bluuebunny/crossref_metadata_2025 huggingface dataset:
Confidence intervals following Box‐Cox transformation
Authors: Hooper Peter M. , Yang Zhenlin
Published: June 2006

What is the interpretation of a confidence interval following estimation of a Box‐Cox transformation parameter λ? Several authors have argued that confidence intervals for linear model parameters ψ can be constructed as if λ. were known in advance, rather than estimated, provided the estimand is interpreted conditionally given\documentclass{article}\pagestyle{empty}\begin{document}$\hat \lambda$\end{document}. If the estimand is defined as\documentclass{article}\pagestyle{empty}\begin{document}$\psi \left( {\hat \lambda } \right)$\end{document}, a function of the estimated transformation, can the nominal confidence level be regarded as a conditional coverage probability given\documentclass{article}\pagestyle{empty}\begin{document}$\hat \lambda$\end{document}, where the interval is random and the estimand is fixed? Or should it be regarded as an unconditional probability, where both the interval and the estimand are random? This article investigates these questions via large‐napproximations, small‐ σ approximations, and simulations. It is shown that, when model assumptions are satisfied andnis large, the nominal confidence level closely approximates the conditional coverage probability. Whennis small, this conditional approximation is still good for regression models with small error variance. The conditional approximation can be poor for regression models with moderate error variance and single‐factor ANOVA models with small to moderate error variance. In these situations the nominal confidence level still provides a good approximation for the unconditional coverage probability. This suggests that, while the estimand may be interpreted conditionally, the confidence level should sometimes be interpreted unconditionally.
Finite‐population prediction under error‐in‐variables superpopulation models
Authors: Bolfarine Heleno
Published: June 2006

The prediction problem in finite populations is considered under error‐in‐variables super population models. The models considered are the usual regression models involving at most two variables,xandy, where both may be measured with error. Properties of some classical predictors are investigated. A Bayesian approach is proposed.
Contre‐exemple au théorème de P.C. Consul sur la factorisation des distributions de Poisson généralisées
Authors: Letac Gérard
Published: June 2006

This note exhibits two independent random variables on integers, X1 and X2, such that neither X1 nor X2 has a generalized Poisson distribution, but X1 + X2 has. This contradicts statements made by Professor Consul in his recent book.
Some aspects of the reparametrization of statistical models
Authors: Tibshirani Robert , Wasserman Larry
Published: June 2006

Definitions are given for orthogonal parameters in the context of Bayesian inference and likelihood inference. The exact orthogonalizing transformations are derived for both cases, and the connection between the two settings is made precise. These parametrizations simplify the interpretation of likelihood functions and posterior distributions. Further, they make numerical maximization and integration procedures easier to apply. Several applications are studied.
A generalized predictive criterion for model selection
Authors: Trottini Mario , Spezzaferri Fulvio
Published: June 2006

Given a random sample from some unknown model belonging to a finite class of parametric models, assume that the estimate of the density of a future observation is of interest San Martini & Spezzaferri (1984) proposed for this problem a predictive criterion based on the logarithmic utility function. The present authors investigate a generalization of this criterion that uses as a loss function an element of the class of α‐divergences discussed by Ali & Silvey (1966) and Csiszár (1967). They also discuss briefly the case in which the class of models considered is not exhaustive.
Worldwide research output in probability and statistics: An update
Authors: Genest Christian , Guay Mireille
Published: June 2006

The authors update the work of Genest (1997, 1999) on world research output in probability and statistics. The rankings they produce of countries and institutions are based on a survey of papers published between 1986 and 2000 in 25 specialized journals of high reputation in these two fields. The contribution of Canadian probabilists and statisticians is highlighted.
The estimating function bootstrap
Authors: Hu Feifang , Kalbfleisch John D.
Published: June 2006

The authors propose a bootstrap procedure which estimates the distribution of an estimating function by resampling its terms using bootstrap techniques. Studentized versions of this so‐called estimating function (EF) bootstrap yield methods which are invariant under reparametrizations. This approach often has substantial advantage, both in computation and accuracy, over more traditional bootstrap methods and it applies to a wide class of practical problems where the data are independent but not necessarily identically distributed. The methods allow for simultaneous estimation of vector parameters and their components. The authors use simulations to compare the EF bootstrap with competing methods in several examples including the common means problem and nonlinear regression. They also prove symptotic results showing that the studentized EF bootstrap yields higher order approximations for the whole vector parameter in a wide class of problems.
Likelihood inference for small variance components
Authors: Stern Steven E. , Welsh A. H.
Published: June 2006

The authors explore likelihood‐based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, they use local asymptotic approximations to construct confidence intervals for the components of variance when the components are close to the boundary of the parameter space. In the process, they explore the question of how to profile the restricted likelihood (REML). Also, they show that general REML estimates are less likely to fall on the boundary of the parameter space than maximum‐likelihood estimates and that the likelihood‐ratio test based on the local asymptotic approximation has higher power than the likelihood‐ratio test based on the usual chi‐squared approximation. They examine the finite‐sample properties of the proposed intervals by means of a simulation study.
Conjugate analysis of multivariate normal data with incomplete observations
Authors: Dominici Francesca , Parmigiani Giovanni , Clyde Merlise
Published: June 2006

