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Sample records for genetic covariances alter

How much do genetic covariances alter the rate of adaptation?

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Agrawal, Aneil F; Stinchcombe, John R

2009-03-22

Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.
Alterations in Anatomical Covariance in the Prematurely Born.

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Scheinost, Dustin; Kwon, Soo Hyun; Lacadie, Cheryl; Vohr, Betty R; Schneider, Karen C; Papademetris, Xenophon; Constable, R Todd; Ment, Laura R

2017-01-01

Preterm (PT) birth results in long-term alterations in functional and structural connectivity, but the related changes in anatomical covariance are just beginning to be explored. To test the hypothesis that PT birth alters patterns of anatomical covariance, we investigated brain volumes of 25 PTs and 22 terms at young adulthood using magnetic resonance imaging. Using regional volumetrics, seed-based analyses, and whole brain graphs, we show that PT birth is associated with reduced volume in bilateral temporal and inferior frontal lobes, left caudate, left fusiform, and posterior cingulate for prematurely born subjects at young adulthood. Seed-based analyses demonstrate altered patterns of anatomical covariance for PTs compared with terms. PTs exhibit reduced covariance with R Brodmann area (BA) 47, Broca's area, and L BA 21, Wernicke's area, and white matter volume in the left prefrontal lobe, but increased covariance with R BA 47 and left cerebellum. Graph theory analyses demonstrate that measures of network complexity are significantly less robust in PTs compared with term controls. Volumes in regions showing group differences are significantly correlated with phonological awareness, the fundamental basis for reading acquisition, for the PTs. These data suggest both long-lasting and clinically significant alterations in the covariance in the PTs at young adulthood. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Altered Cerebral Blood Flow Covariance Network in Schizophrenia.

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Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui

2016-01-01

Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia.
An alternative covariance estimator to investigate genetic heterogeneity in populations.

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Heslot, Nicolas; Jannink, Jean-Luc

2015-11-26

For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative
The causes of variation in the presence of genetic covariance between sexual traits and preferences.

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Fowler-Finn, Kasey D; Rodríguez, Rafael L

2016-05-01

Mating traits and mate preferences often show patterns of tight correspondence across populations and species. These patterns of apparent coevolution may result from a genetic association between traits and preferences (i.e. trait-preference genetic covariance). We review the literature on trait-preference covariance to determine its prevalence and potential biological relevance. Of the 43 studies we identified, a surprising 63% detected covariance. We test multiple hypotheses for factors that may influence the likelihood of detecting this covariance. The main predictor was the presence of genetic variation in mate preferences, which is one of the three main conditions required for the establishment of covariance. In fact, 89% of the nine studies where heritability of preference was high detected covariance. Variables pertaining to the experimental methods and type of traits involved in different studies did not greatly influence the detection of trait-preference covariance. Trait-preference genetic covariance appears to be widespread and therefore represents an important and currently underappreciated factor in the coevolution of traits and preferences. © 2015 Cambridge Philosophical Society.
A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics.

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Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-12-07

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Performance of penalized maximum likelihood in estimation of genetic covariances matrices

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Meyer Karin

2011-11-01

Full Text Available Abstract Background Estimation of genetic covariance matrices for multivariate problems comprising more than a few traits is inherently problematic, since sampling variation increases dramatically with the number of traits. This paper investigates the efficacy of regularized estimation of covariance components in a maximum likelihood framework, imposing a penalty on the likelihood designed to reduce sampling variation. In particular, penalties that "borrow strength" from the phenotypic covariance matrix are considered. Methods An extensive simulation study was carried out to investigate the reduction in average 'loss', i.e. the deviation in estimated matrices from the population values, and the accompanying bias for a range of parameter values and sample sizes. A number of penalties are examined, penalizing either the canonical eigenvalues or the genetic covariance or correlation matrices. In addition, several strategies to determine the amount of penalization to be applied, i.e. to estimate the appropriate tuning factor, are explored. Results It is shown that substantial reductions in loss for estimates of genetic covariance can be achieved for small to moderate sample sizes. While no penalty performed best overall, penalizing the variance among the estimated canonical eigenvalues on the logarithmic scale or shrinking the genetic towards the phenotypic correlation matrix appeared most advantageous. Estimating the tuning factor using cross-validation resulted in a loss reduction 10 to 15% less than that obtained if population values were known. Applying a mild penalty, chosen so that the deviation in likelihood from the maximum was non-significant, performed as well if not better than cross-validation and can be recommended as a pragmatic strategy. Conclusions Penalized maximum likelihood estimation provides the means to 'make the most' of limited and precious data and facilitates more stable estimation for multi-dimensional analyses. It should
Genetic and Environmental Contributions to Covariation Between DHEA and Testosterone in Adolescent Twins.

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Van Hulle, Carol A; Moore, Mollie N; Shirtcliff, Elizabeth A; Lemery-Chalfant, Kathryn; Goldsmith, H Hill

2015-05-01

Although several studies have shown that pubertal tempo and timing are shaped by genetic and environmental factors, few studies consider to what extent endocrine triggers of puberty are shaped by genetic and environmental factors. Doing so moves the field from examining correlated developmentally-sensitive biomarkers toward understanding what drives those associations. Two puberty related hormones, dehydroepiandrosterone and testosterone, were assayed from salivary samples in 118 MZ (62 % female), 111 same sex DZ (46 % female) and 103 opposite-sex DZ twin pairs, aged 12-16 years (M = 13.1, SD = 1.3). Pubertal status was assessed with a composite of mother- and self-reports. We used biometric models to estimate the genetic and environmental influences on the variance and covariance in testosterone and DHEA, with and without controlling for their association with puberty, and to test for sex differences. In males, the variance in testosterone and pubertal status was due to shared and non-shared environmental factors; variation in DHEA was due to genetic and non-shared environmental factors. In females, variance in testosterone was due to genetic and non-shared environmental factors; genetic, shared, and non-shared environmental factors contributed equally to variation in DHEA. In males, the testosterone-DHEA covariance was primarily due to shared environmental factors that overlapped with puberty as well as shared and non-shared environmental covariation specific to testosterone and DHEA. In females, the testosterone-DHEA covariance was due to genetic factors overlapping with pubertal status, and shared and non-shared environmental covariation specific to testosterone and DHEA.
Perils of parsimony: properties of reduced-rank estimates of genetic covariance matrices.

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Meyer, Karin; Kirkpatrick, Mark

2008-10-01

Eigenvalues and eigenvectors of covariance matrices are important statistics for multivariate problems in many applications, including quantitative genetics. Estimates of these quantities are subject to different types of bias. This article reviews and extends the existing theory on these biases, considering a balanced one-way classification and restricted maximum-likelihood estimation. Biases are due to the spread of sample roots and arise from ignoring selected principal components when imposing constraints on the parameter space, to ensure positive semidefinite estimates or to estimate covariance matrices of chosen, reduced rank. In addition, it is shown that reduced-rank estimators that consider only the leading eigenvalues and -vectors of the "between-group" covariance matrix may be biased due to selecting the wrong subset of principal components. In a genetic context, with groups representing families, this bias is inverse proportional to the degree of genetic relationship among family members, but is independent of sample size. Theoretical results are supplemented by a simulation study, demonstrating close agreement between predicted and observed bias for large samples. It is emphasized that the rank of the genetic covariance matrix should be chosen sufficiently large to accommodate all important genetic principal components, even though, paradoxically, this may require including a number of components with negligible eigenvalues. A strategy for rank selection in practical analyses is outlined.
The effects of stress and sex on selection, genetic covariance, and the evolutionary response.

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Holman, L; Jacomb, F

2017-10-01

The capacity of a population to adapt to selection (evolvability) depends on whether the structure of genetic variation permits the evolution of fitter trait combinations. Selection, genetic variance and genetic covariance can change under environmental stress, and males and females are not genetically independent, yet the combined effects of stress and dioecy on evolvability are not well understood. Here, we estimate selection, genetic (co)variance and evolvability in both sexes of Tribolium castaneum flour beetles under stressful and benign conditions, using a half-sib breeding design. Although stress uncovered substantial latent heritability, stress also affected genetic covariance, such that evolvability remained low under stress. Sexual selection on males and natural selection on females favoured a similar phenotype, and there was positive intersex genetic covariance. Consequently, sexual selection on males augmented adaptation in females, and intralocus sexual conflict was weak or absent. This study highlights that increased heritability does not necessarily increase evolvability, suggests that selection can deplete genetic variance for multivariate trait combinations with strong effects on fitness, and tests the recent hypothesis that sexual conflict is weaker in stressful or novel environments. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.
Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

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Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.
Altered structural covariance of the striatum in functional dyspepsia patients.

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Liu, P; Zeng, F; Yang, F; Wang, J; Liu, X; Wang, Q; Zhou, G; Zhang, D; Zhu, M; Zhao, R; Wang, A; Gong, Q; Liang, F

2014-08-01

Functional dyspepsia (FD) is thought to be involved in dysregulation within the brain-gut axis. Recently, altered striatum activation has been reported in patients with FD. However, the gray matter (GM) volumes in the striatum and structural covariance patterns of this area are rarely explored. The purpose of this study was to examine the GM volumes and structural covariance patterns of the striatum between FD patients and healthy controls (HCs). T1-weighted magnetic resonance images were obtained from 44 FD patients and 39 HCs. Voxel-based morphometry (VBM) analysis was adopted to examine the GM volumes in the two groups. The caudate- or putamen-related regions identified from VBM analysis were then used as seeds to map the whole brain voxel-wise structural covariance patterns. Finally, a correlation analysis was used to investigate the effects of FD symptoms on the striatum. The results showed increased GM volumes in the bilateral putamen and right caudate. Compared with the structural covariance patterns of the HCs, the FD-related differences were mainly located in the amygdala, hippocampus/parahippocampus (HIPP/paraHIPP), thalamus, lingual gyrus, and cerebellum. And significant positive correlations were found between the volumes in the striatum and the FD duration in the patients. These findings provided preliminary evidence for GM changes in the striatum and different structural covariance patterns in patients with FD. The current results might expand our understanding of the pathophysiology of FD. © 2014 John Wiley & Sons Ltd.
Evolution of the additive genetic variance–covariance matrix under continuous directional selection on a complex behavioural phenotype

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Careau, Vincent; Wolak, Matthew E.; Carter, Patrick A.; Garland, Theodore

2015-01-01

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance–covariance matrix (G). Yet knowledge of G in a population experiencing new or altered selection is not sufficient to predict selection response because G itself evolves in ways that are poorly understood. We experimentally evaluated changes in G when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. PMID:26582016
Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

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Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2015-11-22

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. © 2015 The Author(s).
The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

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Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

2018-03-22

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.
Alternative life histories in the Atlantic salmon: genetic covariances within the sneaker sexual tactic in males.

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Páez, David James; Bernatchez, Louis; Dodson, Julian J

2011-07-22

Alternative reproductive tactics are ubiquitous in many species. Tactic expression often depends on whether an individual's condition surpasses thresholds that are responsible for activating particular developmental pathways. Two central goals in understanding the evolution of reproductive tactics are quantifying the extent to which thresholds are explained by additive genetic effects, and describing their covariation with condition-related traits. We monitored the development of early sexual maturation that leads to the sneaker reproductive tactic in Atlantic salmon (Salmo salar L.). We found evidence for additive genetic variance in the timing of sexual maturity (which is a measure of the surpassing of threshold values) and body-size traits. This suggests that selection can affect the patterns of sexual development by changing the timing of this event and/or body size. Significant levels of covariation between these traits also occurred, implying a potential for correlated responses to selection. Closer examination of genetic covariances suggests that the detected genetic variation is distributed along at least five directions of phenotypic variation. Our results show that the potential for evolution of the life-history traits constituting this reproductive phenotype is greatly influenced by their patterns of genetic covariance.
Genetic covariance components within and among linear type traits differ among contrasting beef cattle breeds.

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Doyle, Jennifer L; Berry, Donagh P; Walsh, Siobhan W; Veerkamp, Roel F; Evans, Ross D; Carthy, Tara R

2018-05-04

Linear type traits describing the skeletal, muscular, and functional characteristics of an animal are routinely scored on live animals in both the dairy and beef cattle industries. Previous studies have demonstrated that genetic parameters for certain performance traits may differ between breeds; no study, however, has attempted to determine if differences exist in genetic parameters of linear type traits among breeds or sexes. Therefore, the objective of the present study was to determine if genetic covariance components for linear type traits differed among five contrasting cattle breeds, and to also investigate if these components differed by sex. A total of 18 linear type traits scored on 3,356 Angus (AA), 31,049 Charolais (CH), 3,004 Hereford (HE), 35,159 Limousin (LM), and 8,632 Simmental (SI) were used in the analysis. Data were analyzed using animal linear mixed models which included the fixed effects of sex of the animal (except in the investigation into the presence of sexual dimorphism), age at scoring, parity of the dam, and contemporary group of herd-date of scoring. Differences (P covariance parameters estimated from the CH breed with a linear function of breeding values computed conditional on covariance parameters estimated from the other breeds was estimated. Replacing the genetic covariance components estimated in the CH breed with those of the LM had least effect but the impact was considerable when the genetic covariance components of the AA were used. Genetic correlations between the same linear type traits in the two sexes were all close to unity (≥0.90) suggesting little advantage in considering these as separate traits for males and females. Results for the present study indicate the potential increase in accuracy of estimated breeding value prediction from considering, at least, the British breed traits separate to continental breed traits.
Genetic diversity and species diversity of stream fishes covary across a land-use gradient

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Blum, M.J.; Bagley, M.J.; Walters, D.M.; Jackson, S.A.; Daniel, F.B.; Chaloud, D.J.; Cade, B.S.

2012-01-01

Genetic diversity and species diversity are expected to covary according to area and isolation, but may not always covary with environmental heterogeneity. In this study, we examined how patterns of genetic and species diversity in stream fishes correspond to local and regional environmental conditions. To do so, we compared population size, genetic diversity and divergence in central stonerollers (Campostoma anomalum) to measures of species diversity and turnover in stream fish assemblages among similarly sized watersheds across an agriculture-forest land-use gradient in the Little Miami River basin (Ohio, USA). Significant correlations were found in many, but not all, pair-wise comparisons. Allelic richness and species richness were strongly correlated, for example, but diversity measures based on allele frequencies and assemblage structure were not. In-stream conditions related to agricultural land use were identified as significant predictors of genetic diversity and species diversity. Comparisons to population size indicate, however, that genetic diversity and species diversity are not necessarily independent and that variation also corresponds to watershed location and glaciation history in the drainage basin. Our findings demonstrate that genetic diversity and species diversity can covary in stream fish assemblages, and illustrate the potential importance of scaling observations to capture responses to hierarchical environmental variation. More comparisons according to life history variation could further improve understanding of conditions that give rise to parallel variation in genetic diversity and species diversity, which in turn could improve diagnosis of anthropogenic influences on aquatic ecosystems. ?? 2011 Springer-Verlag.
The evolution of phenotypic integration: How directional selection reshapes covariation in mice.

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Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel

2017-10-01

Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.
Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes.

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Hosseini, S M Hadi; Mazaika, Paul; Mauras, Nelly; Buckingham, Bruce; Weinzimer, Stuart A; Tsalikian, Eva; White, Neil H; Reiss, Allan L

2016-11-01

Type 1 diabetes mellitus (T1D), one of the most frequent chronic diseases in children, is associated with glucose dysregulation that contributes to an increased risk for neurocognitive deficits. While there is a bulk of evidence regarding neurocognitive deficits in adults with T1D, little is known about how early-onset T1D affects neural networks in young children. Recent data demonstrated widespread alterations in regional gray matter and white matter associated with T1D in young children. These widespread neuroanatomical changes might impact the organization of large-scale brain networks. In the present study, we applied graph-theoretical analysis to test whether the organization of structural covariance networks in the brain for a cohort of young children with T1D (N = 141) is altered compared to healthy controls (HC; N = 69). While the networks in both groups followed a small world organization-an architecture that is simultaneously highly segregated and integrated-the T1D network showed significantly longer path length compared with HC, suggesting reduced global integration of brain networks in young children with T1D. In addition, network robustness analysis revealed that the T1D network model showed more vulnerability to neural insult compared with HC. These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. This is the first study to examine structural covariance networks in young children with T1D. Improving glycemic control for young children with T1D might help prevent alterations in brain networks in this population. Hum Brain Mapp 37:4034-4046, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Identification of alterations in the Jacobian of biochemical reaction networks from steady state covariance data at two conditions.

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Kügler, Philipp; Yang, Wei

2014-06-01

Model building of biochemical reaction networks typically involves experiments in which changes in the behavior due to natural or experimental perturbations are observed. Computational models of reaction networks are also used in a systems biology approach to study how transitions from a healthy to a diseased state result from changes in genetic or environmental conditions. In this paper we consider the nonlinear inverse problem of inferring information about the Jacobian of a Langevin type network model from covariance data of steady state concentrations associated to two different experimental conditions. Under idealized assumptions on the Langevin fluctuation matrices we prove that relative alterations in the network Jacobian can be uniquely identified when comparing the two data sets. Based on this result and the premise that alteration is locally confined to separable parts due to network modularity we suggest a computational approach using hybrid stochastic-deterministic optimization for the detection of perturbations in the network Jacobian using the sparsity promoting effect of [Formula: see text]-penalization. Our approach is illustrated by means of published metabolomic and signaling reaction networks.
Analysis of stock investment selection based on CAPM using covariance and genetic algorithm approach

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Sukono; Susanti, D.; Najmia, M.; Lesmana, E.; Napitupulu, H.; Supian, S.; Putra, A. S.

2018-03-01

Investment is one of the economic growth factors of countries, especially in Indonesia. Stocks is a form of investment, which is liquid. In determining the stock investment decisions which need to be considered by investors is to choose stocks that can generate maximum returns with a minimum risk level. Therefore, we need to know how to allocate the capital which may give the optimal benefit. This study discusses the issue of stock investment based on CAPM which is estimated using covariance and Genetic Algorithm approach. It is assumed that the stocks analyzed follow the CAPM model. To do the estimation of beta parameter on CAPM equation is done by two approach, first is to be represented by covariance approach, and second with genetic algorithm optimization. As a numerical illustration, in this paper analyzed ten stocks traded on the capital market in Indonesia. The results of the analysis show that estimation of beta parameters using covariance and genetic algorithm approach, give the same decision, that is, six underpriced stocks with buying decision, and four overpriced stocks with a sales decision. Based on the analysis, it can be concluded that the results can be used as a consideration for investors buying six under-priced stocks, and selling four overpriced stocks.
Segmenting by Risk Perceptions: Predicting Young Adults’ Genetic-Belief Profiles with Health and Opinion-Leader Covariates

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Smith, Rachel A.; Greenberg, Marisa; Parrott, Roxanne L.

2014-01-01

With a growing interest in using genetic information to motivate young adults’ health behaviors, audience segmentation is needed for effective campaign design. Using latent class analysis, this study identifies segments based on young adults’ (N = 327) beliefs about genetic threats to their health and personal efficacy over genetic influences on their health. A four-class model was identified. The model indicators fit the risk perception attitude framework (Rimal & Real, 2003), but the covariates (e.g., current health behaviors) did not. In addition, opinion leader qualities covaried with one profile: those in this profile engaged in fewer preventative behaviors and more dangerous treatment options, and also liked to persuade others, making them a particularly salient group for campaign efforts. The implications for adult-onset disorders, like alpha-1 antitrypsin deficiency are discussed. PMID:24111749
Short communication: Alteration of priors for random effects in Gaussian linear mixed model

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Vandenplas, Jérémie; Christensen, Ole Fredslund; Gengler, Nicholas

2014-01-01

such alterations. Therefore, the aim of this study was to propose a method to alter both the mean and (co)variance of the prior multivariate normal distributions of random effects of linear mixed models while using currently available software packages. The proposed method was tested on simulated examples with 3......, multiple-trait predictions of lactation yields, and Bayesian approaches integrating external information into genetic evaluations) need to alter both the mean and (co)variance of the prior distributions and, to our knowledge, most software packages available in the animal breeding community do not permit...... different software packages available in animal breeding. The examples showed the possibility of the proposed method to alter both the mean and (co)variance of the prior distributions with currently available software packages through the use of an extended data file and a user-supplied (co)variance matrix....
lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals.

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Ziyatdinov, Andrey; Vázquez-Santiago, Miquel; Brunel, Helena; Martinez-Perez, Angel; Aschard, Hugues; Soria, Jose Manuel

2018-02-27

Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by modeling such correlations as random effects in linear mixed models (LMMs). The R package lme4 is a well-established tool that implements major LMM features using sparse matrix methods; however, it is not fully adapted for QTL mapping association and linkage studies. In particular, two LMM features are lacking in the base version of lme4: the definition of random effects by custom covariance matrices; and parameter constraints, which are essential in advanced QTL models. Apart from applications in linkage studies of related individuals, such functionalities are of high interest for association studies in situations where multiple covariance matrices need to be modeled, a scenario not covered by many genome-wide association study (GWAS) software. To address the aforementioned limitations, we developed a new R package lme4qtl as an extension of lme4. First, lme4qtl contributes new models for genetic studies within a single tool integrated with lme4 and its companion packages. Second, lme4qtl offers a flexible framework for scenarios with multiple levels of relatedness and becomes efficient when covariance matrices are sparse. We showed the value of our package using real family-based data in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT2) project. Our software lme4qtl enables QTL mapping models with a versatile structure of random effects and efficient computation for sparse covariances. lme4qtl is available at https://github.com/variani/lme4qtl .
Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

Science.gov (United States)

Lebigre, Christophe; Arcese, Peter; Reid, Jane M

2013-07-01

Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased
A Common Genetic Factor Explains the Covariation among ADHD ODD and CD Symptoms in 9-10 Year Old Boys and Girls

Science.gov (United States)

Tuvblad, Catherine; Zheng, Mo; Raine, Adrian; Baker, Laura A.

2009-01-01

Previous studies examining the covariation among Attention Deficit Hyperactivity Disorder (ADHD), Oppositional Defiant Disorder (ODD) and Conduct Disorder (CD) have yielded inconsistent results. Some studies have concluded that the covariation among these symptoms is due to common genetic influences, whereas others have found a common…
Genetic alterations in hepatocellular carcinoma: An update

Science.gov (United States)

Niu, Zhao-Shan; Niu, Xiao-Jun; Wang, Wen-Hong

2016-01-01

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Although recent advances in therapeutic approaches for treating HCC have improved the prognoses of patients with HCC, this cancer is still associated with a poor survival rate mainly due to late diagnosis. Therefore, a diagnosis must be made sufficiently early to perform curative and effective treatments. There is a need for a deeper understanding of the molecular mechanisms underlying the initiation and progression of HCC because these mechanisms are critical for making early diagnoses and developing novel therapeutic strategies. Over the past decade, much progress has been made in elucidating the molecular mechanisms underlying hepatocarcinogenesis. In particular, recent advances in next-generation sequencing technologies have revealed numerous genetic alterations, including recurrently mutated genes and dysregulated signaling pathways in HCC. A better understanding of the genetic alterations in HCC could contribute to identifying potential driver mutations and discovering novel therapeutic targets in the future. In this article, we summarize the current advances in research on the genetic alterations, including genomic instability, single-nucleotide polymorphisms, somatic mutations and deregulated signaling pathways, implicated in the initiation and progression of HCC. We also attempt to elucidate some of the genetic mechanisms that contribute to making early diagnoses of and developing molecularly targeted therapies for HCC. PMID:27895396
Genetic Alterations in Glioma

International Nuclear Information System (INIS)

Bralten, Linda B. C.; French, Pim J.

2011-01-01

Gliomas are the most common type of primary brain tumor and have a dismal prognosis. Understanding the genetic alterations that drive glioma formation and progression may help improve patient prognosis by identification of novel treatment targets. Recently, two major studies have performed in-depth mutation analysis of glioblastomas (the most common and aggressive subtype of glioma). This systematic approach revealed three major pathways that are affected in glioblastomas: The receptor tyrosine kinase signaling pathway, the TP53 pathway and the pRB pathway. Apart from frequent mutations in the IDH1/2 gene, much less is known about the causal genetic changes of grade II and III (anaplastic) gliomas. Exceptions include TP53 mutations and fusion genes involving the BRAF gene in astrocytic and pilocytic glioma subtypes, respectively. In this review, we provide an update on all common events involved in the initiation and/or progression across the different subtypes of glioma and provide future directions for research into the genetic changes
[Algorithm of toxigenic genetically altered Vibrio cholerae El Tor biovar strain identification].

Science.gov (United States)

Smirnova, N I; Agafonov, D A; Zadnova, S P; Cherkasov, A V; Kutyrev, V V

2014-01-01

Development of an algorithm of genetically altered Vibrio cholerae biovar El Tor strai identification that ensures determination of serogroup, serovar and biovar of the studied isolate based on pheno- and genotypic properties, detection of genetically altered cholera El Tor causative agents, their differentiation by epidemic potential as well as evaluation of variability of key pathogenicity genes. Complex analysis of 28 natural V. cholerae strains was carried out by using traditional microbiological methods, PCR and fragmentary sequencing. An algorithm of toxigenic genetically altered V. cholerae biovar El Tor strain identification was developed that includes 4 stages: determination of serogroup, serovar and biovar based on phenotypic properties, confirmation of serogroup and biovar based on molecular-genetic properties determination of strains as genetically altered, differentiation of genetically altered strains by their epidemic potential and detection of ctxB and tcpA key pathogenicity gene polymorphism. The algorithm is based on the use of traditional microbiological methods, PCR and sequencing of gene fragments. The use of the developed algorithm will increase the effectiveness of detection of genetically altered variants of the cholera El Tor causative agent, their differentiation by epidemic potential and will ensure establishment of polymorphism of genes that code key pathogenicity factors for determination of origins of the strains and possible routes of introduction of the infection.
The covariance between genetic and environmental influences across ecological gradients: reassessing the evolutionary significance of countergradient and cogradient variation.

Science.gov (United States)

Conover, David O; Duffy, Tara A; Hice, Lyndie A

2009-06-01

Patterns of phenotypic change across environmental gradients (e.g., latitude, altitude) have long captivated the interest of evolutionary ecologists. The pattern and magnitude of phenotypic change is determined by the covariance between genetic and environmental influences across a gradient. Cogradient variation (CoGV) occurs when covariance is positive: that is, genetic and environmental influences on phenotypic expression are aligned and their joint influence accentuates the change in mean trait value across the gradient. Conversely, countergradient variation (CnGV) occurs when covariance is negative: that is, genetic and environmental influences on phenotypes oppose one another, thereby diminishing the change in mean trait expression across the gradient. CnGV has so far been found in at least 60 species, with most examples coming from fishes, amphibians, and insects across latitudinal or altitudinal gradients. Traits that display CnGV most often involve metabolic compensation, that is, the elevation of various physiological rates processes (development, growth, feeding, metabolism, activity) to counteract the dampening effect of reduced temperature, growing season length, or food supply. Far fewer examples of CoGV have been identified (11 species), and these most often involve morphological characters. Increased knowledge of spatial covariance patterns has furthered our understanding of Bergmann size clines, phenotypic plasticity, species range limits, tradeoffs in juvenile growth rate, and the design of conservation strategies for wild species. Moreover, temporal CnGV explains some cases of an apparent lack of phenotypic response to directional selection and provides a framework for predicting evolutionary responses to climate change.
The Genetic and Environmental Covariation among Psychopathic Personality Traits, and Reactive and Proactive Aggression in Childhood

Science.gov (United States)

Bezdjian, Serena; Tuvblad, Catherine; Raine, Adrian; Baker, Laura A.

2011-01-01

The present study investigated the genetic and environmental covariance between psychopathic personality traits with reactive and proactive aggression in 9- to 10-year-old twins (N = 1,219). Psychopathic personality traits were assessed with the Child Psychopathy Scale (D. R. Lynam, 1997), while aggressive behaviors were assessed using the…
Cortical Thinning and Altered Cortico-Cortical Structural Covariance of the Default Mode Network in Patients with Persistent Insomnia Symptoms.

Science.gov (United States)

Suh, Sooyeon; Kim, Hosung; Dang-Vu, Thien Thanh; Joo, Eunyeon; Shin, Chol

2016-01-01

Recent studies have suggested that structural abnormalities in insomnia may be linked with alterations in the default-mode network (DMN). This study compared cortical thickness and structural connectivity linked to the DMN in patients with persistent insomnia (PI) and good sleepers (GS). The current study used a clinical subsample from the longitudinal community-based Korean Genome and Epidemiology Study (KoGES). Cortical thickness and structural connectivity linked to the DMN in patients with persistent insomnia symptoms (PIS; n = 57) were compared to good sleepers (GS; n = 40). All participants underwent MRI acquisition. Based on literature review, we selected cortical regions corresponding to the DMN. A seed-based structural covariance analysis measured cortical thickness correlation between each seed region of the DMN and other cortical areas. Association of cortical thickness and covariance with sleep quality and neuropsychological assessments were further assessed. Compared to GS, cortical thinning was found in PIS in the anterior cingulate cortex, precentral cortex, and lateral prefrontal cortex. Decreased structural connectivity between anterior and posterior regions of the DMN was observed in the PIS group. Decreased structural covariance within the DMN was associated with higher PSQI scores. Cortical thinning in the lateral frontal lobe was related to poor performance in executive function in PIS. Disrupted structural covariance network in PIS might reflect malfunctioning of antero-posterior disconnection of the DMN during the wake to sleep transition that is commonly found during normal sleep. The observed structural network alteration may further implicate commonly observed sustained sleep difficulties and cognitive impairment in insomnia. © 2016 Associated Professional Sleep Societies, LLC.
Genetic Alterations and Their Clinical Implications in High-Recurrence Risk Papillary Thyroid Cancer.

Science.gov (United States)

Lee, Min-Young; Ku, Bo Mi; Kim, Hae Su; Lee, Ji Yun; Lim, Sung Hee; Sun, Jong-Mu; Lee, Se-Hoon; Park, Keunchil; Oh, Young Lyun; Hong, Mineui; Jeong, Han-Sin; Son, Young-Ik; Baek, Chung-Hwan; Ahn, Myung-Ju

2017-10-01

Papillary thyroid carcinomas (PTCs) frequently involve genetic alterations. The objective of this study was to investigate genetic alterations and further explore the relationships between these genetic alterations and clinicopathological characteristics in a high-recurrence risk (node positive, N1) PTC group. Tumor tissue blocks were obtained from 240 surgically resected patients with histologically confirmed stage III/IV (pT3/4 or N1) PTCs. We screened gene fusions using NanoString's nCounter technology and mutational analysis was performed by direct DNA sequencing. Data describing the clinicopathological characteristics and clinical courses were retrospectively collected. Of the 240 PTC patients, 207 (86.3%) had at least one genetic alteration, including BRAF mutation in 190 patients (79.2%), PIK3CA mutation in 25 patients (10.4%), NTRK1/3 fusion in six patients (2.5%), and RET fusion in 24 patients (10.0%). Concomitant presence of more than two genetic alterations was seen in 36 patients (15%). PTCs harboring BRAF mutation were associated with RET wild-type expression (p=0.001). RET fusion genes have been found to occur with significantly higher frequency in N1b stage patients (p=0.003) or groups of patients aged 45 years or older (p=0.031); however, no significant correlation was found between other genetic alterations. There was no trend toward favorable recurrence-free survival or overall survival among patients lacking genetic alterations. In the selected high-recurrence risk PTC group, most patients had more than one genetic alteration. However, these known alterations could not entirely account for clinicopathological features of high-recurrence risk PTC.
Genetic covariance functioners for live weight, condition score, and dry-matter intake measured at different lactations stages of Holstein-Friesian heifers

NARCIS (Netherlands)

Koenen, E.P.C.; Veerkamp, R.F.

1998-01-01

Genetic parameters for live weight, body condition score and dry-matter intake of dairy heifers were estimated using covariance function methodology. Data were from 469 heifers of the Langhill Dairy Cattle Research Centre and included observations during the first 25 weeks in lactation. Genetic
Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes

DEFF Research Database (Denmark)

Rohde, Palle Duun; Demontis, Ditte; Castro Dias Cuyabano, Beatriz

2016-01-01

was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case–control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism......Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited...... genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT...
The genetic alteration of p53 in esophageal cancer

Energy Technology Data Exchange (ETDEWEB)

Cho, Jae Il; Baik, Hee Jong; Kim, Chang Min; Kim, Mi Hee [Korea Cancer Center Hospital, Seoul (Korea, Republic of)

1996-01-01

Genetic alterations in the p53 gene have been detected in various human malignancies, and its alterations inactive the function of p53 as a tumor suppressor. Point mutation and gene deletion are the main mechanisms of p53 inactivation. To determine the incidence of genetic alteration of p53 and their clinical implications in Korean patients of esophageal cancer, we investigated p53 alterations in 26 esophageal cancer tissues paired with its normal tissue by Southern blot analysis, PCR-SSCP, and direct sequencing. Allelic loss of chromosome 17p occurred in 12 out of 21 informative cases(57%) by Southern blot analysis, and 16 cases showed mobility shift in PCR-SSCP, so overall incidence of p53 gene alterations was 77%(20/26). The mutations detected was randomly dispersed over exon4-8 and was frequently G-T transversion and C:T transitions. Three identical mutations were clustered at codon 213 suggested the same etiologic agents in this cases. The p53 gene alterations play a significant role in the development of esophageal cancers, however, no relationship between p53 mutation and clinical data was detected so far. 9 refs. (Author).
Genetic alterations in head and neck squamous cell carcinomas

Directory of Open Access Journals (Sweden)

Nagai M.A.

1999-01-01

Full Text Available The genetic alterations observed in head and neck cancer are mainly due to oncogene activation (gain of function mutations and tumor suppressor gene inactivation (loss of function mutations, leading to deregulation of cell proliferation and death. These genetic alterations include gene amplification and overexpression of oncogenes such as myc, erbB-2, EGFR and cyclinD1 and mutations, deletions and hypermethylation leading to p16 and TP53 tumor suppressor gene inactivation. In addition, loss of heterozygosity in several chromosomal regions is frequently observed, suggesting that other tumor suppressor genes not yet identified could be involved in the tumorigenic process of head and neck cancers. The exact temporal sequence of the genetic alterations during head and neck squamous cell carcinoma (HNSCC development and progression has not yet been defined and their diagnostic or prognostic significance is controversial. Advances in the understanding of the molecular basis of head and neck cancer should help in the identification of new markers that could be used for the diagnosis, prognosis and treatment of the disease.
Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes.

Science.gov (United States)

Rohde, Palle Duun; Demontis, Ditte; Cuyabano, Beatriz Castro Dias; Børglum, Anders D; Sørensen, Peter

2016-08-01

Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case-control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies. Copyright © 2016 by the Genetics Society of America.
Tissue culture-induced genetic and epigenetic alterations in rice pure-lines, F1 hybrids and polyploids.

Science.gov (United States)

Wang, Xiaoran; Wu, Rui; Lin, Xiuyun; Bai, Yan; Song, Congdi; Yu, Xiaoming; Xu, Chunming; Zhao, Na; Dong, Yuzhu; Liu, Bao

2013-05-05

Genetic and epigenetic alterations can be invoked by plant tissue culture, which may result in heritable changes in phenotypes, a phenomenon collectively termed somaclonal variation. Although extensive studies have been conducted on the molecular nature and spectrum of tissue culture-induced genomic alterations, the issue of whether and to what extent distinct plant genotypes, e.g., pure-lines, hybrids and polyploids, may respond differentially to the tissue culture condition remains poorly understood. We investigated tissue culture-induced genetic and epigenetic alterations in a set of rice genotypes including two pure-lines (different subspecies), a pair of reciprocal F1 hybrids parented by the two pure-lines, and a pair of reciprocal tetraploids resulted from the hybrids. Using two molecular markers, amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP), both genetic and DNA methylation alterations were detected in calli and regenerants from all six genotypes, but genetic alteration is more prominent than epigenetic alteration. While significant genotypic difference was observed in frequencies of both types of alterations, only genetic alteration showed distinctive features among the three types of genomes, with one hybrid (N/9) being exceptionally labile. Surprisingly, difference in genetic alteration frequencies between the pair of reciprocal F1 hybrids is much greater than that between the two pure-line subspecies. Difference also exists in the pair of reciprocal tetraploids, but is to a less extent than that between the hybrids. The steady-state transcript abundance of genes involved in DNA repair and DNA methylation was significantly altered in both calli and regenerants, and some of which were correlated with the genetic and/or epigenetic alterations. Our results, based on molecular marker analysis of ca. 1,000 genomic loci, document that genetic alteration is the major cause of somaclonal variation in rice

Rare endocrine cancers have novel genetic alterations

Science.gov (United States)

A molecular characterization of adrenocortical carcinoma, a rare cancer of the adrenal cortex, analyzed 91 cases for alterations in the tumor genomes and identified several novel genetic mutations as likely mechanisms driving the disease as well as whole genome doubling as a probable driver of the disease.
Multiple feature fusion via covariance matrix for visual tracking

Science.gov (United States)

Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui

2018-04-01

Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.
Dissecting high-dimensional phenotypes with bayesian sparse factor analysis of genetic covariance matrices.

Science.gov (United States)

Runcie, Daniel E; Mukherjee, Sayan

2013-07-01

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism's entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse - affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.
Critical roles for a genetic code alteration in the evolution of the genus Candida.

Science.gov (United States)

Silva, Raquel M; Paredes, João A; Moura, Gabriela R; Manadas, Bruno; Lima-Costa, Tatiana; Rocha, Rita; Miranda, Isabel; Gomes, Ana C; Koerkamp, Marian J G; Perrot, Michel; Holstege, Frank C P; Boucherie, Hélian; Santos, Manuel A S

2007-10-31

During the last 30 years, several alterations to the standard genetic code have been discovered in various bacterial and eukaryotic species. Sense and nonsense codons have been reassigned or reprogrammed to expand the genetic code to selenocysteine and pyrrolysine. These discoveries highlight unexpected flexibility in the genetic code, but do not elucidate how the organisms survived the proteome chaos generated by codon identity redefinition. In order to shed new light on this question, we have reconstructed a Candida genetic code alteration in Saccharomyces cerevisiae and used a combination of DNA microarrays, proteomics and genetics approaches to evaluate its impact on gene expression, adaptation and sexual reproduction. This genetic manipulation blocked mating, locked yeast in a diploid state, remodelled gene expression and created stress cross-protection that generated adaptive advantages under environmental challenging conditions. This study highlights unanticipated roles for codon identity redefinition during the evolution of the genus Candida, and strongly suggests that genetic code alterations create genetic barriers that speed up speciation.
Estimating genetic covariance functions assuming a parametric correlation structure for environmental effects

Directory of Open Access Journals (Sweden)

Meyer Karin

2001-11-01

Full Text Available Abstract A random regression model for the analysis of "repeated" records in animal breeding is described which combines a random regression approach for additive genetic and other random effects with the assumption of a parametric correlation structure for within animal covariances. Both stationary and non-stationary correlation models involving a small number of parameters are considered. Heterogeneity in within animal variances is modelled through polynomial variance functions. Estimation of parameters describing the dispersion structure of such model by restricted maximum likelihood via an "average information" algorithm is outlined. An application to mature weight records of beef cow is given, and results are contrasted to those from analyses fitting sets of random regression coefficients for permanent environmental effects.
A genetic code alteration is a phenotype diversity generator in the human pathogen Candida albicans.

Directory of Open Access Journals (Sweden)

Isabel Miranda

Full Text Available BACKGROUND: The discovery of genetic code alterations and expansions in both prokaryotes and eukaryotes abolished the hypothesis of a frozen and universal genetic code and exposed unanticipated flexibility in codon and amino acid assignments. It is now clear that codon identity alterations involve sense and non-sense codons and can occur in organisms with complex genomes and proteomes. However, the biological functions, the molecular mechanisms of evolution and the diversity of genetic code alterations remain largely unknown. In various species of the genus Candida, the leucine CUG codon is decoded as serine by a unique serine tRNA that contains a leucine 5'-CAG-3'anticodon (tRNA(CAG(Ser. We are using this codon identity redefinition as a model system to elucidate the evolution of genetic code alterations. METHODOLOGY/PRINCIPAL FINDINGS: We have reconstructed the early stages of the Candida genetic code alteration by engineering tRNAs that partially reverted the identity of serine CUG codons back to their standard leucine meaning. Such genetic code manipulation had profound cellular consequences as it exposed important morphological variation, altered gene expression, re-arranged the karyotype, increased cell-cell adhesion and secretion of hydrolytic enzymes. CONCLUSION/SIGNIFICANCE: Our study provides the first experimental evidence for an important role of genetic code alterations as generators of phenotypic diversity of high selective potential and supports the hypothesis that they speed up evolution of new phenotypes.
Genetic Alterations in Hungarian Patients with Papillary Thyroid Cancer.

Science.gov (United States)

Tobiás, Bálint; Halászlaki, Csaba; Balla, Bernadett; Kósa, János P; Árvai, Kristóf; Horváth, Péter; Takács, István; Nagy, Zsolt; Horváth, Evelin; Horányi, János; Járay, Balázs; Székely, Eszter; Székely, Tamás; Győri, Gabriella; Putz, Zsuzsanna; Dank, Magdolna; Valkusz, Zsuzsanna; Vasas, Béla; Iványi, Béla; Lakatos, Péter

2016-01-01

The incidence of thyroid cancers is increasing worldwide. Some somatic oncogene mutations (BRAF, NRAS, HRAS, KRAS) as well as gene translocations (RET/PTC, PAX8/PPAR-gamma) have been associated with the development of thyroid cancer. In our study, we analyzed these genetic alterations in 394 thyroid tissue samples (197 papillary carcinomas and 197 healthy). The somatic mutations and translocations were detected by Light Cycler melting method and Real-Time Polymerase Chain Reaction techniques, respectively. In tumorous samples, 86 BRAF (44.2%), 5 NRAS (3.1%), 2 HRAS (1.0%) and 1 KRAS (0.5%) mutations were found, as well as 9 RET/PTC1 (4.6%) and 1 RET/PTC3 (0.5%) translocations. No genetic alteration was seen in the non tumorous control thyroid tissues. No correlation was detected between the genetic variants and the pathological subtypes of papillary cancer as well as the severity of the disease. Our results are only partly concordant with the data found in the literature.
Genetic alterations during radiation-induced carcinogenesis

International Nuclear Information System (INIS)

Kodama, Seiji

1995-01-01

This paper reviews radiation-induced genetic alterations and its carcinogenesis, focusing on the previous in vitro assay outcome. A colony formation assay using Syrian hamster fetal cells and focus formation assay using mouse C3H10T1/2 cells are currently available to find malignant transformation of cells. Such in vitro assays has proposed the hypothesis that radiation-induced carcinogenesis arises from at least two-stage processes; i.e., that an early step induced by irradiation plays an important role in promoting the potential to cause the subsequent mutation. A type of genetic instability induced by radiation results in a persistently elevated frequency of spontaneous mutations, so-called the phenomenon of delayed reproductive death. One possible mechanism by which genetic instability arises has been shown to be due to the development of abnormality in the gene group involved in the maintenance mechanism of genome stability. Another possibility has also been shown to stem from the loss of telomere (the extremities of a chromosome). The importance of search for radiation-induced genetic instability is emphasized in view of the elucidation of carcinogenesis. (N.K.)
Statistical power to detect genetic (covariance of complex traits using SNP data in unrelated samples.

Directory of Open Access Journals (Sweden)

Peter M Visscher

2014-04-01

Full Text Available We have recently developed analysis methods (GREML to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (covariation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases in particular when the traits (diseases are not measured on the same samples.
An Underlying Common Factor, Influenced by Genetics and Unique Environment, Explains the Covariation Between Major Depressive Disorder, Generalized Anxiety Disorder, and Burnout: A Swedish Twin Study.

Science.gov (United States)

Mather, Lisa; Blom, Victoria; Bergström, Gunnar; Svedberg, Pia

2016-12-01

Depression and anxiety are highly comorbid due to shared genetic risk factors, but less is known about whether burnout shares these risk factors. We aimed to examine whether the covariation between major depressive disorder (MDD), generalized anxiety disorder (GAD), and burnout is explained by common genetic and/or environmental factors. This cross-sectional study included 25,378 Swedish twins responding to a survey in 2005-2006. Structural equation models were used to analyze whether the trait variances and covariances were due to additive genetics, non-additive genetics, shared environment, and unique environment. Univariate analyses tested sex limitation models and multivariate analysis tested Cholesky, independent pathway, and common pathway models. The phenotypic correlations were 0.71 (0.69-0.74) between MDD and GAD, 0.58 (0.56-0.60) between MDD and burnout, and 0.53 (0.50-0.56) between GAD and burnout. Heritabilities were 45% for MDD, 49% for GAD, and 38% for burnout; no statistically significant sex differences were found. A common pathway model was chosen as the final model. The common factor was influenced by genetics (58%) and unique environment (42%), and explained 77% of the variation in MDD, 69% in GAD, and 44% in burnout. GAD and burnout had additive genetic factors unique to the phenotypes (11% each), while MDD did not. Unique environment explained 23% of the variability in MDD, 20% in GAD, and 45% in burnout. In conclusion, the covariation was explained by an underlying common factor, largely influenced by genetics. Burnout was to a large degree influenced by unique environmental factors not shared with MDD and GAD.
DNA Fingerprinting Techniques for the Analysis of Genetic and Epigenetic Alterations in Colorectal Cancer

OpenAIRE

Samuelsson, Johanna K.; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

2010-01-01

Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in ca...
Parental Virtue and Prenatal Genetic Alteration Research.

Science.gov (United States)

Tonkens, Ryan

2015-12-01

Although the philosophical literature on the ethics of human prenatal genetic alteration (PGA) purports to inform us about how to act, it rarely explicitly recognizes the perspective of those who will be making the PGA decision in practice. Here I approach the ethics of PGA from a distinctly virtue-based perspective, taking seriously what it means to be a good parent making this decision for one's child. From this perspective, I generate a sound verdict on the moral standing of human PGA (research): given the current state of the art, good parents have compelling reason not to consent to PGA (research) for their child, especially as part of the first wave(s) of PGA research participants and especially for non-medically oriented purposes. This is because doing otherwise is inconsistent with a plausible and defensible understanding of virtuous parenting and parental virtues, founded on a genuine concern for promoting the overall flourishing of the eventual child. In essence, given the current and foreseeable state of the art, parents who allow prenatal genetic alteration of their children are less-than-virtuous parents to those children, even in cases where they have a right to do so and even if PGA turns out to be beneficial to the eventual child.
Mating animals by minimising the covariance between ancestral contributions generates less inbreeding without compromising genetic gain in breeding schemes with truncation selection

DEFF Research Database (Denmark)

Henryon, M; Berg, P; Sørensen, A C

2009-01-01

We reasoned that mating animals by minimising the covariance between ancestral contributions (MCAC mating) will generate less inbreeding and at least as much genetic gain as minimum-coancestry mating in breeding schemes where the animals are truncation-selected. We tested this hypothesis by stoch...
Structural covariance of neostriatal and limbic regions in patients with obsessive-compulsive disorder.

