Ineraction Model Between HRSV G-Protein and Flavonoids

Background: Acute respiratory infections (ARI) are the leading cause of infant mortality in the world, and human respiratory syncytial virus (HRSV) is one of the main agents of ARI. One of the key targets of the adaptive host immune response is the RSV G-protein, which is responsible for attachment to the host cell. There is evidence that compounds such as flavonoids can inhibit viral infection in vitro. With this in mind, the main purpose of this study was to determine, using computational tools, the potential sites for interactions between G-protein and flavonoids. Results: Our study allowed the recognition of an hRSV G-protein model, as well as a model of the interaction with flavonoids. These models were composed, mainly, of -helix and random coil proteins. The docking process showed that molecular interactions are likely to occur. The flavonoid kaempferol-3-O-α-L-arabinopyranosil-(2 → 1)-α-L-apiofuranoside-7-O-α-L-rhamnopyranoside was selected as a candidate inhibitor. The main forces of the interaction were hydrophobic, hydrogen and electrostatic. Conclusions: The model of G-protein is consistent with literature expectations, since it was mostly composed of random coils (highly glycosylated sites) and -helices (lipid regions), which are common in transmembrane proteins. The docking analysis showed that flavonoids interact with G-protein in an important ectodomain region, addressing experimental studies to these sites. The determination of the G-protein structure is of great importance to elucidate the mechanism of viral infectivity, and the results obtained in this study will allow us to propose mechanisms of cellular recognition and to coordinate further experimental studies in order to discover effective inhibitors of attachment proteins.

N-Terminal microdomain peptide from human dihydroorotate dehydrogenase: structure and model membrane interactions

The N-terminus of the human dihydroorotate dehydrogenase (HsDHODH) has been described as important for the enzyme attachment in the inner mitochondrial membrane and possibly to regulate enzymatic activity. In this study, we synthesized the peptide acetyl-GDERFYAEHLMPTLQGLLDPESAHRL AVRFTSLGamide, comprising the residues 33-66 of HsDHODH N-terminal conserved microdomain. Langmuir monolayers and circular dichroism (CD) were employed to investigate the interactions between the peptide and membrane model, as micelles and monolayers of the lipids phosphatidylcholine (PC), 3-phosphatidylethanolamine (PE) and cardiolipin (CL). These lipids represent the major constituents of inner mitochondrial membranes. According to CD data, the peptide adopted a random structure in water, whereas it acquired α-helical structures in the presence of micelles. The π–A isotherms and polarization- modulated infrared reflection-absorption spectroscopy on monolayers showed that the peptide interacted with all lipids, but in different ways. In DPPC monolayers, the peptide penetrated into the hydrophobic region. The strongest initial interaction occurred with DPPE, but the peptide was expelled from this monolayer at high surface pressures. In CL, the peptide could induce a partial dissolution of the monolayer, leading to shorter areas at the monolayer collapse. These results corroborate the literature, where the HsDHODH microdomain is anchored into the inner mitochondrial membrane. Moreover, the existence of distinct conformations and interactions with the different membrane lipids indicates that the access to the enzyme active site may be controlled not only by conformational changes occurring at the microdomain of the protein, but also by some lipid-protein synergetic mechanism, where the HsDHODH peptide would be able to recognize lipid domains in the membrane. - See more at: http://www.eurekaselect.com/122062/article#sthash.1ZZbc7E0.dpuf

Random regression models for milk, fat and protein in Colombian Buffaloes

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

Genotype x environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

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

Yang-Lee zeros of the two- and three-state Potts model defined on π3 Feynman diagrams

We present both analytical and numerical results on the position of partition function zeros on the complex magnetic field plane of the q=2 state (Ising) and the q=3 state Potts model defined on phi(3) Feynman diagrams (thin random graphs). Our analytic results are based on the ideas of destructive interference of coexisting phases and low temperature expansions. For the case of the Ising model, an argument based on a symmetry of the saddle point equations leads us to a nonperturbative proof that the Yang-Lee zeros are located on the unit circle, although no circle theorem is known in this case of random graphs. For the q=3 state Potts model, our perturbative results indicate that the Yang-Lee zeros lie outside the unit circle. Both analytic results are confirmed by finite lattice numerical calculations.

Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variabilidade espaço-temporal da emissão de CO2 do solo em curto período sob influência de eventos de precipitação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Partially Observed Markov Random Fields Are Variable Neighborhood Random Fields

The present paper has two goals. First to present a natural example of a new class of random fields which are the variable neighborhood random fields. The example we consider is a partially observed nearest neighbor binary Markov random field. The second goal is to establish sufficient conditions ensuring that the variable neighborhoods are almost surely finite. We discuss the relationship between the almost sure finiteness of the interaction neighborhoods and the presence/absence of phase transition of the underlying Markov random field. In the case where the underlying random field has no phase transition we show that the finiteness of neighborhoods depends on a specific relation between the noise level and the minimum values of the one-point specification of the Markov random field. The case in which there is phase transition is addressed in the frame of the ferromagnetic Ising model. We prove that the existence of infinite interaction neighborhoods depends on the phase.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Anderson-like Transition for a Class of Random Sparse Models in d >= 2 Dimensions

We show that the Kronecker sum of d >= 2 copies of a random one-dimensional sparse model displays a spectral transition of the type predicted by Anderson, from absolutely continuous around the center of the band to pure point around the boundaries. Possible applications to physics and open problems are discussed briefly.

Supersymmetric extension of the quantum spherical model

In this work, we present a supersymmetric extension of the quantum spherical model, both in components and also in the superspace formalisms. We find the solution for short- and long-range interactions through the imaginary time formalism path integral approach. The existence of critical points (classical and quantum) is analyzed and the corresponding critical dimensions are determined.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Effects of 830 and 670 nm Laser on Viability of Random Skin Flap in Rats

Objective: This study aimed to investigate the effect of 830 and 670 nm diode laser on the viability of random skin flaps in rats. Background data: Low-level laser therapy (LLLT) has been reported to be successful in stimulating the formation of new blood vessels and reducing the inflammatory process after injury. However, the efficiency of such treatment remains uncertain, and there is also some controversy regarding the efficacy of different wavelengths currently on the market. Materials and methods: Thirty Wistar rats were used and divided into three groups, with 10 rats in each. A random skin flap was raised on the dorsum of each animal. Group 1 was the control group, group 2 received 830 nm laser radiations, and group 3 was submitted to 670 nm laser radiation (power density = 0.5 mW/cm(2)). The animals underwent laser therapy with 36 J/cm(2) energy density (total energy = 2.52 J and 72 sec per session) immediately after surgery and on the 4 subsequent days. The application site of laser radiation was one point at 2.5 cm from the flap's cranial base. The percentage of skin flap necrosis area was calculated on the 7th postoperative day using the paper template method. A skin sample was collected immediately after to determine the vascular endothelial growth factor (VEGF) expression and the epidermal cell proliferation index (KiD67). Results: Statistically significant differences were found among the percentages of necrosis, with higher values observed in group 1 compared with groups 2 and 3. No statistically significant differences were found among these groups using the paper template method. Group 3 presented the highest mean number of blood vessels expressing VEGF and of cells in the proliferative phase when compared with groups 1 and 2. Conclusions: LLLT was effective in increasing random skin flap viability in rats. The 670 nm laser presented more satisfactory results than the 830 nm laser.

Mean-Field critical behavior and ergodicity break in a nonequilibrium one-dimensional RSOS growth model

We investigate the nonequilibrium roughening transition of a one-dimensional restricted solid-on-solid model by directly sampling the stationary probability density of a suitable order parameter as the surface adsorption rate varies. The shapes of the probability density histograms suggest a typical Ginzburg-Landau scenario for the phase transition of the model, and estimates of the "magnetic" exponent seem to confirm its mean-field critical behavior. We also found that the flipping times between the metastable phases of the model scale exponentially with the system size, signaling the breaking of ergodicity in the thermodynamic limit. Incidentally, we discovered that a closely related model not considered before also displays a phase transition with the same critical behavior as the original model. Our results support the usefulness of off-critical histogram techniques in the investigation of nonequilibrium phase transitions. We also briefly discuss in the appendix a good and simple pseudo-random number generator used in our simulations.

Probabilistic crack growth analyses using a boundary element model: Applications in linear elastic fracture and fatigue problems

This paper addresses the numerical solution of random crack propagation problems using the coupling boundary element method (BEM) and reliability algorithms. Crack propagation phenomenon is efficiently modelled using BEM, due to its mesh reduction features. The BEM model is based on the dual BEM formulation, in which singular and hyper-singular integral equations are adopted to construct the system of algebraic equations. Two reliability algorithms are coupled with BEM model. The first is the well known response surface method, in which local, adaptive polynomial approximations of the mechanical response are constructed in search of the design point. Different experiment designs and adaptive schemes are considered. The alternative approach direct coupling, in which the limit state function remains implicit and its gradients are calculated directly from the numerical mechanical response, is also considered. The performance of both coupling methods is compared in application to some crack propagation problems. The investigation shows that direct coupling scheme converged for all problems studied, irrespective of the problem nonlinearity. The computational cost of direct coupling has shown to be a fraction of the cost of response surface solutions, regardless of experiment design or adaptive scheme considered. (C) 2012 Elsevier Ltd. All rights reserved.