The authors discuss prior distributions that are conjugate to the multivariate normal likelihood when some of the observations are incomplete. They present a general class of priors for incorporating information about unidentified parameters in the covariance matrix. They analyze the special case of monotone patterns of missing data, providing an explicit recursive form for the posterior distribution resulting from a conjugate prior distribution. They develop an importance sampling and a Gibbs sampling approach to sample from a general posterior distribution and compare the two methods.
Kendall's tau for serial dependence
Authors: Ferguson Thomas S. , Genest Christian , Hallin Marc
Published: June 2006

The authors show how Kendall's tau can be adapted to test against serial dependence in a univariate time series context. They provide formulas for the mean and variance of circular and noncircular versions of this statistic, and they prove its asymptotic normality under the hypothesis of independence. They present also a Monte Carlo study comparing the power and size of a test based on Kendall's tau with the power and size of competing procedures based on alternative parametric and nonparametric measures of serial dependence. In particular, their simulations indicate that Kendall's tau outperforms Spearman's rho in detecting first‐order autoregressive dependence, despite the fact that these two statistics are asymptotically equivalent under the null hypothesis, as well as under local alternatives.
Geometric ergodicity of nonlinear autoregressive models with changing conditional variances
Authors: Chen Min , Chen Gemai
Published: June 2006

The authors give easy‐to‐check sufficient conditions for the geometric ergodicity and the finiteness of the moments of a random processxt= ϕ(xt‐1,…,xt‐p) + ϵtσ(xt‐1,…,xt‐q) in which ϕ: Rp→ R, σ Rq→ R and (ϵt) is a sequence of independent and identically distributed random variables. They deduce strong mixing properties for this class of nonlinear autoregressive models with changing conditional variances which includes, among others, the ARCH(p), the AR(p)‐ARCH(p), and the double‐threshold autoregressive models.
Nonparametric estimating equations based on a penalized information criterion
Authors: Li Bing
Published: June 2006

It has recently been observed that, given the mean‐variance relation, one can improve on the accuracy of the quasi‐likelihood estimator by the adaptive estimator based on the estimation of the higher moments. The estimation of such moments is usually unstable, however, and consequently only for large samples does the improvement become evident. The author proposes a nonparametric estimating equation that does not depend on the estimation of such moments, but instead on the penalized minimization of asymptotic variance. His method provides a strong improvement over the quasi‐likelihood estimator and the adaptive estimators, for a wide range of sample sizes.
Penalized regression with model‐based penalties
Authors: Heckman Nancy E. , Ramsay James O.
Published: June 2006

Nonparametric regression techniques such as spline smoothing and local fitting depend implicitly on a parametric model. For instance, the cubic smoothing spline estimate of a regression function ∫ μ based on observationsti,Yi is the minimizer of Σ{Yi ‐ μ(ti)}2+ λ∫(μ′′)2. Since ∫(μ″)2is zero when μ is a line, the cubic smoothing spline estimate favors the parametric model μ(t) = αo+ α1t. Here the authors consider replacing ∫(μ″)2with the more general expression ∫(Lμ)2whereLis a linear differential operator with possibly nonconstant coefficients. The resulting estimate of μ performs well, particularly ifLμ is small. They present an O(n) algorithm for the computation of μ. This algorithm is applicable to a wide class ofL's. They also suggest a method for the estimation ofL. They study their estimates via simulation and apply them to several data sets.
Regression residuals and test statistics: Assessing naive outlier deletion
Authors: Dupuis Debbie J. , Hamilton David C.
Published: June 2006

The authors derive the joint distributions of a studentized deleted residual and various regression quantities, calculated with all the data or with one case deleted. They show that the correlation between the studentized deleted residual and the deleted test statistic has an interesting interpretation in terms of well‐known regression quantities. These results allow them to examine the effect of applying some naive outlier deletion methods before making inferences about a regression parameter.
Robust estimation of the SUR model
Authors: Bilodeau Martin , Duchesne Pierre
Published: June 2006

This paper proposes robust regression to solve the problem of outliers in seemingly unrelated regression (SUR) models. The authors present an adaptation of S‐estimators to SUR models. S‐estimators are robust, have a high breakdown point and are much more efficient than other robust regression estimators commonly used in practice. Furthermore, modifications to Ruppert's algorithm allow a fast evaluation of them in this context. The classical example of U.S. corporations is revisited, and it appears that the procedure gives an interesting insight into the problem.
Bayesian prediction of waiting times in stochastic models
Authors: Butler Ronald W. , Huzurbazar Aparna V.
Published: June 2006