Science.gov (United States)

Subirà, Marta; Cano, Marta; de Wit, Stella J; Alonso, Pino; Cardoner, Narcís; Hoexter, Marcelo Q; Kwon, Jun Soo; Nakamae, Takashi; Lochner, Christine; Sato, João R; Jung, Wi Hoon; Narumoto, Jin; Stein, Dan J; Pujol, Jesus; Mataix-Cols, David; Veltman, Dick J; Menchón, José M; van den Heuvel, Odile A; Soriano-Mas, Carles

2016-03-01

Frontostriatal and frontoamygdalar connectivity alterations in patients with obsessive-compulsive disorder (OCD) have been typically described in functional neuroimaging studies. However, structural covariance, or volumetric correlations across distant brain regions, also provides network-level information. Altered structural covariance has been described in patients with different psychiatric disorders, including OCD, but to our knowledge, alterations within frontostriatal and frontoamygdalar circuits have not been explored. We performed a mega-analysis pooling structural MRI scans from the Obsessive-compulsive Brain Imaging Consortium and assessed whole-brain voxel-wise structural covariance of 4 striatal regions (dorsal and ventral caudate nucleus, and dorsal-caudal and ventral-rostral putamen) and 2 amygdalar nuclei (basolateral and centromedial-superficial). Images were preprocessed with the standard pipeline of voxel-based morphometry studies using Statistical Parametric Mapping software. Our analyses involved 329 patients with OCD and 316 healthy controls. Patients showed increased structural covariance between the left ventral-rostral putamen and the left inferior frontal gyrus/frontal operculum region. This finding had a significant interaction with age; the association held only in the subgroup of older participants. Patients with OCD also showed increased structural covariance between the right centromedial-superficial amygdala and the ventromedial prefrontal cortex. This was a cross-sectional study. Because this is a multisite data set analysis, participant recruitment and image acquisition were performed in different centres. Most patients were taking medication, and treatment protocols differed across centres. Our results provide evidence for structural network-level alterations in patients with OCD involving 2 frontosubcortical circuits of relevance for the disorder and indicate that structural covariance contributes to fully characterizing brain
[Colorectal cancer (CCR): genetic and molecular alterations].

Science.gov (United States)

Juárez-Vázquez, Clara Ibet; Rosales-Reynoso, Mónica Alejandra

2014-01-01

The aim of this review is to present a genetic and molecular overview of colorectal carcinogenesis (sporadic and hereditary origin) as a multistage process, where there are a number of molecular mechanisms associated with the development of colorectal cancer and genomic instability that allows the accumulation of mutations in proto-oncogenes and tumor suppressor genes, chromosomal instability, and methylation and microsatellite instability, and the involvement of altered expression of microRNAs' prognosis factors.
Validity of covariance models for the analysis of geographical variation

DEFF Research Database (Denmark)

Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio

2014-01-01

1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained att...
DNA fingerprinting techniques for the analysis of genetic and epigenetic alterations in colorectal cancer.

Science.gov (United States)

Samuelsson, Johanna K; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

2010-11-10

Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in carcinogenesis. Epigenetic regulation mechanisms underlie the maintenance of cell identity crucial for development and differentiation. These epigenetic regulatory mechanisms have been found substantially altered during cancer development and progression. In this review, we discuss approaches designed to analyze genetic and epigenetic alterations in colorectal cancer, especially DNA fingerprinting approaches to detect changes in DNA copy number and methylation. DNA fingerprinting techniques, despite their modest throughput, played a pivotal role in significant discoveries in the molecular basis of colorectal cancer. The aim of this review is to revisit the fingerprinting technologies employed and the oncogenic processes that they unveiled. 2010 Elsevier B.V. All rights reserved.
Genetic effect of MTHFR C677T polymorphism on the structural covariance network and white-matter integrity in Alzheimer's disease.

Science.gov (United States)

Chang, Yu-Tzu; Hsu, Shih-Wei; Tsai, Shih-Jen; Chang, Ya-Ting; Huang, Chi-Wei; Liu, Mu-En; Chen, Nai-Ching; Chang, Wen-Neng; Hsu, Jung-Lung; Lee, Chen-Chang; Chang, Chiung-Chih

2017-06-01

The 677 C to T transition in the MTHFR gene is a genetic determinant for hyperhomocysteinemia. We investigated whether this polymorphism modulates gray matter (GM) structural covariance networks independently of white-matter integrity in patients with Alzheimer's disease (AD). GM structural covariance networks were constructed by 3D T1-magnetic resonance imaging and seed-based analysis. The patients were divided into two genotype groups: C homozygotes (n = 73) and T carriers (n = 62). Using diffusion tensor imaging and white-matter parcellation, 11 fiber bundle integrities were compared between the two genotype groups. Cognitive test scores were the major outcome factors. The T carriers had higher homocysteine levels, lower posterior cingulate cortex GM volume, and more clusters in the dorsal medial lobe subsystem showing stronger covariance strength. Both posterior cingulate cortex seed and interconnected peak cluster volumes predicted cognitive test scores, especially in the T carriers. There were no between-group differences in fiber tract diffusion parameters. The MTHFR 677T polymorphism modulates posterior cingulate cortex-anchored structural covariance strength independently of white matter integrities. Hum Brain Mapp 38:3039-3051, 2017. © 2017 The Authors Human Brain Mapping Published Wiley by Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published Wiley by Periodicals, Inc.
Heritability, covariation and natural selection on 24 traits of common evening primrose (Oenothera biennis) from a field experiment.

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Johnson, M T J; Agrawal, A A; Maron, J L; Salminen, J-P

2009-06-01

This study explored genetic variation and co-variation in multiple functional plant traits. Our goal was to characterize selection, heritabilities and genetic correlations among different types of traits to gain insight into the evolutionary ecology of plant populations and their interactions with insect herbivores. In a field experiment, we detected significant heritable variation for each of 24 traits of Oenothera biennis and extensive genetic covariance among traits. Traits with diverse functions formed several distinct groups that exhibited positive genetic covariation with each other. Genetic variation in life-history traits and secondary chemistry together explained a large proportion of variation in herbivory (r(2) = 0.73). At the same time, selection acted on lifetime biomass, life-history traits and two secondary compounds of O. biennis, explaining over 95% of the variation in relative fitness among genotypes. The combination of genetic covariances and directional selection acting on multiple traits suggests that adaptive evolution of particular traits is constrained, and that correlated evolution of groups of traits will occur, which is expected to drive the evolution of increased herbivore susceptibility. As a whole, our study indicates that an examination of genetic variation and covariation among many different types of traits can provide greater insight into the evolutionary ecology of plant populations and plant-herbivore interactions.
Genetic and epigenetic alterations induced by different levels of rye genome integration in wheat recipient.

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Zheng, X L; Zhou, J P; Zang, L L; Tang, A T; Liu, D Q; Deng, K J; Zhang, Y

2016-06-17

The narrow genetic variation present in common wheat (Triticum aestivum) varieties has greatly restricted the improvement of crop yield in modern breeding systems. Alien addition lines have proven to be an effective means to broaden the genetic diversity of common wheat. Wheat-rye addition lines, which are the direct bridge materials for wheat improvement, have been wildly used to produce new wheat cultivars carrying alien rye germplasm. In this study, we investigated the genetic and epigenetic alterations in two sets of wheat-rye disomic addition lines (1R-7R) and the corresponding triticales. We used expressed sequence tag-simple sequence repeat, amplified fragment length polymorphism, and methylation-sensitive amplification polymorphism analyses to analyze the effects of the introduction of alien chromosomes (either the entire genome or sub-genome) to wheat genetic background. We found obvious and diversiform variations in the genomic primary structure, as well as alterations in the extent and pattern of the genomic DNA methylation of the recipient. Meanwhile, these results also showed that introduction of different rye chromosomes could induce different genetic and epigenetic alterations in its recipient, and the genetic background of the parents is an important factor for genomic and epigenetic variation induced by alien chromosome addition.

Genetic alterations and epigenetic changes in hepatocarcinogenesis

Directory of Open Access Journals (Sweden)

Luz Stella Hoyos Giraldo

2007-02-01

Full Text Available
Hepatocarcinogenesis as hepatocellular carcinoma (HCC is associated with background of chronic liver disease usually in association with cirrhosis, marked hepatic fibrosis, hepatitis B virus (HBV and/or hepatitis virus (HCV infection, chronic inflammation, Aflatoxin B1(AFB1 exposure, chronic alcoholism, metabolic disorder of the liver and necroinflamatory liver disease. Hepatocarcinogenesis involve two mechanisms, genetic alterations (with changes in the cell's DNA sequence and epigenetic changes (without changes in the cell's DNA sequence, but changes in the pattern of gene expression that can persist through one or more generations (somatic sense. Hepatocarcinogenesis is associated with activation of oncogenes and decreased expression of tumor suppressor genes (TSG; include those involved in cell cycle control, apoptosis, DNA repair, immortalization and angiogenesis. AFB1 is metabolized in the liver into a potent carcinogen, aflatoxin 8, 9-epoxide, which is detoxified by epoxide hydrolase (EPHX and glutathione S-transferase M1 (GSTM1.

A failure of detoxification processes can allow to mutagenic metabolite to bind to DNA and inducing P53 mutation. Genetic polymorphism of EPHX and GSTM1 can make individuals more susceptible to AFB1. Epigenetic inactivation of GSTP1 by promoter hypermethylation plays a role in the development of HCC because, it leads that electrophilic metabolite increase DNA damage and mutations. HBV DNA integration into the host chromosomal DNA of hepatocytes has been detected in HBV-related HCC.

DNA tumor viruses cause cancer mainly by interfering with cell cycle controls, and activating the cell's replication machinery by blocking the action of key TSG. HBx protein is a
Generation of Infectious Poliovirus with Altered Genetic Information from Cloned cDNA.

Science.gov (United States)

Bujaki, Erika

2016-01-01

The effect of specific genetic alterations on virus biology and phenotype can be studied by a great number of available assays. The following method describes the basic protocol to generate infectious poliovirus with altered genetic information from cloned cDNA in cultured cells.The example explained here involves generation of a recombinant poliovirus genome by simply replacing a portion of the 5' noncoding region with a synthetic gene by restriction cloning. The vector containing the full length poliovirus genome and the insert DNA with the known mutation(s) are cleaved for directional cloning, then ligated and transformed into competent bacteria. The recombinant plasmid DNA is then propagated in bacteria and transcribed to RNA in vitro before RNA transfection of cultured cells is performed. Finally, viral particles are recovered from the cell culture.
The genetic alteration of retinoblastoma gene in esophageal cancer

International Nuclear Information System (INIS)

Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min

1994-12-01

Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it's alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author)
The genetic alteration of retinoblastoma gene in esophageal cancer

Energy Technology Data Exchange (ETDEWEB)

Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min [Korea Cancer Center Hospital of Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1994-12-01

Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it`s alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author).
The genetic architecture of shoot-root covariation during seedling emergence of a desert tree, Populus euphratica.

Science.gov (United States)

Zhang, Miaomiao; Bo, Wenhao; Xu, Fang; Li, Huan; Ye, Meixia; Jiang, Libo; Shi, Chaozhong; Fu, Yaru; Zhao, Guomiao; Huang, Yuejiao; Gosik, Kirk; Liang, Dan; Wu, Rongling

2017-06-01

The coordination of shoots and roots is critical for plants to adapt to changing environments by fine-tuning energy production in leaves and the availability of water and nutrients from roots. To understand the genetic architecture of how these two organs covary during developmental ontogeny, we conducted a mapping experiment using Euphrates poplar (Populus euphratica), a so-called hero tree able to grow in the desert. We geminated intraspecific F 1 seeds of Euphrates Poplar individually in a tube to obtain a total of 370 seedlings, whose shoot and taproot lengths were measured repeatedly during the early stage of growth. By fitting a growth equation, we estimated asymptotic growth, relative growth rate, the timing of inflection point and duration of linear growth for both shoot and taproot growth. Treating these heterochronic parameters as phenotypes, a univariate mapping model detected 19 heterochronic quantitative trait loci (hQTLs), of which 15 mediate the forms of shoot growth and four mediate taproot growth. A bivariate mapping model identified 11 pleiotropic hQTLs that determine the covariation of shoot and taproot growth. Most QTLs detected reside within the region of candidate genes with various functions, thus confirming their roles in the biochemical processes underlying plant growth. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.
Genetic alterations of hepatocellular carcinoma by random amplified polymorphic DNA analysis and cloning sequencing of tumor differential DNA fragment

Science.gov (United States)

Xian, Zhi-Hong; Cong, Wen-Ming; Zhang, Shu-Hui; Wu, Meng-Chao

2005-01-01

AIM: To study the genetic alterations and their association with clinicopathological characteristics of hepatocellular carcinoma (HCC), and to find the tumor related DNA fragments. METHODS: DNA isolated from tumors and corresponding noncancerous liver tissues of 56 HCC patients was amplified by random amplified polymorphic DNA (RAPD) with 10 random 10-mer arbitrary primers. The RAPD bands showing obvious differences in tumor tissue DNA corresponding to that of normal tissue were separated, purified, cloned and sequenced. DNA sequences were analyzed and compared with GenBank data. RESULTS: A total of 56 cases of HCC were demonstrated to have genetic alterations, which were detected by at least one primer. The detestability of genetic alterations ranged from 20% to 70% in each case, and 17.9% to 50% in each primer. Serum HBV infection, tumor size, histological grade, tumor capsule, as well as tumor intrahepatic metastasis, might be correlated with genetic alterations on certain primers. A band with a higher intensity of 480 bp or so amplified fragments in tumor DNA relative to normal DNA could be seen in 27 of 56 tumor samples using primer 4. Sequence analysis of these fragments showed 91% homology with Homo sapiens double homeobox protein DUX10 gene. CONCLUSION: Genetic alterations are a frequent event in HCC, and tumor related DNA fragments have been found in this study, which may be associated with hepatocarcin-ogenesis. RAPD is an effective method for the identification and analysis of genetic alterations in HCC, and may provide new information for further evaluating the molecular mechanism of hepatocarcinogenesis. PMID:15996039
Language Ability Predicts Cortical Structure and Covariance in Boys with Autism Spectrum Disorder.

Science.gov (United States)

Sharda, Megha; Foster, Nicholas E V; Tryfon, Ana; Doyle-Thomas, Krissy A R; Ouimet, Tia; Anagnostou, Evdokia; Evans, Alan C; Zwaigenbaum, Lonnie; Lerch, Jason P; Lewis, John D; Hyde, Krista L

2017-03-01

There is significant clinical heterogeneity in language and communication abilities of individuals with Autism Spectrum Disorders (ASD). However, no consistent pathology regarding the relationship of these abilities to brain structure has emerged. Recent developments in anatomical correlation-based approaches to map structural covariance networks (SCNs), combined with detailed behavioral characterization, offer an alternative for studying these relationships. In this study, such an approach was used to study the integrity of SCNs of cortical thickness and surface area associated with language and communication, in 46 high-functioning, school-age children with ASD compared with 50 matched, typically developing controls (all males) with IQ > 75. Findings showed that there was alteration of cortical structure and disruption of fronto-temporal cortical covariance in ASD compared with controls. Furthermore, in an analysis of a subset of ASD participants, alterations in both cortical structure and covariance were modulated by structural language ability of the participants, but not communicative function. These findings indicate that structural language abilities are related to altered fronto-temporal cortical covariance in ASD, much more than symptom severity or cognitive ability. They also support the importance of better characterizing ASD samples while studying brain structure and for better understanding individual differences in language and communication abilities in ASD. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
The application of sparse estimation of covariance matrix to quadratic discriminant analysis.

Science.gov (United States)

Sun, Jiehuan; Zhao, Hongyu

2015-02-18

Although Linear Discriminant Analysis (LDA) is commonly used for classification, it may not be directly applied in genomics studies due to the large p, small n problem in these studies. Different versions of sparse LDA have been proposed to address this significant challenge. One implicit assumption of various LDA-based methods is that the covariance matrices are the same across different classes. However, rewiring of genetic networks (therefore different covariance matrices) across different diseases has been observed in many genomics studies, which suggests that LDA and its variations may be suboptimal for disease classifications. However, it is not clear whether considering differing genetic networks across diseases can improve classification in genomics studies. We propose a sparse version of Quadratic Discriminant Analysis (SQDA) to explicitly consider the differences of the genetic networks across diseases. Both simulation and real data analysis are performed to compare the performance of SQDA with six commonly used classification methods. SQDA provides more accurate classification results than other methods for both simulated and real data. Our method should prove useful for classification in genomics studies and other research settings, where covariances differ among classes.
Widespread covariation of early environmental exposures and trait-associated polygenic variation.

Science.gov (United States)

Krapohl, E; Hannigan, L J; Pingault, J-B; Patel, H; Kadeva, N; Curtis, C; Breen, G; Newhouse, S J; Eley, T C; O'Reilly, P F; Plomin, R

2017-10-31

Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample ( n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age ( R 2 = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding ( R 2 = 0.021; P = 7e-30), maternal smoking during pregnancy ( R 2 = 0.008; P = 5e-13), parental smacking ( R 2 = 0.01; P = 4e-15), household income ( R 2 = 0.032; P = 1e-22), watching television ( R 2 = 0.034; P = 5e-47), and maternal education ( R 2 = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.
Genetics of body shape and armour variation in threespine sticklebacks.

Science.gov (United States)

Leinonen, T; Cano, J M; Merilä, J

2011-01-01

Patterns of genetic variation and covariation can influence the rate and direction of phenotypic evolution. We explored the possibility that the parallel morphological evolution seen in threespine stickleback (Gasterosteus aculeatus) populations colonizing freshwater environments is facilitated by patterns of genetic variation and covariation in the ancestral (marine) population. We estimated the genetic (G) and phenotypic (P) covariance matrices and directions of maximum additive genetic (g(max) ) and phenotypic (p(max) ) covariances of body shape and armour traits. Our results suggest a role for the ancestral G in explaining parallel morphological evolution in freshwater populations. We also found evidence of genetic constraints owing to the lack of variance in the ancestral G. Furthermore, strong genetic covariances and correlations among traits revealed that selective factors responsible for threespine stickleback body shape and armour divergence may be difficult to disentangle. The directions of g(max) and p(max) were correlated, but the correlations were not high enough to imply that phenotypic patterns of trait variation and covariation within populations are very informative of underlying genetic patterns. © 2010 The Authors. Journal of Evolutionary Biology © 2010 European Society For Evolutionary Biology.
Structural covariance in the hallucinating brain: a voxel-based morphometry study

Science.gov (United States)

Modinos, Gemma; Vercammen, Ans; Mechelli, Andrea; Knegtering, Henderikus; McGuire, Philip K.; Aleman, André

2009-01-01

Background Neuroimaging studies have indicated that a number of cortical regions express altered patterns of structural covariance in schizophrenia. The relation between these alterations and specific psychotic symptoms is yet to be investigated. We used voxel-based morphometry to examine regional grey matter volumes and structural covariance associated with severity of auditory verbal hallucinations. Methods We applied optimized voxel-based morphometry to volumetric magnetic resonance imaging data from 26 patients with medication-resistant auditory verbal hallucinations (AVHs); statistical inferences were made at p < 0.05 after correction for multiple comparisons. Results Grey matter volume in the left inferior frontal gyrus was positively correlated with severity of AVHs. Hallucination severity influenced the pattern of structural covariance between this region and the left superior/middle temporal gyri, the right inferior frontal gyrus and hippocampus, and the insula bilaterally. Limitations The results are based on self-reported severity of auditory hallucinations. Complementing with a clinician-based instrument could have made the findings more compelling. Future studies would benefit from including a measure to control for other symptoms that may covary with AVHs and for the effects of antipsychotic medication. Conclusion The results revealed that overall severity of AVHs modulated cortical intercorrelations between frontotemporal regions involved in language production and verbal monitoring, supporting the critical role of this network in the pathophysiology of hallucinations. PMID:19949723
Whole-genome and Transcriptome Sequencing of Prostate Cancer Identify New Genetic Alterations Driving Disease Progression

DEFF Research Database (Denmark)

Ren, Shancheng; Wei, Gong-Hong; Liu, Dongbing

2018-01-01

BACKGROUND: Global disparities in prostate cancer (PCa) incidence highlight the urgent need to identify genomic abnormalities in prostate tumors in different ethnic populations including Asian men. OBJECTIVE: To systematically explore the genomic complexity and define disease-driven genetic......-scale and comprehensive genomic data of prostate cancer from Asian population. Identification of these genetic alterations may help advance prostate cancer diagnosis, prognosis, and treatment....... alterations in PCa. DESIGN, SETTING, AND PARTICIPANTS: The study sequenced whole-genome and transcriptome of tumor-benign paired tissues from 65 treatment-naive Chinese PCa patients. Subsequent targeted deep sequencing of 293 PCa-relevant genes was performed in another cohort of 145 prostate tumors. OUTCOME...
Analysis of Genetic Diversity of Two Mangrove Species with Morphological Alterations in a Natural Environment

Directory of Open Access Journals (Sweden)

Catarina Fonseca Lira-Medeiros

2015-04-01

Full Text Available Mangrove is an ecosystem subjected to tide, salinity and nutrient variations. These conditions are stressful to most plants, except to mangrove plants that are well-adapted. However, many mangrove areas have extremely stressful conditions, such as salt marshes, and the plants nearby usually present morphological alterations. In Sepetiba Bay, two species of mangrove plants, Avicennia schaueriana and Laguncularia racemosa, have poor development near a salt marsh (SM compared to plants at the riverside (RS, which is considered a favorable habitat in mangroves. The level of genetic diversity and its possible correlation with the morphological divergence of SM and RS plants of both species were assessed by AFLP molecular markers. We found moderate genetic differentiation between A. schaueriana plants from SM and RS areas and depleted genetic diversity on SM plants. On the other hand, Laguncularia racemosa plants had no genetic differentiation between areas. It is possible that a limited gene flow among the studied areas might be acting more intensely on A. schaueriana plants, resulting in the observed genetic differentiation. The populations of Laguncularia racemosa appear to be well connected, as genetic differentiation was not significant between the SM and RS populations. Gene flow and genetic drift are acting on neutral genetic diversity of these two mangrove species in the studied areas, and the observed genetic differentiation of A. schaueriana plants might be correlated with its morphological variation. For L. racemosa, morphological alterations could be related to epigenetic phenomena or adaptive loci polymorphism that should be further investigated.
Genetic and metabolic signals during acute enteric bacterial infection alter the microbiota and drive progression to chronic inflammatory disease

Energy Technology Data Exchange (ETDEWEB)

Kamdar, Karishma; Khakpour, Samira; Chen, Jingyu; Leone, Vanessa; Brulc, Jennifer; Mangatu, Thomas; Antonopoulos, Dionysios A.; Chang, Eugene B; Kahn, Stacy A.; Kirschner, Barbara S; Young, Glenn; DePaolo, R. William

2016-01-13

Chronic inflammatory disorders are thought to arise due to an interplay between predisposing host genetics and environmental factors. For example, the onset of inflammatory bowel disease is associated with enteric proteobacterial infection, yet the mechanistic basis for this association is unclear. We have shown previously that genetic defiency in TLR1 promotes acute enteric infection by the proteobacteria Yersinia enterocolitica. Examining that model further, we uncovered an altered cellular immune response that promotes the recruitment of neutrophils which in turn increases metabolism of the respiratory electron acceptor tetrathionate by Yersinia. These events drive permanent alterations in anti-commensal immunity, microbiota composition, and chronic inflammation, which persist long after Yersinia clearence. Deletion of the bacterial genes involved in tetrathionate respiration or treatment using targeted probiotics could prevent microbiota alterations and inflammation. Thus, acute infection can drive long term immune and microbiota alterations leading to chronic inflammatory disease in genetically predisposed individuals.
Genetic alterations in B-cell non-Hodgkin's lymphoma

Directory of Open Access Journals (Sweden)

Magić Zvonko

2005-01-01

Full Text Available Background. Although the patients with diagnosed B-NHL are classified into the same disease stage on the basis of clinical, histopathological, and immunological parameters, they respond significantly different to the applied treatment. This points out the possibility that within the same group of lymphoma there are different diseases at molecular level. For that reason many studies deal with the detection of gene alterations in lymphomas to provide a better framework for diagnosis and treatment of these hematological malignancies. Aim. To define genetic alterations in the B-NHL with highest possibilities for diagnostic purposes and molecular detection of MRD. Methods. Formalin fixed and paraffin embedded lymph node tissues from 45 patients were examined by different PCR techniques for the presence of IgH and TCR γ gene rearrangement; K-ras and H-ras mutations; c-myc amplification and bcl-2 translocation. There were 34 cases of B-cell non-Hodgkin’s lymphoma (B-NHL, 5 cases of T-cell non-Hodgkin’s lymphoma (T-NHL and 6 cases of chronic lymphadenitis (CL. The mononuclear cell fraction of the peripheral blood of 12 patients with B-NHL was analyzed for the presence of monoclonality at the time of diagnosis and in 3 to 6 months time intervals after an autologous bone marrow transplantation (BMT. Results. The monoclonality of B-lymphocytes, as evidenced by DNA fragment length homogeneity, was detected in 88 % (30/34 of B-NHL, but never in CL, T-NHL, or in normal PBL. Bcl-2 translocation was detected in 7/31 (22.6% B-NHL specimens, c-myc amplification 9/31 (29%, all were more than doubled, K-ras mutations in 1/31 (3.23% and H-ras mutations in 2/31 (6.45% of the examined B-NHL samples. In the case of LC and normal PBL, however, these gene alterations were not detected. All the patients (12 with B-NHL had dominant clone of B-lymphocyte in the peripheral blood at the time of diagnosis while only in 2 of 12 patients MRD was detected 3 or 6 months after
Covariance functions across herd production levels for test day records on milk, fat, and protein yields

NARCIS (Netherlands)

Veerkamp, R.F.; Goddard, M.E.

1998-01-01

Multiple-trait BLUP evaluations of test day records require a large number of genetic parameters. This study estimated covariances with a reduced model that included covariance functions in two dimensions (stage of lactation and herd production level) and all three yield traits. Records came from
Unexpected Nongenetic Individual Heterogeneity and Trait Covariance in Daphnia and Its Consequences for Ecological and Evolutionary Dynamics.

Science.gov (United States)

Cressler, Clayton E; Bengtson, Stefan; Nelson, William A

2017-07-01

Individual differences in genetics, age, or environment can cause tremendous differences in individual life-history traits. This individual heterogeneity generates demographic heterogeneity at the population level, which is predicted to have a strong impact on both ecological and evolutionary dynamics. However, we know surprisingly little about the sources of individual heterogeneity for particular taxa or how different sources scale up to impact ecological and evolutionary dynamics. Here we experimentally study the individual heterogeneity that emerges from both genetic and nongenetic sources in a species of freshwater zooplankton across a large gradient of food quality. Despite the tight control of environment, we still find that the variation from nongenetic sources is greater than that from genetic sources over a wide range of food quality and that this variation has strong positive covariance between growth and reproduction. We evaluate the general consequences of genetic and nongenetic covariance for ecological and evolutionary dynamics theoretically and find that increasing nongenetic variation slows evolution independent of the correlation in heritable life-history traits but that the impact on ecological dynamics depends on both nongenetic and genetic covariance. Our results demonstrate that variation in the relative magnitude of nongenetic versus genetic sources of variation impacts the predicted ecological and evolutionary dynamics.
The application of sparse estimation of covariance matrix to quadratic discriminant analysis

OpenAIRE

Sun, Jiehuan; Zhao, Hongyu

2015-01-01

Background Although Linear Discriminant Analysis (LDA) is commonly used for classification, it may not be directly applied in genomics studies due to the large p, small n problem in these studies. Different versions of sparse LDA have been proposed to address this significant challenge. One implicit assumption of various LDA-based methods is that the covariance matrices are the same across different classes. However, rewiring of genetic networks (therefore different covariance matrices) acros...
Additive genetic variation in the craniofacial skeleton of baboons (genus Papio) and its relationship to body and cranial size.

Science.gov (United States)

Joganic, Jessica L; Willmore, Katherine E; Richtsmeier, Joan T; Weiss, Kenneth M; Mahaney, Michael C; Rogers, Jeffrey; Cheverud, James M

2018-02-01

Determining the genetic architecture of quantitative traits and genetic correlations among them is important for understanding morphological evolution patterns. We address two questions regarding papionin evolution: (1) what effect do body and cranial size, age, and sex have on phenotypic (V P ) and additive genetic (V A ) variation in baboon crania, and (2) how might additive genetic correlations between craniofacial traits and body mass affect morphological evolution? We use a large captive pedigreed baboon sample to estimate quantitative genetic parameters for craniofacial dimensions (EIDs). Our models include nested combinations of the covariates listed above. We also simulate the correlated response of a given EID due to selection on body mass alone. Covariates account for 1.2-91% of craniofacial V P . EID V A decreases across models as more covariates are included. The median genetic correlation estimate between each EID and body mass is 0.33. Analysis of the multivariate response to selection reveals that observed patterns of craniofacial variation in extant baboons cannot be attributed solely to correlated response to selection on body mass, particularly in males. Because a relatively large proportion of EID V A is shared with body mass variation, different methods of correcting for allometry by statistically controlling for size can alter residual V P patterns. This may conflate direct selection effects on craniofacial variation with those resulting from a correlated response to body mass selection. This shared genetic variation may partially explain how selection for increased body mass in two different papionin lineages produced remarkably similar craniofacial phenotypes. © 2017 Wiley Periodicals, Inc.
Genetic alterations during the progression of squamous cell carcinomas of the uterine cervix

NARCIS (Netherlands)

Kersemaekers, A. M.; van de Vijver, M. J.; Kenter, G. G.; Fleuren, G. J.

1999-01-01

Most cervical carcinomas appear to arise from cervical intraepithelial neoplasia (CIN) lesions. In addition to infection with high-risk human papilloma viruses, which is indicative of an increased risk of progression, alterations of oncogenes and tumor suppressor genes play a role. Genetic studies

Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library

International Nuclear Information System (INIS)

Oblozinsky, P.; Oblozinsky, P.; Mattoon, C.M.; Herman, M.; Mughabghab, S.F.; Pigni, M.T.; Talou, P.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Young, P.G

2009-01-01

Improved neutron cross section covariances were produced for 110 materials including 12 light nuclei (coolants and moderators), 78 structural materials and fission products, and 20 actinides. Improved covariances were organized into AFCI-1.2 covariance library in 33-energy groups, from 10 -5 eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: 23 Na and 55 Mn where more detailed evaluation was done; improvements in major structural materials 52 Cr, 56 Fe and 58 Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for 23 Na and 56 Fe. LANL contributed improved covariance data for 235 U and 239 Pu including prompt neutron fission spectra and completely new evaluation for 240 Pu. New R-matrix evaluation for 16 O including mubar covariances is under completion. BNL assembled the library and performed basic testing using improved procedures including inspection of uncertainty and correlation plots for each material. The AFCI-1.2 library was released to ANL and INL in August 2009.
Directional selection effects on patterns of phenotypic (co)variation in wild populations.

Science.gov (United States)

Assis, A P A; Patton, J L; Hubbe, A; Marroig, G

2016-11-30

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient. © 2016 The Author(s).
Population genetic dynamics of three-spined sticklebacks (Gasterosteus aculeatus) in anthropogenic altered habitats.

Science.gov (United States)

Scharsack, Joern P; Schweyen, Hannah; Schmidt, Alexander M; Dittmar, Janine; Reusch, Thorsten Bh; Kurtz, Joachim

2012-06-01

In industrialized and/or agriculturally used landscapes, inhabiting species are exposed to a variety of anthropogenic changes in their environments. Genetic diversity may be reduced if populations encounter founder events, bottlenecks, or isolation. Conversely, genetic diversity may increase if populations adapt to changes in selective regimes in newly created habitats. With the present study, genetic variability of 918 sticklebacks from 43 samplings (21.3 ± 3.8 per sample) at 36 locations from cultivated landscapes in Northwest Germany was analyzed at nine neutral microsatellite loci. To test if differentiation is influenced by habitat alterations, sticklebacks were collected from ancient running waters and adjacent artificial stagnant waters, from brooks with salt water inflow of anthropogenic and natural origin and adjacent freshwater sites. Overall population structure was dominated by isolation by distance (IBD), which was significant across all populations, and analysis of molecular variance (AMOVA) revealed that 10.6% of the variation was explained by river catchment area. Populations in anthropogenic modified habitats deviated from the general IBD structure and in the AMOVA, grouping by habitat type running/stagnant water explained 4.9% of variation and 1.4% of the variation was explained by salt-/freshwater habitat. Sticklebacks in salt-polluted water systems seem to exhibit elevated migratory activity between fresh- and saltwater habitats, reducing IBD. In other situations, populations showed distinct signs of genetic isolation, which in some locations was attributed to mechanical migration barriers, but in others to potential anthropogenic induced bottleneck or founder effects. The present study shows that anthropogenic habitat alterations may have diverse effects on the population genetic structure of inhabiting species. Depending on the type of habitat change, increased genetic differentiation, diversification, or isolation are possible consequences.
Genetic Variant in Flavin-Containing Monooxygenase 3 Alters Lipid Metabolism in Laying Hens in a Diet-Specific Manner

OpenAIRE

Wang, Jing; Long, Cheng; Zhang, Haijun; Zhang, Yanan; Wang, Hao; Yue, Hongyuan; Wang, Xiaocui; Wu, Shugeng; Qi, Guanghai

2016-01-01

Genetic variant T329S in flavin-containing monooxygenase 3 (FMO3) impairs trimethylamine (TMA) metabolism in birds. The TMA metabolism that under complex genetic and dietary regulation, closely linked to cardiovascular disease risk. We determined whether the genetic defects in TMA metabolism may change other metabolic traits in birds, determined whether the genetic effects depend on diets, and to identify genes or gene pathways that underlie the metabolic alteration induced by genetic and die...
Structural and Maturational Covariance in Early Childhood Brain Development.

Science.gov (United States)

Geng, Xiujuan; Li, Gang; Lu, Zhaohua; Gao, Wei; Wang, Li; Shen, Dinggang; Zhu, Hongtu; Gilmore, John H

2017-03-01

Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Phytoplasmal infection derails genetically preprogrammed meristem fate and alters plant architecture

OpenAIRE

Wei, Wei; Davis, Robert Edward; Nuss, Donald L.; Zhao, Yan

2013-01-01

In higher plants, the destiny of apical meristems (stem cells) is specific organogenesis, which determines the pattern of plant growth, and therefore morphotype and fertility. We found that bacterial infection can derail the meristems from their genetically preprogrammed destiny, altering plant morphogenesis. We identified four abnormal growth patterns, symptoms, in tomato infected with a cell wall-less bacterium, and found that each symptom corresponds to a distinct phase in meristem fate de...
Genetic Alterations of the Thrombopoietin/MPL/JAK2 Axis Impacting Megakaryopoiesis

OpenAIRE

Plo, Isabelle; Bellanné-Chantelot, Christine; Mosca, Matthieu; Mazzi, Stefania; Marty, Caroline; Vainchenker, William

2017-01-01

Megakaryopoiesis is an original and complex cell process which leads to the formation of platelets. The homeostatic production of platelets is mainly regulated and controlled by thrombopoietin (TPO) and the TPO receptor (MPL)/JAK2 axis. Therefore, any hereditary or acquired abnormality affecting this signaling axis can result in thrombocytosis or thrombocytopenia. Thrombocytosis can be due to genetic alterations that affect either the intrinsic MPL signaling through gain-of-function (GOF) act...
Examination of the causes of covariation between conduct disorder symptoms and vulnerability to drug dependence.

Science.gov (United States)

Button, Tanya M M; Hewitt, John K; Rhee, Soo Hyun; Young, Susan E; Corley, Robin P; Stallings, Michael C

2006-02-01

Conduct disorder (CD) symptoms and substance dependence commonly co-occur. Both phenotypes are highly heritable and a common genetic influence on the covariation has been suggested. The aim of this study was to determine the extent to which genes and environment contribute to the covariance between CD and drug dependence using twins from the Colorado Longitudinal Twin Sample and the Colorado Twin Registry. A total of 880 twin pairs (237 monozygotic [MZ] female, 195 MZ male, 116 dizygotic [DZ] female, 118 DZ male and 214 DZ opposite-sex) aged 13 to 18 (mean = 15.65) were included in the analysis. CD was assessed by lifetime Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) symptom count and a polysubstance dependence vulnerability index was developed from responses to the Composite International Diagnostic Interview--Substance Abuse Module. A bivariate Cholesky Decomposition model was used to partition the cause of variation and covariation of the two phenotypes. No sex-limitation was observed in our data, and male and female parameter estimates were constrained to be equal. Both CD symptoms and dependence vulnerability were significantly heritable, and genes, shared environment and nonshared environment all contributed to the covariation between them. Genes contributed 35% of the phenotypic covariance, shared environment contributed 46%, and nonshared environmental influences contributed the remaining 19% to the phenotypic covariance. Therefore, there appears to be pleiotropic genetic influence on CD symptoms and dependence vulnerability.
Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

Science.gov (United States)

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.
Genetic and epigenetic alterations of the reduced folate carrier in untreated diffuse large B-cell lymphoma

DEFF Research Database (Denmark)

Kastrup, I.B.; Worm, J.; Ralfkiaer, E.

2008-01-01

The reduced folate carrier (RFC) is a transmembrane protein that mediates cellular uptake of reduced folates and antifolate drugs, including methotrexate (MTX). Acquired alterations of the RFC gene have been associated with resistance to MTX in cancer cell lines and primary osteosarcomas. Here, w...... with adverse outcome. In DLBCL, genetic and epigenetic alterations of RFC were detected at diagnosis in the absence of a selective MTX pressure, suggesting that these alterations may possibly contribute to the development of lymphoma Udgivelsesdato: 2008/1...
Contributions to Large Covariance and Inverse Covariance Matrices Estimation

OpenAIRE

Kang, Xiaoning

2016-01-01

Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant analysis and gene expression analysis. However, accurate estimation of covariance or inverse covariance matrices is challenging due to the positive definiteness constraint and large number of parameters, especially in the high-dimensional cases. In this thesis, I develop several approaches for estimat...
The wild life at Chernobyl. Analysis of a prosperous but genetically altered fauna

International Nuclear Information System (INIS)

Chesser, R.; Baker, R.

1996-01-01

The ecological study of zones contaminated by Chernobyl accident reveals that the wild life abounds, because of inhabitants absence, evacuated. On the other hand, significant genetical alterations are observed, whom functional consequences, low visible, stay, at term, unknown. This kind of studies illustrates the development of a new discipline, the evolving toxicology
Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

Science.gov (United States)

Zhong, Qing; Rüschoff, Jan H; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J; Rupp, Niels J; Fankhauser, Christian; Buhmann, Joachim M; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C; Jochum, Wolfram; Wild, Peter J

2016-04-07

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.
Covariant Transform

OpenAIRE

Kisil, Vladimir V.

2010-01-01

The paper develops theory of covariant transform, which is inspired by the wavelet construction. It was observed that many interesting types of wavelets (or coherent states) arise from group representations which are not square integrable or vacuum vectors which are not admissible. Covariant transform extends an applicability of the popular wavelets construction to classic examples like the Hardy space H_2, Banach spaces, covariant functional calculus and many others. Keywords: Wavelets, cohe...
Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation

Science.gov (United States)

Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.

2018-01-01

Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.
Are your covariates under control? How normalization can re-introduce covariate effects.

Science.gov (United States)

Pain, Oliver; Dudbridge, Frank; Ronald, Angelica

2018-04-30

Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.
Developmental constraints revealed by co-variation within and among molar rows in two murine rodents.

Science.gov (United States)

Renaud, Sabrina; Pantalacci, Sophie; Quéré, Jean-Pierre; Laudet, Vincent; Auffray, Jean-Christophe

2009-01-01

Morphological integration corresponds to interdependency between characters that can arise from several causes. Proximal causes of integration include that different phenotypic features may share common genetic sets and/or interact during their development. Ultimate causes may be the prolonged effect of selection favoring integration of functionally interacting characters, achieved by the molding of these proximal causes. Strong and direct interactions among successive teeth of a molar row are predicted by genetic and developmental evidences. Functional constraints related to occlusion, however, should have selected more strongly for a morphological integration of occluding teeth and a corresponding evolution of the underlying developmental and genetic pathways. To investigate how these predictions match the patterns of phenotypic integration, we studied the co-variation among the six molars of the murine molar row, focusing on two populations of house mice (Mus musculus domesticus) and wood mice (Apodemus sylvaticus). The size and shape of the three upper and lower molars were quantified and compared. Our results evidenced similar patterns in both species, size being more integrated than shape among all the teeth, and both size and shape co-varying strongly between adjacent teeth, but also between occluding teeth. Strong co-variation within each molar row is in agreement with developmental models showing a cascade influence of the first molar on the subsequent molars. In contrast, the strong co-variation between molars of the occluding tooth rows confirms that functional constraints molded patterns of integration and probably the underlying developmental pathways despite the low level of direct developmental interactions occurring among molar rows. These patterns of co-variation are furthermore conserved between the house mouse and the wood mouse that diverged >10 Ma, suggesting that they may constitute long-running constraints to the diversification of the murine
Simultaneous genetic analysis of longitudinal means and covariance structure in the simplex model using twin data

NARCIS (Netherlands)

Dolan, C.V.; Molenaar, P.C.M.; Boomsma, D.I.

1991-01-01

D. Soerbom's (1974, 1976) simplex model approach to simultaneous analysis of means and covariance structure was applied to analysis of means observed in a single group. The present approach to the simultaneous biometric analysis of covariance and mean structure is based on the testable assumption
Genetic variants alter T-bet binding and gene expression in mucosal inflammatory disease.

Directory of Open Access Journals (Sweden)

Katrina Soderquest

2017-02-01

Full Text Available The polarization of CD4+ T cells into distinct T helper cell lineages is essential for protective immunity against infection, but aberrant T cell polarization can cause autoimmunity. The transcription factor T-bet (TBX21 specifies the Th1 lineage and represses alternative T cell fates. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs that may be causative for autoimmune diseases. The majority of these polymorphisms are located within non-coding distal regulatory elements. It is considered that these genetic variants contribute to disease by altering the binding of regulatory proteins and thus gene expression, but whether these variants alter the binding of lineage-specifying transcription factors has not been determined. Here, we show that SNPs associated with the mucosal inflammatory diseases Crohn's disease, ulcerative colitis (UC and celiac disease, but not rheumatoid arthritis or psoriasis, are enriched at T-bet binding sites. Furthermore, we identify disease-associated variants that alter T-bet binding in vitro and in vivo. ChIP-seq for T-bet in individuals heterozygous for the celiac disease-associated SNPs rs1465321 and rs2058622 and the IBD-associated SNPs rs1551398 and rs1551399, reveals decreased binding to the minor disease-associated alleles. Furthermore, we show that rs1465321 is an expression quantitative trait locus (eQTL for the neighboring gene IL18RAP, with decreased T-bet binding associated with decreased expression of this gene. These results suggest that genetic polymorphisms may predispose individuals to mucosal autoimmune disease through alterations in T-bet binding. Other disease-associated variants may similarly act by modulating the binding of lineage-specifying transcription factors in a tissue-selective and disease-specific manner.
Covariance evaluation system

International Nuclear Information System (INIS)

Kawano, Toshihiko; Shibata, Keiichi.

1997-09-01

A covariance evaluation system for the evaluated nuclear data library was established. The parameter estimation method and the least squares method with a spline function are used to generate the covariance data. Uncertainties of nuclear reaction model parameters are estimated from experimental data uncertainties, then the covariance of the evaluated cross sections is calculated by means of error propagation. Computer programs ELIESE-3, EGNASH4, ECIS, and CASTHY are used. Covariances of 238 U reaction cross sections were calculated with this system. (author)

Genetic and phenotypic variance and covariance components for methane emission and postweaning traits in Angus cattle.

Science.gov (United States)

Donoghue, K A; Bird-Gardiner, T; Arthur, P F; Herd, R M; Hegarty, R F

2016-04-01

Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that
Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

Science.gov (United States)

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.
Variance and covariance components for liability of piglet survival during different periods

DEFF Research Database (Denmark)

Su, G; Sorensen, D; Lund, M S

2008-01-01

Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individu...
On the algebraic structure of covariant anomalies and covariant Schwinger terms

International Nuclear Information System (INIS)

Kelnhofer, G.

1992-01-01

A cohomological characterization of covariant anomalies and covariant Schwinger terms in an anomalous Yang-Mills theory is formulated and w ill be geometrically interpreted. The BRS and anti-BRS transformations are defined as purely differential geometric objects. Finally the covariant descent equations are formulated within this context. (author)
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families

Science.gov (United States)

Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert

2016-01-01

In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes. PMID:27402363
A class of covariate-dependent spatiotemporal covariance functions

Science.gov (United States)

Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.

2014-01-01

In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199
Rapid changes in genetic architecture of behavioural syndromes following colonization of a novel environment.

Science.gov (United States)

Karlsson Green, K; Eroukhmanoff, F; Harris, S; Pettersson, L B; Svensson, E I

2016-01-01

Behavioural syndromes, that is correlated behaviours, may be a result from adaptive correlational selection, but in a new environmental setting, the trait correlation might act as an evolutionary constraint. However, knowledge about the quantitative genetic basis of behavioural syndromes, and the stability and evolvability of genetic correlations under different ecological conditions, is limited. We investigated the quantitative genetic basis of correlated behaviours in the freshwater isopod Asellus aquaticus. In some Swedish lakes, A. aquaticus has recently colonized a novel habitat and diverged into two ecotypes, presumably due to habitat-specific selection from predation. Using a common garden approach and animal model analyses, we estimated quantitative genetic parameters for behavioural traits and compared the genetic architecture between the ecotypes. We report that the genetic covariance structure of the behavioural traits has been altered in the novel ecotype, demonstrating divergence in behavioural correlations. Thus, our study confirms that genetic correlations behind behaviours can change rapidly in response to novel selective environments. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.
ENDF-6 File 30: Data covariances obtained from parameter covariances and sensitivities

International Nuclear Information System (INIS)

Muir, D.W.

1989-01-01

File 30 is provided as a means of describing the covariances of tabulated cross sections, multiplicities, and energy-angle distributions that result from propagating the covariances of a set of underlying parameters (for example, the input parameters of a nuclear-model code), using an evaluator-supplied set of parameter covariances and sensitivities. Whenever nuclear data are evaluated primarily through the application of nuclear models, the covariances of the resulting data can be described very adequately, and compactly, by specifying the covariance matrix for the underlying nuclear parameters, along with a set of sensitivity coefficients giving the rate of change of each nuclear datum of interest with respect to each of the model parameters. Although motivated primarily by these applications of nuclear theory, use of File 30 is not restricted to any one particular evaluation methodology. It can be used to describe data covariances of any origin, so long as they can be formally separated into a set of parameters with specified covariances and a set of data sensitivities
The Landscape of Somatic Genetic Alterations in Breast Cancers From ATM Germline Mutation Carriers.

