958 resultados para Protein Structure, Multifractal Analysis, 6 Letter Model


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Hemoproteins are a very important class of enzymes in nature sharing the essentially same prosthetic group, heme, and are good models for exploring the relationship between protein structure and function. Three important hemoproteins, chloroperoxidase (CPO), horseradish peroxidase (HRP), and cytochrome P450cam (P450cam), have been extensively studied as archetypes for the relationship between structure and function. In this study, a series of 1D and 2D NMR experiments were successfully conducted to contribute to the structural studies of these hemoproteins. ^ During the epoxidation of allylbenzene, CPO is converted to an inactive green species with the prosthetic heme modified by addition of the alkene plus an oxygen atom forming a five-membered chelate ring. Complete assignment of the NMR resonances of the modified porphyrin extracted and demetallated from green CPO unambiguously established the structure of this porphyrin as an NIII-alkylated product. A novel substrate binding motif of CPO was proposed from this concluded regiospecific N-alkylation structure. ^ Soybean peroxidase (SBP) is considered as a more stable, more abundant and less expensive substitute of HRP for industrial applications. A NMR study of SBP using 1D and 2D NOE methods successfully established the active site structure of SBP and consequently fills in the blank of the SBP NMR study. All of the hyperfine shifts of the SBP-CN- complex are unambiguously assigned together with most of the prosthetic heme and all proximal His170 resonances identified. The active site structure of SBP revealed by this NMR study is in complete agreement with the recombinant SBP crystal structure and is highly similar to that of the HRP with minor differences. ^ The NMR study of paramagnetic P450cam had been greatly restricted for a long time. A combination of 2D NMR methods was used in this study for P450cam-CN - complexes with and without camphor bound. The results lead to the first unequivocal assignments of all heme hyperfine-shifted signals, together with certain correlated diamagnetic resonances. The observed alternation of the assigned novel proximal cysteine β-CH2 resonances induced by camphor binding indicated a conformational change near the proximal side.^

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The focus of this study is to elucidate the components of the nurse shark (Ginglymostoma cirratum) membrane attack complex (MAC), specifically complement component C8a (GcC8u). Nurse shark C8a gene was cloned, sequenced, and analyzed and Western blot analysis performed to identify components of shark MAC. GcC8a consists of 2341 nucleotides that translate into a 589 amino acid sequence that shares 41.1% and 47.4 % identity with human and xenopus C8a, respectively. GcC8a conserves the MAC modular architecture and cysteine-rich backbone characteristic of complement proteins, including the cysteine residue that forms the C8a-y bond as well as the indel that is unique to C8a. Conservation of MAC protein structure is evident from crossreactivity of antihuman-MAC antibodies with shark serum proteins in Western blots which confirmed the presence of C8 and C9-like proteins in shark serum, however, did not resolve the question of whether C6 and/or C7 like proteins are present in shark.

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The role of steroids hormones on the behavior of vertebrates have been described as organizational and activational effects. These actions occur in different periods of the ontogenetic development as fetal, early post natal and during puberty (organizational effect) or modifying the expression of behavioral patterns during time life (activational effects). Studies on brain lateralization in hand use in human and non-human primates have shown that sexual hormones seems to participate in the process of handedness strength that begins in the puberal period and is stabilized at the adult age. The aim of this study was to investigate in adult male Callithrix jacchus if the strength of use of the hand in common marmoset adult male is stable (organizational effect) or androgens variations could affect its stability (activational effect). The preferential use of one hand in 14 common marmoset (Callithrix jacchus was studied in two contexts: (1) spontaneous holding food and directing the food to mouth (feeding episodes), and (2) forced reaching food tests where the animal have to reach the food through a hole within a cover plate with a central hole that allow the use of one hand only to reach the food. The records were made during 5 sessions/20 bouts each during baseline totalizing 100 episodes before two treatments. Firstly it was used GnRH antagonist: a single subcutaneous injection of 100µg de Cetrotide – acetate of cetrorrelix (Baxter Oncology GmbH, Germany) (n=10). Secondly, a single GnRH injection of 0.2mg of GnRH (Sigma – Aldrich) (n= 8) was used. After injections 20 successful attempts of hand use episodes was recorded in the 1st , 2 nd, 7th, 15th and 30 th days, totalizing in the whole period 100 episodes for each context, after both treatments. Fecal sampling to measure extracted fecal androgens was performed in all days of data collection across the length of the basal and during the experimental periods. Statistical analysis by mixed model, Tukey test to compare mean values after the two treatments, and Levene test to compare mean variance were used, all for p-value < 0.05. In basal phase 6 animals used preferentially the right hand, 5 the left and 3 were ambidextrous. Mean handedness index in basal phase were different from that after both treatment starting at 7th day. Mean variance of handedness index for spontaneous and forced activities does not differs before and after both treatments but the mean values for GnRH index were higher than that observed for its antagonist. These findings suggested that androgens have an activational effect on handedness in adult male C. jacchus