The authors show how saddlepoint techniques lead to highly accurate approximations for Bayesian predictive densities and cumulative distribution functions in stochastic model settings where the prior is tractable, but not necessarily the likelihood or the predictand distribution. They consider more specifically models involving predictions associated with waiting times for semi‐Markov processes whose distributions are indexed by an unknown parameter θ. Bayesian prediction for such processes when they are not stationary is also addressed and the inverse‐Gaussian based saddlepoint approximation of Wood, Booth & Butler (1993) is shown to accurately deal with the nonstationarity whereas the normal‐based Lugannani & Rice (1980) approximation cannot, Their methods are illustrated by predicting various waiting times associated withM/M/qandM/G/1queues. They also discuss modifications to the matrix renewal theory needed for computing the moment generating functions that are used in the saddlepoint methods.
Sensitivity of the fractional Bayes factor to prior distributions
Authors: Conigliani Caterina , O'hagan Anthony
Published: June 2006

The authors derive a measure of the sensitivity of the fractional Bayes factor, an index which is used to compare models when the priors for their respective parameters are improper, or when there is concern about robustness of the prior specification. They prove that in a large class of problems, this measure is a decreasing function of the fraction of the sample used to update the prior distribution before the models are compared.
Reconstructing the history of forest fire frequency: Identifying hazard rate change points using the bayes information criterion
Authors: Reed William J.
Published: June 2006

A problem in model selection, namely the identification of multiple change points for a piece‐wise constant hazard rate, is discussed. A methodology using the Bayes Information Criterion is developed in an overdispersed survival model (with corresponding quasi‐likelihood function). The technique is used to identify changes in the historical frequency of forest fire. It is applied to two datasets derived from time‐since‐fire maps in the Canadian Rockies.
Modeling of rates over a hierarchical health administrative structure
Authors: Dean Charmaine B. , Macnab Ying Cai
Published: June 2006

Identifying the distribution of the incidence rate of a disease over a region is a prediction problem where area‐specific random effects are to be estimated. The authors consider the inclusion of such effects at different levels of a hierarchical health administrative structure. They develop inference procedures for this type of multi‐level model and show that the predicted rates are approximately weighted sums of the crude rates obtained by pooling data on each level of the hierarchy. Their techniques are illustrated using infant mortality data from British Columbia.
Survival analysis with long‐term survivors and partially observed covariates
Authors: Cho Meehyung , Schenker Nathaniel , Taylor Jeremy M. G. , Zhuang Dongliang
Published: June 2006

The authors describe a method for fitting failure time mixture models that postulate the existence of both susceptibles and long‐term survivors when covariate data are only partially observed. Their method is based on a joint model that combines a Weibull regression model for the susceptibles, a logistic regression model for the probability of being a susceptible, and a general location model for the distribution of the covariates. A Bayesian approach is taken, and Gibbs sampling is used to fit the model to the incomplete data. An application to clinical data on tonsil cancer and a small Monte Carlo study indicate potential large gains in efficiency over standard complete‐case analysis as well as reasonable performance in a variety of situations.
A new approach to default priors and robust bayes methodology
Authors: Delampady Mohan , Dasgupta Anirban , Casella George , Rubin Herman , Strawderman William E.
Published: June 2006

Following the developments in DasGupta et al. (2000), the authors propose and explore a new method for constructing proper default priors and a method for selecting a Bayes estimate from a family. Their results are based on asymptotic expansions of certain marginal correlations. For ease of exposition, most results are presented for location families and squared error loss only. The default prior methodology amounts, ultimately, to the minimization of Fisher information, and hence, Bickel's prior works out as the default prior if the location parameter is bounded. As for the selected Bayes estimate, it corresponds to ‘Gaussian tilting’ of an initial reference prior.
Testing fit for the grouped exponential distribution
Authors: Spinelli John J.
Published: June 2006

Grouped data can often arise due to the lack of resolution of the measurement instruments; they also arise when data are deliberately rounded to a certain accuracy and are presented, say, in the form of a histogram. The author uses statistics of the Cramér‐von Mises type to test for the exponential distribution when data are grouped.
On the application of extended quasi‐likelihood to the clustered data case
Authors: Hall Daniel B.
Published: June 2006

The author describes the relationship between the extended generalized estimating equations (EGEEs) of Hall & Severini (1998) and various similar methods. He proposes a true extended quasi‐likelihood approach for the clustered data case and explores restricted maximum likelihood‐like versions of the EGEE and extended quasi‐likelihood estimating equations. He also presents simulation results comparing the various estimators in terms of mean squared error of estimation based on three moderate sample size, discrete data situations.
Estimating the order of a hidden markov model
Authors: Mackay Rachel J.
Published: June 2006

While the estimation of the parameters of a hidden Markov model has been studied extensively, the consistent estimation of the number of hidden states is still an unsolved problem. The AIC and BIC methods are used most commonly, but their use in this context has not been justified theoretically. The author shows that for many common models, the penalized minimum‐distance method yields a consistent estimate of the number of hidden states in a stationary hidden Markov model. In addition to addressing the identifiability issues, she applies her method to a multiple sclerosis data set and assesses its performance via simulation.
Testing circular symmetry
Authors: Pewsey Arthur
Published: June 2006