Science.gov (United States)

Weigelt, Britta; Bi, Rui; Kumar, Rahul; Blecua, Pedro; Mandelker, Diana L; Geyer, Felipe C; Pareja, Fresia; James, Paul A; Couch, Fergus J; Eccles, Diana M; Blows, Fiona; Pharoah, Paul; Li, Anqi; Selenica, Pier; Lim, Raymond S; Jayakumaran, Gowtham; Waddell, Nic; Shen, Ronglai; Norton, Larry; Wen, Hannah Y; Powell, Simon N; Riaz, Nadeem; Robson, Mark E; Reis-Filho, Jorge S; Chenevix-Trench, Georgia

2018-02-28

Pathogenic germline variants in ataxia-telangiectasia mutated (ATM), a gene that plays a role in DNA damage response and cell cycle checkpoints, confer an increased breast cancer (BC) risk. Here, we investigated the phenotypic characteristics and landscape of somatic genetic alterations in 24 BCs from ATM germline mutation carriers by whole-exome and targeted sequencing. ATM-associated BCs were consistently hormone receptor positive and largely displayed minimal immune infiltrate. Although 79.2% of these tumors exhibited loss of heterozygosity of the ATM wild-type allele, none displayed high activity of mutational signature 3 associated with defective homologous recombination DNA (HRD) repair. No TP53 mutations were found in the ATM-associated BCs. Analysis of an independent data set confirmed that germline ATM variants and TP53 somatic mutations are mutually exclusive. Our findings indicate that ATM-associated BCs often harbor bi-allelic inactivation of ATM, are phenotypically distinct from BRCA1/2-associated BCs, lack HRD-related mutational signatures, and that TP53 and ATM genetic alterations are likely epistatic.
Genetic and environmental variance and covariance parameters for some reproductive traits of Holstein and Jersey cattle in Antioquia (Colombia

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Juan Carlos Zambrano

2014-03-01

Full Text Available The objective of this study was to estimate the genetic, phenotypic and environmental parameters for calving interval (CI, days open (DO, number of services per conception (NSC and conception rate (CR in Holstein and Jersey cattle in Antioquia (Colombia. Variance and covariance component estimates were obtained by an animal model that was solved using the derivative-free restricted maximum likelihood method. The means and standard deviations for CI, DO, NSC and CR were: 430.32±77.93 days, 127.15±76.96 days, 1.58±1.03 services per conception and 79.88±28.66% in Holstein cattle, and 409.33±86.48 days, 125.62±86.09 days, 1.48±0.98 services per conception and 84.08±27.23% in Jersey cattle, respectively. The heritability estimates (standard errors were: 0.088(0.037, 0.082(0.037, 0.040(0.025 and 0.030(0.026 in Holstein cattle and 0.072(0.098, 0.090(0.104, 0.093(0.097 and 0.147(0.117 in Jersey cattle, respectively. The results show that the genetic, phenotypic and permanent environmental correlations in the two evaluated breeds were favorable for CI × DO, CI × NSC and DO × NSC, but not for CI × CR, DO × CR and NSC × CR. Genetic and permanent environmental correlations were high in most cases in Holstein cattle, whereas in Jersey cattle they were moderate. In contrast, phenotypic correlations were very low in both breeds, except for CI × DO and NSC × CR, which were high. Overall, the genetic component found was very low (<8% in both evaluated breeds and this implies that their selection would take long time and that a good practical management of the herd will be essential in order to improve the reproductive performance.
Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

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Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information

NARCIS (Netherlands)

Binsbergen, van R.; Veerkamp, R.F.; Calus, M.P.L.

2012-01-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk
Brownian distance covariance

OpenAIRE

Székely, Gábor J.; Rizzo, Maria L.

2010-01-01

Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...
Genetic Alterations of the Thrombopoietin/MPL/JAK2 Axis Impacting Megakaryopoiesis.

Science.gov (United States)

Plo, Isabelle; Bellanné-Chantelot, Christine; Mosca, Matthieu; Mazzi, Stefania; Marty, Caroline; Vainchenker, William

2017-01-01

Megakaryopoiesis is an original and complex cell process which leads to the formation of platelets. The homeostatic production of platelets is mainly regulated and controlled by thrombopoietin (TPO) and the TPO receptor (MPL)/JAK2 axis. Therefore, any hereditary or acquired abnormality affecting this signaling axis can result in thrombocytosis or thrombocytopenia. Thrombocytosis can be due to genetic alterations that affect either the intrinsic MPL signaling through gain-of-function (GOF) activity ( MPL, JAK2, CALR ) and loss-of-function (LOF) activity of negative regulators ( CBL, LNK ) or the extrinsic MPL signaling by THPO GOF mutations leading to increased TPO synthesis. Alternatively, thrombocytosis may paradoxically result from mutations of MPL leading to an abnormal MPL trafficking, inducing increased TPO levels by alteration of its clearance. In contrast, thrombocytopenia can also result from LOF THPO or MPL mutations, which cause a complete defect in MPL trafficking to the cell membrane, impaired MPL signaling or stability, defects in the TPO/MPL interaction, or an absence of TPO production.
The genetic covariance between life cycle stages separated by metamorphosis.

Science.gov (United States)

Aguirre, J David; Blows, Mark W; Marshall, Dustin J

2014-08-07

Metamorphosis is common in animals, yet the genetic associations between life cycle stages are poorly understood. Given the radical changes that occur at metamorphosis, selection may differ before and after metamorphosis, and the extent that genetic associations between pre- and post-metamorphic traits constrain evolutionary change is a subject of considerable interest. In some instances, metamorphosis may allow the genetic decoupling of life cycle stages, whereas in others, metamorphosis could allow complementary responses to selection across the life cycle. Using a diallel breeding design, we measured viability at four ontogenetic stages (embryo, larval, juvenile and adult viability), in the ascidian Ciona intestinalis and examined the orientation of additive genetic variation with respect to the metamorphic boundary. We found support for one eigenvector of G: (gobsmax ), which contrasted larval viability against embryo viability and juvenile viability. Target matrix rotation confirmed that while gobsmax shows genetic associations can extend beyond metamorphosis, there is still considerable scope for decoupled phenotypic evolution. Therefore, although genetic associations across metamorphosis could limit that range of phenotypes that are attainable, traits on either side of the metamorphic boundary are capable of some independent evolutionary change in response to the divergent conditions encountered during each life cycle stage. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Covariant representations of nuclear *-algebras

International Nuclear Information System (INIS)

Moore, S.M.

1978-01-01

Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations
variance components and genetic parameters for live weight

African Journals Online (AJOL)

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Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.
Earth Observing System Covariance Realism

Science.gov (United States)

Zaidi, Waqar H.; Hejduk, Matthew D.

2016-01-01

The purpose of covariance realism is to properly size a primary object's covariance in order to add validity to the calculation of the probability of collision. The covariance realism technique in this paper consists of three parts: collection/calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics. An empirical cumulative distribution function (ECDF) Goodness-of-Fit (GOF) method is employed to determine if a covariance is properly sized by comparing the empirical distribution of Mahalanobis distance calculations to the hypothesized parent 3-DoF chi-squared distribution. To realistically size a covariance for collision probability calculations, this study uses a state noise compensation algorithm that adds process noise to the definitive epoch covariance to account for uncertainty in the force model. Process noise is added until the GOF tests pass a group significance level threshold. The results of this study indicate that when outliers attributed to persistently high or extreme levels of solar activity are removed, the aforementioned covariance realism compensation method produces a tuned covariance with up to 80 to 90% of the covariance propagation timespan passing (against a 60% minimum passing threshold) the GOF tests-a quite satisfactory and useful result.
Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors.

Science.gov (United States)

Naseri, Parisa; Khodakarim, Soheila; Guity, Kamran; Daneshpour, Maryam S

2018-06-15

Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates. Copyright © 2018. Published by Elsevier B.V.
Hierarchical multivariate covariance analysis of metabolic connectivity.

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Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Immunity traits in pigs: substantial genetic variation and limited covariation.

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Laurence Flori

Full Text Available BACKGROUND: Increasing robustness via improvement of resistance to pathogens is a major selection objective in livestock breeding. As resistance traits are difficult or impossible to measure directly, potential indirect criteria are measures of immune traits (ITs. Our underlying hypothesis is that levels of ITs with no focus on specific pathogens define an individual's immunocompetence and thus predict response to pathogens in general. Since variation in ITs depends on genetic, environmental and probably epigenetic factors, our aim was to estimate the relative importance of genetics. In this report, we present a large genetic survey of innate and adaptive ITs in pig families bred in the same environment. METHODOLOGY/PRINCIPAL FINDINGS: Fifty four ITs were studied on 443 Large White pigs vaccinated against Mycoplasma hyopneumoniae and analyzed by combining a principal component analysis (PCA and genetic parameter estimation. ITs include specific and non specific antibodies, seric inflammatory proteins, cell subsets by hemogram and flow cytometry, ex vivo production of cytokines (IFNα, TNFα, IL6, IL8, IL12, IFNγ, IL2, IL4, IL10, phagocytosis and lymphocyte proliferation. While six ITs had heritabilities that were weak or not significantly different from zero, 18 and 30 ITs had moderate (0.10.4 heritability values, respectively. Phenotypic and genetic correlations between ITs were weak except for a few traits that mostly include cell subsets. PCA revealed no cluster of innate or adaptive ITs. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that variation in many innate and adaptive ITs is genetically controlled in swine, as already reported for a smaller number of traits by other laboratories. A limited redundancy of the traits was also observed confirming the high degree of complementarity between innate and adaptive ITs. Our data provide a genetic framework for choosing ITs to be included as selection criteria in multitrait selection
The Effect of Unequal Samples, Heterogeneity of Covariance Matrices, and Number of Variables on Discriminant Analysis Classification Tables and Related Statistics.

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Spearing, Debra; Woehlke, Paula

To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…
Macro-environment of breast carcinoma: frequent genetic alterations in the normal appearing skins of patients with breast cancer.

Science.gov (United States)

Moinfar, Farid; Beham, Alfred; Friedrich, Gerhard; Deutsch, Alexander; Hrzenjak, Andelko; Luschin, Gero; Tavassoli, Fattaneh A

2008-05-01

Genetic abnormalities in microenvironmental tissues with subsequent alterations of reciprocal interactions between epithelial and mesenchymal cells play a key role in the breast carcinogenesis. Although a few reports have demonstrated abnormal fibroblastic functions in normal-appearing fibroblasts taken from the skins of breast cancer patients, the genetic basis of this phenomenon and its implication for carcinogenesis are unexplored. We analyzed 12 mastectomy specimens showing invasive ductal carcinomas. In each case, morphologically normal epidermis and dermis, carcinoma, normal stroma close to carcinoma, and stroma at a distant from carcinoma were microdissected. Metastatic-free lymphatic tissues from lymph nodes served as a control. Using PCR, DNA extracts were examined with 11 microsatellite markers known for a high frequency of allelic imbalances in breast cancer. Losses of heterozygosity and/or microsatellite instability were detected in 83% of the skin samples occurring either concurrently with or independently from the cancerous tissues. In 80% of these cases at least one microsatellite marker displayed loss of heterozygosity or microsatellite instability in the skin, which was absent in carcinoma. A total of 41% of samples showed alterations of certain loci observed exclusively in the carcinoma but not in the skin compartments. Our study suggests that breast cancer is not just a localized genetic disorder, but rather part of a larger field of genetic alterations/instabilities affecting multiple cell populations in the organ with various cellular elements, ultimately contributing to the manifestation of the more 'localized' carcinoma. These data indicate that more global assessment of tumor micro- and macro-environment is crucial for our understanding of breast carcinogenesis.
Parkinson's disease and pesticides: A meta-analysis of disease connection and genetic alterations.

Science.gov (United States)

Ahmed, Hussien; Abushouk, Abdelrahman Ibrahim; Gabr, Mohamed; Negida, Ahmed; Abdel-Daim, Mohamed M

2017-06-01

Parkinson's disease (PD) is a globally prevalent, multifactorial disorder that occurs due to interactions between genetic and environmental factors. Observational studies have shown a link between exposure to pesticides and the risk of PD. We performed this study to systemically review published case-control studies and estimate quantitatively the association between pesticide exposure and PD. We searched Medline (through PubMed) for eligible case-control studies. The association between pesticide exposure and PD risk or occurrence of certain genetic alterations, related to the pathogenesis of PD was presented as odds ratios (OR) and pooled under the random effects model, using the statistical add-in (MetaXL, version 5.0). The pooled result showed that exposure to pesticides is linked to PD (OR 1.46, 95% CI [1.21, 1.77]), but there was a significant heterogeneity among included studies. Exposure to pesticides increased the risk of alterations in different PD pathogenesis-related genes, such as GST (OR 1.97, 95% CI [1.41, 2.76]), PON-1 (OR 1.32, 95% CI [1.09, 1.6]), MDR1 (OR 2.06, 95% CI [1.58, 2.68]), and SNCA genes (OR 1.28, 95% CI [1.02, 1.37]). There was no statistically significant association between exposure to pesticides and alteration of CYP2D6 (OR 1.19, 95% CI [0.91, 1.54]), SLC6A3 (OR 0.74, 95% CI [0.55, 1]), MnSOD (OR 1.45, 95% CI [0.97, 2.16]), NQO1 (OR 1.35, 95% CI [0.91, 2.01]), and PON-2 genes (OR 0.88, 95% CI [0.53, 1.45]). In conclusion, this meta-analysis provides evidence that pesticide exposure is significantly associated with the risk of PD and alterations in genes involved in PD pathogenesis. However, the underlying mechanism of this association and the effect of the duration of exposure or the type of pesticides should be addressed by future research. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
Structural Covariance Networks in Children with Autism or ADHD.

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Bethlehem, R A I; Romero-Garcia, R; Mak, E; Bullmore, E T; Baron-Cohen, S

2017-08-01

While autism and attention-deficit/hyperactivity disorder (ADHD) are considered distinct conditions from a diagnostic perspective, clinically they share some phenotypic features and have high comorbidity. Regardless, most studies have focused on only one condition, with considerable heterogeneity in their results. Taking a dual-condition approach might help elucidate shared and distinct neural characteristics. Graph theory was used to analyse topological properties of structural covariance networks across both conditions and relative to a neurotypical (NT; n = 87) group using data from the ABIDE (autism; n = 62) and ADHD-200 datasets (ADHD; n = 69). Regional cortical thickness was used to construct the structural covariance networks. This was analysed in a theoretical framework examining potential differences in long and short-range connectivity, with a specific focus on relation between central graph measures and cortical thickness. We found convergence between autism and ADHD, where both conditions show an overall decrease in CT covariance with increased Euclidean distance between centroids compared with a NT population. The 2 conditions also show divergence. Namely, there is less modular overlap between the 2 conditions than there is between each condition and the NT group. The ADHD group also showed reduced cortical thickness and lower degree in hub regions than the autism group. Lastly, the ADHD group also showed reduced wiring costs compared with the autism groups. Our results indicate a need for taking an integrated approach when considering highly comorbid conditions such as autism and ADHD. Furthermore, autism and ADHD both showed alterations in the relation between inter-regional covariance and centroid distance, where both groups show a steeper decline in covariance as a function of distance. The 2 groups also diverge on modular organization, cortical thickness of hub regions and wiring cost of the covariance network. Thus, on some network features the
Covariant field equations in supergravity

Energy Technology Data Exchange (ETDEWEB)

Vanhecke, Bram [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium); Ghent University, Faculty of Physics, Gent (Belgium); Proeyen, Antoine van [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium)

2017-12-15

Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Covariant field equations in supergravity

International Nuclear Information System (INIS)

Vanhecke, Bram; Proeyen, Antoine van

2017-01-01

Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs

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Liang Kung-Yee

2010-07-01

Full Text Available Abstract Background Many dichotomous traits for complex diseases are often involved more than one locus and/or associated with quantitative biomarkers or environmental factors. Incorporating these quantitative variables into linkage analysis as well as localizing two linked disease loci simultaneously could therefore improve the efficiency in mapping genes. We extended the robust multipoint Identity-by-Descent (IBD approach with incorporation of covariates developed previously to simultaneously estimate two linked loci using different types of affected relative pairs (ARPs. Results We showed that the efficiency was enhanced by incorporating a quantitative covariate parametrically or non-parametrically while localizing two disease loci using ARPs. In addition to its help in identifying factors associated with the disease and in improving the efficiency in estimating disease loci, this extension also allows investigators to account for heterogeneity in risk-ratios for different ARPs. Data released from the collaborative study on the genetics of alcoholism (COGA for Genetic Analysis Workshop 14 (GAW 14 were used to illustrate the application of this extended method. Conclusions The simulation studies and example illustrated that the efficiency in estimating disease loci was demonstratively enhanced by incorporating a quantitative covariate and by using all relative pairs while mapping two linked loci simultaneously.
Genetic and Non-genetic Factors Associated WithConstipation in Cancer Patients Receiving Opioids

OpenAIRE

Laugsand, Eivor Alette; Skorpen, Frank; Kaasa, Stein; Sabatowski, Rainer; Strasser, Florian; Fayers, Peter; Klepstad, Pål

2015-01-01

Objectives: To examine whether the inter-individual variation in constipation among patients receiving opioids for cancer pain is associated with genetic or non-genetic factors. Methods: Cancer patients receiving opioids were included from 17 centers in 11 European countries. Intensity of constipation was reported by 1,568 patients on a four-point categorical scale. Non-genetic factors were included as covariates in stratified regression analyses on the association between constipation a...
Behavior of genetic (covariance components in populations simulated from non-additive genetic models of dominance and overdominance Comportamento dos componentes de (covariância genética em populações simuladas a partir de modelos genéticos não-aditivos de dominância e sobredominância

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Elizângela Emídio Cunha

2010-09-01

Full Text Available The aim of this work was to investigate the short-term behavior of the genetic variability of quantitative traits simulated from models with additive and non-additive gene action in control and phenotypic selection populations. Both traits, one with low (h² = 0.10 and the other with high (h² = 0.60 heritability, were controlled by 600 biallelic loci. From a standard genome, it was obtained six genetic models which included the following: only the additive gene effects; complete and positive dominance for 25, 50, 75 and 100% of the loci; and positive overdominance for 50% of the loci. In the models with dominance deviation, the additive allelic effects were also included for 100% of the loci. Genetic variability was quantified from generation to generation using the genetic variance components. In the absence of selection, genotypic and additive genetic variances were higher. In the models with non-additive gene action, a small magnitude covariance component raised between the additive and dominance genetic effects whose correlation tended to be positive on the control population and negative under selection. Dominance variance increased as the number of loci with dominance deviation or the value of the deviation increased, implying on the increase in genotypic and additive genetic variances among the successive models.Objetivou-se estudar a variabilidade genética a curto prazo de características quantitativas simuladas a partir de modelos com ação gênica aditiva e não-aditiva em populações controle e de seleção fenotípica. As duas características, uma de baixa (h² = 0,10 e outra de alta (h² = 0,60 herdabilidade, foram controladas por 600 locos bialélicos. A partir de um genoma-padrão, foram obtidos seis modelos genéticos que incluíram: apenas efeitos aditivos dos genes; dominância completa e positiva para 25, 50, 75 e 100% dos locos; e sobredominância positiva para 50% dos locos. Nos modelos com desvio da dominância tamb
Genetic and epigenetic alteration among three homoeologous genes of a class E MADS box gene in hexaploid wheat.

Science.gov (United States)

Shitsukawa, Naoki; Tahira, Chikako; Kassai, Ken-Ichiro; Hirabayashi, Chizuru; Shimizu, Tomoaki; Takumi, Shigeo; Mochida, Keiichi; Kawaura, Kanako; Ogihara, Yasunari; Murai, Koji

2007-06-01

Bread wheat (Triticum aestivum) is a hexaploid species with A, B, and D ancestral genomes. Most bread wheat genes are present in the genome as triplicated homoeologous genes (homoeologs) derived from the ancestral species. Here, we report that both genetic and epigenetic alterations have occurred in the homoeologs of a wheat class E MADS box gene. Two class E genes are identified in wheat, wheat SEPALLATA (WSEP) and wheat LEAFY HULL STERILE1 (WLHS1), which are homologs of Os MADS45 and Os MADS1 in rice (Oryza sativa), respectively. The three wheat homoeologs of WSEP showed similar genomic structures and expression profiles. By contrast, the three homoeologs of WLHS1 showed genetic and epigenetic alterations. The A genome WLHS1 homoeolog (WLHS1-A) had a structural alteration that contained a large novel sequence in place of the K domain sequence. A yeast two-hybrid analysis and a transgenic experiment indicated that the WLHS1-A protein had no apparent function. The B and D genome homoeologs, WLHS1-B and WLHS1-D, respectively, had an intact MADS box gene structure, but WLHS1-B was predominantly silenced by cytosine methylation. Consequently, of the three WLHS1 homoeologs, only WLHS1-D functions in hexaploid wheat. This is a situation where three homoeologs are differentially regulated by genetic and epigenetic mechanisms.
Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates.

Science.gov (United States)

Gautier, Mathieu

2015-12-01

In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier
Genetic Parameters of Common Wheat in Nepal

Directory of Open Access Journals (Sweden)

Bal Krishna Joshi

2015-12-01

Full Text Available Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correlated response. Differences between phenotypic and genotypic variances in heading days, maturity days and plant height were not large. Grain yield and plant height showed the highest phenotypic (18.189% and genotypic (12.06% coefficient of variances, respectively. Phenotypic covariance was higher than genotypic and environmental covariance in most of the traits. The highest heritability and realized heritability were of heading days followed by maturity days. Genetic gain for plant height was the highest. Co-heritability of 1000-grain weight with tillers number was the highest. The highest correlated response was expressed by grain yield with tillers number. This study indicates the possibility of improving wheat genotypes through selection utilizing existing variation in these traits.
Structural whole-brain covariance of the anterior and posterior hippocampus: Associations with age and memory.

Science.gov (United States)

Nordin, Kristin; Persson, Jonas; Stening, Eva; Herlitz, Agneta; Larsson, Elna-Marie; Söderlund, Hedvig

2018-02-01

The hippocampus (HC) interacts with distributed brain regions to support memory and shows significant volume reductions in aging, but little is known about age effects on hippocampal whole-brain structural covariance. It is also unclear whether the anterior and posterior HC show similar or distinct patterns of whole-brain covariance and to what extent these are related to memory functions organized along the hippocampal longitudinal axis. Using the multivariate approach partial least squares, we assessed structural whole-brain covariance of the HC in addition to regional volume, in young, middle-aged and older adults (n = 221), and assessed associations with episodic and spatial memory. Based on findings of sex differences in both memory and brain aging, we further considered sex as a potential modulating factor of age effects. There were two main covariance patterns: one capturing common anterior and posterior covariance, and one differentiating the two regions by capturing anterior-specific covariance only. These patterns were differentially related to associative memory while unrelated to measures of single-item memory and spatial memory. Although patterns were qualitatively comparable across age groups, participants' expression of both patterns decreased with age, independently of sex. The results suggest that the organization of hippocampal structural whole-brain covariance remains stable across age, but that the integrity of these networks decreases as the brain undergoes age-related alterations. © 2017 Wiley Periodicals, Inc.
A special covariance structure for random coefficient models with both between and within covariates

International Nuclear Information System (INIS)

Riedel, K.S.

1990-07-01

We review random coefficient (RC) models in linear regression and propose a bias correction to the maximum likelihood (ML) estimator. Asymmptotic expansion of the ML equations are given when the between individual variance is much larger or smaller than the variance from within individual fluctuations. The standard model assumes all but one covariate varies within each individual, (we denote the within covariates by vector χ 1 ). We consider random coefficient models where some of the covariates do not vary in any single individual (we denote the between covariates by vector χ 0 ). The regression coefficients, vector β k , can only be estimated in the subspace X k of X. Thus the number of individuals necessary to estimate vector β and the covariance matrix Δ of vector β increases significantly in the presence of more than one between covariate. When the number of individuals is sufficient to estimate vector β but not the entire matrix Δ , additional assumptions must be imposed on the structure of Δ. A simple reduced model is that the between component of vector β is fixed and only the within component varies randomly. This model fails because it is not invariant under linear coordinate transformations and it can significantly overestimate the variance of new observations. We propose a covariance structure for Δ without these difficulties by first projecting the within covariates onto the space perpendicular to be between covariates. (orig.)
Production of extracellular nucleic acids by genetically altered bacteria in aquatic-environment microcosms

International Nuclear Information System (INIS)

Paul, J.H.; David, A.W.

1989-01-01

The factors which affect the production of extracellular DNA by genetically altered strains of Escherichia coli, Pseudomonas aeruginosa, Pseudomonas cepacia, and Bradyrhizobium japonicum in aquatic environments were investigated. Cellular nucleic acids were labeled in vivo by incubation with [ 3 H]thymidine or [ 3 H]adenine, and production of extracellular DNA in marine waters, artificial seawater, or minimal salts media was determined by detecting radiolabeled macromolecules in incubation filtrates. The presence or absence of the ambient microbial community had little effect on the production of extracellular DNA. Three of four organisms produced the greatest amounts of extracellular nucleic acids when incubated in low-salinity media (2% artificial seawater) rather than high-salinity media (10 to 50% artificial seawater). The greatest production of extracellular nucleic acids by P. cepacia occurred at pH 7 and 37 degree C, suggesting that extracellular-DNA production may be a normal physiologic function of the cell. Incubation of labeled P. cepacia cells in water from Bimini Harbor, Bahamas, resulted in labeling of macromolecules of the ambient microbial population. Collectively these results indicate that (i) extracellular-DNA production by genetically altered bacteria released into aquatic environments is more strongly influenced by physicochemical factors than biotic factors, (ii) extracellular-DNA production rates are usually greater for organisms released in freshwater than marine environments, and (iii) ambient microbial populations can readily utilize materials released by these organisms
Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Knowledge of genetic correlations is essential to understand the joint evolution of traits through correlated responses to selection, a difficult and seldom, very precise task even with easy-to-breed species. Here, a simulation-based method to estimate genetic correlations and genetic covariances that relies only on ...
Covariant w∞ gravity

NARCIS (Netherlands)

Bergshoeff, E.; Pope, C.N.; Stelle, K.S.

1990-01-01

We discuss the notion of higher-spin covariance in w∞ gravity. We show how a recently proposed covariant w∞ gravity action can be obtained from non-chiral w∞ gravity by making field redefinitions that introduce new gauge-field components with corresponding new gauge transformations.
Evaluation and processing of covariance data

International Nuclear Information System (INIS)

Wagner, M.

1993-01-01

These proceedings of a specialists'meeting on evaluation and processing of covariance data is divided into 4 parts bearing on: part 1- Needs for evaluated covariance data (2 Papers), part 2- generation of covariance data (15 Papers), part 3- Processing of covariance files (2 Papers), part 4-Experience in the use of evaluated covariance data (2 Papers)
Covariance data processing code. ERRORJ

International Nuclear Information System (INIS)

Kosako, Kazuaki

2001-01-01

The covariance data processing code, ERRORJ, was developed to process the covariance data of JENDL-3.2. ERRORJ has the processing functions of covariance data for cross sections including resonance parameters, angular distribution and energy distribution. (author)

Linking neocortical, cognitive, and genetic variability in autism with alterations of brain plasticity: the Trigger-Threshold-Target model.

Science.gov (United States)

Mottron, Laurent; Belleville, Sylvie; Rouleau, Guy A; Collignon, Olivier

2014-11-01

The phenotype of autism involves heterogeneous adaptive traits (strengths vs. disabilities), different domains of alterations (social vs. non-social), and various associated genetic conditions (syndromic vs. nonsyndromic autism). Three observations suggest that alterations in experience-dependent plasticity are an etiological factor in autism: (1) the main cognitive domains enhanced in autism are controlled by the most plastic cortical brain regions, the multimodal association cortices; (2) autism and sensory deprivation share several features of cortical and functional reorganization; and (3) genetic mutations and/or environmental insults involved in autism all appear to affect developmental synaptic plasticity, and mostly lead to its upregulation. We present the Trigger-Threshold-Target (TTT) model of autism to organize these findings. In this model, genetic mutations trigger brain reorganization in individuals with a low plasticity threshold, mostly within regions sensitive to cortical reallocations. These changes account for the cognitive enhancements and reduced social expertise associated with autism. Enhanced but normal plasticity may underlie non-syndromic autism, whereas syndromic autism may occur when a triggering mutation or event produces an altered plastic reaction, also resulting in intellectual disability and dysmorphism in addition to autism. Differences in the target of brain reorganization (perceptual vs. language regions) account for the main autistic subgroups. In light of this model, future research should investigate how individual and sex-related differences in synaptic/regional brain plasticity influence the occurrence of autism. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Genetic variation and co-variation for fitness between intra-population and inter-population backgrounds in the red flour beetle, Tribolium castaneum

Science.gov (United States)

Drury, Douglas W.; Wade, Michael J.

2010-01-01

Hybrids from crosses between populations of the flour beetle, Tribolium castaneum, express varying degrees of inviability and morphological abnormalities. The proportion of allopatric population hybrids exhibiting these negative hybrid phenotypes varies widely, from 3% to 100%, depending upon the pair of populations crossed. We crossed three populations and measured two fitness components, fertility and adult offspring numbers from successful crosses, to determine how genes segregating within populations interact in inter-population hybrids to cause the negative phenotypes. With data from crosses of 40 sires from each of three populations to groups of 5 dams from their own and two divergent populations, we estimated the genetic variance and covariance for breeding value of fitness between the intra- and inter-population backgrounds and the sire × dam-population interaction variance. The latter component of the variance in breeding values estimates the change in genic effects between backgrounds owing to epistasis. Interacting genes with a positive effect, prior to fixation, in the sympatric background but a negative effect in the hybrid background cause reproductive incompatibility in the Dobzhansky-Muller speciation model. Thus, the sire × dam-population interaction provides a way to measure the progress toward speciation of genetically differentiating populations on a trait by trait basis using inter-population hybrids. PMID:21044199
Deriving Genomic Breeding Values for Residual Feed Intake from Covariance Functions of Random Regression Models

DEFF Research Database (Denmark)

Strathe, Anders B; Mark, Thomas; Nielsen, Bjarne

2014-01-01

Random regression models were used to estimate covariance functions between cumulated feed intake (CFI) and body weight (BW) in 8424 Danish Duroc pigs. Random regressions on second order Legendre polynomials of age were used to describe genetic and permanent environmental curves in BW and CFI...
A Phylogenetic Analysis of Shape Covariance Structure in the Anthropoid Skull

OpenAIRE

De Oliveira, Felipe; Marroig, Gabriel; Garcia, Guilherme

2016-01-01

Phenotypic traits evolve in a coordinated manner due to developmental and functional interactions, mediated by the dynamics of natural selection; the dependence between traits arising from these three factors is captured by genetic ( G ) and phenotypic ( P ) covariance matrices. Mammalian skull development produces an intricate pattern of tissue organization and mutual signaling that integrates this structure, although the set of functions it performs is quite disparate. Therefore, the interp...
Structural Covariance of Sensory Networks, the Cerebellum, and Amygdala in Autism Spectrum Disorder

Directory of Open Access Journals (Sweden)

Garrett J. Cardon

2017-11-01

Full Text Available Sensory dysfunction is a core symptom of autism spectrum disorder (ASD, and abnormalities with sensory responsivity and processing can be extremely debilitating to ASD patients and their families. However, relatively little is known about the underlying neuroanatomical and neurophysiological factors that lead to sensory abnormalities in ASD. Investigation into these aspects of ASD could lead to significant advancements in our general knowledge about ASD, as well as provide targets for treatment and inform diagnostic procedures. Thus, the current study aimed to measure the covariation of volumes of brain structures (i.e., structural magnetic resonance imaging that may be involved in abnormal sensory processing, in order to infer connectivity of these brain regions. Specifically, we quantified the structural covariation of sensory-related cerebral cortical structures, in addition to the cerebellum and amygdala by computing partial correlations between the structural volumes of these structures. These analyses were performed in participants with ASD (n = 36, as well as typically developing peers (n = 32. Results showed decreased structural covariation between sensory-related cortical structures, especially between the left and right cerebral hemispheres, in participants with ASD. In contrast, these same participants presented with increased structural covariation of structures in the right cerebral hemisphere. Additionally, sensory-related cerebral structures exhibited decreased structural covariation with functionally identified cerebellar networks. Also, the left amygdala showed significantly increased structural covariation with cerebral structures related to visual processing. Taken together, these results may suggest several patterns of altered connectivity both within and between cerebral cortices and other brain structures that may be related to sensory processing.
Covariance Bell inequalities

Science.gov (United States)

Pozsgay, Victor; Hirsch, Flavien; Branciard, Cyril; Brunner, Nicolas

2017-12-01

We introduce Bell inequalities based on covariance, one of the most common measures of correlation. Explicit examples are discussed, and violations in quantum theory are demonstrated. A crucial feature of these covariance Bell inequalities is their nonlinearity; this has nontrivial consequences for the derivation of their local bound, which is not reached by deterministic local correlations. For our simplest inequality, we derive analytically tight bounds for both local and quantum correlations. An interesting application of covariance Bell inequalities is that they can act as "shared randomness witnesses": specifically, the value of the Bell expression gives device-independent lower bounds on both the dimension and the entropy of the shared random variable in a local model.
Distance covariance for stochastic processes

DEFF Research Database (Denmark)

Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady

2017-01-01

The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...
Covariance Manipulation for Conjunction Assessment

Science.gov (United States)

Hejduk, M. D.

2016-01-01

The manipulation of space object covariances to try to provide additional or improved information to conjunction risk assessment is not an uncommon practice. Types of manipulation include fabricating a covariance when it is missing or unreliable to force the probability of collision (Pc) to a maximum value ('PcMax'), scaling a covariance to try to improve its realism or see the effect of covariance volatility on the calculated Pc, and constructing the equivalent of an epoch covariance at a convenient future point in the event ('covariance forecasting'). In bringing these methods to bear for Conjunction Assessment (CA) operations, however, some do not remain fully consistent with best practices for conducting risk management, some seem to be of relatively low utility, and some require additional information before they can contribute fully to risk analysis. This study describes some basic principles of modern risk management (following the Kaplan construct) and then examines the PcMax and covariance forecasting paradigms for alignment with these principles; it then further examines the expected utility of these methods in the modern CA framework. Both paradigms are found to be not without utility, but only in situations that are somewhat carefully circumscribed.
Estimation of genetic parameters for test day records of dairy traits in the first three lactations

Directory of Open Access Journals (Sweden)

Ducrocq Vincent

2005-05-01

Full Text Available Abstract Application of test-day models for the genetic evaluation of dairy populations requires the solution of large mixed model equations. The size of the (covariance matrices required with such models can be reduced through the use of its first eigenvectors. Here, the first two eigenvectors of (covariance matrices estimated for dairy traits in first lactation were used as covariables to jointly estimate genetic parameters of the first three lactations. These eigenvectors appear to be similar across traits and have a biological interpretation, one being related to the level of production and the other to persistency. Furthermore, they explain more than 95% of the total genetic variation. Variances and heritabilities obtained with this model were consistent with previous studies. High correlations were found among production levels in different lactations. Persistency measures were less correlated. Genetic correlations between second and third lactations were close to one, indicating that these can be considered as the same trait. Genetic correlations within lactation were high except between extreme parts of the lactation. This study shows that the use of eigenvectors can reduce the rank of (covariance matrices for the test-day model and can provide consistent genetic parameters.
Disruption of structural covariance networks for language in autism is modulated by verbal ability.

Science.gov (United States)

Sharda, Megha; Khundrakpam, Budhachandra S; Evans, Alan C; Singh, Nandini C

2016-03-01

The presence of widespread speech and language deficits is a core feature of autism spectrum disorders (ASD). These impairments have often been attributed to altered connections between brain regions. Recent developments in anatomical correlation-based approaches to map structural covariance offer an effective way of studying such connections in vivo. In this study, we employed such a structural covariance network (SCN)-based approach to investigate the integrity of anatomical networks in fronto-temporal brain regions of twenty children with ASD compared to an age and gender-matched control group of twenty-two children. Our findings reflected large-scale disruption of inter and intrahemispheric covariance in left frontal SCNs in the ASD group compared to controls, but no differences in right fronto-temporal SCNs. Interhemispheric covariance in left-seeded networks was further found to be modulated by verbal ability of the participants irrespective of autism diagnosis, suggesting that language function might be related to the strength of interhemispheric structural covariance between frontal regions. Additionally, regional cortical thickening was observed in right frontal and left posterior regions, which was predicted by decreasing symptom severity and increasing verbal ability in ASD. These findings unify reports of regional differences in cortical morphology in ASD. They also suggest that reduced left hemisphere asymmetry and increased frontal growth may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.
Genetics of human body size and shape: pleiotropic and independent genetic determinants of adiposity.

Science.gov (United States)

Livshits, G; Yakovenko, K; Ginsburg, E; Kobyliansky, E

1998-01-01

The present study utilized pedigree data from three ethnically different populations of Kirghizstan, Turkmenia and Chuvasha. Principal component analysis was performed on a matrix of genetic correlations between 22 measures of adiposity, including skinfolds, circumferences and indices. Findings are summarized as follows: (1) All three genetic matrices were not positive definite and the first four factors retained even after exclusion RG > or = 1.0, explained from 88% to 97% of the total additive genetic variation in the 22 trials studied. This clearly emphasizes the massive involvement of pleiotropic gene effects in the variability of adiposity traits. (2) Despite the quite natural differences in pairwise correlations between the adiposity traits in the three ethnically different samples under study, factor analysis revealed a common basic pattern of covariability for the adiposity traits. In each of the three samples, four genetic factors were retained, namely, the amount of subcutaneous fat, the total body obesity, the pattern of distribution of subcutaneous fat and the central adiposity distribution. (3) Genetic correlations between the retained four factors were virtually non-existent, suggesting that several independent genetic sources may be governing the variation of adiposity traits. (4) Variance decomposition analysis on the obtained genetic factors leaves no doubt regarding the substantial familial and (most probably genetic) effects on variation of each factor in each studied population. The similarity of results in the three different samples indicates that the findings may be deemed valid and reliable descriptions of the genetic variation and covariation pattern of adiposity traits in the human species.
Pedigree-based estimation of covariance between dominance deviations and additive genetic effects in closed rabbit lines considering inbreeding and using a computationally simpler equivalent model.

Science.gov (United States)

Fernández, E N; Legarra, A; Martínez, R; Sánchez, J P; Baselga, M

2017-06-01

Inbreeding generates covariances between additive and dominance effects (breeding values and dominance deviations). In this work, we developed and applied models for estimation of dominance and additive genetic variances and their covariance, a model that we call "full dominance," from pedigree and phenotypic data. Estimates with this model such as presented here are very scarce both in livestock and in wild genetics. First, we estimated pedigree-based condensed probabilities of identity using recursion. Second, we developed an equivalent linear model in which variance components can be estimated using closed-form algorithms such as REML or Gibbs sampling and existing software. Third, we present a new method to refer the estimated variance components to meaningful parameters in a particular population, i.e., final partially inbred generations as opposed to outbred base populations. We applied these developments to three closed rabbit lines (A, V and H) selected for number of weaned at the Polytechnic University of Valencia. Pedigree and phenotypes are complete and span 43, 39 and 14 generations, respectively. Estimates of broad-sense heritability are 0.07, 0.07 and 0.05 at the base versus 0.07, 0.07 and 0.09 in the final generations. Narrow-sense heritability estimates are 0.06, 0.06 and 0.02 at the base versus 0.04, 0.04 and 0.01 at the final generations. There is also a reduction in the genotypic variance due to the negative additive-dominance correlation. Thus, the contribution of dominance variation is fairly large and increases with inbreeding and (over)compensates for the loss in additive variation. In addition, estimates of the additive-dominance correlation are -0.37, -0.31 and 0.00, in agreement with the few published estimates and theoretical considerations. © 2017 Blackwell Verlag GmbH.
Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

Science.gov (United States)

Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P

2018-05-18

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the
Efeito da inclusão da covariância genética aditiva direta-materna no modelo de análise sobre a magnitude das estimativas de parâmetros e valores genéticos preditos para ganho de peso na raça Brangus Effect of genetic direct-maternal covariance inclusion in the model of analizys on the estimate of parameters and predicted genetic values for weight gain in Brangus breed

Directory of Open Access Journals (Sweden)

Luiz Felipe Waihrich Guterres

2007-06-01

this research was to study the effect of accouting for the covariance between the additive genetic direct and the maternal effects (covd-m on the estimates of genetic parameters and on predictions of genetic values (VG, for average daily gain from birth to weaning (GMDND and from weaning to 550 days of age (GMDDS. They were analyzed 28,949 records for GMDND and 11,884 for GMDDS of a Brangus breed population (58 Angus x 3/8 Nellore, collected from 1986 to 2002. The (covariance components were obtained by REML. In the animal model for GMDND, the additive genetic direct and maternal and residual effects were considered as random, and the effects of contemporaneous group at weaning (Gc²05, the interaction of the Nellore-Angus breed genetic percentage of the bull and cow (FGNA and the covariables, age of the cow at birth (IV and age at weaning (ID as fixed effects. For GMDDS, the model was the same, except that Gc²05 was substituted by contemporaneous group at 550 days of age (CG550 and ID by age at 550 days. In both models, permanent environmental effect of the cow was considered as a random effect. The heritabilities estimated for direct genetic effects ranged from 0.14 ± 0.03 to 0.21 ± 0.03 and for maternal effects from 0.00 ± 0.01 to 0.15 ± 0.02, the estimates had smaller values when covd-m was included in the model for GMDND. The correlations between genetic direct and maternal effects were negative -0.25 ± 0.12 (GMDND and -0.77 ± 0.19 (GMDDS. The likelihood ratio test showed that there is no significant diference, at 5% significance level, between the adopted models for boths characteristics. The rank correlation between the VG predicted by the two models, were 0.89 for GMDND and 0.98 for GMDND, suggesting that a slight change in the rank of the animals can happen, for GMDND.
Assessing fluctuating evolutionary pressure in yeast and mammal evolutionary rate covariation using bioinformatics of meiotic protein genetic sequences

Science.gov (United States)

Dehipawala, Sunil; Nguyen, A.; Tremberger, G.; Cheung, E.; Holden, T.; Lieberman, D.; Cheung, T.

2013-09-01

The evolutionary rate co-variation in meiotic proteins has been reported for yeast and mammal using phylogenic branch lengths which assess retention, duplication and mutation. The bioinformatics of the corresponding DNA sequences could be classified as a diagram of fractal dimension and Shannon entropy. Results from biomedical gene research provide examples on the diagram methodology. The identification of adaptive selection using entropy marker and functional-structural diversity using fractal dimension would support a regression analysis where the coefficient of determination would serve as evolutionary pathway marker for DNA sequences and be an important component in the astrobiology community. Comparisons between biomedical genes such as EEF2 (elongation factor 2 human, mouse, etc), WDR85 in epigenetics, HAR1 in human specificity, clinical trial targeted cancer gene CD47, SIRT6 in spermatogenesis, and HLA-C in mosquito bite immunology demonstrate the diagram classification methodology. Comparisons to the SEPT4-XIAP pair in stem cell apoptosis, testesexpressed taste genes TAS1R3-GNAT3 pair, and amyloid beta APLP1-APLP2 pair with the yeast-mammal DNA sequences for meiotic proteins RAD50-MRE11 pair and NCAPD2-ICK pair have accounted for the observed fluctuating evolutionary pressure systematically. Regression with high R-sq values or a triangular-like cluster pattern for concordant pairs in co-variation among the studied species could serve as evidences for the possible location of common ancestors in the entropy-fractal dimension diagram, consistent with an example of the human-chimp common ancestor study using the FOXP2 regulated genes reported in human fetal brain study. The Deinococcus radiodurans R1 Rad-A could be viewed as an outlier in the RAD50 diagram and also in the free energy versus fractal dimension regression Cook's distance, consistent with a non-Earth source for this radiation resistant bacterium. Convergent and divergent fluctuating evolutionary
A multivariate analysis of genetic variation in the advertisement call of the gray treefrog, Hyla versicolor.

Science.gov (United States)

Welch, Allison M; Smith, Michael J; Gerhardt, H Carl

2014-06-01

Genetic variation in sexual displays is crucial for an evolutionary response to sexual selection, but can be eroded by strong selection. Identifying the magnitude and sources of additive genetic variance underlying sexually selected traits is thus an important issue in evolutionary biology. We conducted a quantitative genetics experiment with gray treefrogs (Hyla versicolor) to investigate genetic variances and covariances among features of the male advertisement call. Two energetically expensive traits showed significant genetic variation: call duration, expressed as number of pulses per call, and call rate, represented by its inverse, call period. These two properties also showed significant genetic covariance, consistent with an energetic constraint to call production. Combining the genetic variance-covariance matrix with previous estimates of directional sexual selection imposed by female preferences predicts a limited increase in call duration but no change in call rate despite significant selection on both traits. In addition to constraints imposed by the genetic covariance structure, an evolutionary response to sexual selection may also be limited by high energetic costs of long-duration calls and by preferences that act most strongly against very short-duration calls. Meanwhile, the persistence of these preferences could be explained by costs of mating with males with especially unattractive calls. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
Poincare covariance and κ-Minkowski spacetime

International Nuclear Information System (INIS)

Dabrowski, Ludwik; Piacitelli, Gherardo

2011-01-01

A fully Poincare covariant model is constructed as an extension of the κ-Minkowski spacetime. Covariance is implemented by a unitary representation of the Poincare group, and thus complies with the original Wigner approach to quantum symmetries. This provides yet another example (besides the DFR model), where Poincare covariance is realised a la Wigner in the presence of two characteristic dimensionful parameters: the light speed and the Planck length. In other words, a Doubly Special Relativity (DSR) framework may well be realised without deforming the meaning of 'Poincare covariance'. -- Highlights: → We construct a 4d model of noncommuting coordinates (quantum spacetime). → The coordinates are fully covariant under the undeformed Poincare group. → Covariance a la Wigner holds in presence of two dimensionful parameters. → Hence we are not forced to deform covariance (e.g. as quantum groups). → The underlying κ-Minkowski model is unphysical; covariantisation does not cure this.
Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma.

Directory of Open Access Journals (Sweden)

Stine H Kresse

Full Text Available BACKGROUND: Osteosarcomas are the most common non-haematological primary malignant tumours of bone, and all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. PRINCIPAL FINDINGS: The cell lines showed complex patterns of DNA copy number changes, where genomic copy number gains were significantly associated with gene-rich regions and losses with gene-poor regions. By integrating the datasets, 350 genes were identified as having two types of aberrations (gain/over-expression, hypo-methylation/over-expression, loss/under-expression or hyper-methylation/under-expression using a recurrence threshold of 6/19 (>30% cell lines. The genes showed in general alterations in either DNA copy number or DNA methylation, both within individual samples and across the sample panel. These 350 genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. The aberrations of three selected genes, CXCL5, DLX5 and RUNX2, were validated in five cell lines and five tumour samples using PCR techniques. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2'-deoxycytidine treatment for four genes tested; AKAP12, CXCL5, EFEMP1 and IL11RA. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for detrimental genes. CONCLUSIONS: Integrative analysis of genome-wide genetic and epigenetic alterations identified dependencies and relationships between
Modeling Covariance Breakdowns in Multivariate GARCH

OpenAIRE

Jin, Xin; Maheu, John M

2014-01-01

This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation of the conditional covariance matrix from its implied MGARCH dynamics. This is captured through a flexible stochastic component that allows for changes in the conditional variances, covariances and impl...
Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

OpenAIRE

Ole E. Barndorff-Nielsen; Neil Shephard

2002-01-01

This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

ISSUES IN NEUTRON CROSS SECTION COVARIANCES

Energy Technology Data Exchange (ETDEWEB)

Mattoon, C.M.; Oblozinsky,P.