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Analogous to sunspots and solar photospheric faculae, which visibility is modulated by stellar rotation, stellar active regions consist of cool spots and bright faculae caused by the magnetic field of the star. Such starspots are now well established as major tracers used to estimate the stellar rotation period, but their dynamic behavior may also be used to analyze other relevant phenomena such as the presence of magnetic activity and its cycles. To calculate the stellar rotation period, identify the presence of active regions and investigate if the star exhibits or not differential rotation, we apply two methods: a wavelet analysis and a spot model. The wavelet procedure is also applied here to study pulsation in order to identify specific signatures of this particular stellar variability for different types of pulsating variable stars. The wavelet transform has been used as a powerful tool for treating several problems in astrophysics. In this work, we show that the time-frequency analysis of stellar light curves using the wavelet transform is a practical tool for identifying rotation, magnetic activity, and pulsation signatures. We present the wavelet spectral composition and multiscale variations of the time series for four classes of stars: targets dominated by magnetic activity, stars with transiting planets, those with binary transits, and pulsating stars. We applied the Morlet wavelet (6th order), which offers high time and frequency resolution. By applying the wavelet transform to the signal, we obtain the wavelet local and global power spectra. The first is interpreted as energy distribution of the signal in time-frequency space, and the second is obtained by time integration of the local map. Since the wavelet transform is a useful mathematical tool for nonstationary signals, this technique applied to Kepler and CoRoT light curves allows us to clearly identify particular signatures for different phenomena. In particular, patterns were identified for the temporal evolution of the rotation period and other periodicity due to active regions affecting these light curves. In addition, a beat-pattern vii signature in the local wavelet map of pulsating stars over the entire time span was also detected. The second method is based on starspots detection during transits of an extrasolar planet orbiting its host star. As a planet eclipses its parent star, we can detect physical phenomena on the surface of the star. If a dark spot on the disk of the star is partially or totally eclipsed, the integrated stellar luminosity will increase slightly. By analyzing the transit light curve it is possible to infer the physical properties of starspots, such as size, intensity, position and temperature. By detecting the same spot on consecutive transits, it is possible to obtain additional information such as the stellar rotation period in the planetary transit latitude, differential rotation, and magnetic activity cycles. Transit observations of CoRoT-18 and Kepler-17 were used to implement this model.

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Sexual harassment at work is a form of gender violence barely made visible but still present in labor organizations, where it keeps generating high levels of suffering, discrimination and inequality mainly affecting women. To address it properly it is necessary an organizational change towards equity arising from the knowledge of the subjective meanings that stakeholders (staff, union representatives, employers, public administration, etc.) attribute to that reality. In this article we present the main findings of a qualitative study on the social perception of sexual harassment. The work highlights the existence of many strategies aimed at legitimize and minimize the relevance of the problem, blaming the victim, justifying the lack of support from the environment and / or the involvement of the organization in the solutions. Among the conclusions we underline the need for new models of business management involving all stakeholders in the prevention and control of the in a responsible way.

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The category of rational SO(2)--equivariant spectra admits an algebraic model. That is, there is an abelian category A(SO(2)) whose derived category is equivalent to the homotopy category of rational$SO(2)--equivariant spectra. An important question is: does this algebraic model capture the smash product of spectra? The category A(SO(2)) is known as Greenlees' standard model, it is an abelian category that has no projective objects and is constructed from modules over a non--Noetherian ring. As a consequence, the standard techniques for constructing a monoidal model structure cannot be applied. In this paper a monoidal model structure on A(SO(2)) is constructed and the derived tensor product on the homotopy category is shown to be compatible with the smash product of spectra. The method used is related to techniques developed by the author in earlier joint work with Roitzheim. That work constructed a monoidal model structure on Franke's exotic model for the K_(p)--local stable homotopy category. A monoidal Quillen equivalence to a simpler monoidal model category that has explicit generating sets is also given. Having monoidal model structures on the two categories removes a serious obstruction to constructing a series of monoidal Quillen equivalences between the algebraic model and rational SO(2)--equivariant spectra.