The author addresses the problem of testing circular data for reflective symmetry about an unknown central direction and proposes a simple omnibus test based on the sample second sine moment about an estimation of this direction. Under quite general conditions, for an underlying distribution which is reflectively symmetric, the large‐sample asymptotic distribution of the test statistic is standard normal. Randomization and bootstrap variants of the test are also introduced, and the operating characteristics of different versions of the test are investigated in a Monte Carlo study. The large‐sample and bootstrap versions of the test are applied in the analysis of two illustrative examples drawn from the circular statistics literature.
Bayesian computation for the superposition of nonhomogeneous poisson processes
Authors: Yang Tae Young , Kuo Lynn
Published: June 2006

Bayesian inference for the superposition of nonhomogeneous Poisson processes is studied. A Markov‐chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, a latent variable is introduced that indicates which component of the superposition model gives rise to the failure. This data‐augmentation approach facilitates specification of the transitional kernel in the Markov chain. Moreover, new Bayesian tests are developed for the full superposition model against simpler submodels. Model determination by a predictive likelihood approach is studied. A numerical example based on a real data set is given.
Some linear model techniques for analyzing small‐circle spherical data
Authors: Rivest Louis‐Paul
Published: June 2006

The author investigates least squares as a method for fitting small‐circle models to a sample of unit vectors in R3. He highlights a local linear model underlying the estimation of the parameters of a circle. This model is used to construct an estimation algorithm and regression‐type inference procedures for the parameters of a circle. It makes it possible to compare the fit of a small circle with that of a spherical ellipse. The limitations of the least‐squares approach are emphasized: when the errors are bounded away from 0, the least‐squares estimators are not consistent as the sample size goes to infinity. Two examples, concerned with the migration of elephant seals and with the classification of geological folds, are analyzed using the linear model techniques proposed in this work.
Convergence properties of the EM algorithm in constrained parameter spaces
Authors: Nettleton Dan
Published: June 2006

The established general results on convergence properties of the EM algorithm require the sequence of EM parameter estimates to fall in the interior of the parameter space over which the likelihood is being maximized. This paper presents convergence properties of the EM sequence of likelihood values and parameter estimates in constrained parameter spaces for which the sequence of EM parameter estimates may converge to the boundary of the constrained parameter space contained in the interior of the unconstrained parameter space. Examples of the behavior of the EM algorithm applied to such parameter spaces are presented.
A minimally informative likelihood for decision analysis: Illustration and robustness
Authors: Yuan Ao , Clarke Bertrand S.
Published: June 2006

The authors discuss a class of likelihood functions involving weak assumptions on data generating mechanisms. These likelihoods may be appropriate when it is difficult to propose models for the data. The properties of these likelihoods are given and it is shown how they can be computed numerically by use of the Blahut‐Arimoto algorithm. The authors then show how these likelihoods can give useful inferences using a data set for which no plausible physical model is apparent. The plausibility of the inferences is enhanced by the extensive robustness analysis these likelihoods permit.
La revue canadiennede statistique statistical science: Concepts, opportunities and challenges
Authors: Lawless Jerald F.
Published: June 2006

Advances in computing and information technology have had a profound impact on many areas of human activity. Statistical tools are ever more widely used, often in new and unconventional environments. Opportunities for statisticians have never been greater, and at the same time, the use of statistics by others is increasing. The author discusses challenges which arise from these conditions, with emphasis on the identity, activities and education of statisticians.
Robust extrapolation designs and weights for biased regression models with heteroscedastic errors
Authors: Fang Zhide , Wiens Douglas P.
Published: June 2006

We consider the construction of designs for the extrapolation of regression responses, allowing both for possible heteroscedasticity in the errors and for imprecision in the specification of the response function. We find minimax designs and correspondingly optimal estimation weights in the context of the following problems: (1) for ordinary least squares estimation, determine a design to minimize the maximum value of the integrated mean squared prediction error (IMSPE), with the maximum being evaluated over both types of departure; (2) for weighted least squares estimation, determine both weights and a design to minimize the maximum IMSPE; (3) choose weights and design points to minimize the maximum IMSPE, subject to a side condition of unbiasedness. Solutions to (1) and (2) are given for multiple linear regression with no interactions, a spherical design space and an annular extrapolation space. For (3) the solution is given in complete generality; as one example we consider polynomial regression. Applications to a dose‐response problem for bioassays are discussed. Numerical comparisons, including a simulation study, indicate that, as well as being easily implemented, the designs and weights for (3) perform as well as those for (1) and (2) and outperform some common competitors for moderate but undetectable amounts of model bias.
L'analyse de la variation saisonniére quand l'amplitude et la taille sont faibles
Authors: Marrero Osvaldo
Published: June 2006

Studies of seasonal variation are valuable in biomedical research because they can help to discover the etiology of diseases that are not well understood. Generally in these studies the data have certain characteristics that require specialized tests and methods for the statistical analysis. But the effectiveness of these specialized tests is variable, especially according to the seasonal variation, the dimension of the amplitude in the seasonal variation, and the sample size. The purpose of this paper is to present a test and methods appropriate for the analysis and modeling of data whose seasonal variation has small amplitude and whose sample size is small. This test can detect different kinds of seasonal variation. The results from a simulation study show that the test performs very well. The application of these methods is illustrated by two examples.
Methodological agreement between two‐compartment body‐composition methods in children
Authors: Buison Anne M. , Ittenbach Richard F. , Stallings Virginia A. , Zemel Babette S.
Published: June 2006