2010-04-30

We review neutron cross section covariances in both the resonance and fast neutron regions with the goal to identify existing issues in evaluation methods and their impact on covariances. We also outline ideas for suitable covariance quality assurance procedures.We show that the topic of covariance data remains controversial, the evaluation methodologies are not fully established and covariances produced by different approaches have unacceptable spread. The main controversy is in very low uncertainties generated by rigorous evaluation methods and much larger uncertainties based on simple estimates from experimental data. Since the evaluators tend to trust the former, while the users tend to trust the latter, this controversy has considerable practical implications. Dedicated effort is needed to arrive at covariance evaluation methods that would resolve this issue and produce results accepted internationally both by evaluators and users.
Distinct genetic alteration profiles of acute myeloid leukemia between Caucasian and Eastern Asian population.

Science.gov (United States)

Wei, Hui; Wang, Ying; Zhou, Chunlin; Lin, Dong; Liu, Bingcheng; Liu, Kaiqi; Qiu, Shaowei; Gong, Benfa; Li, Yan; Zhang, Guangji; Wei, Shuning; Gong, Xiaoyuan; Liu, Yuntao; Zhao, Xingli; Gu, Runxia; Mi, Yingchang; Wang, Jianxiang

2018-02-10

Racial and ethnic disparities in malignancies attract extensive attention. To investigate whether there are racial and ethnic disparities in genetic alteration between Caucasian and Eastern Asian population, data from several prospective AML trials were retrospectively analyzed in this study. We found that there were more patients with core binding factor (CBF) leukemia in Eastern Asian cohorts and there were different CBF leukemia constitutions between them. The ratios of CBF leukemia are 27.7, 22.1, 21.1, and 23.4%, respectively, in our (ChiCTR-TRC-10001202), another Chinese, Korean, and Japanese Eastern Asian cohorts, which are significantly higher than those in ECOG1900, MRC AML15, UK NCRI AML17, HOVON/SAKK AML-42, and German AML2003 (15.5, 12.5, 9.3, 10.2, and 12%, respectively). And CBFbeta-MYH11 occurred more prevalently in HOVON/SAKK AML- 42 and ECOG1900 trials (50.0 and 54.3% of CBF leukemia, respectively) than in Chinese and Japanese trials (20.1 and 20.8%, respectively). The proportion of FLT3-ITD mutation is 11.2% in our cohort, which is lower than that in MRC AML15 and UK NCRI AML17 (24.6 and 17.9%, respectively). Even after excluding the age bias, there are still different incidence rates of mutation between Caucasian and Eastern Asian population. These data suggest that there are racial and ethnic disparities in genetic alteration between Caucasian and Eastern Asian population.
Early selection in open-pollinated Eucalyptus families based on competition covariates

Directory of Open Access Journals (Sweden)

Bruno Ettore Pavan

2014-06-01

Full Text Available The objetive of this work was to evaluate the influence of intergenotypic competition in open-pollinated families of Eucalyptus and its effects on early selection efficiency. Two experiments were carried out, in which the timber volume was evaluated at three ages, in a randomized complete block design. Data from the three years of evaluation (experiment 1, at 2, 4, and 7 years; and experiment 2, at 2, 5, and 7 years were analyzed using mixed models. The following were estimated: variance components, genetic parameters, selection gains, effective number, early selection efficiency, selection gain per unit time, and coincidence of selection with and without the use of competition covariates. Competition effect was nonsignificant for ages under three years, and adjustment using competition covariates was unnecessary. Early selection for families is effective; families that have a late growth spurt are more vulnerable to competition, which markedly impairs ranking at the end of the cycle. Early selection is efficient according to all adopted criteria, and the age of around three years is the most recommended, given the high efficiency and accuracy rate in the indication of trees and families. The addition of competition covariates at the end of the cycle improves early selection efficiency for almost all studied criteria.
A novel nuclear genetic code alteration in yeasts and the evolution of codon reassignment in eukaryotes.

Science.gov (United States)

Mühlhausen, Stefanie; Findeisen, Peggy; Plessmann, Uwe; Urlaub, Henning; Kollmar, Martin

2016-07-01

The genetic code is the cellular translation table for the conversion of nucleotide sequences into amino acid sequences. Changes to the meaning of sense codons would introduce errors into almost every translated message and are expected to be highly detrimental. However, reassignment of single or multiple codons in mitochondria and nuclear genomes, although extremely rare, demonstrates that the code can evolve. Several models for the mechanism of alteration of nuclear genetic codes have been proposed (including "codon capture," "genome streamlining," and "ambiguous intermediate" theories), but with little resolution. Here, we report a novel sense codon reassignment in Pachysolen tannophilus, a yeast related to the Pichiaceae. By generating proteomics data and using tRNA sequence comparisons, we show that Pachysolen translates CUG codons as alanine and not as the more usual leucine. The Pachysolen tRNACAG is an anticodon-mutated tRNA(Ala) containing all major alanine tRNA recognition sites. The polyphyly of the CUG-decoding tRNAs in yeasts is best explained by a tRNA loss driven codon reassignment mechanism. Loss of the CUG-tRNA in the ancient yeast is followed by gradual decrease of respective codons and subsequent codon capture by tRNAs whose anticodon is not part of the aminoacyl-tRNA synthetase recognition region. Our hypothesis applies to all nuclear genetic code alterations and provides several testable predictions. We anticipate more codon reassignments to be uncovered in existing and upcoming genome projects. © 2016 Mühlhausen et al.; Published by Cold Spring Harbor Laboratory Press.
Structure and stability of genetic variance-covariance matrices: A Bayesian sparse factor analysis of transcriptional variation in the three-spined stickleback.

Science.gov (United States)

Siren, J; Ovaskainen, O; Merilä, J

2017-10-01

The genetic variance-covariance matrix (G) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G-matrices is limited for two reasons. First, phenotypes are high-dimensional, whereas traditional statistical methods are tuned to estimate and analyse low-dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high-dimensional G-matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half-sib breeding design of three-spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low-temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability-as well as the similarity among G-matrices-may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G-matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G, they also illustrate that by enabling the estimation of large G-matrices, the BSFG method can improve predicted evolutionary responses to selection. © 2017 John Wiley & Sons Ltd.
Implications of Genetic and Epigenetic Alterations of CDKN2A (p16INK4a in Cancer

Directory of Open Access Journals (Sweden)

Ran Zhao

2016-06-01

Full Text Available Aberrant gene silencing is highly associated with altered cell cycle regulation during carcinogenesis. In particular, silencing of the CDKN2A tumor suppressor gene, which encodes the p16INK4a protein, has a causal link with several different types of cancers. The p16INK4a protein plays an executional role in cell cycle and senescence through the regulation of the cyclin-dependent kinase (CDK 4/6 and cyclin D complexes. Several genetic and epigenetic aberrations of CDKN2A lead to enhanced tumorigenesis and metastasis with recurrence of cancer and poor prognosis. In these cases, the restoration of genetic and epigenetic reactivation of CDKN2A is a practical approach for the prevention and therapy of cancer. This review highlights the genetic status of CDKN2A as a prognostic and predictive biomarker in various cancers.
Covariance Partition Priors: A Bayesian Approach to Simultaneous Covariance Estimation for Longitudinal Data.

Science.gov (United States)

Gaskins, J T; Daniels, M J

2016-01-02

The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.
Covariant diagrams for one-loop matching

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhengkang [Michigan Center for Theoretical Physics (MCTP), University of Michigan,450 Church Street, Ann Arbor, MI 48109 (United States); Deutsches Elektronen-Synchrotron (DESY),Notkestraße 85, 22607 Hamburg (Germany)

2017-05-30

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching

International Nuclear Information System (INIS)

Zhang, Zhengkang

2017-01-01

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Genetic Variation in Choline-Metabolizing Enzymes Alters Choline Metabolism in Young Women Consuming Choline Intakes Meeting Current Recommendations

Directory of Open Access Journals (Sweden)

Ariel B. Ganz

2017-01-01

Full Text Available Single nucleotide polymorphisms (SNPs in choline metabolizing genes are associated with disease risk and greater susceptibility to organ dysfunction under conditions of dietary choline restriction. However, the underlying metabolic signatures of these variants are not well characterized and it is unknown whether genotypic differences persist at recommended choline intakes. Thus, we sought to determine if common genetic risk factors alter choline dynamics in pregnant, lactating, and non-pregnant women consuming choline intakes meeting and exceeding current recommendations. Women (n = 75 consumed 480 or 930 mg choline/day (22% as a metabolic tracer, choline-d9 for 10–12 weeks in a controlled feeding study. Genotyping was performed for eight variant SNPs and genetic differences in metabolic flux and partitioning of plasma choline metabolites were evaluated using stable isotope methodology. CHKA rs10791957, CHDH rs9001, CHDH rs12676, PEMT rs4646343, PEMT rs7946, FMO3 rs2266782, SLC44A1 rs7873937, and SLC44A1 rs3199966 altered the use of choline as a methyl donor; CHDH rs9001 and BHMT rs3733890 altered the partitioning of dietary choline between betaine and phosphatidylcholine synthesis via the cytidine diphosphate (CDP-choline pathway; and CHKA rs10791957, CHDH rs12676, PEMT rs4646343, PEMT rs7946 and SLC44A1 rs7873937 altered the distribution of dietary choline between the CDP-choline and phosphatidylethanolamine N-methyltransferase (PEMT denovo pathway. Such metabolic differences may contribute to disease pathogenesis and prognosis over the long-term.
Fast Computing for Distance Covariance

OpenAIRE

Huo, Xiaoming; Szekely, Gabor J.

2014-01-01

Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly accordingly to its definition then its computational complexity is O($n^2$) which is a disadvantage compared to other faster methods. In this paper we show that the computation of distance covariance and distance correlation of real valued random variables can be...
On estimating cosmology-dependent covariance matrices

International Nuclear Information System (INIS)

Morrison, Christopher B.; Schneider, Michael D.

2013-01-01

We describe a statistical model to estimate the covariance matrix of matter tracer two-point correlation functions with cosmological simulations. Assuming a fixed number of cosmological simulation runs, we describe how to build a 'statistical emulator' of the two-point function covariance over a specified range of input cosmological parameters. Because the simulation runs with different cosmological models help to constrain the form of the covariance, we predict that the cosmology-dependent covariance may be estimated with a comparable number of simulations as would be needed to estimate the covariance for fixed cosmology. Our framework is a necessary first step in planning a simulations campaign for analyzing the next generation of cosmological surveys
Overlapping genetic and environmental influences among men's alcohol consumption and problems, romantic quality and social support.

Science.gov (United States)

Salvatore, J E; Prom-Wormley, E; Prescott, C A; Kendler, K S

2015-08-01

Alcohol consumption and problems are associated with interpersonal difficulties. We used a twin design to assess in men the degree to which genetic or environmental influences contributed to the covariance between alcohol consumption and problems, romantic quality and social support. The sample included adult male-male twin pairs (697 monozygotic and 487 dizygotic) for whom there were interview-based data on: alcohol consumption (average monthly alcohol consumption in the past year); alcohol problems (lifetime alcohol dependence symptoms); romantic conflict and warmth; friend problems and support; and relative problems and support. Key findings were that genetic and unique environmental factors contributed to the covariance between alcohol consumption and romantic conflict; genetic factors contributed to the covariance between alcohol problems and romantic conflict; and common and unique environmental factors contributed to the covariance between alcohol problems and friend problems. Recognizing and addressing the overlapping genetic and environmental influences that alcohol consumption and problems share with romantic quality and other indicators of social support may have implications for substance use prevention and intervention efforts.
ERRORJ. Covariance processing code. Version 2.2

International Nuclear Information System (INIS)

Chiba, Go

2004-07-01

ERRORJ is the covariance processing code that can produce covariance data of multi-group cross sections, which are essential for uncertainty analyses of nuclear parameters, such as neutron multiplication factor. The ERRORJ code can process the covariance data of cross sections including resonance parameters, angular and energy distributions of secondary neutrons. Those covariance data cannot be processed by the other covariance processing codes. ERRORJ has been modified and the version 2.2 has been developed. This document describes the modifications and how to use. The main topics of the modifications are as follows. Non-diagonal elements of covariance matrices are calculated in the resonance energy region. Option for high-speed calculation is implemented. Perturbation amount is optimized in a sensitivity calculation. Effect of the resonance self-shielding on covariance of multi-group cross section can be considered. It is possible to read a compact covariance format proposed by N.M. Larson. (author)
Covariance matrix estimation for stationary time series

OpenAIRE

Xiao, Han; Wu, Wei Biao

2011-01-01

We obtain a sharp convergence rate for banded covariance matrix estimates of stationary processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices. We also consider a thresholded covariance matrix estimator that can better characterize sparsity if the true covariance matrix is sparse. As our main tool, we implement Toeplitz [Math. Ann. 70 (1911) 351–376] idea and relate eigenvalues of covariance matrices to the spectral densities or Fourier transforms...
General Galilei Covariant Gaussian Maps

Science.gov (United States)

Gasbarri, Giulio; Toroš, Marko; Bassi, Angelo

2017-09-01

We characterize general non-Markovian Gaussian maps which are covariant under Galilean transformations. In particular, we consider translational and Galilean covariant maps and show that they reduce to the known Holevo result in the Markovian limit. We apply the results to discuss measures of macroscopicity based on classicalization maps, specifically addressing dissipation, Galilean covariance and non-Markovianity. We further suggest a possible generalization of the macroscopicity measure defined by Nimmrichter and Hornberger [Phys. Rev. Lett. 110, 16 (2013)].
Direct and maternal genetic effects for birth weight in dorper and ...

African Journals Online (AJOL)

Variance components for birth (BWT) in Dorper and Mutton Merino sheep were estimated by Average Information Restricted Maximum Likelihood (AIREML). Animal model was fitted allowing for genetic maternal effects and a genetic covariance between direct and maternal effects. Estimates of heritability for direct genetic ...
Genetic Parameters of Common Wheat in Nepal

OpenAIRE

Bal Krishna Joshi; Dhruba Bahadur Thapa; Madan Raj Bhatta

2015-01-01

Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correla...
Epigenetic Alterations in Alzheimer's Disease

Directory of Open Access Journals (Sweden)

Johannes eGräff

2015-12-01

Full Text Available Alzheimer’s disease (AD is the major cause of dementia in Western societies. It progresses asymptomatically during decades before being belatedly diagnosed when therapeutic strategies have become unviable. Although several genetic alterations have been associated with AD, the vast majority of AD cases do not show strong genetic underpinnings and are thus considered a consequence of non-genetic factors. Epigenetic mechanisms allow for the integration of long-lasting non-genetic inputs on specific genetic backgrounds, and recently, a growing number of epigenetic alterations in AD have been described. For instance, an accumulation of dysregulated epigenetic mechanisms in aging, the predominant risk factor of AD, might facilitate the onset of the disease. Likewise, mutations in several enzymes of the epigenetic machinery have been associated with neurodegenerative processes that are altered in AD such as impaired learning and memory formation. Genome-wide and locus-specific epigenetic alterations have also been reported, and several epigenetically dysregulated genes validated by independent groups. From these studies, a picture emerges of AD as being associated with DNA hypermethylation and histone deacetylation, suggesting a general repressed chromatin state and epigenetically reduced plasticity in AD. Here we review these recent findings and discuss several technical and methodological considerations that are imperative for their correct interpretation. We also pay particular focus on potential implementations and theoretical frameworks that we expect will help to better direct future studies aimed to unravel the epigenetic participation in AD.
Epigenetic Alterations in Alzheimer's Disease.

Science.gov (United States)

Sanchez-Mut, Jose V; Gräff, Johannes

2015-01-01

Alzheimer's disease (AD) is the major cause of dementia in Western societies. It progresses asymptomatically during decades before being belatedly diagnosed when therapeutic strategies have become unviable. Although several genetic alterations have been associated with AD, the vast majority of AD cases do not show strong genetic underpinnings and are thus considered a consequence of non-genetic factors. Epigenetic mechanisms allow for the integration of long-lasting non-genetic inputs on specific genetic backgrounds, and recently, a growing number of epigenetic alterations in AD have been described. For instance, an accumulation of dysregulated epigenetic mechanisms in aging, the predominant risk factor of AD, might facilitate the onset of the disease. Likewise, mutations in several enzymes of the epigenetic machinery have been associated with neurodegenerative processes that are altered in AD such as impaired learning and memory formation. Genome-wide and locus-specific epigenetic alterations have also been reported, and several epigenetically dysregulated genes validated by independent groups. From these studies, a picture emerges of AD as being associated with DNA hypermethylation and histone deacetylation, suggesting a general repressed chromatin state and epigenetically reduced plasticity in AD. Here we review these recent findings and discuss several technical and methodological considerations that are imperative for their correct interpretation. We also pay particular focus on potential implementations and theoretical frameworks that we expect will help to better direct future studies aimed to unravel the epigenetic participation in AD.

Genetic Alterations in Pesticide Exposed Bolivian Farmers

DEFF Research Database (Denmark)

Jørs, Erik; González, Ana Rosa; Ascarrunz, Maria Eugenia

2007-01-01

: Questionnaires were applied and blood tests taken from 81 volunteers from La Paz County, of whom 48 were pesticide exposed farmers and 33 non-exposed controls. Sixty males and 21 females participated with a mean age of 37.3 years (range 17-76). Data of exposure and possible genetic damage were collected...... and evaluated by well known statistical methods, controlling for relevant confounders. To measure genetic damage chromosomal aberrations and the comet assay analysis were performed. Results: Pesticide exposed farmers had a higher degree of genetic damage compared to the control group. The number of chromosomal......, probably related to exposure to pesticides. Due to the potentially negative long term health effects of genetic damage on reproduction and the development of cancer, preventive measures are recommended. Effective control with imports and sales, banning of the most toxic pesticides, education...
Competing risks and time-dependent covariates

DEFF Research Database (Denmark)

Cortese, Giuliana; Andersen, Per K

2010-01-01

Time-dependent covariates are frequently encountered in regression analysis for event history data and competing risks. They are often essential predictors, which cannot be substituted by time-fixed covariates. This study briefly recalls the different types of time-dependent covariates......, as classified by Kalbfleisch and Prentice [The Statistical Analysis of Failure Time Data, Wiley, New York, 2002] with the intent of clarifying their role and emphasizing the limitations in standard survival models and in the competing risks setting. If random (internal) time-dependent covariates...
Activities of covariance utilization working group

International Nuclear Information System (INIS)

Tsujimoto, Kazufumi

2013-01-01

During the past decade, there has been a interest in the calculational uncertainties induced by nuclear data uncertainties in the neutronics design of advanced nuclear system. The covariance nuclear data is absolutely essential for the uncertainty analysis. In the latest version of JENDL, JENDL-4.0, the covariance data for many nuclides, especially actinide nuclides, was substantialy enhanced. The growing interest in the uncertainty analysis and the covariance data has led to the organisation of the working group for covariance utilization under the JENDL committee. (author)
The genetic analysis of repeated measures II: The Karhunen-Loeve expansion.

NARCIS (Netherlands)

Molenaar, P.C.M.; Boomsma, D.I.

1987-01-01

Outlines the Karhunen-Loeve (N. Ahmed and K. R. Rao, 1975) approach to the genetic analysis of time series of arbitrary length and with arbitrary covariance function. This approach is based on the simultaneous eigenvalue decomposition of the covariance matrices of the original time series obtained
Quality Quantification of Evaluated Cross Section Covariances

International Nuclear Information System (INIS)

Varet, S.; Dossantos-Uzarralde, P.; Vayatis, N.

2015-01-01

Presently, several methods are used to estimate the covariance matrix of evaluated nuclear cross sections. Because the resulting covariance matrices can be different according to the method used and according to the assumptions of the method, we propose a general and objective approach to quantify the quality of the covariance estimation for evaluated cross sections. The first step consists in defining an objective criterion. The second step is computation of the criterion. In this paper the Kullback-Leibler distance is proposed for the quality quantification of a covariance matrix estimation and its inverse. It is based on the distance to the true covariance matrix. A method based on the bootstrap is presented for the estimation of this criterion, which can be applied with most methods for covariance matrix estimation and without the knowledge of the true covariance matrix. The full approach is illustrated on the 85 Rb nucleus evaluations and the results are then used for a discussion on scoring and Monte Carlo approaches for covariance matrix estimation of the cross section evaluations
Improvement of covariance data for fast reactors

International Nuclear Information System (INIS)

Shibata, Keiichi; Hasegawa, Akira

2000-02-01

We estimated covariances of the JENDL-3.2 data on the nuclides and reactions needed to analyze fast-reactor cores for the past three years, and produced covariance files. The present work was undertaken to re-examine the covariance files and to make some improvements. The covariances improved are the ones for the inelastic scattering cross section of 16 O, the total cross section of 23 Na, the fission cross section of 235 U, the capture cross section of 238 U, and the resolved resonance parameters for 238 U. Moreover, the covariances of 233 U data were newly estimated by the present work. The covariances obtained were compiled in the ENDF-6 format. (author)
Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations: insulin/TOR and associated phenotypes in Drosophila melanogaster

Directory of Open Access Journals (Sweden)

Harshman Lawrence G

2009-03-01

Full Text Available Abstract Background A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.
Lorentz Covariance of Langevin Equation

International Nuclear Information System (INIS)

Koide, T.; Denicol, G.S.; Kodama, T.

2008-01-01

Relativistic covariance of a Langevin type equation is discussed. The requirement of Lorentz invariance generates an entanglement between the force and noise terms so that the noise itself should not be a covariant quantity. (author)
Genetic and environmental sources of covariation between early drinking and adult functioning.

Science.gov (United States)

Waldron, Jordan Sparks; Malone, Stephen M; McGue, Matt; Iacono, William G

2017-08-01

The vast majority of individuals initiate alcohol consumption for the first time in adolescence. Given the widespread nature of its use and evidence that adolescents may be especially vulnerable to its effects, there is concern about the long-term detrimental impact of adolescent drinking on adult functioning. While some researchers have suggested that genetic processes may confound the relationship, the mechanisms linking drinking and later adjustment remain unclear. The current study utilized a genetically informed sample and biometric modeling to examine the nature of the familial influences on this association and identify the potential for genetic confounding. The sample was drawn from the Minnesota Twin Family Study (MTFS), a longitudinal study consisting of 2,764 twins assessed in 2 cohorts at regular follow-ups from age 17 to age 29 (older cohort) or age 11 to age 29 (younger cohort). A broad range of adult measures was included assessing substance use, antisocial behavior, personality, socioeconomic status, and social functioning. A bivariate Cholesky decomposition was used to examine the common genetic and environmental influences on adolescent drinking and each of the measures of adult adjustment. The results revealed that genetic factors and nonshared environmental influences were generally most important in explaining the relationship between adolescent drinking and later functioning. While the presence of nonshared environmental influences on the association are not inconsistent with a causal impact of adolescent drinking, the findings suggest that many of the adjustment issues associated with adolescent alcohol consumption are best understood as genetically influenced vulnerabilities. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Gene-environment interaction and covariation in schizophrenia: the role of obstetric complications.

Science.gov (United States)

Mittal, Vijay A; Ellman, Lauren M; Cannon, Tyrone D

2008-11-01

While genetic factors account for a significant proportion of liability to schizophrenia, a body of evidence attests to a significant environmental contribution. Understanding the mechanisms through which genetic and environmental factors coalesce in influencing schizophrenia is critical for elucidating the pathways underlying psychotic illness and for developing primary prevention strategies. Although obstetric complications (OCs) remain among the most well-documented environmental indicators of risk for schizophrenia, the pathogenic role they play in the etiology of schizophrenia continues to remain poorly understood. A question of major importance is do these factors result from a genetic diathesis to schizophrenia (as in gene-environment covariation), act additively or interactively with predisposing genes for the disorder in influencing disease risk, or independently cause disease onset? In this review, we evaluate 3 classes of OCs commonly related to schizophrenia including hypoxia-associated OCs, maternal infection during pregnancy, and maternal stress during pregnancy. In addition, we discuss several mechanisms by which OCs impact on genetically susceptible brain regions, increasing constitutional vulnerability to neuromaturational events and stressors later in life (ie, adolescence), which may in turn contribute to triggering psychosis.
Introgression from cultivated rice alters genetic structures of wild relative populations: implications for in situ conservation

Science.gov (United States)

Jin, Xin; Chen, Yu; Liu, Ping; Li, Chen; Cai, Xingxing; Rong, Jun

2018-01-01

Abstract Maintaining genetic integrity is essential for in situ and ex situ conservation of crop wild relative (CWR) species. However, introgression of crop alleles into CWR species/populations may change their genetic structure and diversity, resulting in more invasive weeds or, in contrast, the extinction of endangered populations. To determine crop-wild introgression and its consequences, we examined the genetic structure and diversity of six wild rice (Oryza rufipogon) populations under in situ conservation in China. Thirty-four simple sequence repeat (SSR) and 34 insertion/deletion markers were used to genotype the wild rice populations and two sets of rice cultivars (O. sativa), corresponding to the two types of molecular markers. Shared alleles and STRUCTURE analyses suggested a variable level of crop-wild introgression and admixture. Principal coordinates and cluster analyses indicated differentiation of wild rice populations, which was associated with the spatial distances to cultivated rice fields. The level of overall genetic diversity was comparable between wild rice populations and rice cultivars, but a great number of wild-specific alleles was detected in the wild populations. We conclude based on the results that crop-wild introgression can considerably alter the pattern of genetic structure and relationships of CWR populations. Appropriate measures should be taken for effective in situ conservation of CWR species under the scenario of crop-wild introgression. PMID:29308123
Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2014-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...
Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2013-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...
Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

Science.gov (United States)

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.
Covariance descriptor fusion for target detection

Science.gov (United States)

Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

2016-05-01

Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.
Generalized Linear Covariance Analysis

Science.gov (United States)

Carpenter, James R.; Markley, F. Landis

2014-01-01

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
Econometric analysis of realized covariation: high frequency based covariance, regression, and correlation in financial economics

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2004-01-01

This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....
Covariant canonical quantization of fields and Bohmian mechanics

International Nuclear Information System (INIS)

Nikolic, H.

2005-01-01

We propose a manifestly covariant canonical method of field quantization based on the classical De Donder-Weyl covariant canonical formulation of field theory. Owing to covariance, the space and time arguments of fields are treated on an equal footing. To achieve both covariance and consistency with standard non-covariant canonical quantization of fields in Minkowski spacetime, it is necessary to adopt a covariant Bohmian formulation of quantum field theory. A preferred foliation of spacetime emerges dynamically owing to a purely quantum effect. The application to a simple time-reparametrization invariant system and quantum gravity is discussed and compared with the conventional non-covariant Wheeler-DeWitt approach. (orig.)
Genetic variance components for residual feed intake and feed ...

African Journals Online (AJOL)

Feeding costs of animals is a major determinant of profitability in livestock production enterprises. Genetic selection to improve feed efficiency aims to reduce feeding cost in beef cattle and thereby improve profitability. This study estimated genetic (co)variances between weaning weight and other production, reproduction ...
Proofs of Contracted Length Non-covariance

International Nuclear Information System (INIS)

Strel'tsov, V.N.

1994-01-01

Different proofs of contracted length non covariance are discussed. The way based on the establishment of interval inconstancy (dependence on velocity) seems to be the most convincing one. It is stressed that the known non covariance of the electromagnetic field energy and momentum of a moving charge ('the problem 4/3') is a direct consequence of contracted length non covariance. 8 refs

[Epigenetic alterations in acute lymphoblastic leukemia].

Science.gov (United States)

Navarrete-Meneses, María Del Pilar; Pérez-Vera, Patricia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. It is well-known that genetic alterations constitute the basis for the etiology of ALL. However, genetic abnormalities are not enough for the complete development of the disease, and additional alterations such as epigenetic modifications are required. Such alterations, like DNA methylation, histone modifications, and noncoding RNA regulation have been identified in ALL. DNA hypermethylation in promoter regions is one of the most frequent epigenetic modifications observed in ALL. This modification frequently leads to gene silencing in tumor suppressor genes, and in consequence, contributes to leukemogenesis. Alterations in histone remodeling proteins have also been detected in ALL, such as the overexpression of histone deacetylases enzymes, and alteration of acetyltransferases and methyltransferases. ALL also shows alteration in the expression of miRNAs, and in consequence, the modification in the expression of their target genes. All of these epigenetic modifications are key events in the malignant transformation since they lead to the deregulation of oncogenes as BLK, WNT5B and WISP1, and tumor suppressors such as FHIT, CDKN2A, CDKN2B, and TP53, which alter fundamental cellular processes and potentially lead to the development of ALL. Both genetic and epigenetic alterations contribute to the development and evolution of ALL. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.
Covariate analysis of bivariate survival data

Energy Technology Data Exchange (ETDEWEB)

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Covariant diagrams for one-loop matching

International Nuclear Information System (INIS)

Zhang, Zhengkang

2016-10-01

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2016-10-15

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariance and sensitivity data generation at ORNL

International Nuclear Information System (INIS)

Leal, L. C.; Derrien, H.; Larson, N. M.; Alpan, A.

2005-01-01

Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. In this paper we address the generation of covariance data in the resonance region done with the computer code SAMMY. SAMMY is used in the evaluation of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on the generalised least-squares formalism (Bayesian theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, it provides the resonance parameter covariances. For resonance parameter evaluations where there are no resonance parameter covariance data available, the alternative is to use an approach called the 'retroactive' resonance parameter covariance generation. In this paper, we describe the application of the retroactive covariance generation approach for the gadolinium isotopes. (authors)
Covariance Evaluation Methodology for Neutron Cross Sections

Energy Technology Data Exchange (ETDEWEB)

Herman,M.; Arcilla, R.; Mattoon, C.M.; Mughabghab, S.F.; Oblozinsky, P.; Pigni, M.; Pritychenko, b.; Songzoni, A.A.

2008-09-01

We present the NNDC-BNL methodology for estimating neutron cross section covariances in thermal, resolved resonance, unresolved resonance and fast neutron regions. The three key elements of the methodology are Atlas of Neutron Resonances, nuclear reaction code EMPIRE, and the Bayesian code implementing Kalman filter concept. The covariance data processing, visualization and distribution capabilities are integral components of the NNDC methodology. We illustrate its application on examples including relatively detailed evaluation of covariances for two individual nuclei and massive production of simple covariance estimates for 307 materials. Certain peculiarities regarding evaluation of covariances for resolved resonances and the consistency between resonance parameter uncertainties and thermal cross section uncertainties are also discussed.
Covariance matrices of experimental data

International Nuclear Information System (INIS)

Perey, F.G.

1978-01-01

A complete statement of the uncertainties in data is given by its covariance matrix. It is shown how the covariance matrix of data can be generated using the information available to obtain their standard deviations. Determination of resonance energies by the time-of-flight method is used as an example. The procedure for combining data when the covariance matrix is non-diagonal is given. The method is illustrated by means of examples taken from the recent literature to obtain an estimate of the energy of the first resonance in carbon and for five resonances of 238 U
Genetic influences on schizophrenia and subcortical brain volumes

DEFF Research Database (Denmark)

Franke, Barbara; Stein, Jason L; Ripke, Stephan

2016-01-01

and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between...... genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk...
Alterations of social interaction through genetic and environmental manipulation of the 22q11.2 gene Sept5 in the mouse brain.

Science.gov (United States)

Harper, Kathryn M; Hiramoto, Takeshi; Tanigaki, Kenji; Kang, Gina; Suzuki, Go; Trimble, William; Hiroi, Noboru

2012-08-01

Social behavior dysfunction is a symptomatic element of schizophrenia and autism spectrum disorder (ASD). Although altered activities in numerous brain regions are associated with defective social cognition and perception, the causative relationship between these altered activities and social cognition and perception-and their genetic underpinnings-are not known in humans. To address these issues, we took advantage of the link between hemizygous deletion of human chromosome 22q11.2 and high rates of social behavior dysfunction, schizophrenia and ASD. We genetically manipulated Sept5, a 22q11.2 gene, and evaluated its role in social interaction in mice. Sept5 deficiency, against a high degree of homogeneity in a congenic genetic background, selectively impaired active affiliative social interaction in mice. Conversely, virally guided overexpression of Sept5 in the hippocampus or, to a lesser extent, the amygdala elevated levels of active affiliative social interaction in C57BL/6J mice. Congenic knockout mice and mice overexpressing Sept5 in the hippocampus or amygdala were indistinguishable from control mice in novelty and olfactory responses, anxiety or motor activity. Moreover, post-weaning individual housing, an environmental condition designed to reduce stress in male mice, selectively raised levels of Sept5 protein in the amygdala and increased active affiliative social interaction in C57BL/6J mice. These findings identify this 22q11.2 gene in the hippocampus and amygdala as a determinant of social interaction and suggest that defective social interaction seen in 22q11.2-associated schizophrenia and ASD can be genetically and environmentally modified by altering this 22q11.2 gene.
New perspective in covariance evaluation for nuclear data

International Nuclear Information System (INIS)

Kanda, Y.

1992-01-01

Methods of nuclear data evaluation have been highly developed during the past decade, especially after introducing the concept of covariance. This makes it utmost important how to evaluate covariance matrices for nuclear data. It can be said that covariance evaluation is just the nuclear data evaluation, because the covariance matrix has quantitatively decisive function in current evaluation methods. The covariance primarily represents experimental uncertainties. However, correlation of individual uncertainties between different data must be taken into account and it can not be conducted without detailed physical considerations on experimental conditions. This procedure depends on the evaluator and the estimated covariance does also. The mathematical properties of the covariance have been intensively discussed. Their physical properties should be studied to apply it to the nuclear data evaluation, and then, in this report, are reviewed to give the base for further development of the covariance application. (orig.)
Covariant perturbations of Schwarzschild black holes

International Nuclear Information System (INIS)

Clarkson, Chris A; Barrett, Richard K

2003-01-01

We present a new covariant and gauge-invariant perturbation formalism for dealing with spacetimes having spherical symmetry (or some preferred spatial direction) in the background, and apply it to the case of gravitational wave propagation in a Schwarzschild black-hole spacetime. The 1 + 3 covariant approach is extended to a '1 + 1 + 2 covariant sheet' formalism by introducing a radial unit vector in addition to the timelike congruence, and decomposing all covariant quantities with respect to this. The background Schwarzschild solution is discussed and a covariant characterization is given. We give the full first-order system of linearized 1 + 1 + 2 covariant equations, and we show how, by introducing (time and spherical) harmonic functions, these may be reduced to a system of first-order ordinary differential equations and algebraic constraints for the 1 + 1 + 2 variables which may be solved straightforwardly. We show how both odd- and even-parity perturbations may be unified by the discovery of a covariant, frame- and gauge-invariant, transverse-traceless tensor describing gravitational waves, which satisfies a covariant wave equation equivalent to the Regge-Wheeler equation for both even- and odd-parity perturbations. We show how the Zerilli equation may be derived from this tensor, and derive a similar transverse-traceless tensor equation equivalent to this equation. The so-called special quasinormal modes with purely imaginary frequency emerge naturally. The significance of the degrees of freedom in the choice of the two frame vectors is discussed, and we demonstrate that, for a certain frame choice, the underlying dynamics is governed purely by the Regge-Wheeler tensor. The two transverse-traceless Weyl tensors which carry the curvature of gravitational waves are discussed, and we give the closed system of four first-order ordinary differential equations describing their propagation. Finally, we consider the extension of this work to the study of
Epigenetic Alterations in Alzheimer’s Disease

Science.gov (United States)

Sanchez-Mut, Jose V.; Gräff, Johannes

2015-01-01

Alzheimer’s disease (AD) is the major cause of dementia in Western societies. It progresses asymptomatically during decades before being belatedly diagnosed when therapeutic strategies have become unviable. Although several genetic alterations have been associated with AD, the vast majority of AD cases do not show strong genetic underpinnings and are thus considered a consequence of non-genetic factors. Epigenetic mechanisms allow for the integration of long-lasting non-genetic inputs on specific genetic backgrounds, and recently, a growing number of epigenetic alterations in AD have been described. For instance, an accumulation of dysregulated epigenetic mechanisms in aging, the predominant risk factor of AD, might facilitate the onset of the disease. Likewise, mutations in several enzymes of the epigenetic machinery have been associated with neurodegenerative processes that are altered in AD such as impaired learning and memory formation. Genome-wide and locus-specific epigenetic alterations have also been reported, and several epigenetically dysregulated genes validated by independent groups. From these studies, a picture emerges of AD as being associated with DNA hypermethylation and histone deacetylation, suggesting a general repressed chromatin state and epigenetically reduced plasticity in AD. Here we review these recent findings and discuss several technical and methodological considerations that are imperative for their correct interpretation. We also pay particular focus on potential implementations and theoretical frameworks that we expect will help to better direct future studies aimed to unravel the epigenetic participation in AD. PMID:26734709
Altering BDNF expression by genetics and/or environment: impact for emotional and depression-like behaviour in laboratory mice.

Science.gov (United States)

Chourbaji, Sabine; Brandwein, Christiane; Gass, Peter

2011-01-01

According to the "neurotrophin hypothesis", brain-derived neurotrophic factor (BDNF) is an important candidate gene in depression. Moreover, environmental stress is known to represent a risk factor in the pathophysiology and treatment of this disease. To elucidate, whether changes of BDNF availability signify cause or consequence of depressive-like alterations, it is essential to look for endophenotypes under distinct genetic conditions (e.g. altered BDNF expression). Furthermore it is crucial to examine environment-driven BDNF regulation and its effect on depressive-linked features. Consequently, gene × environment studies investigating prospective genetic mouse models of depression in different environmental contexts become increasingly important. The present review summarizes recent findings in BDNF-mutant mice, which have been controversially discussed as models of depression and anxiety. It furthermore illustrates the potential of environment to serve as naturalistic stressor with the potential to modulate the phenotype in wildtype and mutant mice. Moreover, environment may exert protective effects by regulating BDNF levels as attributed to "environmental enrichment". The effect of this beneficial condition will also be discussed with regard to probable "curative/therapeutic" approaches. Copyright © 2010 Elsevier Ltd. All rights reserved.
Covariation in Natural Causal Induction.

Science.gov (United States)

Cheng, Patricia W.; Novick, Laura R.

1991-01-01

Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
Genetic covariance structure of reading, intelligence and memory in children

NARCIS (Netherlands)

van Leeuwen, Marieke; van den Berg, Stéphanie Martine; Peper, Jiska S.; Hulshoff Pol, Hilleke E.; Boomsma, Dorret I.

2009-01-01

This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained
Genetic Covariance Structure of Reading, Intelligence and Memory in Children

NARCIS (Netherlands)

van Leeuwen, M.; van den Berg, S.M.; Peper, J.S.; Hulshoff Pol, H.E.; Boomsma, D.I.

2009-01-01

This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained
Genetic Covariance Structure of Reading, Intelligence and Memory in Children

NARCIS (Netherlands)

van Leeuwen, Marieke; van den Berg, Stephanie M.; Peper, Jiska S.; Pol, Hilleke E. Hulshoff; Boomsma, Dorret I.

This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained
Genetic alterations in lung cancer: Assessing limitations in routine clinical use

Directory of Open Access Journals (Sweden)

Joana Espiga Macedo

2007-01-01

Full Text Available Lung cancer is the most frequent cause of cancer mortality worldwide, responsible for approximately 1.1 million deaths per year. Median survival is short, both as most tumours are diagnosed at an advanced stage and because of the limited efficacy of available treatments. The development of tumour molecular genetics carries the promise of altering this state of affairs, as it should lead to a more precise classification of tumours, identify specific molecular targets for therapy and, above all, allow the development of new methods for early diagnosis. Despite numerous studies demonstrating the usefulness of molecular genetic techniques in the study of lung cancer, its routine clinical use in Portugal has, however, been limited.In this study, we used a p53 mutation screen in multiple clinical samples from a series of lung cancer patients to attempt to identify the main practical limitations to the integration of molecular genetics in routine clinical practice. Our results suggest that the main limiting factor is the availability of samples with good quality DNA; a problem that could be overcome by alterations in common sample collection and storage procedures. Resumo: O cancro do pulmÃ£o Ã© a causa mais frequente de mortalidade por cancro no mundo, sendo responsÃ¡vel por cerca de 1,1 milhÃµes de mortes por ano. A sobrevivÃªncia mÃ©dia dos doentes Ã© geralmente curta, por a doenÃ§a se encontrar em estÃ¡dios avanÃ§ados na altura do diagnÃ³stico, mas tambÃ©m devido Ã falta de eficÃ¡cia dos tratamentos disponÃveis. O advento da genÃ©tica molecular dos tumores trouxe consigo a possibilidade de modificar esta situaÃ§Ã£o, quer atravÃ©s do refinamento do diagnÃ³stico, quer da identificaÃ§Ã£o de alvos terapÃªuticos especÃficos, quer sobretudo por â pelo menos em teoria â permitir o diagnÃ³stico precoce da doenÃ§a. No entanto, e apesar de numerosos trabalhos terem jÃ¡ demonstrado a utilidade
Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder.

Science.gov (United States)

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-04-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.
Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

Science.gov (United States)

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-01-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC–vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder. PMID:28944772

Structural Analysis of Covariance and Correlation Matrices.

Science.gov (United States)

Joreskog, Karl G.

1978-01-01

A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data

International Nuclear Information System (INIS)

Jun, Sung C; Plis, Sergey M; Ranken, Doug M; Schmidt, David M

2006-01-01

The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse. To overcome these difficulties, noise covariance models consisting of one pair or a sum of multi-pairs of Kronecker products of spatial covariance and temporal covariance have been proposed. However, these approaches cannot be applied when the noise information is very limited, i.e., the amount of noise information is less than the degrees of freedom of the noise covariance models. A common example of this is when only averaged noise data are available for a limited prestimulus region (typically at most a few hundred milliseconds duration). For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. In this work, we propose a different noise covariance model which consists of diagonal spatial noise covariance and Toeplitz temporal noise covariance. It can easily be estimated from limited noise information, and no time-consuming optimization and data-processing are required. Thus, it can be used as an alternative choice when one-pair or multi-pair noise covariance models cannot be estimated due to lack of noise information. To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. We compared this covariance model with other existing covariance models such as conventional diagonal covariance, one-pair and multi-pair noise covariance models, when noise information is sufficient to estimate them. We
Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.

Science.gov (United States)

Gu, Yunyan; Wang, Hongwei; Qin, Yao; Zhang, Yujing; Zhao, Wenyuan; Qi, Lishuang; Zhang, Yuannv; Wang, Chenguang; Guo, Zheng

2013-03-01

The heterogeneity of genetic alterations in human cancer genomes presents a major challenge to advancing our understanding of cancer mechanisms and identifying cancer driver genes. To tackle this heterogeneity problem, many approaches have been proposed to investigate genetic alterations and predict driver genes at the individual pathway level. However, most of these approaches ignore the correlation of alteration events between pathways and miss many genes with rare alterations collectively contributing to carcinogenesis. Here, we devise a network-based approach to capture the cooperative functional modules hidden in genome-wide somatic mutation and copy number alteration profiles of glioblastoma (GBM) from The Cancer Genome Atlas (TCGA), where a module is a set of altered genes with dense interactions in the protein interaction network. We identify 7 pairs of significantly co-altered modules that involve the main pathways known to be altered in GBM (TP53, RB and RTK signaling pathways) and highlight the striking co-occurring alterations among these GBM pathways. By taking into account the non-random correlation of gene alterations, the property of co-alteration could distinguish oncogenic modules that contain driver genes involved in the progression of GBM. The collaboration among cancer pathways suggests that the redundant models and aggravating models could shed new light on the potential mechanisms during carcinogenesis and provide new indications for the design of cancer therapeutic strategies.
Genetic variance and covariance and breed differences for feed intake and average daily gain to improve feed efficiency in growing cattle.

Science.gov (United States)

Retallick, K J; Bormann, J M; Weaber, R L; MacNeil, M D; Bradford, H L; Freetly, H C; Hales, K E; Moser, D W; Snelling, W M; Thallman, R M; Kuehn, L A

2017-04-01

Feed costs are a major economic expense in finishing and developing cattle; however, collection of feed intake data is costly. Examining relationships among measures of growth and intake, including breed differences, could facilitate selection for efficient cattle. Objectives of this study were to estimate genetic parameters for growth and intake traits and compare indices for feed efficiency to accelerate selection response. On-test ADFI and on-test ADG (TESTADG) and postweaning ADG (PWADG) records for 5,606 finishing steers and growing heifers were collected at the U.S. Meat Animal Research Center in Clay Center, NE. On-test ADFI and ADG data were recorded over testing periods that ranged from 62 to 148 d. Individual quadratic regressions were fitted for BW on time, and TESTADG was predicted from the resulting equations. We included PWADG in the model to improve estimates of growth and intake parameters; PWADG was derived by dividing gain from weaning weight to yearling weight by the number of days between the weights. Genetic parameters were estimated using multiple-trait REML animal models with TESTADG, ADFI, and PWADG for both sexes as dependent variables. Fixed contemporary groups were cohorts of calves simultaneously tested, and covariates included age on test, age of dam, direct and maternal heterosis, and breed composition. Genetic correlations (SE) between steer TESTADG and ADFI, PWADG and ADFI, and TESTADG and PWADG were 0.33 (0.10), 0.59 (0.06), and 0.50 (0.09), respectively, and corresponding estimates for heifers were 0.66 (0.073), 0.77 (0.05), and 0.88 (0.05), respectively. Indices combining EBV for ADFI with EBV for ADG were developed and evaluated. Greater improvement in feed efficiency can be expected using an unrestricted index versus a restricted index. Heterosis significantly affected each trait contributing to greater ADFI and TESTADG. Breed additive effects were estimated for ADFI, TESTADG, and the efficiency indices.
Evolutionary potential of root chemical defense: genetic correlations with shoot chemistry and plant growth.