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We formally compare fundamental factor and latent factor approaches to oil price modelling. Fundamental modelling has a long history in seeking to understand oil price movements, while latent factor modelling has a more recent and limited history, but has gained popularity in other financial markets. The two approaches, though competing, have not formally been compared as to effectiveness. For a range of short- medium- and long-dated WTI oil futures we test a recently proposed five-factor fundamental model and a Principal Component Analysis latent factor model. Our findings demonstrate that there is no discernible difference between the two techniques in a dynamic setting. We conclude that this infers some advantages in adopting the latent factor approach due to the difficulty in determining a well specified fundamental model.

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Respiratory infections by bacteria of the Burkholderia cepacia complex (Bcc) remain an important cause of morbidity and mortality among cystic fibrosis patients, highlighting the need for novel therapeutic strategies. In the present work we have studied the B. cenocepacia protein BCAL2958, a member of the OmpA-like family of proteins, demonstrated as highly immunogenic in other pathogens and capable of eliciting strong host immune responses. The encoding gene was cloned and the protein, produced as a 6× His-tagged derivative, was used to produce polyclonal antibodies. Bioinformatics analyses led to the identification of sequences encoding proteins with a similarity higher than 96 % to BCAL2958 in all the publicly available Bcc genomes. Furthermore, using the antibody it was experimentally demonstrated that this protein is produced by all the 12 analyzed strains from 7 Bcc species. In addition, results are also presented showing the presence of anti-BCAL2958 antibodies in sera from cystic fibrosis patients with a clinical record of respiratory infection by Bcc, and the ability of the purified protein to in vitro stimulate neutrophils. The widespread production of the protein by Bcc members, together with its ability to stimulate the immune system and the detection of circulating antibodies in patients with a documented record of Bcc infection strongly suggest that the protein is a potential candidate for usage in preventive therapies of infections by Bcc.

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Les déficits cognitifs sont présents chez les patients atteints de cancer. Les tests cognitifs tels que le Montreal Cognitive Assessment se sont révélés peu spécifiques, incapables de détecter des déficits légers et ne sont pas linéaires. Pour suppléer à ces limitations nous avons développé un questionnaire cognitif simple, bref et adapté aux dimensions cognitives atteintes chez les patients avec un cancer, le FaCE « The Fast Cognitif Evaluation », en utilisant la modélisation Rasch (MR). La MR est une méthode mathématique probabiliste qui détermine les conditions pour qu’un outil soit considéré une échelle de mesure et elle est indépendante de l’échantillon. Si les résultats s’ajustent au modèle, l’échelle de mesure est linéaire avec des intervalles égaux. Les réponses sont basées sur la capacité des sujets et la difficulté des items. La carte des items permet de sélectionner les items les plus adaptés pour l’évaluation de chaque aspect cognitif et d’en réduire le nombre au minimum. L’analyse de l’unidimensionnalité évalue si l’outil mesure une autre dimension que celle attendue. Les résultats d’analyses, conduites sur 165 patients, montrent que le FaCE distingue avec une excellente fiabilité et des niveaux suffisamment différents les compétences des patients (person-reliability-index=0.86; person-separation-index=2.51). La taille de la population et le nombre d’items sont suffisants pour que les items aient une hiérarchisation fiable et précise (item-reliability=0.99; item-séparation-index=8.75). La carte des items montre une bonne dispersion de ceux-ci et une linéarité du score sans effet plafond. Enfin, l’unidimensionnalité est respectée et le temps d’accomplissement moyen est d’environ 6 minutes. Par définition la MR permet d’assurer la linéarité et la continuité de l’échelle de mesure. Nous avons réussi à développer un questionnaire bref, simple, rapide et adapté aux déficits cognitifs des patients avec un cancer. Le FaCE pourrait, aussi, servir de mesure de référence pour les futures recherches dans le domaine.

