Prevalence and nonrandom distribution of exonic mutations in interferon regulatory factor 6 in 307 families with Van der Woude syndrome and 37 families with popliteal pterygium syndrome

Purpose: Interferon regulatory factor 6 encodes a member of the IRF family of transcription factors. Mutations in interferon regulatory factor 6 cause Van der Woude and popliteal pterygium syndrome, two related orofacial clefting disorders. Here, we compared and contrasted the frequency and distribution of exonic Mutations in interferon regulatory factor 6 between two large geographically distinct collections of families with Van der Woude and between one collection of families with popliteal pterygium syndrome. Methods: We performed direct sequence analysis of interferon regulatory factor 6 exons oil samples from three collections, two with Van der Woude and one with popliteal pterygium syndrome. Results: We identified mutations in interferon regulatory factor 6 exons in 68% of families in both Van der Woude collections and in 97% of families with popliteal pterygium syndrome. In sum, 106 novel disease-causing variants were found. The distribution of mutations in the interferon regulatory factor 6 exons in each collection was not random; exons 3, 4, 7, and 9 accounted for 80%. In the Van der Woude collections, the mutations were evenly divided between protein truncation and missense, whereas most mutations identified in the popliteal pterygium syndrome collection were missense. Further, the missense mutations associated with popliteal pterygium syndrome were localized significantly to exon 4, at residues that are predicted to bind directly to DNA. Conclusion: The nonrandom distribution of mutations in the interferon regulatory factor 6 exons suggests a two-tier approach for efficient mutation screens for interferon regulatory factor 6. The type and distribution of mutations are consistent with the hypothesis that Van der Woude is caused by haploinsufficiency of interferon regulatory factor 6. Oil the other hand, the distribution of popliteal pterygium syndrome-associated mutations suggests a different, though not mutually exclusive, effect oil interferon regulatory factor 6 function. Genet Med 2009:11(4):241-247.

An approach to chemotaxonomy to the fatty acid content of some Malvaceae species

Malvales is an order of flowering plants with a controversial circumscription. The relationships between taxa, particularly Malvaceae, Bombacaceae, Sterculiaceae, and Tiliaceae, are not well delineated. Several studies have reported the fatty acid compositions of Malvaceae plants but not for taxonomic purposes. In the present study, the fatty acid composition of oilseeds from seven species belonging to the Malvaceae family was determined by capillary gas chromatography/mass spectrometry (GC/MS), and the quantitative distribution of fatty acids was analyzed by a cluster analysis With Euclidean Distance and UPGMA. The oil content in the seeds was very low (8.3-11.8%). The profile of fatty acids showed that there were two distinct groups: species rich in palmitic acid (Herissantia tiubae, Sidastrum paniculatum and Sida rhombifolia) and species rich in linoleic acid (other Sida species). The fatty acid profiles found for Sida species are consistent with other reported data. Although our data support a distinction between Sida and Sidastrum, more species should be analyzed to evaluate the real taxonomic value of differences in fatty acid content for distinguishing Malvaceae. (C) 2010 Elsevier Ltd. All rights reserved.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

Two-level network design with intermediate facilities: An application to electrical distribution systems

We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times. (C) 2010 Elsevier Ltd. All rights reserved.

A hands-on approach for fitting long-term survival models under the GAMLSS framework

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. in this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

The complementary exponential geometric distribution: Model, properties, and a comparison with its counterpart

In this paper, we proposed a new two-parameter lifetime distribution with increasing failure rate, the complementary exponential geometric distribution, which is complementary to the exponential geometric model proposed by Adamidis and Loukas (1998). The new distribution arises on a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the maximum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its reliability and failure rate functions, moments, including the mean and variance, variation coefficient, and modal value. The parameter estimation is based on the usual maximum likelihood approach. We report the results of a misspecification simulation study performed in order to assess the extent of misspecification errors when testing the exponential geometric distribution against our complementary one in the presence of different sample size and censoring percentage. The methodology is illustrated on four real datasets; we also make a comparison between both modeling approaches. (C) 2011 Elsevier B.V. All rights reserved.