Science.gov (United States)

Parker, J D; Salminen, J-P; Agrawal, Anurag A

2012-08-01

Root herbivores can affect plant fitness, and roots often contain the same secondary metabolites that act as defenses in shoots, but the ecology and evolution of root chemical defense have been little investigated. Here, we investigated genetic variance, heritability, and correlations among defensive phenolic compounds in shoot vs. root tissues of common evening primrose, Oenothera biennis. Across 20 genotypes, there were roughly similar concentrations of total phenolics in shoots vs. roots, but the allocation of particular phenolics to shoots vs. roots varied along a continuum of genotype growth rate. Slow-growing genotypes allocated 2-fold more of the potential pro-oxidant oenothein B to shoots than roots, whereas fast-growing genotypes had roughly equivalent above and belowground concentrations. Phenolic concentrations in both roots and shoots were strongly heritable, with mostly positive patterns of genetic covariation. Nonetheless, there was genotype-specific variation in the presence/absence of two major ellagitannins (oenothein A and its precursor oenothein B), indicating two different chemotypes based on alterations in this chemical pathway. Overall, the presence of strong genetic variation in root defenses suggests ample scope for the evolution of these compounds as defenses against root herbivores.
Modifications of Sp(2) covariant superfield quantization

Energy Technology Data Exchange (ETDEWEB)

Gitman, D.M.; Moshin, P.Yu

2003-12-04

We propose a modification of the Sp(2) covariant superfield quantization to realize a superalgebra of generating operators isomorphic to the massless limit of the corresponding superalgebra of the osp(1,2) covariant formalism. The modified scheme ensures the compatibility of the superalgebra of generating operators with extended BRST symmetry without imposing restrictions eliminating superfield components from the quantum action. The formalism coincides with the Sp(2) covariant superfield scheme and with the massless limit of the osp(1,2) covariant quantization in particular cases of gauge-fixing and solutions of the quantum master equations.
Covariant quantizations in plane and curved spaces

International Nuclear Information System (INIS)

Assirati, J.L.M.; Gitman, D.M.

2017-01-01

We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Covariant quantizations in plane and curved spaces

Energy Technology Data Exchange (ETDEWEB)

Assirati, J.L.M. [University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil); Gitman, D.M. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); P.N. Lebedev Physical Institute, Moscow (Russian Federation); University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil)

2017-07-15

We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Construction of covariance matrix for experimental data

International Nuclear Information System (INIS)

Liu Tingjin; Zhang Jianhua

1992-01-01

For evaluators and experimenters, the information is complete only in the case when the covariance matrix is given. The covariance matrix of the indirectly measured data has been constructed and discussed. As an example, the covariance matrix of 23 Na(n, 2n) cross section is constructed. A reasonable result is obtained
Smooth individual level covariates adjustment in disease mapping.

Science.gov (United States)

Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise

2018-05-01

Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Development of covariance date for fast reactor cores. 3

International Nuclear Information System (INIS)

Shibata, Keiichi; Hasegawa, Akira

1999-03-01

Covariances have been estimated for nuclear data contained in JENDL-3.2. As for Cr and Ni, the physical quantities for which covariances are deduced are cross sections and the first order Legendre-polynomial coefficient for the angular distribution of elastically scattered neutrons. The covariances were estimated by using the same methodology that had been used in the JENDL-3.2 evaluation in order to keep a consistency between mean values and their covariances. In a case where evaluated data were based on experimental data, the covariances were estimated from the same experimental data. For cross section that had been evaluated by nuclear model calculations, the same model was applied to generate the covariances. The covariances obtained were compiled into ENDF-6 format files. The covariances, which had been prepared by the previous fiscal year, were re-examined, and some improvements were performed. Parts of Fe and 235 U covariances were updated. Covariances of nu-p and nu-d for 241 Pu and of fission neutron spectra for 233,235,238 U and 239,240 Pu were newly added to data files. (author)
Externalizing problems, attention regulation, and household chaos: a longitudinal behavioral genetic study.

Science.gov (United States)

Wang, Zhe; Deater-Deckard, Kirby; Petrill, Stephen A; Thompson, Lee A

2012-08-01

Previous research documented a robust link between difficulties in self-regulation and development of externalizing problems (i.e., aggression and delinquency). In this study, we examined the longitudinal additive and interactive genetic and environmental covariation underlying this well-established link using a twin design. The sample included 131 pairs of monozygotic twins and 173 pairs of same-sex dizygotic twins who participated in three waves of annual assessment. Mothers and fathers provided reports of externalizing problems. Teacher report and observer rating were used to assess twin's attention regulation. The etiology underlying the link between externalizing problems and attention regulation shifted from a common genetic mechanism to a common environmental mechanism in the transition across middle childhood. Household chaos moderated the genetic variance of and covariance between externalizing problems and attention regulation. The genetic influence on individual differences in both externalizing problems and attention regulation was stronger in more chaotic households. However, higher levels of household chaos attenuated the genetic link between externalizing problems and attention regulation.
Genetic determination of mortality rate in Danish dairy cows

DEFF Research Database (Denmark)

Maia, Rafael Pimentel; Ask, Birgitte; Madsen, Per

2014-01-01

: a sire random component with pedigree representing the sire genetic effects and a herd-year-season component. Moreover, the level of heterozygosity and the sire breed proportions were included in the models as covariates in order to account for potential non-additive genetic effects due to the massive...... introduction of genetic material from other populations. The correlations between the sire components for death rate and slaughter rate were negative and small for the 3 populations, suggesting the existence of specific genetic mechanisms for each culling reason and common concurrent genetic mechanisms...
Precomputing Process Noise Covariance for Onboard Sequential Filters

Science.gov (United States)

Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell

2017-01-01

Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.
Drug-induced and genetic alterations in stress-responsive systems: Implications for specific addictive diseases.

Science.gov (United States)

Zhou, Yan; Proudnikov, Dmitri; Yuferov, Vadim; Kreek, Mary Jeanne

2010-02-16

From the earliest work in our laboratory, we hypothesized, and with studies conducted in both clinical research and animal models, we have shown that drugs of abuse, administered or self-administered, on a chronic basis, profoundly alter stress-responsive systems. Alterations of expression of specific genes involved in stress responsivity, with increases or decreases in mRNA levels, receptor, and neuropeptide levels, and resultant changes in hormone levels, have been documented to occur after chronic intermittent exposure to heroin, morphine, other opiates, cocaine, other stimulants, and alcohol in animal models and in human molecular genetics. The best studied of the stress-responsive systems in humans and mammalian species in general is undoubtedly the HPA axis. In addition, there are stress-responsive systems in other parts in the brain itself, and some of these include components of the HPA axis, such as CRF and CRF receptors, along with POMC gene and gene products. Several other stress-responsive systems are known to influence the HPA axis, such as the vasopressin-vasopressin receptor system. Orexin-hypocretin, acting at its receptors, may effect changes which suggest that it should be properly categorized as a stress-responsive system. However, less is known about the interactions and connectivity of some of these different neuropeptide and receptor systems, and in particular, about the possible connectivity of fast-acting (e.g., glutamate and GABA) and slow-acting (including dopamine, serotonin, and norepinephrine) neurotransmitters with each of these stress-responsive components and the resultant impact, especially in the setting of chronic exposure to drugs of abuse. Several of these stress-responsive systems and components, primarily based on our laboratory-based and human molecular genetics research of addictive diseases, will be briefly discussed in this review. Copyright 2009 Elsevier B.V. All rights reserved.
Genetic Alterations in the Molecular Subtypes of Bladder Cancer: Illustration in the Cancer Genome Atlas Dataset.

Science.gov (United States)

Choi, Woonyoung; Ochoa, Andrea; McConkey, David J; Aine, Mattias; Höglund, Mattias; Kim, William Y; Real, Francisco X; Kiltie, Anne E; Milsom, Ian; Dyrskjøt, Lars; Lerner, Seth P

2017-09-01

Recent whole genome mRNA expression profiling studies revealed that bladder cancers can be grouped into molecular subtypes, some of which share clinical properties and gene expression patterns with the intrinsic subtypes of breast cancer and the molecular subtypes found in other solid tumors. The molecular subtypes in other solid tumors are enriched with specific mutations and copy number aberrations that are thought to underlie their distinct progression patterns, and biological and clinical properties. The availability of comprehensive genomic data from The Cancer Genome Atlas (TCGA) and other large projects made it possible to correlate the presence of DNA alterations with tumor molecular subtype membership. Our overall goal was to determine whether specific DNA mutations and/or copy number variations are enriched in specific molecular subtypes. We used the complete TCGA RNA-seq dataset and three different published classifiers developed by our groups to assign TCGA's bladder cancers to molecular subtypes, and examined the prevalence of the most common DNA alterations within them. We interpreted the results against the background of what was known from the published literature about the prevalence of these alterations in nonmuscle-invasive and muscle-invasive bladder cancers. The results confirmed that alterations involving RB1 and NFE2L2 were enriched in basal cancers, whereas alterations involving FGFR3 and KDM6A were enriched in luminal tumors. The results further reinforce the conclusion that the molecular subtypes of bladder cancer are distinct disease entities with specific genetic alterations. Our observation showed that some of subtype-enriched mutations and copy number aberrations are clinically actionable, which has direct implications for the clinical management of patients with bladder cancer. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.
The covariant chiral ring

Energy Technology Data Exchange (ETDEWEB)

Bourget, Antoine; Troost, Jan [Laboratoire de Physique Théorique, École Normale Supérieure, 24 rue Lhomond, 75005 Paris (France)

2016-03-23

We construct a covariant generating function for the spectrum of chiral primaries of symmetric orbifold conformal field theories with N=(4,4) supersymmetry in two dimensions. For seed target spaces K3 and T{sup 4}, the generating functions capture the SO(21) and SO(5) representation theoretic content of the chiral ring respectively. Via string dualities, we relate the transformation properties of the chiral ring under these isometries of the moduli space to the Lorentz covariance of perturbative string partition functions in flat space.
GLq(N)-covariant quantum algebras and covariant differential calculus

International Nuclear Information System (INIS)

Isaev, A.P.; Pyatov, P.N.

1992-01-01

GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations are considered. It is that, up to some innessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. 25 refs
Genetic contribution to patent ductus arteriosus in the premature newborn.

Science.gov (United States)

Bhandari, Vineet; Zhou, Gongfu; Bizzarro, Matthew J; Buhimschi, Catalin; Hussain, Naveed; Gruen, Jeffrey R; Zhang, Heping

2009-02-01

The most common congenital heart disease in the newborn population, patent ductus arteriosus, accounts for significant morbidity in preterm newborns. In addition to prematurity and environmental factors, we hypothesized that genetic factors play a significant role in this condition. The objective of this study was to quantify the contribution of genetic factors to the variance in liability for patent ductus arteriosus in premature newborns. A retrospective study (1991-2006) from 2 centers was performed by using zygosity data from premature twins born at Patent ductus arteriosus was diagnosed by echocardiography at each center. Mixed-effects logistic regression was used to assess the effect of specific covariates. Latent variable probit modeling was then performed to estimate the heritability of patent ductus arteriosus, and mixed-effects probit modeling was used to quantify the genetic component. We obtained data from 333 dizygotic twin pairs and 99 monozygotic twin pairs from 2 centers (Yale University and University of Connecticut). Data on chorioamnionitis, antenatal steroids, gestational age, body weight, gender, respiratory distress syndrome, patent ductus arteriosus, necrotizing enterocolitis, oxygen supplementation, and bronchopulmonary dysplasia were comparable between monozygotic and dizygotic twins. We found that gestational age, respiratory distress syndrome, and institution were significant covariates for patent ductus arteriosus. After controlling for specific covariates, genetic factors or the shared environment accounted for 76.1% of the variance in liability for patent ductus arteriosus. Preterm patent ductus arteriosus is highly familial (contributed to by genetic and environmental factors), with the effect being mainly environmental, after controlling for known confounders.
Genetic pleiotropy explains associations between musical auditory discrimination and intelligence.

Science.gov (United States)

Mosing, Miriam A; Pedersen, Nancy L; Madison, Guy; Ullén, Fredrik

2014-01-01

Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions.

Introduction to covariant formulation of superstring (field) theory

International Nuclear Information System (INIS)

Anon.

1987-01-01

The author discusses covariant formulation of superstring theories based on BRS invariance. New formulation of superstring was constructed by Green and Schwarz in the light-cone gauge first and then a covariant action was discovered. The covariant action has some interesting geometrical interpretation, however, covariant quantizations are difficult to perform because of existence of local supersymmetries. Introducing extra variables into the action, a modified action has been proposed. However, it would be difficult to prescribe constraints to define a physical subspace, or to reproduce the correct physical spectrum. Hence the old formulation, i.e., the Neveu-Schwarz-Ramond (NSR) model for covariant quantization is used. The author begins by quantizing the NSR model in a covariant way using BRS charges. Then the author discusses the field theory of (free) superstring
Graphical representation of covariant-contravariant modal formulae

Directory of Open Access Journals (Sweden)

Miguel Palomino

2011-08-01

Full Text Available Covariant-contravariant simulation is a combination of standard (covariant simulation, its contravariant counterpart and bisimulation. We have previously studied its logical characterization by means of the covariant-contravariant modal logic. Moreover, we have investigated the relationships between this model and that of modal transition systems, where two kinds of transitions (the so-called may and must transitions were combined in order to obtain a simple framework to express a notion of refinement over state-transition models. In a classic paper, Boudol and Larsen established a precise connection between the graphical approach, by means of modal transition systems, and the logical approach, based on Hennessy-Milner logic without negation, to system specification. They obtained a (graphical representation theorem proving that a formula can be represented by a term if, and only if, it is consistent and prime. We show in this paper that the formulae from the covariant-contravariant modal logic that admit a "graphical" representation by means of processes, modulo the covariant-contravariant simulation preorder, are also the consistent and prime ones. In order to obtain the desired graphical representation result, we first restrict ourselves to the case of covariant-contravariant systems without bivariant actions. Bivariant actions can be incorporated later by means of an encoding that splits each bivariant action into its covariant and its contravariant parts.
Multivariate covariance generalized linear models

DEFF Research Database (Denmark)

Bonat, W. H.; Jørgensen, Bent

2016-01-01

are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...
Genetic analysis of body weight in South African Angora kids and ...

African Journals Online (AJOL)

Variance and covariance components and ratios pertaining to direct additive genetic variation, maternal additive genetic variation, maternal permanent environmental variation, and the relationship between direct and maternal effects for birth weight (BW; kg), weaning weight (WW; kg) and body weight at 8, 12 and 16 ...
Associations of Bcl-2 rs956572 genotype groups in the structural covariance network in early-stage Alzheimer's disease.

Science.gov (United States)

Chang, Chiung-Chih; Chang, Ya-Ting; Huang, Chi-Wei; Tsai, Shih-Jen; Hsu, Shih-Wei; Huang, Shu-Hua; Lee, Chen-Chang; Chang, Wen-Neng; Lui, Chun-Chung; Lien, Chia-Yi

2018-02-08

Alzheimer's disease (AD) is a complex neurodegenerative disease, and genetic differences may mediate neuronal degeneration. In humans, a single-nucleotide polymorphism in the B-cell chronic lymphocytic leukemia/lymphoma-2 (Bcl-2) gene, rs956572, has been found to significantly modulate Bcl-2 protein expression in the brain. The Bcl-2 AA genotype has been associated with reduced Bcl-2 levels and lower gray matter volume in healthy populations. We hypothesized that different Bcl-2 genotype groups may modulate large-scale brain networks that determine neurobehavioral test scores. Gray matter structural covariance networks (SCNs) were constructed in 104 patients with AD using T1-weighted magnetic resonance imaging with seed-based correlation analysis. The patients were stratified into two genotype groups on the basis of Bcl-2 expression (G carriers, n = 76; A homozygotes, n = 28). Four SCNs characteristic of AD were constructed from seeds in the default mode network, salience network, and executive control network, and cognitive test scores served as the major outcome factor. For the G carriers, influences of the SCNs were observed mostly in the default mode network, of which the peak clusters anchored by the posterior cingulate cortex seed determined the cognitive test scores. In contrast, genetic influences in the A homozygotes were found mainly in the executive control network, and both the dorsolateral prefrontal cortex seed and the interconnected peak clusters were correlated with the clinical scores. Despite a small number of cases, the A homozygotes showed greater covariance strength than the G carriers among all four SCNs. Our results suggest that the Bcl-2 rs956572 polymorphism is associated with different strengths of structural covariance in AD that determine clinical outcomes. The greater covariance strength in the four SCNs shown in the A homozygotes suggests that different Bcl-2 polymorphisms play different modulatory roles.
Alcohol use disorder and divorce: evidence for a genetic correlation in a population-based Swedish sample.

Science.gov (United States)

Salvatore, Jessica E; Larsson Lönn, Sara; Sundquist, Jan; Lichtenstein, Paul; Sundquist, Kristina; Kendler, Kenneth S

2017-04-01

We tested the association between alcohol use disorder (AUD) and divorce; estimated the genetic and environmental influences on divorce; estimated how much genetic and environmental influences accounted for covariance between AUD and divorce; and estimated latent genetic and environmental correlations between AUD and divorce. We tested sex differences in these effects. We identified twin and sibling pairs with AUD and divorce information in Swedish national registers. We described the association between AUD and divorce using tetrachorics and used twin and sibling models to estimate genetic and environmental influences on divorce, on the covariance between AUD and divorce and the latent genetic and environmental correlations between AUD and divorce. Sweden. A total of 670 836 individuals (53% male) born 1940-1965. Life-time measures of AUD and divorce. AUD and divorce were related strongly (males: r tet = +0.44, 95% CI = 0.43, 0.45; females r tet = +0.37, 95% CI = 0.36, 0.38). Genetic factors accounted for a modest proportion of the variance in divorce (males: 21.3%, 95% CI = 7.6, 28.5; females: 31.0%, 95% CI = 18.8, 37.1). Genetic factors accounted for most of the covariance between AUD and divorce (males: 52.0%, 95% CI = 48.8, 67.9; females: 53.74%, 95% CI = 17.6, 54.5), followed by non-shared environmental factors (males: 45.0%, 95% CI = 37.5, 54.9; females: 41.6%, 95% CI = 40.3, 60.2). Shared environmental factors accounted for a negligible proportion of the covariance (males: 3.0%, 95% CI = -3.0, 13.5; females: 4.75%, 95% CI = 0.0, 6.6). The AUD-divorce genetic correlations were high (males: rA = +0.76, 95% CI = 0.53, 0.90; females +0.52, 95% CI = 0.24, 0.67). The non-shared environmental correlations were modest (males: rE = +0.32, 95% CI = 0.31, 0.40; females: +0.27, 95% CI = 0.27, 0.36). Divorce and alcohol use disorder are correlated strongly in the Swedish population, and the heritability of divorce is consistent
Distinct genetic alterations in colorectal cancer.

Directory of Open Access Journals (Sweden)

Hassan Ashktorab

Full Text Available BACKGROUND: Colon cancer (CRC development often includes chromosomal instability (CIN leading to amplifications and deletions of large DNA segments. Epidemiological, clinical, and cytogenetic studies showed that there are considerable differences between CRC tumors from African Americans (AAs and Caucasian patients. In this study, we determined genomic copy number aberrations in sporadic CRC tumors from AAs, in order to investigate possible explanations for the observed disparities. METHODOLOGY/PRINCIPAL FINDINGS: We applied genome-wide array comparative genome hybridization (aCGH using a 105k chip to identify copy number aberrations in samples from 15 AAs. In addition, we did a population comparative analysis with aCGH data in Caucasians as well as with a widely publicized list of colon cancer genes (CAN genes. There was an average of 20 aberrations per patient with more amplifications than deletions. Analysis of DNA copy number of frequently altered chromosomes revealed that deletions occurred primarily in chromosomes 4, 8 and 18. Chromosomal duplications occurred in more than 50% of cases on chromosomes 7, 8, 13, 20 and X. The CIN profile showed some differences when compared to Caucasian alterations. CONCLUSIONS/SIGNIFICANCE: Chromosome X amplification in male patients and chromosomes 4, 8 and 18 deletions were prominent aberrations in AAs. Some CAN genes were altered at high frequencies in AAs with EXOC4, EPHB6, GNAS, MLL3 and TBX22 as the most frequently deleted genes and HAPLN1, ADAM29, SMAD2 and SMAD4 as the most frequently amplified genes. The observed CIN may play a distinctive role in CRC in AAs.
Covariant single-hole optical potential

International Nuclear Information System (INIS)

Kam, J. de

1982-01-01

In this investigation a covariant optical potential model is constructed for scattering processes of mesons from nuclei in which the meson interacts repeatedly with one of the target nucleons. The nuclear binding interactions in the intermediate scattering state are consistently taken into account. In particular for pions and K - projectiles this is important in view of the strong energy dependence of the elementary projectile-nucleon amplitude. Furthermore, this optical potential satisfies unitarity and relativistic covariance. The starting point in our discussion is the three-body model for the optical potential. To obtain a practical covariant theory I formulate the three-body model as a relativistic quasi two-body problem. Expressions for the transition interactions and propagators in the quasi two-body equations are found by imposing the correct s-channel unitarity relations and by using dispersion integrals. This is done in such a way that the correct non-relativistic limit is obtained, avoiding clustering problems. Corrections to the quasi two-body treatment from the Pauli principle and the required ground-state exclusion are taken into account. The covariant equations that we arrive at are amenable to practical calculations. (orig.)
Genetic transformation of rare Verbascum eriophorum Godr. plants and metabolic alterations revealed by NMR-based metabolomics.

Science.gov (United States)

Marchev, Andrey; Yordanova, Zhenya; Alipieva, Kalina; Zahmanov, Georgi; Rusinova-Videva, Snezhana; Kapchina-Toteva, Veneta; Simova, Svetlana; Popova, Milena; Georgiev, Milen I

2016-09-01

To develop a protocol to transform Verbascum eriophorum and to study the metabolic differences between mother plants and hairy root culture by applying NMR and processing the datasets with chemometric tools. Verbascum eriophorum is a rare species with restricted distribution, which is poorly studied. Agrobacterium rhizogenes-mediated genetic transformation of V. eriophorum and hairy root culture induction are reported for the first time. To determine metabolic alterations, V. eriophorum mother plants and relevant hairy root culture were subjected to comprehensive metabolomic analyses, using NMR (1D and 2D). Metabolomics data, processed using chemometric tools (and principal component analysis in particular) allowed exploration of V. eriophorum metabolome and have enabled identification of verbascoside (by means of 2D-TOCSY NMR) as the most abundant compound in hairy root culture. Metabolomics data contribute to the elucidation of metabolic alterations after T-DNA transfer to the host V. eriophorum genome and the development of hairy root culture for sustainable bioproduction of high value verbascoside.
Nuclear data covariances in the Indian context

International Nuclear Information System (INIS)

Ganesan, S.

2014-01-01

The topic of covariances is recognized as an important part of several ongoing nuclear data science activities, since 2007, in the Nuclear Data Physics Centre of India (NDPCI). A Phase-1 project in collaboration with the Statistics department in Manipal University, Karnataka (Prof. K.M. Prasad and Prof. S. Nair) on nuclear data covariances was executed successfully during 2007-2011 period. In Phase-I, the NDPCI has conducted three national Theme meetings sponsored by the DAE-BRNS in 2008, 2010 and 2013 on nuclear data covariances. In Phase-1, the emphasis was on a thorough basic understanding of the concept of covariances including assigning uncertainties to experimental data in terms of partial errors and micro correlations, through a study and a detailed discussion of open literature. Towards the end of Phase-1, measurements and a first time covariance analysis of cross-sections for 58 Ni (n, p) 58 Co reaction measured in Mumbai Pelletron accelerator using 7 Li (p,n) reactions as neutron source in the MeV energy region were performed under a PhD programme on nuclear data covariances in which enrolled are two students, Shri B.S. Shivashankar and Ms. Shanti Sheela. India is also successfully evolving a team of young researchers to code nuclear data of uncertainties, with the perspectives on covariances, in the IAEA-EXFOR format. A Phase-II DAE-BRNS-NDPCI proposal of project at Manipal has been submitted and the proposal is undergoing a peer-review at this time. In Phase-2, modern nuclear data evaluation techniques that including covariances will be further studied as a research and development effort, as a first time effort. These efforts include the use of techniques such as that of the Kalman filter. Presently, a 48 hours lecture series on treatment of errors and their propagation is being formulated under auspices of the Homi Bhabha National Institute. The talk describes the progress achieved thus far in the learning curve of the above-mentioned and exciting
AFCI-2.0 Neutron Cross Section Covariance Library

Energy Technology Data Exchange (ETDEWEB)

Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.

2011-03-01

The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R&D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78 structural
AFCI-2.0 Neutron Cross Section Covariance Library

International Nuclear Information System (INIS)

Herman, M.; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.

2011-01-01

The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R and D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78
Experience in using the covariances of some ENDF/B-V dosimetry cross sections: proposed improvements and addition of cross-reaction covariances

International Nuclear Information System (INIS)

Fu, C.Y.; Hetrick, D.M.

1982-01-01

Recent ratio data, with carefully evaluated covariances, were combined with eleven of the ENDF/B-V dosimetry cross sections using the generalized least-squares method. The purpose was to improve these evaluated cross sections and covariances, as well as to generate values for the cross-reaction covariances. The results represent improved cross sections as well as realistic and usable covariances. The latter are necessary for meaningful intergral-differential comparisons and for spectrum unfolding
High-dimensional covariance estimation with high-dimensional data

CERN Document Server

Pourahmadi, Mohsen

2013-01-01

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac
Altered expression of MGMT in high-grade gliomas results from the combined effect of epigenetic and genetic aberrations.

Directory of Open Access Journals (Sweden)

João Ramalho-Carvalho

Full Text Available MGMT downregulation in high-grade gliomas (HGG has been mostly attributed to aberrant promoter methylation and is associated with increased sensitivity to alkylating agent-based chemotherapy. However, HGG harboring 10q deletions also benefit from treatment with alkylating agents. Because the MGMT gene is mapped at 10q26, we hypothesized that both epigenetic and genetic alterations might affect its expression and predict response to chemotherapy. To test this hypothesis, promoter methylation and mRNA levels of MGMT were determined by quantitative methylation-specific PCR (qMSP or methylation-specific multiplex ligation dependent probe amplification (MS-MLPA and quantitative RT-PCR, respectively, in a retrospective series of 61 HGG. MGMT/chromosome 10 copy number variations were determined by FISH or MS-MLPA analysis. Molecular findings were correlated with clinical parameters to assess their predictive value. Overall, MGMT methylation ratios assessed by qMSP and MS-MLPA were inversely correlated with mRNA expression levels (best coefficient value obtained with MS-MLPA. By FISH analysis in 68.3% of the cases there was loss of 10q26.1 and in 15% of the cases polysomy was demonstrated; the latter displayed the highest levels of transcript. When genetic and epigenetic data were combined, cases with MGMT promoter methylation and MGMT loss depicted the lowest transcript levels, although an impact in response to alkylating agent chemotherapy was not apparent. Cooperation between epigenetic (promoter methylation and genetic (monosomy, locus deletion changes affecting MGMT in HGG is required for effective MGMT silencing. Hence, evaluation of copy number alterations might add relevant prognostic and predictive information concerning response to alkylating agent-based chemotherapy.
Covariance problem in two-dimensional quantum chromodynamics

International Nuclear Information System (INIS)

Hagen, C.R.

1979-01-01

The problem of covariance in the field theory of a two-dimensional non-Abelian gauge field is considered. Since earlier work has shown that covariance fails (in charged sectors) for the Schwinger model, particular attention is given to an evaluation of the role played by the non-Abelian nature of the fields. In contrast to all earlier attempts at this problem, it is found that the potential covariance-breaking terms are identical to those found in the Abelian theory provided that one expresses them in terms of the total (i.e., conserved) current operator. The question of covariance is thus seen to reduce in all cases to a determination as to whether there exists a conserved global charge in the theory. Since the charge operator in the Schwinger model is conserved only in neutral sectors, one is thereby led to infer a probable failure of covariance in the non-Abelian theory, but one which is identical to that found for the U(1) case
Structural covariance networks in the mouse brain.

Science.gov (United States)

Pagani, Marco; Bifone, Angelo; Gozzi, Alessandro

2016-04-01

The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks. Copyright © 2016 Elsevier Inc. All rights reserved.
Schroedinger covariance states in anisotropic waveguides

International Nuclear Information System (INIS)

Angelow, A.; Trifonov, D.

1995-03-01

In this paper Squeezed and Covariance States based on Schroedinger inequality and their connection with other nonclassical states are considered for particular case of anisotropic waveguide in LiNiO 3 . Here, the problem of photon creation and generation of squeezed and Schroedinger covariance states in optical waveguides is solved in two steps: 1. Quantization of electromagnetic field is provided in the presence of dielectric waveguide using normal-mode expansion. The photon creation and annihilation operators are introduced, expanding the solution A-vector(r-vector,t) in a series in terms of the Sturm - Liouville mode-functions. 2. In terms of these operators the Hamiltonian of the field in a nonlinear waveguide is derived. For such Hamiltonian we construct the covariance states as stable (with nonzero covariance), which minimize the Schroedinger uncertainty relation. The evolutions of the three second momenta of q-circumflex j and p-circumflex j are calculated. For this Hamiltonian all three momenta are expressed in terms of one real parameters s only. It is found out how covariance, via this parameter s, depends on the waveguide profile n(x,y), on the mode-distributions u-vector j (x,y), and on the waveguide phase mismatching Δβ. (author). 37 refs
Form of the manifestly covariant Lagrangian

Science.gov (United States)

Johns, Oliver Davis

1985-10-01

The preferred form for the manifestly covariant Lagrangian function of a single, charged particle in a given electromagnetic field is the subject of some disagreement in the textbooks. Some authors use a ``homogeneous'' Lagrangian and others use a ``modified'' form in which the covariant Hamiltonian function is made to be nonzero. We argue in favor of the ``homogeneous'' form. We show that the covariant Lagrangian theories can be understood only if one is careful to distinguish quantities evaluated on the varied (in the sense of the calculus of variations) world lines from quantities evaluated on the unvaried world lines. By making this distinction, we are able to derive the Hamilton-Jacobi and Klein-Gordon equations from the ``homogeneous'' Lagrangian, even though the covariant Hamiltonian function is identically zero on all world lines. The derivation of the Klein-Gordon equation in particular gives Lagrangian theoretical support to the derivations found in standard quantum texts, and is also shown to be consistent with the Feynman path-integral method. We conclude that the ``homogeneous'' Lagrangian is a completely adequate basis for covariant Lagrangian theory both in classical and quantum mechanics. The article also explores the analogy with the Fermat theorem of optics, and illustrates a simple invariant notation for the Lagrangian and other four-vector equations.
Convex Banding of the Covariance Matrix.

Science.gov (United States)

Bien, Jacob; Bunea, Florentina; Xiao, Luo

2016-01-01

We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings.

Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease.

Science.gov (United States)

Xu, Jinping; Zhang, Jiuquan; Zhang, Jinlei; Wang, Yue; Zhang, Yanling; Wang, Jian; Li, Guanglin; Hu, Qingmao; Zhang, Yuanchao

2017-01-01

Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups. Compared with the HC group, PD patients showed significantly increased integrated characteristic path length and integrated clustering coefficient, as well as decreased integrated global efficiency in structural brain networks. Distinct distributions of hub regions were identified between the two groups, showing more hub regions in the frontal cortex in PD patients. Moreover, the modular analyses revealed significantly decreased integrated regional efficiency in lateral Fronto-Insula-Temporal module, and increased integrated regional efficiency in Parieto-Temporal module in the PD group as compared to the HC group. In summary, our study demonstrated altered topological properties of structural networks at a global, regional and modular level in PD patients. These findings suggests that the structural networks of PD patients have a suboptimal topological organization, resulting in less effective integration of information between brain regions.
Determination of covariant Schwinger terms in anomalous gauge theories

International Nuclear Information System (INIS)

Kelnhofer, G.

1991-01-01

A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the covariant commutator anomalies are calculated for the two- and four dimensional case. (orig.)
Cross-population myelination covariance of human cerebral cortex.

Science.gov (United States)

Ma, Zhiwei; Zhang, Nanyin

2017-09-01

Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small-worldness. Furthermore, we found that the correlation between myelination covariance and resting-state functional connectivity (RSFC) was uniform within each resting-state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance-RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730-4743, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Covariant extensions and the nonsymmetric unified field

International Nuclear Information System (INIS)

Borchsenius, K.

1976-01-01

The problem of generally covariant extension of Lorentz invariant field equations, by means of covariant derivatives extracted from the nonsymmetric unified field, is considered. It is shown that the contracted curvature tensor can be expressed in terms of a covariant gauge derivative which contains the gauge derivative corresponding to minimal coupling, if the universal constant p, characterizing the nonsymmetric theory, is fixed in terms of Planck's constant and the elementary quantum of charge. By this choice the spinor representation of the linear connection becomes closely related to the spinor affinity used by Infeld and Van Der Waerden (Sitzungsber. Preuss. Akad. Wiss. Phys. Math. Kl.; 9:380 (1933)) in their generally covariant formulation of Dirac's equation. (author)
Computing more proper covariances of energy dependent nuclear data

International Nuclear Information System (INIS)

Vanhanen, R.

2016-01-01

Highlights: • We present conditions for covariances of energy dependent nuclear data to be proper. • We provide methods to detect non-positive and inconsistent covariances in ENDF-6 format. • We propose methods to find nearby more proper covariances. • The methods can be used as a part of a quality assurance program. - Abstract: We present conditions for covariances of energy dependent nuclear data to be proper in the sense that the covariances are positive, i.e., its eigenvalues are non-negative, and consistent with respect to the sum rules of nuclear data. For the ENDF-6 format covariances we present methods to detect non-positive and inconsistent covariances. These methods would be useful as a part of a quality assurance program. We also propose methods that can be used to find nearby more proper energy dependent covariances. These methods can be used to remove unphysical components, while preserving most of the physical components. We consider several different senses in which the nearness can be measured. These methods could be useful if a re-evaluation of improper covariances is not feasible. Two practical examples are processed and analyzed. These demonstrate some of the properties of the methods. We also demonstrate that the ENDF-6 format covariances of linearly dependent nuclear data should usually be encoded with the derivation rules.
Genetic alterations in syndromes with oral manifestations

Directory of Open Access Journals (Sweden)

Krishnamurthy Anuthama

2013-01-01

Full Text Available Ever since Gregor Johan Mendel proposed the law of inheritance, genetics has transcended the field of health and has entered all walks of life in its application. Thus, the gene is the pivoting factor for all happenings revolving around it. Knowledge of gene mapping in various diseases would be a valuable tool in prenatally diagnosing the condition and averting the future disability and stigma for the posterity. This article includes an array of genetically determined conditions in patients seen at our college out-patient department with complete manifestation, partial manifestation and array of manifestations not fitting into a particular syndrome.
Covariance Spectroscopy for Fissile Material Detection

International Nuclear Information System (INIS)

Trainham, Rusty; Tinsley, Jim; Hurley, Paul; Keegan, Ray

2009-01-01

Nuclear fission produces multiple prompt neutrons and gammas at each fission event. The resulting daughter nuclei continue to emit delayed radiation as neutrons boil off, beta decay occurs, etc. All of the radiations are causally connected, and therefore correlated. The correlations are generally positive, but when different decay channels compete, so that some radiations tend to exclude others, negative correlations could also be observed. A similar problem of reduced complexity is that of cascades radiation, whereby a simple radioactive decay produces two or more correlated gamma rays at each decay. Covariance is the usual means for measuring correlation, and techniques of covariance mapping may be useful to produce distinct signatures of special nuclear materials (SNM). A covariance measurement can also be used to filter data streams because uncorrelated signals are largely rejected. The technique is generally more effective than a coincidence measurement. In this poster, we concentrate on cascades and the covariance filtering problem
Optimal covariate designs theory and applications

CERN Document Server

Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar

2015-01-01

This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Covariate Imbalance and Precision in Measuring Treatment Effects

Science.gov (United States)

Liu, Xiaofeng Steven

2011-01-01

Covariate adjustment can increase the precision of estimates by removing unexplained variance from the error in randomized experiments, although chance covariate imbalance tends to counteract the improvement in precision. The author develops an easy measure to examine chance covariate imbalance in randomization by standardizing the average…
Covariant description of Hamiltonian form for field dynamics

International Nuclear Information System (INIS)

Ozaki, Hiroshi

2005-01-01

Hamiltonian form of field dynamics is developed on a space-like hypersurface in space-time. A covariant Poisson bracket on the space-like hypersurface is defined and it plays a key role to describe every algebraic relation into a covariant form. It is shown that the Poisson bracket has the same symplectic structure that was brought in the covariant symplectic approach. An identity invariant under the canonical transformations is obtained. The identity follows a canonical equation in which the interaction Hamiltonian density generates a deformation of the space-like hypersurface. The equation just corresponds to the Yang-Feldman equation in the Heisenberg pictures in quantum field theory. By converting the covariant Poisson bracket on the space-like hypersurface to four-dimensional commutator, we can pass over to quantum field theory in the Heisenberg picture without spoiling the explicit relativistic covariance. As an example the canonical QCD is displayed in a covariant way on a space-like hypersurface
Dimension from covariance matrices.

Science.gov (United States)

Carroll, T L; Byers, J M

2017-02-01

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.
ANL Critical Assembly Covariance Matrix Generation - Addendum

Energy Technology Data Exchange (ETDEWEB)

McKnight, Richard D. [Argonne National Lab. (ANL), Argonne, IL (United States); Grimm, Karl N. [Argonne National Lab. (ANL), Argonne, IL (United States)

2014-01-13

In March 2012, a report was issued on covariance matrices for Argonne National Laboratory (ANL) critical experiments. That report detailed the theory behind the calculation of covariance matrices and the methodology used to determine the matrices for a set of 33 ANL experimental set-ups. Since that time, three new experiments have been evaluated and approved. This report essentially updates the previous report by adding in these new experiments to the preceding covariance matrix structure.
Condition Number Regularized Covariance Estimation.

Science.gov (United States)

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2013-06-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.
Recent and projected increases in atmospheric CO2 concentration can enhance gene flow between wild and genetically altered rice (Oryza sativa.

Directory of Open Access Journals (Sweden)

Lewis H Ziska

Full Text Available Although recent and projected increases in atmospheric carbon dioxide can alter plant phenological development, these changes have not been quantified in terms of floral outcrossing rates or gene transfer. Could differential phenological development in response to rising CO(2 between genetically modified crops and wild, weedy relatives increase the spread of novel genes, potentially altering evolutionary fitness? Here we show that increasing CO(2 from an early 20(th century concentration (300 µmol mol(-1 to current (400 µmol mol(-1 and projected, mid-21(st century (600 µmol mol(-1 values, enhanced the flow of genes from wild, weedy rice to the genetically altered, herbicide resistant, cultivated population, with outcrossing increasing from 0.22% to 0.71% from 300 to 600 µmol mol(-1. The increase in outcrossing and gene transfer was associated with differential increases in plant height, as well as greater tiller and panicle production in the wild, relative to the cultivated population. In addition, increasing CO(2 also resulted in a greater synchronicity in flowering times between the two populations. The observed changes reported here resulted in a subsequent increase in rice dedomestication and a greater number of weedy, herbicide-resistant hybrid progeny. Overall, these data suggest that differential phenological responses to rising atmospheric CO(2 could result in enhanced flow of novel genes and greater success of feral plant species in agroecosystems.
Recent and projected increases in atmospheric CO2 concentration can enhance gene flow between wild and genetically altered rice (Oryza sativa).

Science.gov (United States)

Ziska, Lewis H; Gealy, David R; Tomecek, Martha B; Jackson, Aaron K; Black, Howard L

2012-01-01

Although recent and projected increases in atmospheric carbon dioxide can alter plant phenological development, these changes have not been quantified in terms of floral outcrossing rates or gene transfer. Could differential phenological development in response to rising CO(2) between genetically modified crops and wild, weedy relatives increase the spread of novel genes, potentially altering evolutionary fitness? Here we show that increasing CO(2) from an early 20(th) century concentration (300 µmol mol(-1)) to current (400 µmol mol(-1)) and projected, mid-21(st) century (600 µmol mol(-1)) values, enhanced the flow of genes from wild, weedy rice to the genetically altered, herbicide resistant, cultivated population, with outcrossing increasing from 0.22% to 0.71% from 300 to 600 µmol mol(-1). The increase in outcrossing and gene transfer was associated with differential increases in plant height, as well as greater tiller and panicle production in the wild, relative to the cultivated population. In addition, increasing CO(2) also resulted in a greater synchronicity in flowering times between the two populations. The observed changes reported here resulted in a subsequent increase in rice dedomestication and a greater number of weedy, herbicide-resistant hybrid progeny. Overall, these data suggest that differential phenological responses to rising atmospheric CO(2) could result in enhanced flow of novel genes and greater success of feral plant species in agroecosystems.
Parametric Covariance Model for Horizon-Based Optical Navigation

Science.gov (United States)

Hikes, Jacob; Liounis, Andrew J.; Christian, John A.

2016-01-01

This Note presents an entirely parametric version of the covariance for horizon-based optical navigation measurements. The covariance can be written as a function of only the spacecraft position, two sensor design parameters, the illumination direction, the size of the observed planet, the size of the lit arc to be used, and the total number of observed horizon points. As a result, one may now more clearly understand the sensitivity of horizon-based optical navigation performance as a function of these key design parameters, which is insight that was obscured in previous (and nonparametric) versions of the covariance. Finally, the new parametric covariance is shown to agree with both the nonparametric analytic covariance and results from a Monte Carlo analysis.
Activities on covariance estimation in Japanese Nuclear Data Committee

Energy Technology Data Exchange (ETDEWEB)

Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1997-03-01

Described are activities on covariance estimation in the Japanese Nuclear Data Committee. Covariances are obtained from measurements by using the least-squares methods. A simultaneous evaluation was performed to deduce covariances of fission cross sections of U and Pu isotopes. A code system, KALMAN, is used to estimate covariances of nuclear model calculations from uncertainties in model parameters. (author)
Externalizing problems, attention regulation, and household chaos: A longitudinal behavioral genetic study

Science.gov (United States)

Wang, Zhe; Deater-Deckard, Kirby; Petrill, Stephen A.; Thompson, Lee A.

2015-01-01

Previous research has documented a robust link between difficulties in self-regulation and development of externalizing problems (i.e., aggression and delinquency). In the current study, we examined the longitudinal additive and interactive genetic and environmental covariation underlying this well-established link using a twin design. The sample included 131 pairs of monozygotic twins and 173 pairs of same-sex dizygotic twins who participated in three waves of annual assessment. Mothers and fathers provided reports of externalizing problems. Teacher report and observer rating were used to assess twin’s attention regulation. The etiology underlying the link between externalizing problems and attention regulation shifted from a common genetic mechanism to a common environmental mechanism in the transition across middle childhood. Household chaos moderated the genetic variance of and covariance between externalizing problems and attention regulation. The genetic influence on individual differences in both externalizing problems and attention regulation was stronger in more chaotic household. However, higher levels of household chaos attenuated the genetic link between externalizing problems and attention regulation. PMID:22781853
How to measure genetic heterogeneity

International Nuclear Information System (INIS)

Yamada, Ryo

2009-01-01

Genetic information of organisms is coded as a string of four letters, A, T, G and C, a sequence in macromolecules called deoxyribonucleic acid (DNA). DNA sequence offers blueprint of organisms and its heterogeneity determines identity and variation of species. The quantitation of this genetic heterogeneity is fundamental to understand biology. We compared previously-reported three measures, covariance matrix expression of list of loci (pair-wise r 2 ), the most popular index in genetics, and its multi-dimensional form, Ψ, and entropy-based index, ε. Thereafter we proposed two methods so that we could handle the diplotypic heterogeneity and quantitate the conditions where the number of DNA sequence samples is much smaller than the number of possible variants.
Genetic and Epigenetic Alterations of Brassica nigra Introgression Lines from Somatic Hybridization: A Resource for Cauliflower Improvement.

Science.gov (United States)

Wang, Gui-Xiang; Lv, Jing; Zhang, Jie; Han, Shuo; Zong, Mei; Guo, Ning; Zeng, Xing-Ying; Zhang, Yue-Yun; Wang, You-Ping; Liu, Fan

2016-01-01

Broad phenotypic variations were obtained previously in derivatives from the asymmetric somatic hybridization of cauliflower "Korso" (Brassica oleracea var. botrytis, 2n = 18, CC genome) and black mustard "G1/1" (Brassica nigra, 2n = 16, BB genome). However, the mechanisms underlying these variations were unknown. In this study, 28 putative introgression lines (ILs) were pre-selected according to a series of morphological (leaf shape and color, plant height and branching, curd features, and flower traits) and physiological (black rot/club root resistance) characters. Multi-color fluorescence in situ hybridization revealed that these plants contained 18 chromosomes derived from "Korso." Molecular marker (65 simple sequence repeats and 77 amplified fragment length polymorphisms) analysis identified the presence of "G1/1" DNA segments (average 7.5%). Additionally, DNA profiling revealed many genetic and epigenetic differences among the ILs, including sequence alterations, deletions, and variation in patterns of cytosine methylation. The frequency of fragments lost (5.1%) was higher than presence of novel bands (1.4%), and the presence of fragments specific to Brassica carinata (BBCC 2n = 34) were common (average 15.5%). Methylation-sensitive amplified polymorphism analysis indicated that methylation changes were common and that hypermethylation (12.4%) was more frequent than hypomethylation (4.8%). Our results suggested that asymmetric somatic hybridization and alien DNA introgression induced genetic and epigenetic alterations. Thus, these ILs represent an important, novel germplasm resource for cauliflower improvement that can be mined for diverse traits of interest to breeders and researchers.

Neutron spectrum adjustment. The role of covariances

International Nuclear Information System (INIS)

Remec, I.

1992-01-01

Neutron spectrum adjustment method is shortly reviewed. Practical example dealing with power reactor pressure vessel exposure rates determination is analysed. Adjusted exposure rates are found only slightly affected by the covariances of measured reaction rates and activation cross sections, while the multigroup spectra covariances were found important. Approximate spectra covariance matrices, as suggested in Astm E944-89, were found useful but care is advised if they are applied in adjustments of spectra at locations without dosimetry. (author) [sl
Cross-covariance functions for multivariate geostatistics

KAUST Repository

Genton, Marc G.

2015-05-01

Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Cross-covariance functions for multivariate geostatistics

KAUST Repository

Genton, Marc G.; Kleiber, William

2015-01-01

Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
The method of covariant symbols in curved space-time

International Nuclear Information System (INIS)

Salcedo, L.L.

2007-01-01

Diagonal matrix elements of pseudodifferential operators are needed in order to compute effective Lagrangians and currents. For this purpose the method of symbols is often used, which however lacks manifest covariance. In this work the method of covariant symbols, introduced by Pletnev and Banin, is extended to curved space-time with arbitrary gauge and coordinate connections. For the Riemannian connection we compute the covariant symbols corresponding to external fields, the covariant derivative and the Laplacian, to fourth order in a covariant derivative expansion. This allows one to obtain the covariant symbol of general operators to the same order. The procedure is illustrated by computing the diagonal matrix element of a nontrivial operator to second order. Applications of the method are discussed. (orig.)
Conformally covariant massless spin-two field equations

International Nuclear Information System (INIS)

Drew, M.S.; Gegenberg, J.D.