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Turnip crinkle virus (TCV) and Pea enation mosaic virus (PEMV) are two positive (+)-strand RNA viruses that are used to investigate the regulation of translation and replication due to their small size and simple genomes. Both viruses contain cap-independent translation elements (CITEs) within their 3´ untranslated regions (UTRs) that fold into tRNA-shaped structures (TSS) according to nuclear magnetic resonance and small angle x-ray scattering analysis (TCV) and computational prediction (PEMV). Specifically, the TCV TSS can directly associate with ribosomes and participates in RNA-dependent RNA polymerase (RdRp) binding. The PEMV kissing-loop TSS (kl-TSS) can simultaneously bind to ribosomes and associate with the 5´ UTR of the viral genome. Mutational analysis and chemical structure probing methods provide great insight into the function and secondary structure of the two 3´ CITEs. However, lack of 3-D structural information has limited our understanding of their functional dynamics. Here, I report the folding dynamics for the TCV TSS using optical tweezers (OT), a single molecule technique. My study of the unfolding/folding pathways for the TCV TSS has provided an unexpected unfolding pathway, confirmed the presence of Ψ3 and hairpin elements, and suggested an interconnection between the hairpins and pseudoknots. In addition, this study has demonstrated the importance of the adjacent upstream adenylate-rich sequence for the formation of H4a/Ψ3 along with the contribution of magnesium to the stability of the TCV TSS. In my second project, I report on the structural analysis of the PEMV kl-TSS using NMR and SAXS. This study has re-confirmed the base-pair pattern for the PEMV kl-TSS and the proposed interaction of the PEMV kl-TSS with its interacting partner, hairpin 5H2. The molecular envelope of the kl-TSS built from SAXS analysis suggests the kl-TSS has two functional conformations, one of which has a different shape from the previously predicted tRNA-shaped form. Along with applying biophysical methods to study the structural folding dynamics of RNAs, I have also developed a technique that improves the production of large quantities of recombinant RNAs in vivo for NMR study. In this project, I report using the wild-type and mutant E.coli strains to produce cost-effective, site-specific labeled, recombinant RNAs. This technique was validated with four representative RNAs of different sizes and complexity to produce milligram amounts of RNAs. The benefit of using site-specific labeled RNAs made from E.coli was demonstrated with several NMR techniques.

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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

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We study spatially localized states of a spiking neuronal network populated by a pulse coupled phase oscillator known as the lighthouse model. We show that in the limit of slow synaptic interactions in the continuum limit the dynamics reduce to those of the standard Amari model. For non-slow synaptic connections we are able to go beyond the standard firing rate analysis of localized solutions allowing us to explicitly construct a family of co-existing one-bump solutions, and then track bump width and firing pattern as a function of system parameters. We also present an analysis of the model on a discrete lattice. We show that multiple width bump states can co-exist and uncover a mechanism for bump wandering linked to the speed of synaptic processing. Moreover, beyond a wandering transition point we show that the bump undergoes an effective random walk with a diffusion coefficient that scales exponentially with the rate of synaptic processing and linearly with the lattice spacing.

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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

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Incorporation of carbon nanostructures in metals is desirable to combine the strongly bonded electrons in the metal and the free electrons in carbon nanostructures that give rise to high ampacity and high conductivity, respectively. Carbon in copper has the potential to impact industries such as: building construction, power generation and transmission, and microelectronics. This thesis focuses on the structure and properties of bulk and thin films of a new material, Cu covetic, that contains carbon in concentrations up to 16 at.%. X-ray photoelectron spectroscopy (XPS) shows C 1s peak with both sp2 and sp3 bonded C measuring up to 3.5 wt.% (16 at.%). High resolution transmission electron microscopy and electron diffraction of bulk covetic samples show a modulated structure of ≈ 1.6 nm along several crystallographic directions in regions that have high C content suggesting that the carbon incorporates into the copper lattice forming a network. Electron energy loss spectra (EELS) from covetics reveal that the level of graphitization from the source material, activated carbon, is maintained in the covetic structure. Bulk Cu covetics have a slight increase in the lattice constant, as well as <111> texturing, or possibly a different structure, compared to pure Cu. Density functional theory calculations predict bonding between C and Cu at the edges and defects of graphene sheets. The electrical resistivity of bulk covetics first increases and then decreases with increasing C content. Cu covetic films were deposited using e-beam and pulsed laser deposition (PLD) at different temperatures. No copper oxide or any allotropes of carbon are present in the films. The e-beam films show enhanced electrical and optical properties when compared to pure Cu films of the same thickness even though no carbon was detected by XPS or EELS. They also have slightly higher ampacity than Cu metal films. EELS analysis of the C-K-edge in the PLD films indicate that graphitic carbon is transferred from the bulk into the films with uniform carbon distribution. PLD films exhibit flatter and higher transmittance curves and sheet resistance two orders of magnitude lower than e-beam films leading to a high figure of merit as transparent conductors.