléaires. L’étude de l’interaction de protéines transcriptionnellement actives est parfois difficile par des méthodes classiques du fait de leur grande propension à agréger (famille TRIM) ou de leur association à la matrice nucléaire (ZNF74). L’homo et l’hétérodimérisation de TIF1α, β ainsi que leur interaction avec ZNF74 sont ici testées sur des protéines entières dans des cellules vivantes de mammifères répondant aux résultats conflictuels de la littérature et démontrant que le BRET peut être avantageusement utilisé comme alternative aux essais plus classiques basés sur la transcription. Du fait de l’hétérodimérisation confirmée de TIF1α et β, le premier article présenté ouvre la possibilité d’une relation étroite entre les récepteurs nucléaires et les protéines KRAB- multidoigt de zinc. Des études précédentes ont démontré que la sumoylation de PML est impliquée dans sa dégradation induite par l’As2O3 et dépendante de RNF4, une E3 ubiquitine ligase ayant pour substrat des chaînes de SUMO (polySUMO). Dans le second article, grâce au développement d’une nouvelle application du BRET pour la détection d’interactions covalentes et non-covalentes avec SUMO (BRETSUMO), nous établissons un nouveau lien entre la sumoylation de PML et sa dégradation. Nous confirmons que le recrutement de RNF4 dépend de SUMO mais démontrons également l’implication du SBD (Sumo Binding Domain) de PML dans sa dégradation induite par l’As2O3 et/ou RNF4. De plus, nous démontrons que des sérines, au sein du SBD de PML, qui sont connues comme des cibles de phosphorylation par la voie de la kinase CK2, régulent les interactions non-covalentes de ce SBD mettant en évidence, pour la première fois, que les interactions avec un SBD peuvent dépendre d’un évènement de phosphorylation (“SBD phospho-switch”). Nos résultats nous amènent à proposer l’hypothèse que le recrutement de PML sumoylé au niveau des PML-NBs via son SBD, favorise le recrutement d’une autre activité E3 ubiquitine ligase, outre celle de RNF4, PML étant lui-même un potentiel candidat. Ceci suggère l’existence d’une nouvelle relation dynamique entre phosphorylation, sumoylation et ubiquitination de PML. Finalement, il est suggéré que PML est dégradé par deux voies différentes dépendantes de l’ubiquitine et du protéasome; la voie de CK2 et la voie de RNF4. Enfin une étude sur la sumoylation de TIF1β est également présentée en annexe. Cette étude caractérise les 6 lysines cibles de SUMO sur TIF1β et démontre que la sumoylation est nécessaire à l’activité répressive de TIF1β mais n’est pas impliquée dans son homodimérisation ou son interaction avec la boîte KRAB. La sumoylation est cependant nécessaire au recrutement d’histones déacétylases, dépendante de son homodimérisation et de l’intégrité du domaine PHD. Alors que l’on ne connaît pas de régulateur physiologique de la sumoylation outre les enzymes directement impliquées dans la machinerie de sumoylation, nous mettons en évidence que la sumoylation de TIF1β est positivement régulée par son interaction avec le domaine KRAB et suggérons que ces facteurs transcriptionnels recrutent TIF1β à l’ADN au niveau de promoteur et augmentent son activité répressive en favorisant sa sumoylation.

Analysis of Stochastic Volatility Sequences Generated by Product Autoregressive Models

The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

An improved reliability Cuk based solar inverter with sliding mode control

Many photovoltaic inverter designs make use of a buck based switched mode power supply (SMPS) to produce a rectified sinusoidal waveform. This waveform is then unfolded by a low frequency switching structure to produce a fully sinusoidal waveform. The Cuk SMPS could offer advantages over the buck in such applications. Unfortunately the Cuk converter is considered to be difficult to control using classical methods. Correct closed loop design is essential for stable operation of Cuk converters. Due to these stability issues, Cuk converter based designs often require stiff low bandwidth control loops. In order to achieve this stable closed loop performance, traditional designs invariably need large, unreliable electrolytic capacitors. In this paper, an inverter with a sliding mode control approach is presented which enables the designer to make use of the Cuk converters advantages, while ameliorating control difficulties. This control method allows the selection of passive components based predominantly on ripple and reliability specifications while requiring only one state reference signal. This allows much smaller, more reliable non-electrolytic capacitors to be used. A prototype inverter has been constructed and results obtained which demonstrate the design flexibility of the Cuk topology when coupled with sliding mode control.

The effects of landscape modifications on the long-term persistence of animal populations

Background: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Methodology/Principal Findings: Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Significance: Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.

Diversity of strains of Salmonella enterica serotype Enteritidis from English poultry farms assessed by multiple genetic fingerprinting

Reliable and sufficiently discriminative methods are needed for differentiating individual strains of Salmonella enterica serotype Enteritidis beyond the phenotypic level; however, a consensus has not been reached as to which molecular method is best suited for this purpose. In addition, data are lacking on the molecular fingerprinting of serotype Enteritidis from poultry environments in the United Kingdom. This study evaluated the combined use of classical methods (phage typing) with three well-established molecular methods (ribotyping, macrorestriction analysis of genomic DNA, and plasmid profiling) in the assessment of diversity within 104 isolates of serotype Enteritidis from eight unaffiliated poultry farms in England. The most sensitive technique for identifying polymorphism was PstI-SphII ribotyping, distinguishing a total of 22 patterns, 10 of which were found among phage type 4 isolates. Pulsed-field gel electrophoresis of XhaI-digested genomic DNA segregated the isolates into only six types with minor differences between them. In addition, 14 plasmid profiles were found among this population. When all of the typing methods were combined, 54 types of strains were differentiated, and most of the poultry farms presented a variety of strains, which suggests that serotype Enteritidis organisms representing different genomic groups are circulating in England. In conclusion, geographical and animal origins of Salmonella serotype Enteritidis isolates may have a considerable influence on selecting the best typing strategy for individual programs, and a single method cannot be relied on for discriminating between strains.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.