1980-01-01

An explicit proof is constructed to show that the field equations for a symmetric tensor field hsub(ab) describing massless spin-2 particles in Minkowski space-time are not covariant under the 15-parameter group SOsub(4,2); this group is usually associated with conformal transformations on flat space, and here it will be considered as a global gauge group which acts upon matter fields defined on space-time. Notwithstanding the above noncovariance, the equations governing the rank-4 tensor Ssub(abcd) constructed from hsub(ab) are shown to be covariant provided the contraction Ssub(ab) vanishes. Conformal covariance is proved by demonstrating the covariance of the equations for the equivalent 5-component complex field; in fact, covariance is proved for a general field equation applicable to massless particles of any spin >0. It is shown that the noncovariance of the hsub(ab) equations may be ascribed to the fact that the transformation behaviour of hsub(ab) is not the same as that of a field consisting of a gauge only. Since this is in contradistinction to the situation for the electromagnetic-field equations, the vector form of the electromagnetic equations is cast into a form which can be duplicated for the hsub(ab)-field. This procedure results in an alternative, covariant, field equation for hsub(ab). (author)
Evaluation of covariance for 238U cross sections

International Nuclear Information System (INIS)

Kawano, Toshihiko; Nakamura, Masahiro; Matsuda, Nobuyuki; Kanda, Yukinori

1995-01-01

Covariances of 238 U are generated using analytic functions for representation of the cross sections. The covariances of the (n,2n) and (n,3n) reactions are derived with a spline function, while the covariances of the total and the inelastic scattering cross section are estimated with a linearized nuclear model calculation. (author)
GLq(N)-covariant quantum algebras and covariant differential calculus

International Nuclear Information System (INIS)

Isaev, A.P.; Pyatov, P.N.

1993-01-01

We consider GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations. We show that, up to some inessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. The connection with the bicovariant differential calculus on the linear quantum groups is discussed. (orig.)
Asset allocation with different covariance/correlation estimators

OpenAIRE

Μανταφούνη, Σοφία

2007-01-01

The subject of the study is to test whether the use of different covariance – correlation estimators than the historical covariance matrix that is widely used, would help in portfolio optimization through the mean-variance analysis. In other words, if an investor would like to use the mean-variance analysis in order to invest in assets like stocks or indices, would it be of some help to use more sophisticated estimators for the covariance matrix of the returns of his portfolio? The procedure ...
Students’ Covariational Reasoning in Solving Integrals’ Problems

Science.gov (United States)

Harini, N. V.; Fuad, Y.; Ekawati, R.

2018-01-01

Covariational reasoning plays an important role to indicate quantities vary in learning calculus. This study investigates students’ covariational reasoning during their studies concerning two covarying quantities in integral problem. Six undergraduate students were chosen to solve problems that involved interpreting and representing how quantities change in tandem. Interviews were conducted to reveal the students’ reasoning while solving covariational problems. The result emphasizes that undergraduate students were able to construct the relation of dependent variables that changes in tandem with the independent variable. However, students faced difficulty in forming images of continuously changing rates and could not accurately apply the concept of integrals. These findings suggest that learning calculus should be increased emphasis on coordinating images of two quantities changing in tandem about instantaneously rate of change and to promote conceptual knowledge in integral techniques.
Forecasting Covariance Matrices: A Mixed Frequency Approach

DEFF Research Database (Denmark)

Halbleib, Roxana; Voev, Valeri

This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexi......This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...
Covariance upperbound controllers for networked control systems

International Nuclear Information System (INIS)

Ko, Sang Ho

2012-01-01

This paper deals with designing covariance upperbound controllers for a linear system that can be used in a networked control environment in which control laws are calculated in a remote controller and transmitted through a shared communication link to the plant. In order to compensate for possible packet losses during the transmission, two different techniques are often employed: the zero-input and the hold-input strategy. These use zero input and the latest control input, respectively, when a packet is lost. For each strategy, we synthesize a class of output covariance upperbound controllers for a given covariance upperbound and a packet loss probability. Existence conditions of the covariance upperbound controller are also provided for each strategy. Through numerical examples, performance of the two strategies is compared in terms of feasibility of implementing the controllers
Epilepsy in patients with GRIN2A alterations

DEFF Research Database (Denmark)

von Stülpnagel, Celina; Ensslen, M; Møller, R S

2017-01-01

indicate that children with epilepsy due to pathogenic GRIN2A mutations present with different clinical phenotypes and a spectrum of seizure types in the context of a pharmacoresistant epilepsy providing information for clinicians treating children with this form of genetically determined epileptic......OBJECTIVE: To delineate the genetic, neurodevelopmental and epileptic spectrum associated with GRIN2A alterations with emphasis on epilepsy treatment. METHODS: Retrospective study of 19 patients (7 females; age: 1-38 years; mean 10.1 years) with epilepsy and GRIN2A alteration. Genetic variants were...... classified according to the guidelines and recommendations of the American College of Medical Genetics (ACMG). Clinical findings including epilepsy classification, treatment, EEG findings, early childhood development and neurodevelopmental outcome were collected with an electronic questionnaire. RESULTS: 7...
ERRORJ. Covariance processing code system for JENDL. Version 2

International Nuclear Information System (INIS)

Chiba, Gou

2003-09-01

ERRORJ is the covariance processing code system for Japanese Evaluated Nuclear Data Library (JENDL) that can produce group-averaged covariance data to apply it to the uncertainty analysis of nuclear characteristics. ERRORJ can treat the covariance data for cross sections including resonance parameters as well as angular distributions and energy distributions of secondary neutrons which could not be dealt with by former covariance processing codes. In addition, ERRORJ can treat various forms of multi-group cross section and produce multi-group covariance file with various formats. This document describes an outline of ERRORJ and how to use it. (author)
ACORNS, Covariance and Correlation Matrix Diagonalization

International Nuclear Information System (INIS)

Szondi, E.J.

1990-01-01

1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT
Genetics, the Big Five, and the Tendency to Be Self-Employed

Science.gov (United States)

Shane, Scott; Nicolaou, Nicos; Cherkas, Lynn; Spector, Tim D.

2010-01-01

We applied multivariate genetics techniques to a sample of 3,412 monozygotic and dizygotic twins from the United Kingdom and 1,300 monozygotic and dizygotic twins from the United States to examine whether genetic factors account for part of the covariance between the Big Five personality characteristics and the tendency to be an entrepreneur. We…
Moderating the Covariance Between Family Member’s Substance Use Behavior

Science.gov (United States)

Eaves, Lindon J.; Neale, Michael C.

2014-01-01

Twin and family studies implicitly assume that the covariation between family members remains constant across differences in age between the members of the family. However, age-specificity in gene expression for shared environmental factors could generate higher correlations between family members who are more similar in age. Cohort effects (cohort × genotype or cohort × common environment) could have the same effects, and both potentially reduce effect sizes estimated in genome-wide association studies where the subjects are heterogeneous in age. In this paper we describe a model in which the covariance between twins and non-twin siblings is moderated as a function of age difference. We describe the details of the model and simulate data using a variety of different parameter values to demonstrate that model fitting returns unbiased parameter estimates. Power analyses are then conducted to estimate the sample sizes required to detect the effects of moderation in a design of twins and siblings. Finally, the model is applied to data on cigarette smoking. We find that (1) the model effectively recovers the simulated parameters, (2) the power is relatively low and therefore requires large sample sizes before small to moderate effect sizes can be found reliably, and (3) the genetic covariance between siblings for smoking behavior decays very rapidly. Result 3 implies that, e.g., genome-wide studies of smoking behavior that use individuals assessed at different ages, or belonging to different birth-year cohorts may have had substantially reduced power to detect effects of genotype on cigarette use. It also implies that significant special twin environmental effects can be explained by age-moderation in some cases. This effect likely contributes to the missing heritability paradox. PMID:24647834
Condition Number Regularized Covariance Estimation*

Science.gov (United States)

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2012-01-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197
Targeted molecular profiling of rare genetic alterations in colorectal cancer using next-generation sequencing.

Science.gov (United States)

Jauhri, Mayank; Bhatnagar, Akanksha; Gupta, Satish; Shokeen, Yogender; Minhas, Sachin; Aggarwal, Shyam

2016-10-01

Mutation frequencies of common genetic alterations in colorectal cancer have been in the spotlight for many years. This study highlights few rare somatic mutations, which possess the attributes of a potential CRC biomarker yet are often neglected. Next-generation sequencing was performed over 112 tumor samples to detect genetic alterations in 31 rare genes in colorectal cancer. Mutations were detected in 26/31 (83.9 %) uncommon genes, which together contributed toward 149 gene mutations in 67/112 (59.8 %) colorectal cancer patients. The most frequent mutations include KDR (19.6 %), PTEN (17 %), FBXW7 (10.7 %), SMAD4 (10.7 %), VHL (8 %), KIT (8 %), MET (7.1 %), ATM (6.3 %), CTNNB1 (4.5 %) and CDKN2A (4.5 %). RB1, ERBB4 and ERBB2 mutations were persistent in 3.6 % patients. GNAS, FGFR2 and FGFR3 mutations were persistent in 1.8 % patients. Ten genes (EGFR, NOTCH1, SMARCB1, ABL1, STK11, SMO, RET, GNAQ, CSF1R and FLT3) were found mutated in 0.9 % patients. Lastly, no mutations were observed in AKT, HRAS, MAP2K1, PDGFR and JAK2. Significant associations were observed between VHL with tumor site, ERBB4 and SMARCB1 with tumor invasion, CTNNB1 with lack of lymph node involvement and CTNNB1, FGFR2 and FGFR3 with TNM stage. Significantly coinciding mutation pairs include PTEN and SMAD4, PTEN and KDR, EGFR and RET, EGFR and RB1, FBXW7 and CTNNB1, KDR and FGFR2, FLT3 and CTNNB1, RET and RB1, ATM and SMAD4, ATM and CDKN2A, ERBB4 and SMARCB1. This study elucidates few potential colorectal cancer biomarkers, specifically KDR, PTEN, FBXW7 and SMAD4, which are found mutated in more than 10 % patients.
Covariate-adjusted measures of discrimination for survival data

DEFF Research Database (Denmark)

White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth

2015-01-01

by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...
Heteroscedasticity resistant robust covariance matrix estimator

Czech Academy of Sciences Publication Activity Database

Víšek, Jan Ámos

2010-01-01

Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf

Comparative Analyses of Phenotypic Trait Covariation within and among Populations.

Science.gov (United States)

Peiman, Kathryn S; Robinson, Beren W

2017-10-01

Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.
Earth Observation System Flight Dynamics System Covariance Realism

Science.gov (United States)

Zaidi, Waqar H.; Tracewell, David

2016-01-01

This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.
Transforming growth factor-β and breast cancer: Lessons learned from genetically altered mouse models

International Nuclear Information System (INIS)

Wakefield, Lalage M; Yang, Yu-an; Dukhanina, Oksana

2000-01-01

Transforming growth factor (TGF)-βs are plausible candidate tumor suppressors in the breast. They also have oncogenic activities under certain circumstances, however. Genetically altered mouse models provide powerful tools to analyze the complexities of TGF-βaction in the context of the whole animal. Overexpression of TGF-β can suppress tumorigenesis in the mammary gland, raising the possibility that use of pharmacologic agents to enhance TGF-β function locally might be an effective method for the chemoprevention of breast cancer. Conversely, loss of TGF-β response increases spontaneous and induced tumorigenesis in the mammary gland. This confirms that endogenous TGF-βs have tumor suppressor activity in the mammary gland, and suggests that the loss of TGF-β receptors seen in some human breast hyperplasias may play a causal role in tumor development
Determination of covariant Schwinger terms in anomalous gauge theories

International Nuclear Information System (INIS)

Kelnhofer, G.

1991-01-01

A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the commutator anomalies are calculated for the two- and four dimensional case. (Author) 13 refs
Coherent states and covariant semi-spectral measures

International Nuclear Information System (INIS)

Scutaru, H.

1976-01-01

The close connection between Mackey's theory of imprimitivity systems and the so called generalized coherent states introduced by Perelomov is established. Coherent states give a covariant description of the ''localization'' of a quantum system in the phase space in a similar way as the imprimitivity systems give a covariant description of the localization of a quantum system in the configuration space. The observation that for any system of coherent states one can define a covariant semi-spectral measure made possible a rigurous formulation of this idea. A generalization of the notion of coherent states is given. Covariant semi-spectral measures associated with systems of coherent states are defined and characterized. Necessary and sufficient conditions for a unitary representation of a Lie group to be i) a subrepresentation of an induced one and ii) a representation with coherent states are given (author)
Genetic and Clinical Characteristics of Phyllodes Tumors of the Breast

Directory of Open Access Journals (Sweden)

Ji-Yeon Kim

2018-02-01

Full Text Available PURPOSE: Phyllodes tumors (PTs of the breast are rare, accounting for less than 1% of all breast tumors. Among PTs, malignant PTs (MPTs have malignant characteristics and distant metastases occur in about 20% to 30% of MPTs. However, there is no effective treatment for MPTs with distant metastasis, resulting in an abject prognosis. We performed targeted deep sequencing on PTs to identify the associations between genetic alterations and clinical prognosis. METHODS: We performed targeted deep sequencing to evaluate the genetic characteristics of PTs and analyzed the relationships between clinical and genetic characteristics. RESULTS: A total of 17 PTs were collected between 2001 and 2012. Histologic review was performed by pathologists. The samples included three benign PTs, one borderline PT, and 13 MPTs. The most frequently detected genetic alteration occurred in the TERT promoter region (70.6%, followed by MED12 (64.7%. EGFR amplification and TP53 alteration were detected in four MPTs without genetic alterations in MED12 and TERT promoter regions. Genetic alterations of RARA and ZNF703 were repeatedly found in PTs with local recurrence, and genetic alterations of SETD2, BRCA2, and TSC1 were detected in PTs with distant metastasis. Especially, MPT harboring PTEN and RB1 copy number deletion showed rapid disease progression. CONCLUSIONS: In this study, we provide genetic characterization and potential therapeutic target for this rare, potentially lethal disease. Further large-scale comprehensive genetic study and functional validation are warranted.
Covariance NMR Processing and Analysis for Protein Assignment.

Science.gov (United States)

Harden, Bradley J; Frueh, Dominique P

2018-01-01

During NMR resonance assignment it is often necessary to relate nuclei to one another indirectly, through their common correlations to other nuclei. Covariance NMR has emerged as a powerful technique to correlate such nuclei without relying on error-prone peak peaking. However, false-positive artifacts in covariance spectra have impeded a general application to proteins. We recently introduced pre- and postprocessing steps to reduce the prevalence of artifacts in covariance spectra, allowing for the calculation of a variety of 4D covariance maps obtained from diverse combinations of pairs of 3D spectra, and we have employed them to assign backbone and sidechain resonances in two large and challenging proteins. In this chapter, we present a detailed protocol describing how to (1) properly prepare existing 3D spectra for covariance, (2) understand and apply our processing script, and (3) navigate and interpret the resulting 4D spectra. We also provide solutions to a number of errors that may occur when using our script, and we offer practical advice when assigning difficult signals. We believe such 4D spectra, and covariance NMR in general, can play an integral role in the assignment of NMR signals.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements.

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2013-09-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Touch imprint cytology with massively parallel sequencing (TIC-seq): a simple and rapid method to snapshot genetic alterations in tumors.

Science.gov (United States)

Amemiya, Kenji; Hirotsu, Yosuke; Goto, Taichiro; Nakagomi, Hiroshi; Mochizuki, Hitoshi; Oyama, Toshio; Omata, Masao

2016-12-01

Identifying genetic alterations in tumors is critical for molecular targeting of therapy. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissue is usually employed for genetic analysis. However, DNA extracted from FFPE tissue is often not suitable for analysis because of its low levels and poor quality. Additionally, FFPE sample preparation is time-consuming. To provide early treatment for cancer patients, a more rapid and robust method is required for precision medicine. We present a simple method for genetic analysis, called touch imprint cytology combined with massively paralleled sequencing (touch imprint cytology [TIC]-seq), to detect somatic mutations in tumors. We prepared FFPE tissues and TIC specimens from tumors in nine lung cancer patients and one patient with breast cancer. We found that the quality and quantity of TIC DNA was higher than that of FFPE DNA, which requires microdissection to enrich DNA from target tissues. Targeted sequencing using a next-generation sequencer obtained sufficient sequence data using TIC DNA. Most (92%) somatic mutations in lung primary tumors were found to be consistent between TIC and FFPE DNA. We also applied TIC DNA to primary and metastatic tumor tissues to analyze tumor heterogeneity in a breast cancer patient, and showed that common and distinct mutations among primary and metastatic sites could be classified into two distinct histological subtypes. TIC-seq is an alternative and feasible method to analyze genomic alterations in tumors by simply touching the cut surface of specimens to slides. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.
Melanoma genetics

DEFF Research Database (Denmark)

Read, Jazlyn; Wadt, Karin A W; Hayward, Nicholas K

2015-01-01

Approximately 10% of melanoma cases report a relative affected with melanoma, and a positive family history is associated with an increased risk of developing melanoma. Although the majority of genetic alterations associated with melanoma development are somatic, the underlying presence of herita......Approximately 10% of melanoma cases report a relative affected with melanoma, and a positive family history is associated with an increased risk of developing melanoma. Although the majority of genetic alterations associated with melanoma development are somatic, the underlying presence...... in a combined total of approximately 50% of familial melanoma cases, the underlying genetic basis is unexplained for the remainder of high-density melanoma families. Aside from the possibility of extremely rare mutations in a few additional high penetrance genes yet to be discovered, this suggests a likely...... polygenic component to susceptibility, and a unique level of personal melanoma risk influenced by multiple low-risk alleles and genetic modifiers. In addition to conferring a risk of cutaneous melanoma, some 'melanoma' predisposition genes have been linked to other cancers, with cancer clustering observed...
Some remarks on general covariance of quantum theory

International Nuclear Information System (INIS)

Schmutzer, E.

1977-01-01

If one accepts Einstein's general principle of relativity (covariance principle) also for the sphere of microphysics (quantum, mechanics, quantum field theory, theory of elemtary particles), one has to ask how far the fundamental laws of traditional quantum physics fulfil this principle. Attention is here drawn to a series of papers that have appeared during the last years, in which the author criticized the usual scheme of quantum theory (Heisenberg picture, Schroedinger picture etc.) and presented a new foundation of the basic laws of quantum physics, obeying the 'principle of fundamental covariance' (Einstein's covariance principle in space-time and covariance principle in Hilbert space of quantum operators and states). (author)
Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Gene–gene (CFH with ARMS2 and HTRA1) interactions and correlations with environmental traits (smoking and body mass index) have been established as significant covariates in AMD pathology. In this review, we have provided an overview on the underlying molecular genetic mechanisms in AMD worldwide and ...
Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

Science.gov (United States)

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.
VHL genetic alteration in CCRCC does not determine de-regulation of HIF, CAIX, hnRNP A2/B1 and osteopontin.

LENUS (Irish Health Repository)

Nyhan, Michelle J

2012-01-31

BACKGROUND: von Hippel-Lindau (VHL) tumour suppressor gene inactivation is associated with clear cell renal cell carcinoma (CCRCC) development. The VHL protein (pVHL) has been proposed to regulate the expression of several proteins including Hypoxia Inducible Factor-alpha (HIF-alpha), carbonic anhydrase (CA)IX, heterogeneous nuclear ribonucleoprotein (hnRNP) A2\\/B1 and osteopontin. pVHL has been characterized in vitro, however, clinical studies are limited. We evaluated the impact of VHL genetic alterations on the expression of several pVHL protein targets in paired normal and tumor tissue. METHODS: The VHL gene was sequenced in 23 CCRCC patients and VHL transcript levels were evaluated by real-time RT-PCR. Expression of pVHL\\'s protein targets were determined by Western blotting in 17 paired patient samples. RESULTS: VHL genetic alterations were identified in 43.5% (10\\/23) of CCRCCs. HIF-1alpha, HIF-2alpha and CAIX were up-regulated in 88.2% (15\\/17), 100% (17\\/17) and 88.2% (15\\/17) of tumors respectively and their expression is independent of VHL status. hnRNP A2\\/B1 and osteopontin expression was variable in CCRCCs and had no association with VHL genetic status. CONCLUSION: As expression of these proposed pVHL targets can be achieved independently of VHL mutation (and possibly by hypoxia alone), these data suggests that other pVHL targets may be more crucial in renal carcinogenesis.
The Bayesian Covariance Lasso.

Science.gov (United States)

Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G

2013-04-01

Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Genetic and epigenetic alterations of Brassica nigra introgression lines from somatic hybridization: a resource for cauliflower improvement

Directory of Open Access Journals (Sweden)

Guixiang Wang

2016-08-01

Full Text Available Broad phenotypic variations were obtained previously in derivatives from the asymmetric somatic hybridization of cauliflower ‘Korso’ (Brassica oleracea var. botrytis, 2n = 18, CC genome and black mustard ‘G1/1’ (Brassica nigra, 2n = 16, BB genome. However, the mechanisms underlying these variations were unknown. In this study, 28 putative introgression lines (ILs were pre-selected according to a series of morphological (leaf shape and color, plant height and branching, curd features, and flower traits and physiological (black rot/club root resistance characters. Multi-color fluorescence in situ hybridization revealed that these plants contained 18 chromosomes derived from ‘Korso’. Molecular marker (65 simple sequence repeats and 77 amplified fragment length polymorphisms analysis identified the presence of ‘G1/1’ DNA segments (average 7.5%. Additionally, DNA profiling revealed many genetic and epigenetic differences among the ILs, including sequence alterations, deletions, and variation in patterns of cytosine methylation. The frequency of fragments lost (5.1% was significantly higher than presence of novel bands (1.4%, and the presence of fragments specific to B. carinata (BBCC 2n = 34 were common (average 15.5%. Methylation-sensitive amplified polymorphism analysis indicated that methylation changes were common and that hypermethylation (12.4% was more frequent than hypomethylation (4.8%. Our results suggested that asymmetric somatic hybridization and alien DNA introgression induced genetic and epigenetic alterations. Thus, these ILs represent an important, novel germplasm resource for cauliflower improvement that can be mined for diverse traits of interest to breeders and researchers.
Galaxy-galaxy lensing estimators and their covariance properties

Science.gov (United States)

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose

2017-11-01

We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Galaxy–galaxy lensing estimators and their covariance properties

International Nuclear Information System (INIS)

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; Slosar, Anze; Gonzalez, Jose Vazquez

2017-01-01

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Treatment Effects with Many Covariates and Heteroskedasticity

DEFF Research Database (Denmark)

Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K.

The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results...
Combined M-FISH and CGH analysis allows comprehensive description of genetic alterations in neuroblastoma cell lines.

Science.gov (United States)

Van Roy, N; Van Limbergen, H; Vandesompele, J; Van Gele, M; Poppe, B; Salwen, H; Laureys, G; Manoel, N; De Paepe, A; Speleman, F

2001-10-01

Cancer cell lines are essential gene discovery tools and have often served as models in genetic and functional studies of particular tumor types. One of the future challenges is comparison and interpretation of gene expression data with the available knowledge on the genomic abnormalities in these cell lines. In this context, accurate description of these genomic abnormalities is required. Here, we show that a combination of M-FISH with banding analysis, standard FISH, and CGH allowed a detailed description of the genetic alterations in 16 neuroblastoma cell lines. In total, 14 cryptic chromosome rearrangements were detected, including a balanced t(2;4)(p24.3;q34.3) translocation in cell line NBL-S, with the 2p24 breakpoint located at about 40 kb from MYCN. The chromosomal origin of 22 marker chromosomes and 41 cytogenetically undefined translocated segments was determined. Chromosome arm 2 short arm translocations were observed in six cell lines (38%) with and five (31%) without MYCN amplification, leading to partial chromosome arm 2p gain in all but one cell line and loss of material in the various partner chromosomes, including 1p and 11q. These 2p gains were often masked in the GGH profiles due to MYCN amplification. The commonly overrepresented region was chromosome segment 2pter-2p22, which contains the MYCN gene, and five out of eleven 2p breakpoints clustered to the interface of chromosome bands 2p16 and 2p21. In neuroblastoma cell line SJNB-12, with double minutes (dmins) but no MYCN amplification, the dmins were shown to be derived from 16q22-q23 sequences. The ATBF1 gene, an AT-binding transcription factor involved in normal neurogenesis and located at 16q22.2, was shown to be present in the amplicon. This is the first report describing the possible implication of ATBF1 in neuroblastoma cells. We conclude that a combined approach of M-FISH, cytogenetics, and CGH allowed a more complete and accurate description of the genetic alterations occurring in the

Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.

Science.gov (United States)

Xie, Yanmei; Zhang, Biao

2017-04-20

Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and
Cortical Dysconnectivity Measured by Structural Covariance Is Associated With the Presence of Psychotic Symptoms in 22q11.2 Deletion Syndrome.

Science.gov (United States)

Sandini, Corrado; Scariati, Elisa; Padula, Maria Carmela; Schneider, Maude; Schaer, Marie; Van De Ville, Dimitri; Eliez, Stephan

2018-05-01

22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphology is a method of exploring connectivity among brain regions that to date has not been employed in 22q11DS. In the present study we employed structural covariance of cortical thickness to explore connectivity alterations in a group of 108 patients with 22q11DS compared with 96 control subjects. We subsequently divided patients into two subgroups of 31 subjects each according to the presence of attenuated psychotic symptoms. FreeSurfer software was used to obtain the mean cortical thickness in 148 brain regions from T1-weighted 3T images. For each population we reconstructed a brain graph using Pearson correlation between the average thickness of each couple of brain regions, which we characterized in terms of mean correlation strength and in terms of network architecture using graph theory. Patients with 22q11DS presented increased mean correlation strength, but there was no difference in global architecture compared with control subjects. However, symptomatic patients presented increased mean correlation strength coupled with increased segregation and decreased integration compared with both control subjects and nonsymptomatic patients. They also presented increased centrality for a cluster of anterior cingulate and dorsomedial prefrontal regions. These results confirm the importance of cortical dysconnectivity in the physiopathology of psychosis. Moreover they support the significance of aberrant anterior cingulate connectivity. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Cosmic censorship conjecture revisited: covariantly

International Nuclear Information System (INIS)

Hamid, Aymen I M; Goswami, Rituparno; Maharaj, Sunil D

2014-01-01

In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general locally rotationally symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible. (paper)
The Protective Effect of Minocycline in a Paraquat-Induced Parkinson's Disease Model in Drosophila is Modified in Altered Genetic Backgrounds

Directory of Open Access Journals (Sweden)

Arati A. Inamdar

2012-01-01

Full Text Available Epidemiological studies link the herbicide paraquat to increased incidence of Parkinson's disease (PD. We previously reported that Drosophila exposed to paraquat recapitulate PD symptoms, including region-specific degeneration of dopaminergic neurons. Minocycline, a tetracycline derivative, exerts ameliorative effects in neurodegenerative disease models, including Drosophila. We investigated whether our environmental toxin-based PD model could contribute to an understanding of cellular and genetic mechanisms of minocycline action and whether we could assess potential interference with these drug effects in altered genetic backgrounds. Cofeeding of minocycline with paraquat prolonged survival, rescued mobility defects, blocked generation of reactive oxygen species, and extended dopaminergic neuron survival, as has been reported previously for a genetic model of PD in Drosophila. We then extended this study to identify potential interactions of minocycline with genes regulating dopamine homeostasis that might modify protection against paraquat and found that deficits in GTP cyclohydrolase adversely affect minocycline rescue. We further performed genetic studies to identify signaling pathways that are necessary for minocycline protection against paraquat toxicity and found that mutations in the Drosophila genes that encode c-Jun N-terminal kinase (JNK and Akt/Protein kinase B block minocycline rescue.
Evaluation of covariance in theoretical calculation of nuclear data

International Nuclear Information System (INIS)

Kikuchi, Yasuyuki

1981-01-01

Covariances of the cross sections are discussed on the statistical model calculations. Two categories of covariance are discussed: One is caused by the model approximation and the other by the errors in the model parameters. As an example, the covariances are calculated for 100 Ru. (author)
Updated Covariance Processing Capabilities in the AMPX Code System

International Nuclear Information System (INIS)

Wiarda, Dorothea; Dunn, Michael E.

2007-01-01

A concerted effort is in progress within the nuclear data community to provide new cross-section covariance data evaluations to support sensitivity/uncertainty analyses of fissionable systems. The objective of this work is to update processing capabilities of the AMPX library to process the latest Evaluated Nuclear Data File (ENDF)/B formats to generate covariance data libraries for radiation transport software such as SCALE. The module PUFF-IV was updated to allow processing of new ENDF covariance formats in the resolved resonance region. In the resolved resonance region, covariance matrices are given in terms of resonance parameters, which need to be processed into covariance matrices with respect to the group-averaged cross-section data. The parameter covariance matrix can be quite large if the evaluation has many resonances. The PUFF-IV code has recently been used to process an evaluation of 235U, which was prepared in collaboration between Oak Ridge National Laboratory and Los Alamos National Laboratory.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Impact of the 235U Covariance Data in Benchmark Calculations

International Nuclear Information System (INIS)

Leal, Luiz C.; Mueller, D.; Arbanas, G.; Wiarda, D.; Derrien, H.

2008-01-01

The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235U. The resulting 235U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235U covariance data in calculations of critical benchmark systems
Impact of the 235U covariance data in benchmark calculations

International Nuclear Information System (INIS)

Leal, Luiz; Mueller, Don; Arbanas, Goran; Wiarda, Dorothea; Derrien, Herve

2008-01-01

The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes' method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235 U. The resulting 235 U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235 U covariance data in calculations of critical benchmark systems. (authors)
Parameters of the covariance function of galaxies

International Nuclear Information System (INIS)

Fesenko, B.I.; Onuchina, E.V.

1988-01-01

The two-point angular covariance functions for two samples of galaxies are considered using quick methods of analysis. It is concluded that in the previous investigations the amplitude of the covariance function in the Lick counts was overestimated and the rate of decrease of the function underestimated
Generally covariant gauge theories

International Nuclear Information System (INIS)

Capovilla, R.

1992-01-01

A new class of generally covariant gauge theories in four space-time dimensions is investigated. The field variables are taken to be a Lie algebra valued connection 1-form and a scalar density. Modulo an important degeneracy, complex [euclidean] vacuum general relativity corresponds to a special case in this class. A canonical analysis of the generally covariant gauge theories with the same gauge group as general relativity shows that they describe two degrees of freedom per space point, qualifying therefore as a new set of neighbors of general relativity. The modification of the algebra of the constraints with respect to the general relativity case is computed; this is used in addressing the question of how general relativity stands out from its neighbors. (orig.)
Genetic analysis of growth traits in Polled Nellore cattle raised on pasture in tropical region using Bayesian approaches.

Science.gov (United States)

Lopes, Fernando Brito; Magnabosco, Cláudio Ulhôa; Paulini, Fernanda; da Silva, Marcelo Corrêa; Miyagi, Eliane Sayuri; Lôbo, Raysildo Barbosa

2013-01-01

Components of (co)variance and genetic parameters were estimated for adjusted weights at ages 120 (W120), 240 (W240), 365 (W365) and 450 (W450) days of Polled Nellore cattle raised on pasture and born between 1987 and 2010. Analyses were performed using an animal model, considering fixed effects: herd-year-season of birth and calf sex as contemporary groups and the age of cow as a covariate. Gibbs Samplers were used to estimate (co)variance components, genetic parameters and additive genetic effects, which accounted for great proportion of total variation in these traits. High direct heritability estimates for the growth traits were revealed and presented mean 0.43, 0.61, 0.72 and 0.67 for W120, W240, W365 and W450, respectively. Maternal heritabilities were 0.07 and 0.08 for W120 and W240, respectively. Direct additive genetic correlations between the weight at 120, 240, 365 and 450 days old were strong and positive. These estimates ranged from 0.68 to 0.98. Direct-maternal genetic correlations were negative for W120 and W240. The estimates ranged from -0.31 to -0.54. Estimates of maternal heritability ranged from 0.056 to 0.092 for W120 and from 0.064 to 0.096 for W240. This study showed that genetic progress is possible for the growth traits we studied, which is a novel and favorable indicator for an upcoming and promising Polled Zebu breed in Tropical regions. Maternal effects influenced the performance of weight at 120 and 240 days old. These effects should be taken into account in genetic analyses of growth traits by fitting them as a genetic or a permanent environmental effect, or even both. In general, due to a medium-high estimate of environmental (co)variance components, management and feeding conditions for Polled Nellore raised at pasture in tropical regions of Brazil needs improvement and growth performance can be enhanced.
Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

Science.gov (United States)

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
MYC protein expression and genetic alterations have prognostic impact in patients with diffuse large B-cell lymphoma treated with immunochemotherapy.

Science.gov (United States)

Valera, Alexandra; López-Guillermo, Armando; Cardesa-Salzmann, Teresa; Climent, Fina; González-Barca, Eva; Mercadal, Santiago; Espinosa, Iñigo; Novelli, Silvana; Briones, Javier; Mate, José L; Salamero, Olga; Sancho, Juan M; Arenillas, Leonor; Serrano, Sergi; Erill, Nadina; Martínez, Daniel; Castillo, Paola; Rovira, Jordina; Martínez, Antonio; Campo, Elias; Colomo, Luis

2013-10-01

MYC alterations influence the survival of patients with diffuse large B-cell lymphoma. Most studies have focused on MYC translocations but there is little information regarding the impact of numerical alterations and protein expression. We analyzed the genetic alterations and protein expression of MYC, BCL2, BCL6, and MALT1 in 219 cases of diffuse large B-cell lymphoma. MYC rearrangement occurred as the sole abnormality (MYC single-hit) in 3% of cases, MYC and concurrent BCL2 and/or BCL6 rearrangements (MYC double/triple-hit) in 4%, MYC amplifications in 2% and MYC gains in 19%. MYC single-hit, MYC double/triple-hit and MYC amplifications, but not MYC gains or other gene rearrangements, were associated with unfavorable progression-free survival and overall survival. MYC protein expression, evaluated using computerized image analysis, captured the unfavorable prognosis of MYC translocations/amplifications and identified an additional subset of patients without gene alterations but with similar poor prognosis. Patients with tumors expressing both MYC/BCL2 had the worst prognosis, whereas those with double-negative tumors had the best outcome. High MYC expression was associated with shorter overall survival irrespectively of the International Prognostic Index and BCL2 expression. In conclusion, MYC protein expression identifies a subset of diffuse large B-cell lymphoma with very poor prognosis independently of gene alterations and other prognostic parameters.
New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings.

Science.gov (United States)

Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia

2016-06-01

Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.
EvolQG - An R package for evolutionary quantitative genetics [version 2; referees: 1 approved, 2 approved with reservations

Directory of Open Access Journals (Sweden)

Diogo Melo

2016-06-01

Full Text Available We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the EvolQG package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification.
Nonrelativistic fluids on scale covariant Newton-Cartan backgrounds

Science.gov (United States)

Mitra, Arpita

2017-12-01

The nonrelativistic covariant framework for fields is extended to investigate fields and fluids on scale covariant curved backgrounds. The scale covariant Newton-Cartan background is constructed using the localization of space-time symmetries of nonrelativistic fields in flat space. Following this, we provide a Weyl covariant formalism which can be used to study scale invariant fluids. By considering ideal fluids as an example, we describe its thermodynamic and hydrodynamic properties and explicitly demonstrate that it satisfies the local second law of thermodynamics. As a further application, we consider the low energy description of Hall fluids. Specifically, we find that the gauge fields for scale transformations lead to corrections of the Wen-Zee and Berry phase terms contained in the effective action.
Radiation protection philosophy alters

International Nuclear Information System (INIS)

Firmin, G.

1977-01-01

Two significant events that have taken place this year in the field of radiation protection are reported. New SI units have been proposed (and effectively adopted), and the ICRP has revised its recommendations. Changes of emphasis in the latest recommendations (ICRP Publication 26) imply an altered radiation protection philosophy, in particular the relation of dose limits to estimates of average risk, an altered view of the critical organ approach and a new attitude to genetic dose to the population. (author)
Genetic estimation of hot carcass weight in indigenous Matebele ...

African Journals Online (AJOL)

Genetic parameter estimation for simple carcass traits has been confined to the improved goat breeds worldwide unlike in the unimproved breeds in developing countries where goats are numerous. Variance components for additive direct, additive maternal, permanent environmental maternal effects, the covariance ...
Bayes Factor Covariance Testing in Item Response Models.

Science.gov (United States)

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle.

Science.gov (United States)

Barrozo, D; Buzanskas, M E; Oliveira, J A; Munari, D P; Neves, H H R; Queiroz, S A

2012-01-01

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.
The K-Step Spatial Sign Covariance Matrix

NARCIS (Netherlands)

Croux, C.; Dehon, C.; Yadine, A.

2010-01-01

The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its e±ciency while keeping the maximal breakdown
On the covariance matrices in the evaluated nuclear data

International Nuclear Information System (INIS)

Corcuera, R.P.

1983-05-01

The implications of the uncertainties of nuclear data on reactor calculations are shown. The concept of variance, covariance and correlation are expressed first by intuitive definitions and then through statistical theory. The format of the covariance data for ENDF/B is explained and the formulas to obtain the multigroup covariances are given. (Author) [pt
COMPONENTS OF (COVARIANCE FOR AGE AT FIRST AND SECOND CALVING OF NELLORE FEMALES RAISED IN SOUTHERN BRAZIL

Directory of Open Access Journals (Sweden)

Dionéia Magda Everling

2015-10-01

Full Text Available The objective of this study was to estimate the heritability, genetic correlation and estimated breeding values for age at first (AFC and second calving (ASC for Nellore females raised in Southern Brazil. The (covariance and estimated breeding values were obtained using Bayesian inference in a bivariate analysis, adopting an animal model. The average ages were 49.30 and 69.85 months, and the heritabilities were 0.25 and 0.26, respectively for AFC and ASC. The genetic correlation between AFC and ASC was 0.88. The correlation between the classifications of sires according to their estimated breeding values was 0.93. The heritability estimates for AFC and ASC suggest the possibility of obtaining genetic gain by selection. The correlation between these traits close to one indicates that they are controlled by virtually the same genes and when selected for one will advance correlated gain for the other.
Massive data compression for parameter-dependent covariance matrices

Science.gov (United States)

Heavens, Alan F.; Sellentin, Elena; de Mijolla, Damien; Vianello, Alvise

2017-12-01

We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated data sets which are required to estimate the covariance matrix required for the analysis of Gaussian-distributed data. This is relevant when the covariance matrix cannot be calculated directly. The compression is especially valuable when the covariance matrix varies with the model parameters. In this case, it may be prohibitively expensive to run enough simulations to estimate the full covariance matrix throughout the parameter space. This compression may be particularly valuable for the next generation of weak lensing surveys, such as proposed for Euclid and Large Synoptic Survey Telescope, for which the number of summary data (such as band power or shear correlation estimates) is very large, ∼104, due to the large number of tomographic redshift bins which the data will be divided into. In the pessimistic case where the covariance matrix is estimated separately for all points in an Monte Carlo Markov Chain analysis, this may require an unfeasible 109 simulations. We show here that MOPED can reduce this number by a factor of 1000, or a factor of ∼106 if some regularity in the covariance matrix is assumed, reducing the number of simulations required to a manageable 103, making an otherwise intractable analysis feasible.
Phase-covariant quantum cloning of qudits

International Nuclear Information System (INIS)

Fan Heng; Imai, Hiroshi; Matsumoto, Keiji; Wang, Xiang-Bin

2003-01-01

We study the phase-covariant quantum cloning machine for qudits, i.e., the input states in a d-level quantum system have complex coefficients with arbitrary phase but constant module. A cloning unitary transformation is proposed. After optimizing the fidelity between input state and single qudit reduced density operator of output state, we obtain the optimal fidelity for 1 to 2 phase-covariant quantum cloning of qudits and the corresponding cloning transformation
Genetic effect of interleukin-1 beta (C-511T) polymorphism on the structural covariance network and white matter integrity in Alzheimer's disease.

Science.gov (United States)

Huang, Chi-Wei; Hsu, Shih-Wei; Tsai, Shih-Jen; Chen, Nai-Ching; Liu, Mu-En; Lee, Chen-Chang; Huang, Shu-Hua; Chang, Weng-Neng; Chang, Ya-Ting; Tsai, Wan-Chen; Chang, Chiung-Chih

2017-01-18

Inflammatory processes play a pivotal role in the degenerative process of Alzheimer's disease. In humans, a biallelic (C/T) polymorphism in the promoter region (position-511) (rs16944) of the interleukin-1 beta gene has been significantly associated with differences in the secretory capacity of interleukin-1 beta. In this study, we investigated whether this functional polymorphism mediates the brain networks in patients with Alzheimer's disease. We enrolled a total of 135 patients with Alzheimer's disease (65 males, 70 females), and investigated their gray matter structural covariance networks using 3D T1 magnetic resonance imaging and their white matter macro-structural integrities using fractional anisotropy. The patients were classified into two genotype groups: C-carriers (n = 108) and TT-carriers (n = 27), and the structural covariance networks were constructed using seed-based analysis focusing on the default mode network medial temporal or dorsal medial subsystem, salience network and executive control network. Neurobehavioral scores were used as the major outcome factors for clinical correlations. There were no differences between the two genotype groups in the cognitive test scores, seed, or peak cluster volumes and white matter fractional anisotropy. The covariance strength showing C-carriers > TT-carriers was the entorhinal-cingulum axis. There were two peak clusters (Brodmann 6 and 10) in the salience network and four peak clusters (superior prefrontal, precentral, fusiform, and temporal) in the executive control network that showed C-carriers covariance strength. The salience network and executive control network peak clusters in the TT group and the default mode network peak clusters in the C-carriers strongly predicted the cognitive test scores. Interleukin-1 beta C-511 T polymorphism modulates the structural covariance strength on the anterior brain network and entorhinal-interconnected network which were independent of the white
Covariant differential calculus on quantum spheres of odd dimension

International Nuclear Information System (INIS)

Welk, M.

1998-01-01

Covariant differential calculus on the quantum spheres S q 2N-1 is studied. Two classification results for covariant first order differential calculi are proved. As an important step towards a description of the noncommutative geometry of the quantum spheres, a framework of covariant differential calculus is established, including first and higher order calculi and a symmetry concept. (author)
Genetic predisposition toward suicidal ideation in patients with acute coronary syndrome.

Science.gov (United States)

Kang, Hee-Ju; Bae, Kyung-Yeol; Kim, Sung-Wan; Shin, Il-Seon; Hong, Young Joon; Ahn, Youngkeun; Jeong, Myung Ho; Yoon, Jin-Sang; Kim, Jae-Min

2017-11-07

The genetic predisposition toward suicidal ideation has been explored to identify subgroups at high risk and to prevent suicide. Acute coronary syndrome (ACS) is associated with an increased risk of suicide, but few studies have explored the genetic predisposition toward suicide in ACS populations. Therefore, this longitudinal study explored the genetic predisposition toward suicidal ideation in ACS patients. In total, of 969 patients within 2 weeks after ACS, 711 were followed at 1 year after ACS. Suicidal ideation was evaluated with the relevant items on the Montgomery-Åsberg Depression Rating Scale. Ten genetic polymorphisms associated with serotonergic systems, neurotrophic factors, carbon metabolism, and inflammatory cytokines were examined. Associations between genetic polymorphisms and suicidal ideation within 2 weeks and 1 year of ACS were investigated using logistic regression models. The 5-HTTLPR s allele was significantly associated with suicidal ideation within 2 weeks of ACS after adjusting for covariates and after the Bonferroni correction. TNF-α -308 G/A , IL-1β -511 C/T , and IL-1β + 3953C/T were significantly associated with suicidal ideation within 2 weeks after ACS, but these associations did not reach significance after the Bonferroni correction in unadjusted analyses and after adjusting for covariance. However, no significant association between genetic polymorphisms and suicidal ideation was found at 1 year. Genetic predisposition, 5-HTTLPR s allele in particular, may confer susceptibility to suicidal ideation in ACS patients during the acute phase of ACS.
Covariant Spectator Theory of heavy–light and heavy mesons and the predictive power of covariant interaction kernels

Energy Technology Data Exchange (ETDEWEB)

Leitão, Sofia, E-mail: sofia.leitao@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Stadler, Alfred, E-mail: stadler@uevora.pt [Departamento de Física, Universidade de Évora, 7000-671 Évora (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Peña, M.T., E-mail: teresa.pena@tecnico.ulisboa.pt [Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Biernat, Elmar P., E-mail: elmar.biernat@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

2017-01-10

The Covariant Spectator Theory (CST) is used to calculate the mass spectrum and vertex functions of heavy–light and heavy mesons in Minkowski space. The covariant kernel contains Lorentz scalar, pseudoscalar, and vector contributions. The numerical calculations are performed in momentum space, where special care is taken to treat the strong singularities present in the confining kernel. The observed meson spectrum is very well reproduced after fitting a small number of model parameters. Remarkably, a fit to a few pseudoscalar meson states only, which are insensitive to spin–orbit and tensor forces and do not allow to separate the spin–spin from the central interaction, leads to essentially the same model parameters as a more general fit. This demonstrates that the covariance of the chosen interaction kernel is responsible for the very accurate prediction of the spin-dependent quark–antiquark interactions.
Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities

Science.gov (United States)

Finkel, Deborah; Reynolds, Chandra A.; McArdle, John J.; Hamagami, Fumiaki; Pedersen, Nancy L.

2009-01-01

Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories…
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
Bayesian analysis of multi-state data with individual covariates for estimating genetic effects on demography

Science.gov (United States)

Converse, Sarah J.; Royle, J. Andrew; Urbanek, Richard P.

2012-01-01

Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.
A New Approach for Nuclear Data Covariance and Sensitivity Generation

International Nuclear Information System (INIS)

Leal, L.C.; Larson, N.M.; Derrien, H.; Kawano, T.; Chadwick, M.B.

2005-01-01

Covariance data are required to correctly assess uncertainties in design parameters in nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the U.S. Evaluated Nuclear Data File, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. The computer code SAMMY is used in the analysis of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on generalized least-squares formalism (Bayes' theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance-parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, in addition, it also provides the resonance-parameter covariances. For existing resonance-parameter evaluations where no resonance-parameter covariance data are available, the alternative is to use an approach called the 'retroactive' resonance-parameter covariance generation. In the high-energy region the methodology for generating covariance data consists of least-squares fitting and model parameter adjustment. The least-squares fitting method calculates covariances directly from experimental data. The parameter adjustment method employs a nuclear model calculation such as the optical model and the Hauser-Feshbach model, and estimates a covariance for the nuclear model parameters. In this paper we describe the application of the retroactive method and the parameter adjustment method to generate covariance data for the gadolinium isotopes
Genetic parameters in a Swine Population

Directory of Open Access Journals (Sweden)

Dana Popa

2010-05-01

Full Text Available The estimation of the variance-covariance components is a very important step in animal breeding because these components are necessary for: estimation of the genetic parameters, prediction of the breeding value and design of animal breeding programs. The estimation of genetic parameters is the first step in the development of a swine breeding program, using artificial insemination. Various procedures exist for estimation of heritability. There are three major procedures used for estimating heritability: analysis of variance (ANOVA, parents-offspring regression and restricted maximum likelihood (REML. By using ANOVA methodology or regression method it is possible to obtain aberrant values of genetic parameters (negative or over unit value of heritability coefficient, for example which can not be interpreting because is out of biological limits.
Continuous Covariate Imbalance and Conditional Power for Clinical Trial Interim Analyses

Science.gov (United States)

Ciolino, Jody D.; Martin, Renee' H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

Oftentimes valid statistical analyses for clinical trials involve adjustment for known influential covariates, regardless of imbalance observed in these covariates at baseline across treatment groups. Thus, it must be the case that valid interim analyses also properly adjust for these covariates. There are situations, however, in which covariate adjustment is not possible, not planned, or simply carries less merit as it makes inferences less generalizable and less intuitive. In this case, covariate imbalance between treatment groups can have a substantial effect on both interim and final primary outcome analyses. This paper illustrates the effect of influential continuous baseline covariate imbalance on unadjusted conditional power (CP), and thus, on trial decisions based on futility stopping bounds. The robustness of the relationship is illustrated for normal, skewed, and bimodal continuous baseline covariates that are related to a normally distributed primary outcome. Results suggest that unadjusted CP calculations in the presence of influential covariate imbalance require careful interpretation and evaluation. PMID:24607294
Multisample adjusted U-statistics that account for confounding covariates.