Increases in childhood obesity have emphasized the importance of accurate and accessible body composition assessment, especially in monitoring prevention and treatment efforts. Previous pediatric studies, comparing measures from air‐displacement plethysmography (ADP) to dual‐energy X‐ray absorptiometry (DXA) and anthropometry (ANTH, skinfold measures), were performed in small numbers of children or in children across large age and body‐size ranges. The objectives of this study were: 1) to compare body fat percentage (%BF), fat mass (FM), and fat‐free mass (FFM) from ADP with DXA and ANTH, to determine the agreement between techniques; 2) to identify factors that influence agreement or lack of agreement; and 3) to determine if the agreement is constant over a range of body fatness. Healthy children (n = 125), 7–10 years old, participating in a longitudinal pediatric bone health study, were evaluated. Body composition was assessed by ADP, DXA, and ANTH to determine %BF, FM, and FFM. ADP underestimated %BF compared to DXA and ANTH by 5.0% and 1.4%, respectively. Agreement between techniques was influenced by body fatness, height, age, and gender (all P < 0.05). Relatively good agreement was observed between ADP and both DXA and ANTH for FM and FFM. In conclusion, the underestimation of %BF by ADP compared to DXA may be of a magnitude that is clinically significant, especially when using %BF in children to confirm a diagnosis of obesity. Further development of body‐composition techniques for young children need to account for variability in age, gender, and level of fatness. Am. J. Hum. Biol. 18:470–480, 2006. © 2006 Wiley‐Liss, Inc.
Gene flow in the Iberian Peninsula determined from Y‐chromosome STR loci
Authors: Peña José A. , Garcia‐Obregon Susana , Perez‐Miranda Ana M. , De Pancorbo Marian M. , Alfonso‐Sanchez Miguel A.
Published: June 2006

In this work, seven multiallelic short‐tandem repeat (STR) loci from the nonrecombining region of the human Y‐chromosome (DYS19, DYS389 I, DYS389 II, DYS390, DYS391, DYS392, and DYS393) were typed in a sample of residents in the Basque Country (RBAS). In all, 40 different Y‐STR haplotypic combinations were identified, resulting in a value of haplotypic diversity of 0.979. Y‐STR data compiled from previous works were used for studying Y‐chromosome diversity in the Iberian Peninsula and for assessing the effects of migratory movements on the genetic background of the population living currently in territories traditionally occupied by native (autochthonous) Basques. An analysis of the spatial distribution of allelic frequencies of the Y‐STRs revealed a geographic pattern characterized by variation gradients (frequency clines) oriented for the most part in the direction southwest‐northeast. Accordingly, a neighbor‐joining analysis showed a relative polarization between populations located in the northeast and center of the Iberian Peninsula, and the rest of the samples considered. The study sample (RBAS) occupied an intermediate position in the population tree between the autochthonous Basques (BASQ) and the remaining samples. Interestingly, the RBAS collection only showed genetic heterogeneity with that of native Basques (ΦST = 0.013, P < 0.05). Estimates of admixture proportions in the gene pool of RBAS indicated a high level of hybridization with Basque (56%) and non‐Basque (44%) genes, which could explain the genetic differentiation observed between BASQ and RBAS. Am. J. Hum. Biol. 18:532–539, 2006. © 2006 Wiley‐Liss, Inc.
Common set of genes regulates low‐density lipoprotein size and obesity‐related factors in Alaskan Eskimos: Results from the GOCADAN Study
Authors: Voruganti V. Saroja , Cai Guowen , Cole Shelley A. , Freeland‐Graves Jeanne H. , Laston Sandra , Wenger Charlotte R. , MacCluer Jean W. , Dyke Bennett , Devereux Richard , Ebbesson Sven O.E. , Fabsitz Richard R. , Howard Barbara V. , Comuzzie Anthony G.
Published: June 2006