Recent progress on biosorption of heavy metals from liquids using low cost biosorbents : characterization, biosorption parameters and mechanism studies

A significant number of biosorption studies on the removal of heavy metal from aqueous solutions have been conducted worldwide. Nearly all of them have been directed towards optimizing biosorption parameters to obtain the highest removal efficiency while the rest of them are concerned with the biosorption mechanism. Combinations of FTIR, SEM-EDX, TEM as well as classical methods such as titrations are extremely useful in determining the main processes on the surfaces of biosorbents. Diverse functional groups represented by carboxyl, hydroxyl, sulfate and amino groups play significant roles in the biosorption process. Solution pH normally has a large impact on biosorption performance. In brief, ion exchange and complexation can be pointed out as the most prevalent mechanisms for the biosorption of most heavy metals.

Determinação de Chaveamento para Recomposição do Serviço em Redes de Distribuição de Energia Elétrica em Média Tensão Através de Métodos Baseado em Parâmetros de Sensibilidade

The reconfiguration of a distribution network is a change in its topology, aiming to provide specific operation conditions of the network, by changing the status of its switches. It can be performed regardless of any system anomaly. The service restoration is a particular case of reconfiguration and should be performed whenever there is a network failure or whenever one or more sections of a feeder have been taken out of service for maintenance. In such cases, loads that are supplied through lines sections that are downstream of portions removed for maintenance may be supplied by the closing of switches to the others feeders. By classical methods of reconfiguration, several switches may be required beyond those used to perform the restoration service. This includes switching feeders in the same substation or for substations that do not have any direct connection to the faulted feeder. These operations can cause discomfort, losses and dissatisfaction among consumers, as well as a negative reputation for the energy company. The purpose of this thesis is to develop a heuristic for reconfiguration of a distribution network, upon the occurrence of a failure in this network, making the switching only for feeders directly involved in this specific failed segment, considering that the switching applied is related exclusively to the isolation of failed sections and bars, as well as to supply electricity to the islands generated by the condition, with significant reduction in the number of applications of load flows, due to the use of sensitivity parameters for determining voltages and currents estimated on bars and lines of the feeders directly involved with that failed segment. A comparison between this process and classical methods is performed for different test networks from the literature about networks reconfiguration

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Monitoramento ambiental da costa do Rio Grande do Norte com base em sensoriamento remoto e geodésia de precisão

This paper presents models of parameters of Sea Surface Layer (SSL), such as chlorophyll-a, sea surface temperature (SST), Primary Productivity (PP) and Total Suspended Matter (TSM) for the region adjacent to the continental shelf of Rio Grande do Norte (RN), Brazil. Concentrations of these parameters measured in situ were compared in time quasi-synchronous with images AQUA-MODIS between the years 2003 to 2011. Determination coefficients between samples in situ and bands reflectance sensor AQUA-MODIS were representative. From that, concentrations of SSL parameters were acquired for the continental shelf of the RN (eastern and northern) analyzing the geographic distribution of variation of these parameters between the years 2009-2012. Geographical and seasonal variations mainly influenced by global climate phenomena such as El Niño and La Niña, were found through the analysis of AQUA-MODIS images by Principal Components Analysis (PCA). Images show qualitatively the variance and availability of TSM in the regions, as well as their relationship with coastal erosion hotspots, monitored along the coast of the RN. In one of the areas identified as being of limited availability of TSM, we developed a methodology for assessment and evaluation of Digital Elevation Models (DEM) of beach surfaces (emerged and submerged sections) from the integration of topographic and bathymetric data measured in situ and accurately georeferenced compatible to studies of geomorphology and coastal dynamics of short duration. The methodology consisted of surveys with GNSS positioning operated in cinematic relative mode involved in topographic and bathymetric executed in relation to the stations of the geodetic network of the study area, which provided geodetic link to the Brazilian Geodetic System (GBS), univocal , fixed, and relatively stable over time. In this study Ponta Negra Beach, Natal / RN, was identified as a region with low variance and availability of MPS in the region off, as characterized by intense human occupation and intense coastal erosion in recent decades, which presents potential of the proposed methodology for accuracy and productivity, and the progress achieved in relation to the classical methods of surveying beach profiles

Eletrodo modificado em filme de paládio para a determinação voltamétrica de fosfito

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

Identification of Mycobacteria by Thin Layer Chromatographic Analysis of Mycolic Acids and Conventional Biochemical Method: Four Years of Experience

Mycolic acids analysis by thin-layer chromatography (TLC) has been employed by several laboratories worldwide as a method for fast identification of mycobacteria. This method was introduced in Brazil by our laboratory in 1992 as a routine identification technique. Up to the present, 861 strains isolated were identified by mycolic acids TLC and by standard biochemical tests; 61% out of these strains came as clinical samples, 4% isolated from frogs and 35% as environmental samples. Mycobacterium tuberculosis strains identified by classical methods were confirmed by their mycolic acids contents (I, III and IV). The method allowed earlier differentiation of M. avium complex - MAC (mycolic acids I, IV and VI) from M. simiae (acids I, II and IV), both with similar biochemical properties. The method also permitted to distinguish M. fortuitum (acids I and V) from M. chelonae (acids I and II) , and to detect mixed mycobacterial infections cases as M. tuberculosis with MAC and M. fortuitum with MAC. Concluding, four years experience shows that mycolic acids TLC is an easy, reliable, fast and inexpensive method, an important tool to put together conventional mycobacteria identification methods.

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.