Science.gov (United States)

Satten, Glen A; Kong, Maiying; Datta, Somnath

2018-06-19

Multisample U-statistics encompass a wide class of test statistics that allow the comparison of 2 or more distributions. U-statistics are especially powerful because they can be applied to both numeric and nonnumeric data, eg, ordinal and categorical data where a pairwise similarity or distance-like measure between categories is available. However, when comparing the distribution of a variable across 2 or more groups, observed differences may be due to confounding covariates. For example, in a case-control study, the distribution of exposure in cases may differ from that in controls entirely because of variables that are related to both exposure and case status and are distributed differently among case and control participants. We propose to use individually reweighted data (ie, using the stratification score for retrospective data or the propensity score for prospective data) to construct adjusted U-statistics that can test the equality of distributions across 2 (or more) groups in the presence of confounding covariates. Asymptotic normality of our adjusted U-statistics is established and a closed form expression of their asymptotic variance is presented. The utility of our approach is demonstrated through simulation studies, as well as in an analysis of data from a case-control study conducted among African-Americans, comparing whether the similarity in haplotypes (ie, sets of adjacent genetic loci inherited from the same parent) occurring in a case and a control participant differs from the similarity in haplotypes occurring in 2 control participants. Copyright © 2018 John Wiley & Sons, Ltd.
Covariance Function for Nearshore Wave Assimilation Systems

Science.gov (United States)

2018-01-30

which is applicable for any spectral wave model. The four dimensional variational (4DVar) assimilation methods are based on the mathematical ...covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications , the covariance function depends primarily on...SPECTRAL ACTION DENSITY, RESPECTIVELY. ............................ 5 FIGURE 2. TOP ROW: STATISTICAL ANALYSIS OF THE WAVE-FIELD PROPERTIES AT THE
Visualization and assessment of spatio-temporal covariance properties

KAUST Repository

Huang, Huang

2017-11-23

Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.
Summary of the Workshop on Neutron Cross Section Covariances

International Nuclear Information System (INIS)

Smith, Donald L.

2008-01-01

A Workshop on Neutron Cross Section Covariances was held from June 24-27, 2008, in Port Jefferson, New York. This Workshop was organized by the National Nuclear Data Center, Brookhaven National Laboratory, to provide a forum for reporting on the status of the growing field of neutron cross section covariances for applications and for discussing future directions of the work in this field. The Workshop focused on the following four major topical areas: covariance methodology, recent covariance evaluations, covariance applications, and user perspectives. Attention was given to the entire spectrum of neutron cross section covariance concerns ranging from light nuclei to the actinides, and from the thermal energy region to 20 MeV. The papers presented at this conference explored topics ranging from fundamental nuclear physics concerns to very specific applications in advanced reactor design and nuclear criticality safety. This paper provides a summary of this workshop. Brief comments on the highlights of each Workshop contribution are provided. In addition, a perspective on the achievements and shortcomings of the Workshop as well as on the future direction of research in this field is offered

Real-time probabilistic covariance tracking with efficient model update.

Science.gov (United States)

Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li

2012-05-01

The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.
A three domain covariance framework for EEG/MEG data.

Science.gov (United States)

Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C

2015-10-01

In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.
Dynamics of ASXL1 mutation and other associated genetic alterations during disease progression in patients with primary myelodysplastic syndrome

International Nuclear Information System (INIS)

Chen, T-C; Hou, H-A; Chou, W-C; Tang, J-L; Kuo, Y-Y; Chen, C-Y; Tseng, M-H; Huang, C-F; Lai, Y-J; Chiang, Y-C; Lee, F-Y; Liu, M-C; Liu, C-W; Liu, C-Y; Yao, M; Huang, S-Y; Ko, B-S; Hsu, S-C; Wu, S-J; Tsay, W; Chen, Y-C; Tien, H-F

2014-01-01

Recently, mutations of the additional sex comb-like 1 (ASXL1) gene were identified in patients with myelodysplastic syndrome (MDS), but the interaction of this mutation with other genetic alterations and its dynamic changes during disease progression remain to be determined. In this study, ASXL1 mutations were identified in 106 (22.7%) of the 466 patients with primary MDS based on the French-American-British (FAB) classification and 62 (17.1%) of the 362 patients based on the World Health Organization (WHO) classification. ASXL1 mutation was closely associated with trisomy 8 and mutations of RUNX1, EZH2, IDH, NRAS, JAK2, SETBP1 and SRSF2, but was negatively associated with SF3B1 mutation. Most ASXL1-mutated patients (85%) had concurrent other gene mutations at diagnosis. ASXL1 mutation was an independent poor prognostic factor for survival. Sequential studies showed that the original ASXL1 mutation remained unchanged at disease progression in all 32 ASXL1-mutated patients but were frequently accompanied with acquisition of mutations of other genes, including RUNX1, NRAS, KRAS, SF3B1, SETBP1 and chromosomal evolution. On the other side, among the 80 ASXL1-wild patients, only one acquired ASXL1 mutation at leukemia transformation. In conclusion, ASXL1 mutations in association with other genetic alterations may have a role in the development of MDS but contribute little to disease progression
Integrated analysis of genetic data with R

Directory of Open Access Journals (Sweden)

Zhao Jing

2006-01-01

Full Text Available Abstract Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially when genetic data are analysed in conjunction with a large number of covariates. Here, R http://www.r-project.org, a free, flexible and platform-independent environment for statistical modelling and graphics is explored as an integrated system for genetic data analysis. An overview of some packages currently available for analysis of genetic data is given. This is followed by examples of package development and practical applications. With clear advantages in data management, graphics, statistical analysis, programming, internet capability and use of available codes, it is a feasible, although challenging, task to develop it into an integrated platform for genetic analysis; this will require the joint efforts of many researchers.
Bayesian hierarchical model for large-scale covariance matrix estimation.

Science.gov (United States)

Zhu, Dongxiao; Hero, Alfred O

2007-12-01

Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.
Genetic Evaluation and Ranking of Different Animal Models Using ...

African Journals Online (AJOL)

An animal model utilizes all relationships available in a given data set. Estimates for variance components for additive direct, additive maternal, maternal environmental and direct environmental effects, and their covariances between direct and maternal genetic effects for post weaning growth traits have been obtained with ...
Genetic parameters for quail body weights using a random ...

African Journals Online (AJOL)

A model including fixed and random linear regressions is described for analyzing body weights at different ages. In this study, (co)variance components, heritabilities for quail weekly weights and genetic correlations among these weights were estimated using a random regression model by DFREML under DXMRR option.
The genetic analysis of repeated measures I: Simplex models

NARCIS (Netherlands)

Molenaar, P.C.M.; Boomsma, D.I.

1987-01-01

Extends the simplex model to a model that may be used for the genetic and environmental analysis of covariance (ANCOVA) structures. This "double" simplex structure can be specified as a linear structural relationships model. It is shown that data that give rise to a simplex correlation structure,
Cross-covariance functions for multivariate random fields based on latent dimensions

KAUST Repository

Apanasovich, T. V.

2010-02-16

The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable and computationally feasible classes of cross-covariance functions in closed form. We focus on spatio-temporal cross-covariance functions that can be nonseparable, asymmetric and can have different covariance structures, for instance different smoothness parameters, in each component. We discuss estimation of these models and perform a small simulation study to demonstrate our approach. We illustrate our methodology on a trivariate spatio-temporal pollution dataset from California and demonstrate that our cross-covariance performs better than other competing models. © 2010 Biometrika Trust.
Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander

2015-01-05

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul

2015-01-01

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Position Error Covariance Matrix Validation and Correction

Science.gov (United States)

Frisbee, Joe, Jr.

2016-01-01

In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.
Covariant fields on anti-de Sitter spacetimes

Science.gov (United States)

Cotăescu, Ion I.

2018-02-01

The covariant free fields of any spin on anti-de Sitter (AdS) spacetimes are studied, pointing out that these transform under isometries according to covariant representations (CRs) of the AdS isometry group, induced by those of the Lorentz group. Applying the method of ladder operators, it is shown that the CRs with unique spin are equivalent with discrete unitary irreducible representations (UIRs) of positive energy of the universal covering group of the isometry one. The action of the Casimir operators is studied finding how the weights of these representations (reps.) may depend on the mass and spin of the covariant field. The conclusion is that on AdS spacetime, one cannot formulate a universal mass condition as in special relativity.
Genetic Alterations in Intervertebral Disc Disease

Directory of Open Access Journals (Sweden)

Nikolay L. Martirosyan

2016-11-01

Full Text Available Background: Intervertebral disc degeneration (IVDD is considered a multifactorial disease. The last two decades of research strongly demonstrate that genetic factors contribute about 75% of the IVDD etiology. Recent total genome sequencing studies have shed light on the various single nucleotide polymorphisms (SNPs that are associated with IVDD.Aim: This review explores and presents updated information about the diversity of genetic factors in the inflammatory, degradative, homeostatic, and structural systems involved in the IVDD.Results: SNPs in the genes coding for structural proteins linked with IVDD or disc bulging include the Sp1 polymorphism of COL1A1, Trp3 polymorphism of COL9A3, several polymorphisms of COL11A1 and COL11A2, and a variable number tandem repeat polymorphism of ACAN. The rs4148941 SNP of CHST3 coding for an aggrecan sulfation enzyme is also associated with IVDD. The FokI, TaqI, and ApaI SNPs of the vitamin D receptor gene that is involved in chondrocyte functioning are also associated with IVDD. SNPs relevant to cytokine imbalance in IVDD include 889C/T of IL1a and 15T/A, as well as other SNPs (rs1800795, rs1800796, and rs1800797, of IL6, with effects limited to certain genders and populations. SNPs in collagenase genes include -1605G/D (guanine insertion/deletion of MMP1, -1306C/T of MMP2, -1562C/T and a 5-adenosine (5A variant (in the promotor region of MMP3, -1562C/T of MMP9, and -378T/C of MMP-14. SNPs in aggrecanase genes include 1877T/U of ADAMTS-4 and rs162509 of ADAMTS-5. Among the apoptosis-mediating genes, 1595T/C of the caspase 9 gene, 1525A/G and 1595T/C of the TRAIL gene, and 626C/G of the death receptor 4 gene (DR4 are SNPs associated with IVDD. Among the growth factors involved in disc homeostasis, the rs4871857 SNP of GDF5 was associated with IVDD. VEGF SNPs -2578C/A and -634G/C could foster neovascularization observed in IVDD.Conclusion: Improved understanding of the numerous genetic variants behind various
Covariant Noncommutative Field Theory

Energy Technology Data Exchange (ETDEWEB)

Estrada-Jimenez, S [Licenciaturas en Fisica y en Matematicas, Facultad de Ingenieria, Universidad Autonoma de Chiapas Calle 4a Ote. Nte. 1428, Tuxtla Gutierrez, Chiapas (Mexico); Garcia-Compean, H [Departamento de Fisica, Centro de Investigacion y de Estudios Avanzados del IPN P.O. Box 14-740, 07000 Mexico D.F., Mexico and Centro de Investigacion y de Estudios Avanzados del IPN, Unidad Monterrey Via del Conocimiento 201, Parque de Investigacion e Innovacion Tecnologica (PIIT) Autopista nueva al Aeropuerto km 9.5, Lote 1, Manzana 29, cp. 66600 Apodaca Nuevo Leon (Mexico); Obregon, O [Instituto de Fisica de la Universidad de Guanajuato P.O. Box E-143, 37150 Leon Gto. (Mexico); Ramirez, C [Facultad de Ciencias Fisico Matematicas, Universidad Autonoma de Puebla, P.O. Box 1364, 72000 Puebla (Mexico)

2008-07-02

The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced.
Covariant Noncommutative Field Theory

International Nuclear Information System (INIS)

Estrada-Jimenez, S.; Garcia-Compean, H.; Obregon, O.; Ramirez, C.

2008-01-01

The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced
Physical properties of the Schur complement of local covariance matrices

International Nuclear Information System (INIS)

Haruna, L F; Oliveira, M C de

2007-01-01

General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state ρ 12 described by a 4 x 4 covariance matrix V, the Schur complement of a local covariance submatrix V 1 of it can be interpreted as a new covariance matrix representing a Gaussian operator of party 1 conditioned to local parity measurements on party 2. The connection with a partial parity measurement over a bipartite quantum state and the determination of the reduced Wigner function is given and an operational process of parity measurement is developed. Generalization of this procedure to an n-partite Gaussian state is given, and it is demonstrated that the n - 1 system state conditioned to a partial parity projection is given by a covariance matrix such that its 2 x 2 block elements are Schur complements of special local matrices
Hypergravity-induced altered behavior in Drosophila

Science.gov (United States)

Hosamani, Ravikumar; Wan, Judy; Marcu, Oana; Bhattacharya, Sharmila

2012-07-01

Microgravity and mechanical stress are important factors of the spaceflight environment, and affect astronaut health and behavior. Structural, functional, and behavioral mechanisms of all cells and organisms are adapted to Earth's gravitational force, 1G, while altered gravity can pose challenges to their adaptability to this new environment. On ground, hypergravity paradigms have been used to predict and complement studies on microgravity. Even small changes that take place at a molecular and genetic level during altered gravity may result in changes in phenotypic behavior. Drosophila provides a robust and simple, yet very reliable model system to understand the complexity of hypergravity-induced altered behavior, due to availability of a plethora of genetic tools. Locomotor behavior is a sensitive parameter that reflects the array of molecular adaptive mechanisms recruited during exposure to altered gravity. Thus, understanding the genetic basis of this behavior in a hypergravity environment could potentially extend our understanding of mechanisms of adaptation in microgravity. In our laboratory we are trying to dissect out the cellular and molecular mechanisms underlying hypergravity-induced oxidative stress, and its potential consequences on behavioral alterations by using Drosophila as a model system. In the present study, we employed pan-neuronal and mushroom body specific knock-down adult flies by using Gal4/UAS system to express inverted repeat transgenes (RNAi) to monitor and quantify the hypergravity-induced behavior in Drosophila. We established that acute hypergravity (3G for 60 min) causes a significant and robust decrease in the locomotor behavior in adult Drosophila, and that this change is dependent on genes related to Parkinson's disease, such as DJ-1α , DJ-1β , and parkin. In addition, we also showed that anatomically the control of this behavior is significantly processed in the mushroom body region of the fly brain. This work links a molecular
Covariant n2-plet mass formulas

International Nuclear Information System (INIS)

Davidson, A.

1979-01-01

Using a generalized internal symmetry group analogous to the Lorentz group, we have constructed a covariant n 2 -plet mass operator. This operator is built as a scalar matrix in the (n;n*) representation, and its SU(n) breaking parameters are identified as intrinsic boost ones. Its basic properties are: covariance, Hermiticity, positivity, charge conjugation, quark contents, and a self-consistent n 2 -1, 1 mixing. The GMO and the Okubo formulas are obtained by considering two different limits of the same generalized mass formula
Covariance structure in the skull of Catarrhini: a case of pattern stasis and magnitude evolution.

Science.gov (United States)

de Oliveira, Felipe Bandoni; Porto, Arthur; Marroig, Gabriel

2009-04-01

The study of the genetic variance/covariance matrix (G-matrix) is a recent and fruitful approach in evolutionary biology, providing a window of investigating for the evolution of complex characters. Although G-matrix studies were originally conducted for microevolutionary timescales, they could be extrapolated to macroevolution as long as the G-matrix remains relatively constant, or proportional, along the period of interest. A promising approach to investigating the constancy of G-matrices is to compare their phenotypic counterparts (P-matrices) in a large group of related species; if significant similarity is found among several taxa, it is very likely that the underlying G-matrices are also equivalent. Here we study the similarity of covariance and correlation structure in a broad sample of Old World monkeys and apes (Catarrhini). We made phylogenetically structured comparisons of correlation and covariance matrices derived from 39 skull traits, ranging from between species to the superfamily level. We also compared the overall magnitude of integration between skull traits (r2) for all Catarrhini genera. Our results show that P-matrices were not strictly constant among catarrhines, but the amount of divergence observed among taxa was generally low. There was significant and positive correlation between the amount of divergence in correlation and covariance patterns among the 30 genera and their phylogenetic distances derived from a recently proposed phylogenetic hypothesis. Our data demonstrate that the P-matrices remained relatively similar along the evolutionary history of catarrhines, and comparisons with the G-matrix available for a New World monkey genus (Saguinus) suggests that the same holds for all anthropoids. The magnitude of integration, in contrast, varied considerably among genera, indicating that evolution of the magnitude, rather than the pattern of inter-trait correlations, might have played an important role in the diversification of the

Summary report of technical meeting on neutron cross section covariances

International Nuclear Information System (INIS)

Trkov, A.; Smith, D.L.; Capote Noy, R.

2011-01-01

A summary is given of the Technical Meeting on Neutron Cross Section Covariances. The meeting goal was to assess covariance data needs and recommend appropriate methodologies to address those needs. Discussions on covariance data focused on three general topics: 1) Resonance and unresolved resonance regions; 2) Fast neutron region; and 3) Users' perspective: benchmarks' uncertainty and reactor dosimetry. A number of recommendations for further work were generated and the important work that remains to be done in the field of covariances was identified. (author)
The impact of covariance misspecification in group-based trajectory models for longitudinal data with non-stationary covariance structure.

Science.gov (United States)

Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C

2017-08-01

One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.
Positive semidefinite integrated covariance estimation, factorizations and asynchronicity

DEFF Research Database (Denmark)

Boudt, Kris; Laurent, Sébastien; Lunde, Asger

2017-01-01

An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to estimate the different parameters sequentially with as many...
Cross-covariance based global dynamic sensitivity analysis

Science.gov (United States)

Shi, Yan; Lu, Zhenzhou; Li, Zhao; Wu, Mengmeng

2018-02-01

For identifying the cross-covariance source of dynamic output at each time instant for structural system involving both input random variables and stochastic processes, a global dynamic sensitivity (GDS) technique is proposed. The GDS considers the effect of time history inputs on the dynamic output. In the GDS, the cross-covariance decomposition is firstly developed to measure the contribution of the inputs to the output at different time instant, and an integration of the cross-covariance change over the specific time interval is employed to measure the whole contribution of the input to the cross-covariance of output. Then, the GDS main effect indices and the GDS total effect indices can be easily defined after the integration, and they are effective in identifying the important inputs and the non-influential inputs on the cross-covariance of output at each time instant, respectively. The established GDS analysis model has the same form with the classical ANOVA when it degenerates to the static case. After degeneration, the first order partial effect can reflect the individual effects of inputs to the output variance, and the second order partial effect can reflect the interaction effects to the output variance, which illustrates the consistency of the proposed GDS indices and the classical variance-based sensitivity indices. The MCS procedure and the Kriging surrogate method are developed to solve the proposed GDS indices. Several examples are introduced to illustrate the significance of the proposed GDS analysis technique and the effectiveness of the proposed solution.
Genetics

International Nuclear Information System (INIS)

Hubitschek, H.E.

1975-01-01

Progress is reported on the following research projects: genetic effects of high LET radiations; genetic regulation, alteration, and repair; chromosome replication and the division cycle of Escherichia coli; effects of radioisotope decay in the DNA of microorganisms; initiation and termination of DNA replication in Bacillus subtilis; mutagenesis in mouse myeloma cells; lethal and mutagenic effects of near-uv radiation; effect of 8-methoxypsoralen on photodynamic lethality and mutagenicity in Escherichia coli; DNA repair of the lethal effects of far-uv; and near uv irradiation of bacterial cells
Association of genetic variation in cannabinoid mechanisms and gastric motor functions and satiation in overweight and obesity.

Science.gov (United States)

Vazquez-Roque, M I; Camilleri, M; Vella, A; Carlson, P; Laugen, J; Zinsmeister, A R

2011-07-01

The endocannabinoid system is associated with food intake. We hypothesized that genes regulating cannabinoids are associated with obesity. Genetic variations in fatty acid amide hydroxylase (FAAH) and cannabinoid receptor 1 (CNR1) are associated with satiation and gastric motor function. In 62 overweight or obese adults of European ancestry, single nucleotide polymorphisms of rs806378 (nearest gene CNR1) and rs324420 (nearest gene FAAH) were genotyped and the associations with gastric emptying (GE) of solids and liquids, gastric volume (GV), and satiation [maximum tolerated volume (MTV) and symptoms after Ensure(®) nutrient drink test] were explored using a dominant genetic model, with gender and BMI as covariates. rs806378 CC genotype was associated with reduced fasting GV (210.2±11.0mL for CC group compared to 242.5±11.3mL for CT/TT group, P=0.031) and a modest, non-significant association with GE of solids (P=0.17). rs324420 genotype was not associated with alterations in gastric motor functions; however, there was a difference in the Ensure(®) MTV (1174.6±37.2mL for CC group compared to 1395.0±123.1mL for CA/AA group, P=0.046) suggesting higher satiation with CC genotype. Our data suggest that CNR1 and FAAH are associated with altered gastric functions or satiation that may predispose to obesity. © 2011 Blackwell Publishing Ltd.
Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander

2015-01-07

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul

2015-01-01

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Pu239 Cross-Section Variations Based on Experimental Uncertainties and Covariances

Energy Technology Data Exchange (ETDEWEB)

Sigeti, David Edward [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Brian J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parsons, D. Kent [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-10-18

Algorithms and software have been developed for producing variations in plutonium-239 neutron cross sections based on experimental uncertainties and covariances. The varied cross-section sets may be produced as random samples from the multi-variate normal distribution defined by an experimental mean vector and covariance matrix, or they may be produced as Latin-Hypercube/Orthogonal-Array samples (based on the same means and covariances) for use in parametrized studies. The variations obey two classes of constraints that are obligatory for cross-section sets and which put related constraints on the mean vector and covariance matrix that detemine the sampling. Because the experimental means and covariances do not obey some of these constraints to sufficient precision, imposing the constraints requires modifying the experimental mean vector and covariance matrix. Modification is done with an algorithm based on linear algebra that minimizes changes to the means and covariances while insuring that the operations that impose the different constraints do not conflict with each other.
A scale invariant covariance structure on jet space

DEFF Research Database (Denmark)

Pedersen, Kim Steenstrup; Loog, Marco; Markussen, Bo

2005-01-01

This paper considers scale invariance of statistical image models. We study statistical scale invariance of the covariance structure of jet space under scale space blurring and derive the necessary structure and conditions of the jet covariance matrix in order for it to be scale invariant. As par...
Beyond mean allelic effects: A locus at the major color gene MC1R associates also with differing levels of phenotypic and genetic (co)variance for coloration in barn owls.

Science.gov (United States)

San-Jose, Luis M; Ducret, Valérie; Ducrest, Anne-Lyse; Simon, Céline; Roulin, Alexandre

2017-10-01

The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
Genetic variation shapes protein networks mainly through non-transcriptional mechanisms.

Directory of Open Access Journals (Sweden)

Eric J Foss

2011-09-01

Full Text Available Networks of co-regulated transcripts in genetically diverse populations have been studied extensively, but little is known about the degree to which these networks cause similar co-variation at the protein level. We quantified 354 proteins in a genetically diverse population of yeast segregants, which allowed for the first time construction of a coherent protein co-variation matrix. We identified tightly co-regulated groups of 36 and 93 proteins that were made up predominantly of genes involved in ribosome biogenesis and amino acid metabolism, respectively. Even though the ribosomal genes were tightly co-regulated at both the protein and transcript levels, genetic regulation of proteins was entirely distinct from that of transcripts, and almost no genes in this network showed a significant correlation between protein and transcript levels. This result calls into question the widely held belief that in yeast, as opposed to higher eukaryotes, ribosomal protein levels are regulated primarily by regulating transcript levels. Furthermore, although genetic regulation of the amino acid network was more similar for proteins and transcripts, regression analysis demonstrated that even here, proteins vary predominantly as a result of non-transcriptional variation. We also found that cis regulation, which is common in the transcriptome, is rare at the level of the proteome. We conclude that most inter-individual variation in levels of these particular high abundance proteins in this genetically diverse population is not caused by variation of their underlying transcripts.
Low Genetic Quality Alters Key Dimensions of the Mutational Spectrum.

Directory of Open Access Journals (Sweden)

Nathaniel P Sharp

2016-03-01

Full Text Available Mutations affect individual health, population persistence, adaptation, diversification, and genome evolution. There is evidence that the mutation rate varies among genotypes, but the causes of this variation are poorly understood. Here, we link differences in genetic quality with variation in spontaneous mutation in a Drosophila mutation accumulation experiment. We find that chromosomes maintained in low-quality genetic backgrounds experience a higher rate of indel mutation and a lower rate of gene conversion in a manner consistent with condition-based differences in the mechanisms used to repair DNA double strand breaks. These aspects of the mutational spectrum were also associated with body mass, suggesting that the effect of genetic quality on DNA repair was mediated by overall condition, and providing a mechanistic explanation for the differences in mutational fitness decline among these genotypes. The rate and spectrum of substitutions was unaffected by genetic quality, but we find variation in the probability of substitutions and indels with respect to several aspects of local sequence context, particularly GC content, with implications for models of molecular evolution and genome scans for signs of selection. Our finding that the chances of mutation depend on genetic context and overall condition has important implications for how sequences evolve, the risk of extinction, and human health.
Covarient quantization of heterotic strings in supersymmetric chiral boson formulation

International Nuclear Information System (INIS)

Yu, F.

1992-01-01

This dissertation presents the covariant supersymmetric chiral boson formulation of the heterotic strings. The main feature of this formulation is the covariant quantization of the so-called leftons and rightons -- the (1,0) supersymmetric generalizations of the world-sheet chiral bosons -- that constitute basic building blocks of general heterotic-type string models. Although the (Neveu-Schwarz-Ramond or Green-Schwarz) heterotic strings provide the most realistic string models, their covariant quantization, with the widely-used Siegel formalism, has never been rigorously carried out. It is clarified in this dissertation that the covariant Siegel formalism is pathological upon quantization. As a test, a general classical covariant (NSR) heterotic string action that has the Siegel symmetry is constructed in arbitrary curved space-time coupled to (1,0) world-sheet super-gravity. In the light-cone gauge quantization, the critical dimensions are derived for such an action with leftons and rightons compactified on group manifolds G L x G R . The covariant quantization of this action does not agree with the physical results in the light-cone gauge quantization. This dissertation establishes a new formalism for the covariant quantization of heterotic strings. The desired consistent covariant path integral quantization of supersymmetric chiral bosons, and thus the general (NSR) heterotic-type strings with leftons and rightons compactified on torus circle-times d L S 1 x circle-times d R S 1 are carried out. An infinite set of auxiliary (1,0) scalar superfields is introduced to convert the second-class chiral constraint into first-class ones. The covariant gauge-fixed action has an extended BRST symmetry described by the graded algebra GL(1/1). A regularization respecting this symmetry is proposed to deal with the contributions of the infinite towers of auxiliary fields and associated ghosts
Covariance of time-ordered products implies local commutativity of fields

International Nuclear Information System (INIS)

Greenberg, O.W.

2006-01-01

We formulate Lorentz covariance of a quantum field theory in terms of covariance of time-ordered products (or other Green's functions). This formulation of Lorentz covariance implies spacelike local commutativity or anticommutativity of fields, sometimes called microscopic causality or microcausality. With this formulation microcausality does not have to be taken as a separate assumption
Noncommutative Gauge Theory with Covariant Star Product

International Nuclear Information System (INIS)

Zet, G.

2010-01-01

We present a noncommutative gauge theory with covariant star product on a space-time with torsion. In order to obtain the covariant star product one imposes some restrictions on the connection of the space-time. Then, a noncommutative gauge theory is developed applying this product to the case of differential forms. Some comments on the advantages of using a space-time with torsion to describe the gravitational field are also given.
Altered causal connectivity of resting state brain networks in amnesic MCI.

Directory of Open Access Journals (Sweden)

Peipeng Liang

Full Text Available Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI have concentrated on functional connectivity (FC based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN, hippocampal cortical memory network (HCMN, dorsal attention network (DAN and fronto-parietal control network (FPCN. Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE, and California verbal learning test (CVLT scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.
Signs of depth-luminance covariance in 3-D cluttered scenes.

Science.gov (United States)

Scaccia, Milena; Langer, Michael S

2018-03-01

In three-dimensional (3-D) cluttered scenes such as foliage, deeper surfaces often are more shadowed and hence darker, and so depth and luminance often have negative covariance. We examined whether the sign of depth-luminance covariance plays a role in depth perception in 3-D clutter. We compared scenes rendered with negative and positive depth-luminance covariance where positive covariance means that deeper surfaces are brighter and negative covariance means deeper surfaces are darker. For each scene, the sign of the depth-luminance covariance was given by occlusion cues. We tested whether subjects could use this sign information to judge the depth order of two target surfaces embedded in 3-D clutter. The clutter consisted of distractor surfaces that were randomly distributed in a 3-D volume. We tested three independent variables: the sign of the depth-luminance covariance, the colors of the targets and distractors, and the background luminance. An analysis of variance showed two main effects: Subjects performed better when the deeper surfaces were darker and when the color of the target surfaces was the same as the color of the distractors. There was also a strong interaction: Subjects performed better under a negative depth-luminance covariance condition when targets and distractors had different colors than when they had the same color. Our results are consistent with a "dark means deep" rule, but the use of this rule depends on the similarity between the color of the targets and color of the 3-D clutter.
Covariance fitting of highly-correlated data in lattice QCD

Science.gov (United States)

Yoon, Boram; Jang, Yong-Chull; Jung, Chulwoo; Lee, Weonjong

2013-07-01

We address a frequently-asked question on the covariance fitting of highly-correlated data such as our B K data based on the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have a fitting function accurate enough to fit extremely precise data. When eigenvalues of the covariance matrix are small, even a tiny error in the fitting function yields a large chi-square value and spoils the fitting procedure. We have applied a number of prescriptions available in the market, such as the cut-off method, modified covariance matrix method, and Bayesian method. We also propose a brand new method, the eigenmode shift (ES) method, which allows a full covariance fitting without modifying the covariance matrix at all. We provide a pedagogical example of data analysis in which the cut-off method manifestly fails in fitting, but the rest work well. In our case of the B K fitting, the diagonal approximation, the cut-off method, the ES method, and the Bayesian method work reasonably well in an engineering sense. However, interpreting the meaning of χ 2 is easier in the case of the ES method and the Bayesian method in a theoretical sense aesthetically. Hence, the ES method can be a useful alternative optional tool to check the systematic error caused by the covariance fitting procedure.
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices

KAUST Repository

Lan, Shiwei; Holbrook, Andrew; Fortin, Norbert J.; Ombao, Hernando; Shahbaba, Babak

2017-01-01

Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix

Matérn-based nonstationary cross-covariance models for global processes

KAUST Repository

Jun, Mikyoung

2014-01-01

-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters
Fermionic covariant prolongation structure theory for supernonlinear evolution equation

International Nuclear Information System (INIS)

Cheng Jipeng; Wang Shikun; Wu Ke; Zhao Weizhong

2010-01-01

We investigate the superprincipal bundle and its associated superbundle. The super(nonlinear)connection on the superfiber bundle is constructed. Then by means of the connection theory, we establish the fermionic covariant prolongation structure theory of the supernonlinear evolution equation. In this geometry theory, the fermionic covariant fundamental equations determining the prolongation structure are presented. As an example, the supernonlinear Schroedinger equation is analyzed in the framework of this fermionic covariant prolongation structure theory. We obtain its Lax pairs and Baecklund transformation.
Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

Science.gov (United States)

The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...
Hereditary kidney cancer syndromes: Genetic disorders driven by alterations in metabolism and epigenome regulation.

Science.gov (United States)

Hasumi, Hisashi; Yao, Masahiro

2018-03-01

Although hereditary kidney cancer syndrome accounts for approximately five percent of all kidney cancers, the mechanistic insight into tumor development in these rare conditions has provided the foundation for the development of molecular targeting agents currently used for sporadic kidney cancer. In the late 1980s, the comprehensive study for hereditary kidney cancer syndrome was launched in the National Cancer Institute, USA and the first kidney cancer-associated gene, VHL, was identified through kindred analysis of von Hippel-Lindau (VHL) syndrome in 1993. Subsequent molecular studies on VHL function have elucidated that the VHL protein is a component of E3 ubiquitin ligase complex for hypoxia-inducible factor (HIF), which provided the basis for the development of tyrosine kinase inhibitors targeting the HIF-VEGF/PDGF pathway. Recent whole-exome sequencing analysis of sporadic kidney cancer exhibited the recurrent mutations in chromatin remodeling genes and the later study has revealed that several chromatin remodeling genes are altered in kidney cancer kindred at the germline level. To date, more than 10 hereditary kidney cancer syndromes together with each responsible gene have been characterized and most of the causative genes for these genetic disorders are associated with either metabolism or epigenome regulation. In this review article, we describe the molecular mechanisms of how an alteration of each kidney cancer-associated gene leads to renal tumorigenesis as well as denote therapeutic targets elicited by studies on hereditary kidney cancer. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.
A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference Genetics Selection Evolution 2010, 42:29

DEFF Research Database (Denmark)

Ødegård, Jørgen; Meuwissen, Theo HE; Heringstad, Bjørg

2010-01-01

Background In the genetic analysis of binary traits with one observation per animal, animal threshold models frequently give biased heritability estimates. In some cases, this problem can be circumvented by fitting sire- or sire-dam models. However, these models are not appropriate in cases where...... records exist for the parents). Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to the sire-dam model). Conclusions The new algorithm to estimate genetic parameters via Gibbs sampling solves the bias problems typically occurring in animal...... individual records exist on parents. Therefore, the aim of our study was to develop a new Gibbs sampling algorithm for a proper estimation of genetic (co)variance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative...
On Galilean covariant quantum mechanics

International Nuclear Information System (INIS)

Horzela, A.; Kapuscik, E.; Kempczynski, J.; Joint Inst. for Nuclear Research, Dubna

1991-08-01

Formalism exhibiting the Galilean covariance of wave mechanics is proposed. A new notion of quantum mechanical forces is introduced. The formalism is illustrated on the example of the harmonic oscillator. (author)
Astrophysical tests of scale-covariant gravity theories

International Nuclear Information System (INIS)

Mansfield, V.N.; Malin, S.

1980-01-01

Starting from the most general form of the conservation laws in scale-covariant gravitation theory, a conservation of energy equation appropriate for stars is derived. Applications to white dwarfs and neutron stars reveal serious difficulties for some choices of gauge that have been frequently employed in the literature on scale-covariant gravity. We also show how to restrict some of the possible gauges that result from theories which are independent of the Large Numbers Hypothesis
Covariant phase difference observables in quantum mechanics

International Nuclear Information System (INIS)

Heinonen, Teiko; Lahti, Pekka; Pellonpaeae, Juha-Pekka

2003-01-01

Covariant phase difference observables are determined in two different ways, by a direct computation and by a group theoretical method. A characterization of phase difference observables which can be expressed as the difference of two phase observables is given. The classical limits of such phase difference observables are determined and the Pegg-Barnett phase difference distribution is obtained from the phase difference representation. The relation of Ban's theory to the covariant phase theories is exhibited
How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic effects.

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Christopher H Chandler

2017-11-01

Full Text Available For a given gene, different mutations influence organismal phenotypes to varying degrees. However, the expressivity of these variants not only depends on the DNA lesion associated with the mutation, but also on factors including the genetic background and rearing environment. The degree to which these factors influence related alleles, genes, or pathways similarly, and whether similar developmental mechanisms underlie variation in the expressivity of a single allele across conditions and among alleles is poorly understood. Besides their fundamental biological significance, these questions have important implications for the interpretation of functional genetic analyses, for example, if these factors alter the ordering of allelic series or patterns of complementation. We examined the impact of genetic background and rearing environment for a series of mutations spanning the range of phenotypic effects for both the scalloped and vestigial genes, which influence wing development in Drosophila melanogaster. Genetic background and rearing environment influenced the phenotypic outcome of mutations, including intra-genic interactions, particularly for mutations of moderate expressivity. We examined whether cellular correlates (such as cell proliferation during development of these phenotypic effects matched the observed phenotypic outcome. While cell proliferation decreased with mutations of increasingly severe effects, surprisingly it did not co-vary strongly with the degree of background dependence. We discuss these findings and propose a phenomenological model to aid in understanding the biology of genes, and how this influences our interpretation of allelic effects in genetic analysis.
Genetic overlap between type 2 diabetes and depression in Swedish and Danish twin registries

DEFF Research Database (Denmark)

Kan, C; Pedersen, Nancy L.; Christensen, K

2016-01-01

A bidirectional association between type 2 diabetes (T2DM) and depression has been consistently reported. Depression is associated with worse biomedical outcomes and increased mortality. The mechanisms underlying the association of T2DM with depression remain unclear. One possible question we can...... the association is primarily attributed to genetic effects in females. In the Danish sample, genetic effects account for the majority of the covariance in both males and females. Qualitative genetic sex differences are observed in both samples. We believe this is the first study to demonstrate significant genetic...
Phenotypic covariance at species' borders.

Science.gov (United States)

Caley, M Julian; Cripps, Edward; Game, Edward T

2013-05-28

Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species' borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species' borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future.
Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

Science.gov (United States)

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.
Quasi-local mass in the covariant Newtonian spacetime

International Nuclear Information System (INIS)

Wu, Y-H; Wang, C-H

2008-01-01

In general relativity, quasi-local energy-momentum expressions have been constructed from various formulae. However, the Newtonian theory of gravity gives a well-known and a unique quasi-local mass expression (surface integration). Since geometrical formulation of Newtonian gravity has been established in the covariant Newtonian spacetime, it provides a covariant approximation from relativistic to Newtonian theories. By using this approximation, we calculate the Komar integral, the Brown-York quasi-local energy and the Dougan-Mason quasi-local mass in the covariant Newtonian spacetime. It turns out that the Komar integral naturally gives the Newtonian quasi-local mass expression; however, further conditions (spherical symmetry) need to be made for Brown-York and Dougan-Mason expressions
Genetic dissection of behavioral flexibility: reversal learning in mice.

Science.gov (United States)

Laughlin, Rick E; Grant, Tara L; Williams, Robert W; Jentsch, J David

2011-06-01

Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task. We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels. Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
The Performance Analysis Based on SAR Sample Covariance Matrix

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Esra Erten

2012-03-01

Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.
ANGELO-LAMBDA, Covariance matrix interpolation and mathematical verification

International Nuclear Information System (INIS)

Kodeli, Ivo

2007-01-01

1 - Description of program or function: The codes ANGELO-2.3 and LAMBDA-2.3 are used for the interpolation of the cross section covariance data from the original to a user defined energy group structure, and for the mathematical tests of the matrices, respectively. The LAMBDA-2.3 code calculates the eigenvalues of the matrices (both for the original or the converted) and lists them accordingly into positive and negative matrices. This verification is strongly recommended before using any covariance matrices. These versions of the two codes are the extended versions of the previous codes available in the Packages NEA-1264 - ZZ-VITAMIN-J/COVA. They were specifically developed for the purposes of the OECD LWR UAM benchmark, in particular for the processing of the ZZ-SCALE5.1/COVA-44G cross section covariance matrix library retrieved from the SCALE-5.1 package. Either the original SCALE-5.1 libraries or the libraries separated into several files by Nuclides can be (in principle) processed by ANGELO/LAMBDA codes, but the use of the one-nuclide data is strongly recommended. Due to large deviations of the correlation matrix terms from unity observed in some SCALE5.1 covariance matrices, the previous more severe acceptance condition in the ANGELO2.3 code was released. In case the correlation coefficients exceed 1.0, only a warning message is issued, and coefficients are replaced by 1.0. 2 - Methods: ANGELO-2.3 interpolates the covariance matrices to a union grid using flat weighting. LAMBDA-2.3 code includes the mathematical routines to calculate the eigenvalues of the covariance matrices. 3 - Restrictions on the complexity of the problem: The algorithm used in ANGELO is relatively simple, therefore the interpolations involving energy group structure which are very different from the original (e.g. large difference in the number of energy groups) may not be accurate. In particular in the case of the MT=1018 data (fission spectra covariances) the algorithm may not be
Using machine learning to assess covariate balance in matching studies.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2016-12-01

In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.
Across-environment genetic correlations and the frequency of selective environments shape the evolutionary dynamics of growth rate in Impatiens capensis.

Science.gov (United States)

Stinchcombe, John R; Izem, Rima; Heschel, M Shane; McGoey, Brechann V; Schmitt, Johanna

2010-10-01

Trade-offs can exist within and across environments, and constrain evolutionary trajectories. To examine the effects of competition and resource availability on trade-offs, we grew individuals of recombinant inbred lines of Impatiens capensis in a factorial combination of five densities with two light environments (full light and neutral shade) and used a Bayesian logistic growth analysis to estimate intrinsic growth rates. To estimate across-environment constraints, we developed a variance decomposition approach to principal components analysis, which accounted for sample size, model-fitting, and within-RIL variation prior to eigenanalysis. We detected negative across-environment genetic covariances in intrinsic growth rates, although only under full-light. To evaluate the potential importance of these covariances, we surveyed natural populations of I. capensis to measure the frequency of different density environments across space and time. We combined our empirical estimates of across-environment genetic variance-covariance matrices and frequency of selective environments with hypothetical (yet realistic) selection gradients to project evolutionary responses in multiple density environments. Selection in common environments can lead to correlated responses to selection in rare environments that oppose and counteract direct selection in those rare environments. Our results highlight the importance of considering both the frequency of selective environments and the across-environment genetic covariances in traits simultaneously. © 2010 The Author(s). Journal compilation © 2010 The Society for the Study of Evolution.
Genetic Variability of Show Jumping Attributes in Young Horses Commencing Competing

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Tomasz Próchniak

2015-08-01

Full Text Available The aim of the study was to select traits that may constitute a prospective criterion for breeding value prediction of young horses. The results of 1,232 starts of 894 four-, five-, six-, and seven-year-old horses, obtained during jumping championships for young horses which had not been evaluated in, alternative to championships, training centres were analyed. Nine traits were chosen of those recorded: ranking in the championship, elimination (y/n, conformation, rating of style on day one, two, and three, and penalty points on day one, two, and three of a championship. (Covariance components were estimated via the Gibbs sampling procedure and adequate (covariance component ratios were calculated. Statistical classifications were trait dependent but all fitted random additive genetic and permanent environment effects. It was found that such characteristics as penalty points and jumping style are potential indicators of jumping ability, and the genetic variability of the traits was within the range of 14% to 27%. Given the low genetic correlations between the conformation and other results achieved on the parkour, the relevance of assessment of conformation in four-years-old horses has been questioned.
Covariance and correlation estimation in electron-density maps.

Science.gov (United States)

Altomare, Angela; Cuocci, Corrado; Giacovazzo, Carmelo; Moliterni, Anna; Rizzi, Rosanna

2012-03-01

Quite recently two papers have been published [Giacovazzo & Mazzone (2011). Acta Cryst. A67, 210-218; Giacovazzo et al. (2011). Acta Cryst. A67, 368-382] which calculate the variance in any point of an electron-density map at any stage of the phasing process. The main aim of the papers was to associate a standard deviation to each pixel of the map, in order to obtain a better estimate of the map reliability. This paper deals with the covariance estimate between points of an electron-density map in any space group, centrosymmetric or non-centrosymmetric, no matter the correlation between the model and target structures. The aim is as follows: to verify if the electron density in one point of the map is amplified or depressed as an effect of the electron density in one or more other points of the map. High values of the covariances are usually connected with undesired features of the map. The phases are the primitive random variables of our probabilistic model; the covariance changes with the quality of the model and therefore with the quality of the phases. The conclusive formulas show that the covariance is also influenced by the Patterson map. Uncertainty on measurements may influence the covariance, particularly in the final stages of the structure refinement; a general formula is obtained taking into account both phase and measurement uncertainty, valid at any stage of the crystal structure solution.

Portfolio management using realized covariances: Evidence from Brazil

Directory of Open Access Journals (Sweden)

João F. Caldeira

2017-09-01

Full Text Available It is often argued that intraday returns can be used to construct covariance estimates that are more accurate than those based on daily returns. However, it is still unclear whether high frequency data provide more precise covariance estimates in markets more contaminated from microstructure noise such as higher bid-ask spreads and lower liquidity. We address this question by investigating the benefits of using high frequency data in the Brazilian equities market to construct optimal minimum variance portfolios. We implement alternative realized covariance estimators based on intraday returns sampled at alternative frequencies and obtain their dynamic versions using a multivariate GARCH framework. Our evidence based on a high-dimensional data set suggests that realized covariance estimators performed significantly better from an economic point of view in comparison to standard estimators based on low-frequency (close-to-close data as they delivered less risky portfolios. Resumo: Argumenta-se frequentemente que retornos intradiários podem ser usados para construir estimativas de covariâncias mais precisas em relação àquelas obtidas com retornos diários. No entanto, ainda não está claro se os dados de alta freqüência fornecem estimativas de covariância mais precisas em mercados mais contaminados pelo ruído da microestrutura, como maiores spreads entre ofertas de compra e venda e baixa liquidez. Abordamos essa questão investigando os benefícios do uso de dados de alta freqüência no mercado de ações brasileiro através da construção de portfólios ótimos de variância mínima. Implementamos diversos estimadores de covariâncias realizadas com base em retornos intradiários amostrados em diferentes frequências e obtemos suas versões dinâmicas usando uma estrutura GARCH multivariada. Nossa evidência baseada em um conjunto de dados de alta dimensão sugere que os estimadores de covariâncias realizadas obtiveram um desempenho
Estimates of covariance functions for growth of Anglo-Nubian goats Estimativas de funções de covariância para crescimento de caprinos anglo nubianos

Directory of Open Access Journals (Sweden)

José Ernandes Rufino de Sousa

2011-01-01

Full Text Available It was used 4,313 weight records from birth to 196 days of age from 946 Anglo-nubiana breed goats, progenies from 43 sires and 279 dams, controlled in the period from 1980 to 2005, with the objective of estimating covariance functions and genetic parameters of animals by using random regression models. It was evaluated 12 random regression models, with degrees ranging from 1 to 7 for direct additive genetic and maternal and animal permanent environment effect and residual variance adjusted by using animal age ordinary polynomial of third order. Models were compared by using likelihood ratio test and by Bayesian information criterion of Schwarz and Akaike information criterion. The model selected based on Bayesian information criterion was the one that considered the maternal and direct additive genetic effect adjusted by a quadratic polynomial and the animal permanent environmental effect adjusted by a cubic polynomial (M334. Heritability estimates for direct effect were lower in the beginning and at the end of the studied period and maternal heritability estimates were higher at 196 days of age in comparison to the other growth phases. Genetic correlation ranged from moderate to high and they decreased as the distance between ages increased. Higher efficiency in selection for weight can be obtained by considering weights close to weaning, which is a period when the highest estimates of genetic variance and heritability are obtained.Foram utilizados 4.313 registros de pesos do nascimento aos 196 dias de idade de 946 animais da raça Anglo-Nubiana, filhos de 43 reprodutores e 279 cabras, controlados no período de 1980 a 2005, com o objetivo de estimar funções de covariância e parâmetros genéticos dos animais por meio de modelos de regressão aleatória. Foram avaliados 12 modelos de regressão aleatória, com graus variando de 1 a 7 para os efeitos genéticos aditivo direto e materno e de ambiente permanente de animal e com vari
Effect of correlation on covariate selection in linear and nonlinear mixed effect models.