Increasing incidence of cardiovascular disease in traditionally low‐risk Alaskan Eskimos is a cause for concern. The purpose of this study was to examine the genetic and environmental correlations of low‐density lipoprotein (LDL) subfractions with obesity‐related factors in Alaskan Eskimos, using data from the first 954 participants of the Genetics of Coronary Artery Disease in Alaska Natives Study. Estimates of genetic and environmental influence were calculated using a maximum likelihood variance component method implemented in SOLAR. Mean values of weight, body mass index (BMI), and waist were 73.4 ± 0.5 kg, 27.6 ± 0.2 kg/m2, and 88.0 ± 0.4 cm, respectively. LDL, and its small (LDL1), medium (LDL2), and large (LDL3) subfractions, had mean values of 115.8 ± 1.2 mg/dl, 8.3 ± 0.4 mg/dl, 19.6 ± 0.8 mg/dl, and 71.5 ± 1.5 mg/dl, respectively. Bivariate analysis displayed significant genetic correlations between LDL subfractions and obesity‐related factors: LDL1 with BMI (rhoG = 0.67, P < 0.05), waist (rhoG = 0.80, P < 0.001), and subscapular and tricep skinfolds (rhoG = 0.93, P < 0.005, and rhoG = 0.78, P < 0.05, respectively); LDL2 with BMI (rhoG = 0.52, P < 0.05), waist (rhoG = 0.46, P < 0.05), and tricep skinfold (rhoG = 0.60, P < 0.05); and mean LDL size with BMI (rhoG = −0.36), waist (rhoG = −0.42,), and subscapular and tricep skinfolds (rhoG = −0.44 and −0.43, respectively) (P < 0.005). These results show that a common set of genes is influencing LDL size and obesity‐related factors in Alaskan Eskimos. Am. J. Hum. Biol. 18:525–531, 2006. © 2006 Wiley‐Liss, Inc.
Legendre polynomial kernel estimation of a density function with censored observations and an application to clinical trials
Authors: Berman Simeon M.
Published: June 2006

Let f(x), x ∈ ℝM, M ≥ 1, be a density function on ℝM, and X1, …., Xn a sample of independent random vectors with this common density. For a rectangle B in ℝM, suppose that the X's are censored outside B, that is, the value Xk is observed only if Xk ∈ B. The restriction of f(x) to x ∈ B is clearly estimable by established methods on the basis of the censored observations. The purpose of this paper is to show how to extrapolate a particular estimator, based on the censored sample, from the rectangle B to a specified rectangle C containing B. The results are stated explicitly for M = 1, 2, and are directly extendible to M ≥ 3.

For M = 2, the extrapolation from the rectangle B to the rectangle C is extended to the case where B and C are triangles. This is done by means of an elementary mapping of the positive quarter‐plane onto the strip {(u, v): 0 ≤ u ≤ 1, v > 0}. This particular extrapolation is applied to the estimation of the survival distribution based on censored observations in clinical trials. It represents a generalization of a method proposed in 2001 by the author [2].

The extrapolator has the following form: For m ≥ 1 and n ≥ 1, let Km, n(x) be the classical kernel estimator of f(x), x ∈ B, based on the orthonormal Legendre polynomial kernel of degree m and a sample of n observed vectors censored outside B. The main result, stated in the cases M = 1, 2, is an explicit bound for E|Km, n(x) − f(x)| for x ∈ C, which represents the expected absolute error of extrapolation to C. It is shown that the extrapolator is a consistent estimator of f(x), x ∈ C, if f is sufficiently smooth and if m and n both tend to ∞ in a way that n increases sufficiently rapidly relative to m. © 2006 Wiley Periodicals, Inc.
Temporally regulated delivery of VEGF in vitro and in vivo
Authors: Ennett Alessandra B. , Kaigler Darnell , Mooney David J.
Published: June 2006

The exposure duration and tissue distribution will likely dictate the success of vascular endothelial growth factor (VEGF) in therapeutic angiogenesis. We hypothesized that these variables can be regulated via the manner in which the VEGF is incorporated into polymer constructs (formed with a gas foaming technique) used for its delivery. VEGF was incorporated directly into poly(lactide‐co‐glycolide) (PLG) scaffolds or pre‐encapsulated in PLG microspheres used to fabricate scaffolds. Protein release kinetics and tissue distribution were determined using iodinated VEGF. VEGF was positioned predominantly adjacent to scaffold pores when incorporated directly and was released rapidly (40–60% in 5 days). Pre‐encapsulation led to the VEGF being more deeply embedded and resulted in a delayed release. Alterations in polymer composition, scaffold size, and matrix composition generated minor variations in release kinetics. In vivo, the released VEGF generated local protein concentrations above 10 ng/mL at distances up to 2 cm from the implant site for the 21 days of the experiment, with negligible release into the systemic circulation, and significantly enhanced local angiogenesis. These data indicate that VEGF can be administered in a sustained and localized fashion in vivo, and the timing of VEGF delivery can be altered with the mechanism of incorporation into polymer scaffolds used for its delivery. © 2006 Wiley Periodicals, Inc. J Biomed Mater Res, 2006
Nickel and vanadium metal ions induce apoptosis of T‐lymphocyte Jurkat cells
Authors: Au Angela , Ha Jinny , Hernandez Mauro , Polotsky Anna , Hungerford David S. , Frondoza Carmelita G.
Published: June 2006