The degree of polydispersity in micellar dispersions: A sum rule approach

Statistical properties of a two-dimensional ideal dispersion of polydisperse micelles are derived by analyzing the convergence properties of a sum rule set by mass conservation. Internal micellar degrees of freedom are accounted for by a microscopic model describing small displacements of the constituting amphiphiles with respect to their equilibrium positions. The transfer matrix (TM) method is employed to compute internal micelle partition function. We show that the conditions under which the sum rule is saturated by the largest eigenvalue of the TM determine the value of amphiphile concentration above which the dispersion becomes highly polydisperse and micelle sizes approach a Schultz distribution. (C) 2011 Elsevier B.V. All rights reserved.

Approach to Equilibrium for a Class of Random Quantum Models of Infinite Range

We consider random generalizations of a quantum model of infinite range introduced by Emch and Radin. The generalizations allow a neat extension from the class l (1) of absolutely summable lattice potentials to the optimal class l (2) of square summable potentials first considered by Khanin and Sinai and generalised by van Enter and van Hemmen. The approach to equilibrium in the case of a Gaussian distribution is proved to be faster than for a Bernoulli distribution for both short-range and long-range lattice potentials. While exponential decay to equilibrium is excluded in the nonrandom l (1) case, it is proved to occur for both short and long range potentials for Gaussian distributions, and for potentials of class l (2) in the Bernoulli case. Open problems are discussed.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Solid state NMR as a new approach for the structural characterization of rare-earth doped lead lanthanum zirconate titanate laser ceramics

To facilitate the design of laser host materials with optimized emission properties, detailed structural information at the atomic level is essential, regarding the local bonding environment of the active ions (distribution over distinct lattice sites) and their extent of local clustering as well as their population distribution over separate micro- or nanophases. The present study explores the potential of solid state NMR spectroscopy to provide such understanding for rare-earth doped lead lanthanum zirconate titanate (PLZT) ceramics. As the NMR signals of the paramagnetic dopant species cannot be observed directly, two complementary approaches are utilized: (1) direct observation of diamagnetic mimics using Sc-45 NMR and (2) study of the paramagnetic interaction of the constituent host lattice nuclei with the rare-earth dopant, using Pb-207 NMR lineshape analysis. Sc-45 MAS NMR spectra of scandium-doped PLZT samples unambiguously reveal scandium to be six-coordinated, suggesting that this rare-earth ion substitutes in the B site. Static Pb-207 spin echo NMR spectra of a series of Tm-doped PLZT samples reveal a clear influence of paramagnetic rare-earth dopant concentration on the NMR lineshape. In the latter case high-fidelity spectra can be obtained by spin echo mapping under systematic incrementation of the excitation frequency, benefiting from the signal-to-noise enhancement afforded by spin echo train Fourier transforms. Consistent with XRD data, the Pb-207 NMR lineshape analysis suggests that statistical incorporation into the PLZT lattice occurs at dopant levels of up to 1 wt.% Tm3+, while at higher levels the solubility limit is reached. (C) 2008 Elsevier Masson SAS. All rights reserved.

Measurement error models with a general class of error distribution

In general, the normal distribution is assumed for the surrogate of the true covariates in the classical error model. This paper considers a class of distributions, which includes the normal one, for the variables subject to error. An estimation approach yielding consistent estimators is developed and simulation studies reported.

A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem

In this article, we introduce a semi-parametric Bayesian approach based on Dirichlet process priors for the discrete calibration problem in binomial regression models. An interesting topic is the dosimetry problem related to the dose-response model. A hierarchical formulation is provided so that a Markov chain Monte Carlo approach is developed. The methodology is applied to simulated and real data.

A reparametrization of Triangular Distribution based on the Skew-Symmetric Distributions

In this paper a new approach is considered for studying the triangular distribution using the theoretical development behind Skew distributions. Triangular distribution are obtained by a reparametrization of usual triangular distribution. Main probabilistic properties of the distribution are studied, including moments, asymmetry and kurtosis coefficients, and an stochastic representation, which provides a simple and efficient method for generating random variables. Moments estimation is also implemented. Finally, a simulation study is conducted to illustrate the behavior of the estimation approach proposed.

An information-theoretic approach to statistical dependence: Copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009