Metal alloys are used as prosthetic components in the orthopaedic and dental field. However, there is growing concern over the reported leaching of metal ions from implants. Ions released from metals have been thought to be associated with local immune dysfunction, inflammation, and tissue cell death. The objective of our study was to investigate whether nickel(II) and vanadium(V), present at a smaller percentage in most alloys, are cytotoxic to T‐lymphocyte cell models. Jurkat T cells possess characteristics similar to human T‐lymphocytes and proliferate at a faster rate. Jurkat T cells were incubated with control media alone or with concentrations of 1, 10, and 100 μg/mL of Ni(II) or V(V) for 24 h. Both types of metal ions reduced cell viability and proliferation in a dose‐dependent manner. Ni(II) at 10 μg/mL and V(V) at 100 μg/mL activated Caspase‐3 expression. Hoechst 33258 staining and transmission electron microscopy revealed chromatin condensation, as well as nuclear blebbing and fragmentation. Induction of DNA fragmentation by Ni(II) at 100 μg/mL was also indicated by agarose electrophoresis. Our observations indicate that Ni and V ions kill T cells via apoptotic and nonapoptotic pathways. © 2006 Wiley Periodicals, Inc. J Biomed Mater Res, 2006
Electronic structure of iron(II)–porphyrin nitroxyl complexes: Molecular mechanism of fungal nitric oxide reductase (P450nor)
Authors: Lehnert Nicolai , Praneeth V. K. K. , Paulat Florian
Published: June 2006

Density functional calculations are employed to investigate key intermediates of the catalytic cycle of fungal nitric oxide reductase (P450nor). The formal Fe(II)–nitroxyl species Fe(II)NO/(−) can principally exist in the two spin‐states S = 0 and S = 1. In the S = 0 case, a very covalent FeNO σ bond is present, which leads to an electronic structure description that is actually intermediate between Fe(I)NO and Fe(II)NO−. In contrast, the S = 1 case shows a ferrous Fe(II)NO complex with the extra electron being stored in the π system of the porphyrin ligand. Importantly, the Fe(II)NO/(−) species are very basic. The electronic structures and spectroscopic properties of the corresponding N‐ and O‐protonated forms are very different, and unequivocally show that the Mb–HNO adduct (Mb‐Myoglobin) prepared by farmer and coworkers is in fact N‐protonated. The presence of an axial thiolate ligand enables a second protonation leading to the corresponding Fe(IV)NHOH− species, which is identified with the catalytically active intermediate I of P450nor. This species reacts with a second molecule of NO by initial electron transfer from NO to Fe(IV) followed by addition of NO+ forming an NN bond. This is accompanied by an energetically very favorable intramolecular proton transfer leading to the generation of a quite stable Fe(III)N(OH)(NOH) complex. This way, the enzyme is able to produce dimerized HNO under very controlled conditions and to prevent loss of this ligand from Fe(III). The energetically disfavoured tautomer Fe(III)N(OH2)(NO) is the catalytically productive species that spontaneously cleaves the NOH2 bond forming N2O and H2O in a highly exergonic reaction. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1338–1351, 2006
On the O2 binding of Fe–porphyrin, Fe–porphycene, and Fe–corrphycene complexes
Authors: Nakashima Hiroyuki , Hasegawa Jun‐ya , Nakatsuji Hiroshi
Published: June 2006

Based on our previous study for the O2 binding of the Fe–Por complex, this study investigates the O2 binding mechanism in the Fe–porphyrin isomers, Fe–porphycene (FePc), and Fe–corrphycene (FeCor) complexes. By calculating the potential energy surface of the O2 binding, the present study explains the reason for the dramatic increase of O2 affinities observed in the FePc complex. In the case of FeCor–O2, the O2 binding process includes the intersystem crossing from a triplet to singlet state, as in the FePor–O2 complex. However, FePc–O2 uses only a singlet surface. This is because the ground state of the FePc complex in the deoxy state is a triplet state, while those of FePor and FeCor are a quintet state. Such difference originates from character of the SOMO. We estimated an equilibrium constant for the O2 binding that reasonably reproduced the trend observed in the experiments. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1363–1372, 2006
Quantum chemistry applied to the mechanisms of transition metal containing enzymes—Cytochrome c oxidase, a particularly challenging case
Authors: Blomberg Margareta R. A. , Siegbahn Per E. M.
Published: June 2006

The Density functional theory (B3LYP) has been used to study the mechanisms of OO bond cleavage and proton pumping in cytochrome c oxidase. To understand how the energy from the exergonic reduction of molecular oxygen is used to pump protons across the mitochondrial membrane, the energetics of all steps in the catalytic cycle have to be evaluated. For this purpose, models have to be designed that can accurately reproduce relative redox potentials and pKa values within the active site. The present study shows that it is possible to construct such models and to calculate energy profiles which, to a large extent, agree with experimental information. However, the energy profiles point out a problem with an unbalanced partitioning of the energy between the reductive and oxidative half cycles, which is in disagreement with the experimental observation that the proton pumping is evenly distributed between the two half cycles. A conclusion from the present study is, therefore, that something is probably still missing in the modeling of the active site. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1373–1384, 2006
Do large dogs die young?
Authors: Galis Frietson , Van Der Sluijs Inke , Van Dooren Tom J.M. , Metz Johan A.J. , Nussbaumer Marc
Published: June 2006

In most animal taxa, longevity increases with body size across species, as predicted by the oxidative stress theory of aging. In contrast, in within‐species comparisons of mammals and especially domestic dogs (e.g. Patronek et al.,'97; Michell,'99; Egenvall et al.,2000; Speakman et al.,2003), longevity decreases with body size.

We explore two datasets for dogs and find support for a negative relationship between size and longevity if we consider variation across breeds. Within breeds, however, the relationship is not negative and is slightly, but significantly, positive in the larger of the two datasets. The negative across‐breed relationship is probably the consequence of short life spans in large breeds. Artificial selection for extremely high growth rates in large breeds appears to have led to developmental diseases that seriously diminish longevity.J. Exp. Zool. (Mol. Dev. Evol.) 306B, 2006. © 2006 Wiley‐Liss, Inc.
Lectin‐binding pattern as tool to identify and enrich specific primary testis cells of the tilapia (Oreochromis niloticus) and medaka (Oryzias latipes)
Authors: Tokalov Sergey V. , Gutzeit Herwig O.
Published: June 2006

Cell type‐specific lectin binding is a useful tool for the analysis of developing systems. We describe the binding pattern of 21 different fluorescein isothiocyanate (FITC)‐labelled lectins to the testis of two model teleost species, the medaka (Oryzias latipes) and the tilapia (Oreochromis niloticus). The analysis of the binding pattern was carried out on tissue sections (medaka and tilapia) and using primary culture cells (only tilapia). Lectin binding was studied by confocal microscopy and for histological analysis some sections were, in addition, stained with bodipy to gain additional information concerning the cytological organization of the cystic mode of spermatogenesis in fish. The observed differences in lectin staining of different cell types in primary cultures were quantified by flow cytometry. Only few lectins bound specifically to haploid cells while the reaction to diploid or tetraploid cells was generally stronger. However, the extracellular material around the haploid spermatids and spermatozoa in spermatocysts showed a strong staining reaction with several lectins (e.g., Phaseolus vulgaris Erythro agglutinin). The apparent differences in the cellular lectin‐binding pattern can be used to identify particular cell types, to monitor their differentiation in vitro or to enrich particular cell types from heterogeneous cultures using magnetic beads coated with anti‐FITC antibodies. Using the latter approach, we show that it is possible to enrich for gonial cells and at the same time deplete the preparation for haploid cells and Sertoli cells. J. Exp. Zool. (Mol. Dev. Evol.) 306B, 2006. © 2006 Wiley‐Liss, Inc.
Distinguishing geometric graphs
Authors: Albertson Michael O. , Boutin Debra L.
Published: June 2006

We begin the study of distinguishing geometric graphs. Let G be a geometric graph. An automorphism of the underlying graph that preserves both crossings and noncrossings is called a geometric automorphism. A labeling, f: V(G) → {1, 2, … , r}, is said to be r‐distinguishing if no nontrivial geometric automorphism preserves the labels. The distinguishing number of G is the minimum r such that G has an r‐distinguishing labeling. We show that when Kn is not the nonconvex K4, it can be 3‐distinguished. Furthermore, when n ≥ 6, there is a Kn that can be 1‐distinguished. For n ≥ 4, K2,n can realize any distinguishing number between 1 and n inclusive. Finally, we show that every K3,3 can be 2‐distinguished. We also offer several open questions. © 2006 Wiley Periodicals, Inc. J Graph Theory 53: 135–150, 2006
The comparison of pyrosequencing molecular Gram stain, culture, and conventional Gram stain for diagnosing orthopaedic infections
Authors: Kobayashi Naomi , Bauer Thomas W. , Tuohy Marion J. , Lieberman Isador H. , Krebs Viktor , Togawa Daisuke , Fujishiro Takaaki , Procop Gary W.
Published: June 2006

We have developed a combined real‐time PCR and pyrosequencing assay that successfully differentiated the vast majority of gram‐positive and gram‐negative bacteria when bacterial isolates were tested. The purpose of this study was to evaluate this assay on clinical specimens obtained from orthopedic surgeries, and to prospectively compare the results of “molecular Gram stain” with culture and conventional direct Gram stain. Forty‐five surgical specimens were obtained from patients who underwent orthopedic surgery procedures. The DNA was extracted and a set of broad‐range PCR primers that targeted a part of the 16S rDNA gene was used for pan‐bacterial PCR. The amplicons were submitted for pyrosequencing and the resulting molecular Gram stain characteristics were recorded. Culture and direct Gram staining were performed using standard methods for all cases. Surgical specimens were reviewed histologically for all cases that had a discrepancy between culture and molecular results. There was an 86.7% (39/45) agreement between the traditional and molecular methods. In 12/14 (85.7%) culture‐proven cases of bacterial infection, molecular Gram stain characteristics were in agreement with the culture results, while the conventional Gram stain result was in agreement only for five cases (35.7%). In the 31 culture negative cases, 27 cases were also PCR negative, whereas 4 were PCR positive. Three of these were characterized as gram negative and one as gram positive by this molecular method. Molecular determination of the Gram stain characteristics of bacteria that cause orthopedic infections may be achieved, in most instances, by this method. Further studies are necessary to understand the clinical importance of PCR‐positive/culture‐negative results. © 2006 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 24:1641–1649, 2006