Science.gov (United States)

Bonate, Peter L

2017-01-01

The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Extended covariance data formats for the ENDF/B-VI differential data evaluation

International Nuclear Information System (INIS)

Peelle, R.W.; Muir, D.W.

1988-01-01

The ENDF/B-V included cross section covariance data, but covariances could not be encoded for all the important data types. New ENDF-6 covariance formats are outlined including those for cross-file (MF) covariances, resonance parameters over the whole range, and secondary energy and angle distributions. One ''late entry'' format encodes covariance data for cross sections that are output from model or fitting codes in terms of the model parameter covariance matrix and the tabulated derivatives of cross sections with respect to the model parameters. Another new format yields multigroup cross section variances that increase as the group width decreases. When evaluators use the new formats, the files can be processed and used for improved uncertainty propagation and data combination. 22 refs
Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.

Science.gov (United States)

Rijsdijk, Frühling V; Vernon, P A; Boomsma, Dorret I

2002-05-01

Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard Progressive test score, collected in 194 18-year-old Dutch twin pairs. We investigated whether first-order group factors possess genetic and environmental variance independent of the higher-order general factor and whether the hierarchical structure is significant for all sources of variance. A hierarchical model with the 3 Cohen group-factors (verbal comprehension, perceptual organisation and freedom-from-distractibility) and a higher-order g factor showed the best fit to the phenotypic data and to additive genetic influences (A), whereas the unique environmental source of variance (E) could be modeled by a single general factor and specifics. There was no evidence for common environmental influences. The covariation among the WAIS group factors and the covariation between the group factors and the Raven is predominantly influenced by a second-order genetic factor and strongly support the notion of a biological basis of g.
A Genetically Informed Cross-lagged Analysis of Autistic-Like Traits and Affective Problems in Early Childhood

Science.gov (United States)

Micalizzi, Lauren; Ronald, Angelica; Saudino, Kimberly J.

2015-01-01

A genetically informed cross-lagged model was applied to twin data to explore etiological links between autistic-like traits and affective problems in early childhood. The sample comprised 310 same-sex twin pairs (143 monozygotic and 167 dizygotic; 53% male). Autistic-like traits and affective problems were assessed at ages 2 and 3 using parent ratings. Both constructs were related within and across age (r = .30−.53) and showed moderate stability (r = .45−.54). Autistic-like traits and affective problems showed genetic and environmental influences at both ages. Whereas at age 2, the covariance between autistic-like traits and affective problems was entirely due to environmental influences (shared and nonshared), at age 3, genetic factors also contributed to the covariance between constructs. The stability paths, but not the cross-lagged paths, were significant, indicating that there is stability in both autistic-like traits and affective problems but they do not mutually influence each other across age. Stability effects were due to genetic, shared, and nonshared environmental influences. Substantial novel genetic and nonshared environmental influences emerge at age 3 and suggest change in the etiology of these constructs over time. During early childhood, autistic-like traits tend to occur alongside affective problems and partly overlapping genetic and environmental influences explain this association. PMID:26456961
Covariance specification and estimation to improve top-down Green House Gas emission estimates

Science.gov (United States)

Ghosh, S.; Lopez-Coto, I.; Prasad, K.; Whetstone, J. R.

2015-12-01

The National Institute of Standards and Technology (NIST) operates the North-East Corridor (NEC) project and the Indianapolis Flux Experiment (INFLUX) in order to develop measurement methods to quantify sources of Greenhouse Gas (GHG) emissions as well as their uncertainties in urban domains using a top down inversion method. Top down inversion updates prior knowledge using observations in a Bayesian way. One primary consideration in a Bayesian inversion framework is the covariance structure of (1) the emission prior residuals and (2) the observation residuals (i.e. the difference between observations and model predicted observations). These covariance matrices are respectively referred to as the prior covariance matrix and the model-data mismatch covariance matrix. It is known that the choice of these covariances can have large effect on estimates. The main objective of this work is to determine the impact of different covariance models on inversion estimates and their associated uncertainties in urban domains. We use a pseudo-data Bayesian inversion framework using footprints (i.e. sensitivities of tower measurements of GHGs to surface emissions) and emission priors (based on Hestia project to quantify fossil-fuel emissions) to estimate posterior emissions using different covariance schemes. The posterior emission estimates and uncertainties are compared to the hypothetical truth. We find that, if we correctly specify spatial variability and spatio-temporal variability in prior and model-data mismatch covariances respectively, then we can compute more accurate posterior estimates. We discuss few covariance models to introduce space-time interacting mismatches along with estimation of the involved parameters. We then compare several candidate prior spatial covariance models from the Matern covariance class and estimate their parameters with specified mismatches. We find that best-fitted prior covariances are not always best in recovering the truth. To achieve
Parametric number covariance in quantum chaotic spectra.

Science.gov (United States)

Vinayak; Kumar, Sandeep; Pandey, Akhilesh

2016-03-01

We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.
Modular invariance and covariant loop calculus

International Nuclear Information System (INIS)

Petersen, J.L.; Roland, K.O.; Sidenius, J.R.

1988-01-01

The covariant loop calculus provides an efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit two- and three-loop results derived using analytic geometry (one loop is known to be okay). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various nontrivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
Modular invariance and covariant loop calculus

International Nuclear Information System (INIS)

Petersen, J.L.; Roland, K.O.; Sidenius, J.R.

1988-01-01

The covariant loop calculus provides and efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit 2- and 3- loop results derived using analytic geometry (1 loop is known to be ok). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various non-trivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
A covariant canonical description of Liouville field theory

International Nuclear Information System (INIS)

Papadopoulos, G.; Spence, B.

1993-03-01

This paper presents a new parametrisation of the space of solutions of Liouville field theory on a cylinder. In this parametrisation, the solutions are well-defined and manifestly real functions over all space-time and all of parameter space. It is shown that the resulting covariant phase space of the Liouville theory is diffeomorphic to the Hamiltonian one, and to the space of initial data of the theory. The Poisson brackets are derived and shown to be those of the co-tangent bundle of the loop group of the real line. Using Hamiltonian reduction, it is shown that this covariant phase space formulation of Liouville theory may also be obtained from the covariant phase space formulation of the Wess-Zumino-Witten model. 19 refs
Covariance measurement in the presence of non-synchronous trading and market microstructure noise

NARCIS (Netherlands)

Griffin, J.E.; Oomen, R.C.A.

2011-01-01

This paper studies the problem of covariance estimation when prices are observed non-synchronously and contaminated by i.i.d. microstructure noise. We derive closed form expressions for the bias and variance of three popular covariance estimators, namely realised covariance, realised covariance plus
Abnormalities in structural covariance of cortical gyrification in schizophrenia.

Science.gov (United States)

Palaniyappan, Lena; Park, Bert; Balain, Vijender; Dangi, Raj; Liddle, Peter

2015-07-01

The highly convoluted shape of the adult human brain results from several well-coordinated maturational events that start from embryonic development and extend through the adult life span. Disturbances in these maturational events can result in various neurological and psychiatric disorders, resulting in abnormal patterns of morphological relationship among cortical structures (structural covariance). Structural covariance can be studied using graph theory-based approaches that evaluate topological properties of brain networks. Covariance-based graph metrics allow cross-sectional study of coordinated maturational relationship among brain regions. Disrupted gyrification of focal brain regions is a consistent feature of schizophrenia. However, it is unclear if these localized disturbances result from a failure of coordinated development of brain regions in schizophrenia. We studied the structural covariance of gyrification in a sample of 41 patients with schizophrenia and 40 healthy controls by constructing gyrification-based networks using a 3-dimensional index. We found that several key regions including anterior insula and dorsolateral prefrontal cortex show increased segregation in schizophrenia, alongside reduced segregation in somato-sensory and occipital regions. Patients also showed a lack of prominence of the distributed covariance (hubness) of cingulate cortex. The abnormal segregated folding pattern in the right peri-sylvian regions (insula and fronto-temporal cortex) was associated with greater severity of illness. The study of structural covariance in cortical folding supports the presence of subtle deviation in the coordinated development of cortical convolutions in schizophrenia. The heterogeneity in the severity of schizophrenia could be explained in part by aberrant trajectories of neurodevelopment.
An Empirical State Error Covariance Matrix Orbit Determination Example

Science.gov (United States)

Frisbee, Joseph H., Jr.

2015-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models

OpenAIRE

Liang, Yuli

2015-01-01

This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. We derive two covariance structures under two different invariance restrictions. The obtained covariance structures reflect both circularity and exchangeability present in the data....
Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha

2014-12-08

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
The covariant formulation of f ( T ) gravity

International Nuclear Information System (INIS)

Krššák, Martin; Saridakis, Emmanuel N

2016-01-01

We show that the well-known problem of frame dependence and violation of local Lorentz invariance in the usual formulation of f ( T ) gravity is a consequence of neglecting the role of spin connection. We re-formulate f ( T ) gravity starting from, instead of the ‘pure tetrad’ teleparallel gravity, the covariant teleparallel gravity, using both the tetrad and the spin connection as dynamical variables, resulting in a fully covariant, consistent, and frame-independent version of f ( T ) gravity, which does not suffer from the notorious problems of the usual, pure tetrad, f ( T ) theory. We present the method to extract solutions for the most physically important cases, such as the Minkowski, the Friedmann–Robertson–Walker (FRW) and the spherically symmetric ones. We show that in covariant f ( T ) gravity we are allowed to use an arbitrary tetrad in an arbitrary coordinate system along with the corresponding spin connection, resulting always in the same physically relevant field equations. (paper)
Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha; Huang, Jianhua Z.

2014-01-01

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
Recent Advances with the AMPX Covariance Processing Capabilities in PUFF-IV

International Nuclear Information System (INIS)

Wiarda, Dorothea; Arbanas, Goran; Leal, Luiz C.; Dunn, Michael E.

2008-01-01

The program PUFF-IV is used to process resonance parameter covariance information given in ENDF/B File 32 and point-wise covariance matrices given in ENDF/B File 33 into group-averaged covariances matrices on a user-supplied group structure. For large resonance covariance matrices, found for example in 235U, the execution time of PUFF-IV can be quite long. Recently the code was modified to take advandage of Basic Linear Algebra Subprograms (BLAS) routines for the most time-consuming matrix multiplications. This led to a substantial decrease in execution time. This faster processing capability allowed us to investigate the conversion of File 32 data into File 33 data using a larger number of user-defined groups. While conversion substantially reduces the ENDF/B file size requirements for evaluations with a large number of resonances, a trade-off is made between the number of groups used to represent the resonance parameter covariance as a point-wise covariance matrix and the file size. We are also investigating a hybrid version of the conversion, in which the low-energy part of the File 32 resonance parameter covariances matrix is retained and the correlations with higher energies as well as the high energy part are given in File 33.
Conversed, gauge-covariant colour charge in Su(n)QCD

International Nuclear Information System (INIS)

Selikhov, A.V.

1988-01-01

The definition of the integral of the group tensor and the gauge-covariant differential with respect to a distant point are given in the work. A conserved covariant charge dependence on family of paths has been contracted with the help of these notions. It has been shown that the same family of paths fixes a gauge in which the covariant and noncovariant conserved currents coicide. The gauge is characterized by representation of the vector potential via field strength tensor. The possibility of connecting the choice of the family of paths with the measurement procedure is discussed. 13 refs.; 2 figs

Semiparametric estimation of covariance matrices for longitudinal data.

Science.gov (United States)

Fan, Jianqing; Wu, Yichao

2008-12-01

Estimation of longitudinal data covariance structure poses significant challenges because the data are usually collected at irregular time points. A viable semiparametric model for covariance matrices was proposed in Fan, Huang and Li (2007) that allows one to estimate the variance function nonparametrically and to estimate the correlation function parametrically via aggregating information from irregular and sparse data points within each subject. However, the asymptotic properties of their quasi-maximum likelihood estimator (QMLE) of parameters in the covariance model are largely unknown. In the current work, we address this problem in the context of more general models for the conditional mean function including parametric, nonparametric, or semi-parametric. We also consider the possibility of rough mean regression function and introduce the difference-based method to reduce biases in the context of varying-coefficient partially linear mean regression models. This provides a more robust estimator of the covariance function under a wider range of situations. Under some technical conditions, consistency and asymptotic normality are obtained for the QMLE of the parameters in the correlation function. Simulation studies and a real data example are used to illustrate the proposed approach.
Covariant Gauss law commutator anomaly

International Nuclear Information System (INIS)

Dunne, G.V.; Trugenberger, C.A.; Massachusetts Inst. of Tech., Cambridge

1990-01-01

Using a (fixed-time) hamiltonian formalism we derive a covariant form for the anomaly in the commutator algebra of Gauss law generators for chiral fermions interacting with a dynamical non-abelian gauge field in 3+1 dimensions. (orig.)
Some remarks on estimating a covariance structure model from a sample correlation matrix

OpenAIRE

Maydeu Olivares, Alberto; Hernández Estrada, Adolfo

2000-01-01

A popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one i...
Non-stationary covariance function modelling in 2D least-squares collocation

Science.gov (United States)

Darbeheshti, N.; Featherstone, W. E.

2009-06-01

Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the observed data. However, the assumption that the spatial dependence is constant throughout the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage for dealing with non-stationarity in geodetic data. We then compared stationary and non- stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC.
Matérn-based nonstationary cross-covariance models for global processes

KAUST Repository

Jun, Mikyoung

2014-07-01

Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible cross-covariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-dependences between them and also for improved predictions. We propose various ways to produce cross-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters vary over space, coupled with a differential operators approach for modeling large-scale nonstationarity. We compare their performance to the performance of some existing models in terms of the aic and spatial predictions in two applications: joint modeling of surface temperature and precipitation, and joint modeling of errors in climate model ensembles. © 2014 Elsevier Inc.
Vitamin D time profile based on the contribution of non-genetic and genetic factors in HIV-infected individuals of European ancestry.

Science.gov (United States)

Guidi, Monia; Foletti, Giuseppe; McLaren, Paul; Cavassini, Matthias; Rauch, Andri; Tarr, Philip E; Lamy, Olivier; Panchaud, Alice; Telenti, Amalio; Csajka, Chantal; Rotger, Margalida

2015-01-01

Vitamin D deficiency is prevalent in HIV-infected individuals and vitamin D supplementation is proposed according to standard care. This study aimed at characterizing the kinetics of 25(OH)D in a cohort of HIV-infected individuals of European ancestry to better define the influence of genetic and non-genetic factors on 25(OH)D levels. These data were used for the optimization of vitamin D supplementation in order to reach therapeutic targets. 1,397 25(OH)D plasma levels and relevant clinical information were collected in 664 participants during medical routine follow-up visits. They were genotyped for 7 SNPs in 4 genes known to be associated with 25(OH)D levels. 25(OH)D concentrations were analysed using a population pharmacokinetic approach. The percentage of individuals with 25(OH)D concentrations within the recommended range of 20-40 ng/ml during 12 months of follow-up and several dosage regimens were evaluated by simulation. A one-compartment model with linear absorption and elimination was used to describe 25(OH)D pharmacokinetics, while integrating endogenous baseline plasma concentrations. Covariate analyses confirmed the effect of seasonality, body mass index, smoking habits, the analytical method, darunavir/ritonavir and the genetic variant in GC (rs2282679) on 25(OH)D concentrations. 11% of the inter-individual variability in 25(OH)D levels was explained by seasonality and other non-genetic covariates, and 1% by genetics. The optimal supplementation for severe vitamin D deficient patients was 300,000 IU two times per year. This analysis allowed identifying factors associated with 25(OH)D plasma levels in HIV-infected individuals. Improvement of dosage regimen and timing of vitamin D supplementation is proposed based on those results.
Covariance Based Pre-Filters and Screening Criteria for Conjunction Analysis

Science.gov (United States)

George, E., Chan, K.

2012-09-01

Several relationships are developed relating object size, initial covariance and range at closest approach to probability of collision. These relationships address the following questions: - Given the objects' initial covariance and combined hard body size, what is the maximum possible value of the probability of collision (Pc)? - Given the objects' initial covariance, what is the maximum combined hard body radius for which the probability of collision does not exceed the tolerance limit? - Given the objects' initial covariance and the combined hard body radius, what is the minimum miss distance for which the probability of collision does not exceed the tolerance limit? - Given the objects' initial covariance and the miss distance, what is the maximum combined hard body radius for which the probability of collision does not exceed the tolerance limit? The first relationship above allows the elimination of object pairs from conjunction analysis (CA) on the basis of the initial covariance and hard-body sizes of the objects. The application of this pre-filter to present day catalogs with estimated covariance results in the elimination of approximately 35% of object pairs as unable to ever conjunct with a probability of collision exceeding 1x10-6. Because Pc is directly proportional to object size and inversely proportional to covariance size, this pre-filter will have a significantly larger impact on future catalogs, which are expected to contain a much larger fraction of small debris tracked only by a limited subset of available sensors. This relationship also provides a mathematically rigorous basis for eliminating objects from analysis entirely based on element set age or quality - a practice commonly done by rough rules of thumb today. Further, these relations can be used to determine the required geometric screening radius for all objects. This analysis reveals the screening volumes for small objects are much larger than needed, while the screening volumes for
High-dimensional covariance forecasting for short intra-day horizons

NARCIS (Netherlands)

Oomen, R.C.A.

2010-01-01

Asset return covariances at intra-day horizons are known to tend towards zero due to market microstructure effects. Thus, traders who simply scale their daily covariance forecast to match their trading horizon are likely to over-estimate the actual experienced asset dependence. In this paper, some
Cortisol covariation within parents of young children: Moderation by relationship aggression.

Science.gov (United States)

Saxbe, Darby E; Adam, Emma K; Schetter, Christine Dunkel; Guardino, Christine M; Simon, Clarissa; McKinney, Chelsea O; Shalowitz, Madeleine U

2015-12-01

Covariation in diurnal cortisol has been observed in several studies of cohabiting couples. In two such studies (Liu et al., 2013; Saxbe and Repetti, 2010), relationship distress was associated with stronger within-couple correlations, suggesting that couples' physiological linkage with each other may indicate problematic dyadic functioning. Although intimate partner aggression has been associated with dysregulation in women's diurnal cortisol, it has not yet been tested as a moderator of within-couple covariation. This study reports on a diverse sample of 122 parents who sampled salivary cortisol on matched days for two years following the birth of an infant. Partners showed strong positive cortisol covariation. In couples with higher levels of partner-perpetrated aggression reported by women at one year postpartum, both women and men had a flatter diurnal decrease in cortisol and stronger correlations with partners' cortisol sampled at the same timepoints. In other words, relationship aggression was linked both with indices of suboptimal cortisol rhythms in both members of the couples and with stronger within-couple covariation coefficients. These results persisted when relationship satisfaction and demographic covariates were included in the model. During some of the sampling days, some women were pregnant with a subsequent child, but pregnancy did not significantly moderate cortisol levels or within-couple covariation. The findings suggest that couples experiencing relationship aggression have both suboptimal neuroendocrine profiles and stronger covariation. Cortisol covariation is an understudied phenomenon with potential implications for couples' relationship functioning and physical health. Copyright © 2015 Elsevier Ltd. All rights reserved.
Reconstruction of sparse connectivity in neural networks from spike train covariances

International Nuclear Information System (INIS)

Pernice, Volker; Rotter, Stefan

2013-01-01

The inference of causation from correlation is in general highly problematic. Correspondingly, it is difficult to infer the existence of physical synaptic connections between neurons from correlations in their activity. Covariances in neural spike trains and their relation to network structure have been the subject of intense research, both experimentally and theoretically. The influence of recurrent connections on covariances can be characterized directly in linear models, where connectivity in the network is described by a matrix of linear coupling kernels. However, as indirect connections also give rise to covariances, the inverse problem of inferring network structure from covariances can generally not be solved unambiguously. Here we study to what degree this ambiguity can be resolved if the sparseness of neural networks is taken into account. To reconstruct a sparse network, we determine the minimal set of linear couplings consistent with the measured covariances by minimizing the L 1 norm of the coupling matrix under appropriate constraints. Contrary to intuition, after stochastic optimization of the coupling matrix, the resulting estimate of the underlying network is directed, despite the fact that a symmetric matrix of count covariances is used for inference. The performance of the new method is best if connections are neither exceedingly sparse, nor too dense, and it is easily applicable for networks of a few hundred nodes. Full coupling kernels can be obtained from the matrix of full covariance functions. We apply our method to networks of leaky integrate-and-fire neurons in an asynchronous–irregular state, where spike train covariances are well described by a linear model. (paper)
How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

Science.gov (United States)

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.
Spatio-Temporal Audio Enhancement Based on IAA Noise Covariance Matrix Estimates

DEFF Research Database (Denmark)

Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

2014-01-01

A method for estimating the noise covariance matrix in a mul- tichannel setup is proposed. The method is based on the iter- ative adaptive approach (IAA), which only needs short seg- ments of data to estimate the covariance matrix. Therefore, the method can be used for fast varying signals....... The method is based on an assumption of the desired signal being harmonic, which is used for estimating the noise covariance matrix from the covariance matrix of the observed signal. The noise co- variance estimate is used in the linearly constrained minimum variance (LCMV) filter and compared...
application of covariance analysis to feed/ ration experimental data

African Journals Online (AJOL)

Prince Acheampong

ABSTRACT. The use Analysis of Covariance (ANOCOVA) to feed/ration experimental data for birds was examined. Correlation and Regression analyses were used to adjust for the covariate – initial weight of the experimental birds. The Fisher's F statistic for the straight forward Analysis of Variance (ANOVA) showed ...
A three domain covariance framework for EEG/MEG data

NARCIS (Netherlands)

Ros, B.P.; Bijma, F.; de Gunst, M.C.M.; de Munck, J.C.

2015-01-01

In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three
An Empirical State Error Covariance Matrix for Batch State Estimation

Science.gov (United States)

Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
Paragrassmann analysis and covariant quantum algebras

International Nuclear Information System (INIS)

Filippov, A.T.; Isaev, A.P.; Kurdikov, A.B.; Pyatov, P.N.

1993-01-01

This report is devoted to the consideration from the algebraic point of view the paragrassmann algebras with one and many paragrassmann generators Θ i , Θ p+1 i = 0. We construct the paragrassmann versions of the Heisenberg algebra. For the special case, this algebra is nothing but the algebra for coordinates and derivatives considered in the context of covariant differential calculus on quantum hyperplane. The parameter of deformation q in our case is (p+1)-root of unity. Our construction is nondegenerate only for even p. Taking bilinear combinations of paragrassmann derivatives and coordinates we realize generators for the covariant quantum algebras as tensor products of (p+1) x (p+1) matrices. (orig./HSI)
Remarks on Bousso's covariant entropy bound

CERN Document Server

Mayo, A E

2002-01-01

Bousso's covariant entropy bound is put to the test in the context of a non-singular cosmological solution of general relativity found by Bekenstein. Although the model complies with every assumption made in Bousso's original conjecture, the entropy bound is violated due to the occurrence of negative energy density associated with the interaction of some the matter components in the model. We demonstrate how this property allows for the test model to 'elude' a proof of Bousso's conjecture which was given recently by Flanagan, Marolf and Wald. This corroborates the view that the covariant entropy bound should be applied only to stable systems for which every matter component carries positive energy density.
Group covariant protocols for quantum string commitment

International Nuclear Information System (INIS)

Tsurumaru, Toyohiro

2006-01-01

We study the security of quantum string commitment (QSC) protocols with group covariant encoding scheme. First we consider a class of QSC protocol, which is general enough to incorporate all the QSC protocols given in the preceding literatures. Then among those protocols, we consider group covariant protocols and show that the exact upperbound on the binding condition can be calculated. Next using this result, we prove that for every irreducible representation of a finite group, there always exists a corresponding nontrivial QSC protocol which reaches a level of security impossible to achieve classically
Componentes de (covariância e parâmetros genéticos de caracteres pós-desmama em bovinos da raça Angus (Co variance components and genetic parameters of post-weaning traits in Angus cattle

Directory of Open Access Journals (Sweden)

Fernando Flores Cardoso

2004-04-01

Full Text Available Foram determinados os componentes de (covariância para caracteres do período pós-desmama na raça Angus e de covariância com peso ao nascer (PN e caracteres do período pré-desmama por intermédio de um modelo animal. Utilizaram-se dados de 18.921 animais com registros de peso à desmama e ao sobreano, dos quais 4.452 tinham avaliações completas para escores visuais à desmama e ao sobreano. Registros de PN estavam disponíveis para 11.788 animais. As herdabilidades do ganho de peso pós-desmama (GP205 e dos escores de conformação (CS, precocidade (GS, musculatura (MS e tamanho (TS ao sobreano foram de 0,20, 0,19, 0,25, 0,26 e 0,24 respectivamente. As correlações genéticas entre os caracteres estudados foram todas positivas: entre GP205 e escores visuais variaram de 0,50 a 0,71; para os escores ao sobreano entre si, de 0,22 a 0,94; entre GP205 e PN foram de 0,14; entre GP205 e ganho pré-desmama, de 0,23; e para o mesmo escore visual observado à desmama e ao sobreano, de 0,90 a 0,99. Esses resultados indicam que é possível selecionar para GP205, sem aumento importante do PN, e que a seleção para GP205 deverá promover uma mudança genética correlacionada em escores visuais ao sobreano.(Covariance components were determined for post-weaning traits, and covariances with birth weight (BW and pre-weaning traits, in Angus cattle using an animal model. Records of weaning and yearling weights of 18,921 animals were used and from these 4,452 had complete evaluations of visual scores at weaning and post-weaning phases. Records of BW were available for 11,788 animals. Heritabilities of post-weaning gain (GP205 and visual scores for conformation (YC, precocity (YP, muscling (YM and size (YS were 0.20, 0.19, 0.25, 0.26 and 0.24, respectively. Genetic correlations among all traits considered were positive: between GP205 and visual scores the range was from 0.50 to 0.71; for yearling scores among themselves from 0.22 to 0.94; between GP205
More on Estimation of Banded and Banded Toeplitz Covariance Matrices

OpenAIRE

Berntsson, Fredrik; Ohlson, Martin

2017-01-01

In this paper we consider two different linear covariance structures, e.g., banded and bended Toeplitz, and how to estimate them using different methods, e.g., by minimizing different norms. One way to estimate the parameters in a linear covariance structure is to use tapering, which has been shown to be the solution to a universal least squares problem. We know that tapering not always guarantee the positive definite constraints on the estimated covariance matrix and may not be a suitable me...

Genetic evaluation with major genes and polygenic inheritance when some animals are not genotyped using gene content multiple-trait BLUP.

Science.gov (United States)

Legarra, Andrés; Vitezica, Zulma G

2015-11-17

In pedigreed populations with a major gene segregating for a quantitative trait, it is not clear how to use pedigree, genotype and phenotype information when some individuals are not genotyped. We propose to consider gene content at the major gene as a second trait correlated to the quantitative trait, in a gene content multiple-trait best linear unbiased prediction (GCMTBLUP) method. The genetic covariance between the trait and gene content at the major gene is a function of the substitution effect of the gene. This genetic covariance can be written in a multiple-trait form that accommodates any pattern of missing values for either genotype or phenotype data. Effects of major gene alleles and the genetic covariance between genotype at the major gene and the phenotype can be estimated using standard EM-REML or Gibbs sampling. Prediction of breeding values with genotypes at the major gene can use multiple-trait BLUP software. Major genes with more than two alleles can be considered by including negative covariances between gene contents at each different allele. We simulated two scenarios: a selected and an unselected trait with heritabilities of 0.05 and 0.5, respectively. In both cases, the major gene explained half the genetic variation. Competing methods used imputed gene contents derived by the method of Gengler et al. or by iterative peeling. Imputed gene contents, in contrast to GCMTBLUP, do not consider information on the quantitative trait for genotype prediction. GCMTBLUP gave unbiased estimates of the gene effect, in contrast to the other methods, with less bias and better or equal accuracy of prediction. GCMTBLUP improved estimation of genotypes in non-genotyped individuals, in particular if these individuals had own phenotype records and the trait had a high heritability. Ignoring the major gene in genetic evaluation led to serious biases and decreased prediction accuracy. CGMTBLUP is the best linear predictor of additive genetic merit including
Covariance as input to and output from resonance analyses

International Nuclear Information System (INIS)

Larson, N.M.

1992-01-01

Accurate data analysis requires understanding of the roles played by both data and parameter covariance matrices. In this paper the entire data reduction/analysis process is examined, for neutron-induced reactions in the resonance region. Interrelationships between data and parameter covariance matrices are examined and alternative reduction/analysis methods discussed
Spinors, tensors and the covariant form of Dirac's equation

International Nuclear Information System (INIS)

Chen, W.Q.; Cook, A.H.

1986-01-01

The relations between tensors and spinors are used to establish the form of the covariant derivative of a spinor, making use of the fact that certain bilinear combinations of spinors are vectors. The covariant forms of Dirac's equation are thus obtained and examples in specific coordinate systems are displayed. (author)
Covariant effective action for loop quantum cosmology from order reduction

International Nuclear Information System (INIS)

Sotiriou, Thomas P.

2009-01-01

Loop quantum cosmology (LQC) seems to be predicting modified effective Friedmann equations without extra degrees of freedom. A puzzle arises if one decides to seek for a covariant effective action which would lead to the given Friedmann equation: The Einstein-Hilbert action is the only action that leads to second order field equations and, hence, there exists no covariant action which, under metric variation, leads to a modified Friedmann equation without extra degrees of freedom. It is shown that, at least for isotropic models in LQC, this issue is naturally resolved and a covariant effective action can be found if one considers higher order theories of gravity but faithfully follows effective field theory techniques. However, our analysis also raises doubts on whether a covariant description without background structures can be found for anisotropic models.
New horizontal global solar radiation estimation models for Turkey based on robust coplot supported genetic programming technique

International Nuclear Information System (INIS)

Demirhan, Haydar; Kayhan Atilgan, Yasemin

2015-01-01

Highlights: • Precise horizontal global solar radiation estimation models are proposed for Turkey. • Genetic programming technique is used to construct the models. • Robust coplot analysis is applied to reduce the impact of outlier observations. • Better estimation and prediction properties are observed for the models. - Abstract: Renewable energy sources have been attracting more and more attention of researchers due to the diminishing and harmful nature of fossil energy sources. Because of the importance of solar energy as a renewable energy source, an accurate determination of significant covariates and their relationships with the amount of global solar radiation reaching the Earth is a critical research problem. There are numerous meteorological and terrestrial covariates that can be used in the analysis of horizontal global solar radiation. Some of these covariates are highly correlated with each other. It is possible to find a large variety of linear or non-linear models to explain the amount of horizontal global solar radiation. However, models that explain the amount of global solar radiation with the smallest set of covariates should be obtained. In this study, use of the robust coplot technique to reduce the number of covariates before going forward with advanced modelling techniques is considered. After reducing the dimensionality of model space, yearly and monthly mean daily horizontal global solar radiation estimation models for Turkey are built by using the genetic programming technique. It is observed that application of robust coplot analysis is helpful for building precise models that explain the amount of global solar radiation with the minimum number of covariates without suffering from outlier observations and the multicollinearity problem. Consequently, over a dataset of Turkey, precise yearly and monthly mean daily global solar radiation estimation models are introduced using the model spaces obtained by robust coplot technique and
Group covariance and metrical theory

International Nuclear Information System (INIS)

Halpern, L.

1983-01-01

The a priori introduction of a Lie group of transformations into a physical theory has often proved to be useful; it usually serves to describe special simplified conditions before a general theory can be worked out. Newton's assumptions of absolute space and time are examples where the Euclidian group and translation group have been introduced. These groups were extended to the Galilei group and modified in the special theory of relativity to the Poincare group to describe physics under the given conditions covariantly in the simplest way. The criticism of the a priori character leads to the formulation of the general theory of relativity. The general metric theory does not really give preference to a particular invariance group - even the principle of equivalence can be adapted to a whole family of groups. The physical laws covariantly inserted into the metric space are however adapted to the Poincare group. 8 references
Estimation of genetic parameters for body weights of Kurdish sheep ...

African Journals Online (AJOL)

Genetic parameters and (co)variance components were estimated by restricted maximum likelihood (REML) procedure, using animal models of kind 1, 2, 3, 4, 5 and 6, for body weight in birth, three, six, nine and 12 months of age in a Kurdish sheep flock. Direct and maternal breeding values were estimated using the best ...
Transformation of covariant quark Wigner operator to noncovariant one

International Nuclear Information System (INIS)

Selikhov, A.V.

1989-01-01

The gauge in which covariant and noncovariant quark Wigner operators coincide has been found. In this gauge the representations of vector potential via field strength tensor is valid. The system of equations for the coefficients of covariant Wigner operator expansion in the basis γ-matrices algebra is obtained. 12 refs.; 3 figs
Some observations on interpolating gauges and non-covariant gauges

Indian Academy of Sciences (India)

We discuss the viability of using interpolating gauges to deﬁne the non-covariant gauges starting from the covariant ones. We draw attention to the need for a very careful treatment of boundary condition deﬁning term. We show that the boundary condition needed to maintain gauge-invariance as the interpolating parameter ...
ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.

Science.gov (United States)

Lee, Keunbaik; Baek, Changryong; Daniels, Michael J

2017-11-01

In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.
Covariant conserved currents for scalar-tensor Horndeski theory

Science.gov (United States)

Schmidt, J.; Bičák, J.

2018-04-01

The scalar-tensor theories have become popular recently in particular in connection with attempts to explain present accelerated expansion of the universe, but they have been considered as a natural extension of general relativity long time ago. The Horndeski scalar-tensor theory involving four invariantly defined Lagrangians is a natural choice since it implies field equations involving at most second derivatives. Following the formalisms of defining covariant global quantities and conservation laws for perturbations of spacetimes in standard general relativity, we extend these methods to the general Horndeski theory and find the covariant conserved currents for all four Lagrangians. The current is also constructed in the case of linear perturbations involving both metric and scalar fields. As a specific illustration, we derive a superpotential that leads to the covariantly conserved current in the Branse-Dicke theory.
Covariant electrodynamics in linear media: Optical metric

Science.gov (United States)

Thompson, Robert T.

2018-03-01

While the postulate of covariance of Maxwell's equations for all inertial observers led Einstein to special relativity, it was the further demand of general covariance—form invariance under general coordinate transformations, including between accelerating frames—that led to general relativity. Several lines of inquiry over the past two decades, notably the development of metamaterial-based transformation optics, has spurred a greater interest in the role of geometry and space-time covariance for electrodynamics in ponderable media. I develop a generally covariant, coordinate-free framework for electrodynamics in general dielectric media residing in curved background space-times. In particular, I derive a relation for the spatial medium parameters measured by an arbitrary timelike observer. In terms of those medium parameters I derive an explicit expression for the pseudo-Finslerian optical metric of birefringent media and show how it reduces to a pseudo-Riemannian optical metric for nonbirefringent media. This formulation provides a basis for a unified approach to ray and congruence tracing through media in curved space-times that may smoothly vary among positively refracting, negatively refracting, and vacuum.
Development of covariance capabilities in EMPIRE code

Energy Technology Data Exchange (ETDEWEB)

Herman,M.; Pigni, M.T.; Oblozinsky, P.; Mughabghab, S.F.; Mattoon, C.M.; Capote, R.; Cho, Young-Sik; Trkov, A.

2008-06-24

The nuclear reaction code EMPIRE has been extended to provide evaluation capabilities for neutron cross section covariances in the thermal, resolved resonance, unresolved resonance and fast neutron regions. The Atlas of Neutron Resonances by Mughabghab is used as a primary source of information on uncertainties at low energies. Care is taken to ensure consistency among the resonance parameter uncertainties and those for thermal cross sections. The resulting resonance parameter covariances are formatted in the ENDF-6 File 32. In the fast neutron range our methodology is based on model calculations with the code EMPIRE combined with experimental data through several available approaches. The model-based covariances can be obtained using deterministic (Kalman) or stochastic (Monte Carlo) propagation of model parameter uncertainties. We show that these two procedures yield comparable results. The Kalman filter and/or the generalized least square fitting procedures are employed to incorporate experimental information. We compare the two approaches analyzing results for the major reaction channels on {sup 89}Y. We also discuss a long-standing issue of unreasonably low uncertainties and link it to the rigidity of the model.
Earth Observing System Covariance Realism Updates

Science.gov (United States)

Ojeda Romero, Juan A.; Miguel, Fred

2017-01-01

This presentation will be given at the International Earth Science Constellation Mission Operations Working Group meetings June 13-15, 2017 to discuss the Earth Observing System Covariance Realism updates.
Optimal covariance selection for estimation using graphical models

OpenAIRE

Vichik, Sergey; Oshman, Yaakov

2011-01-01

We consider a problem encountered when trying to estimate a Gaussian random field using a distributed estimation approach based on Gaussian graphical models. Because of constraints imposed by estimation tools used in Gaussian graphical models, the a priori covariance of the random field is constrained to embed conditional independence constraints among a significant number of variables. The problem is, then: given the (unconstrained) a priori covariance of the random field, and the conditiona...
Autism-specific covariation in perceptual performances: "g" or "p" factor?

Science.gov (United States)

Meilleur, Andrée-Anne S; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent

2014-01-01

Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor). Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor), which may drive perceptual abilities differently in autistic and
Autism-specific covariation in perceptual performances: "g" or "p" factor?

Directory of Open Access Journals (Sweden)

Andrée-Anne S Meilleur

Full Text Available Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination and mid-level (e.g., pattern matching tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals.We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ and Raven Progressive Matrices (RPM. We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence.In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism.Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor. Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor, which may drive perceptual abilities differently in
Multilevel maximum likelihood estimation with application to covariance matrices

Czech Academy of Sciences Publication Activity Database

Turčičová, Marie; Mandel, J.; Eben, Kryštof

Published online: 23 January ( 2018 ) ISSN 0361-0926 R&D Projects: GA ČR GA13-34856S Institutional support: RVO:67985807 Keywords : Fisher information * High dimension * Hierarchical maximum likelihood * Nested parameter spaces * Spectral diagonal covariance model * Sparse inverse covariance model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.311, year: 2016
Sir RA Fisher and the Evolution of Genetics

Indian Academy of Sciences (India)

quantitative genetics, a body of work that provides the conceptual underpinnings ... worked extensively with mutations that had large effects on structural ... altering the genetic composition of populations during adaptive ... exercise in ' writing.
Beamforming using subspace estimation from a diagonally averaged sample covariance.

Science.gov (United States)

Quijano, Jorge E; Zurk, Lisa M

2017-08-01

The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

Science.gov (United States)

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.
Genetic Mutations in Cancer

Science.gov (United States)

Many different types of genetic mutations are found in cancer cells. This infographic outlines certain types of alterations that are present in cancer, such as missense, nonsense, frameshift, and chromosome rearrangements.
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices

KAUST Repository

Lan, Shiwei

2017-11-08

Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix into variance and correlation matrices. The highlight is that the correlations are represented as products of vectors on unit spheres. We propose a variety of distributions on spheres (e.g. the squared-Dirichlet distribution) to induce flexible prior distributions for covariance matrices that go beyond the commonly used inverse-Wishart prior. To handle the intractability of the resulting posterior, we introduce the adaptive $\\\\Delta$-Spherical Hamiltonian Monte Carlo. We also extend our structured framework to dynamic cases and introduce unit-vector Gaussian process priors for modeling the evolution of correlation among multiple time series. Using an example of Normal-Inverse-Wishart problem, a simulated periodic process, and an analysis of local field potential data (collected from the hippocampus of rats performing a complex sequence memory task), we demonstrated the validity and effectiveness of our proposed framework for (dynamic) modeling covariance and correlation matrices.
Video based object representation and classification using multiple covariance matrices.

Science.gov (United States)

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.
The utility of covariance of combining ability in plant breeding.

Science.gov (United States)

Arunachalam, V

1976-11-01

The definition of covariances of half- and full sibs, and hence that of variances of general and specific combining ability with regard to a quantitative character, is extended to take into account the respective covariances between a pair of characters. The interpretation of the dispersion and correlation matrices of general and specific combining ability is discussed by considering a set of single, three- and four-way crosses, made using diallel and line × tester mating systems in Pennisetum typhoides. The general implications of the concept of covariance of combining ability in plant breeding are discussed.
Genetic and environmental influences on the association between performance-based self-esteem and exhaustion: A study of the self-worth notion of burnout.

Science.gov (United States)

Svedberg, Pia; Hallsten, Lennart; Narusyte, Jurgita; Bodin, Lennart; Blom, Victoria

2016-10-01

In the self-worth model, burnout is considered to be a syndrome of performance-based self-esteem (PBSE) and experiences of exhaustion. Studies have shown that PBSE and burnout indices such as Pines' Burnout Measure (BM) are associated. Whether these variables have overlapping etiologies has however not been studied before. Genetic and environmental components of covariation between PBSE and exhaustion measured with Pines' BM were examined in a bivariate Cholesky model using data from 14,875 monozygotic and dizygotic Swedish twins. Fifty-two per cent of the phenotypic correlation (r = 0.41) between PBSE and Pines' BM was explained by genetics and 48% by environmental factors. The findings of the present study strengthen the assumption that PBSE should be considered in the burnout process as proposed by the self-worth conception of burnout. The present results extend our understanding of the link between this contingent self-esteem construct and exhaustion and provide additional information about the underlying mechanisms in terms of genetics and environment. This finding corroborates the assumed syndrome view on burnout, while it also suggests an altered view of how the syndrome emerges and how it can be alleviated. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
Fast covariance estimation for innovations computed from a spatial Gibbs point process

DEFF Research Database (Denmark)

Coeurjolly, Jean-Francois; Rubak, Ege

In this paper, we derive an exact formula for the covariance of two innovations computed from a spatial Gibbs point process and suggest a fast method for estimating this covariance. We show how this methodology can be used to estimate the asymptotic covariance matrix of the maximum pseudo...
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

2017-01-01

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

Hu, Zongliang

2017-09-27

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.

Science.gov (United States)

Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

2017-09-21

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
On the Methodology to Calculate the Covariance of Estimated Resonance Parameters

International Nuclear Information System (INIS)

Becker, B.; Kopecky, S.; Schillebeeckx, P.

2015-01-01

Principles to determine resonance parameters and their covariance from experimental data are discussed. Different methods to propagate the covariance of experimental parameters are compared. A full Bayesian statistical analysis reveals that the level to which the initial uncertainty of the experimental parameters propagates, strongly depends on the experimental conditions. For high precision data the initial uncertainties of experimental parameters, like a normalization factor, has almost no impact on the covariance of the parameters in case of thick sample measurements and conventional uncertainty propagation or full Bayesian analysis. The covariances derived from a full Bayesian analysis and least-squares fit are derived under the condition that the model describing the experimental observables is perfect. When the quality of the model can not be verified a more conservative method based on a renormalization of the covariance matrix is recommended to propagate fully the uncertainty of experimental systematic effects. Finally, neutron resonance transmission analysis is proposed as an accurate method to validate evaluated data libraries in the resolved resonance region
Alteration of streamflow magnitudes and potential ecological consequences: A multiregional assessment

Science.gov (United States)

Carlisle, Daren M.; Wolock, David M.; Meador, Michael R.

2011-01-01

Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream-flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa possessed traits characteristic of lake or pond habitats, including a preference for fine-grained substrates and slow-moving currents, as well as the ability to temporarily leave the aquatic environment.
On the Covariance of Moore-Penrose Inverses in Rings with Involution

OpenAIRE

Mahzoon, Hesam

2014-01-01

We consider the so-called covariance set of Moore-Penrose inverses in rings with an involution. We deduce some new results concerning covariance set. We will show that if $a$ is a regular element in a ${C}^{\\ast }$ -algebra, then the covariance set of $a$ is closed in the set of invertible elements (with relative topology) of ${C}^{\\ast }$ -algebra and is a cone in the ${C}^{\\ast }$ -algebra.
The covariant entropy bound in gravitational collapse

International Nuclear Information System (INIS)

Gao, Sijie; Lemos, Jose P. S.

2004-01-01

We study the covariant entropy bound in the context of gravitational collapse. First, we discuss critically the heuristic arguments advanced by Bousso. Then we solve the problem through an exact model: a Tolman-Bondi dust shell collapsing into a Schwarzschild black hole. After the collapse, a new black hole with a larger mass is formed. The horizon, L, of the old black hole then terminates at the singularity. We show that the entropy crossing L does not exceed a quarter of the area of the old horizon. Therefore, the covariant entropy bound is satisfied in this process. (author)
Genome-Wide Association Uncovers Shared Genetic Effects Among Personality Traits and Mood States

NARCIS (Netherlands)

Luciano, Michelle; Huffman, Jennifer E.; Arias-Vásquez, Alejandro; Vinkhuyzen, Anna A. E.; Middeldorp, Christel M.; Giegling, Ina; Payton, Antony; Davies, Gail; Zgaga, Lina; Janzing, Joost; Ke, Xiayi; Galesloot, Tessel; Hartmann, Annette M.; Ollier, William; Tenesa, Albert; Hayward, Caroline; Verhagen, Maaike; Montgomery, Grant W.; Hottenga, Jouke-Jan; Konte, Bettina; Starr, John M.; Vitart, Veronique; Vos, Pieter E.; Madden, Pamela A. F.; Willemsen, Gonneke; Konnerth, Heike; Horan, Michael A.; Porteous, David J.; Campbell, Harry; Vermeulen, Sita H.; Heath, Andrew C.; Wright, Alan; Polasek, Ozren; Kovacevic, Sanja B.; Hastie, Nicholas D.; Franke, Barbara; Boomsma, Dorret I.; Martin, Nicholas G.; Rujescu, Dan; Wilson, James F.; Buitelaar, Jan; Pendleton, Neil; Rudan, Igor; Deary, Ian J.

2012-01-01

Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (similar to 2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of
Molecular alterations and biomarkers in colorectal cancer

Science.gov (United States)

Grady, William M.; Pritchard, Colin C.

2013-01-01

The promise of precision medicine is now a clinical reality. Advances in our understanding of the molecular genetics of colorectal cancer genetics is leading to the development of a variety of biomarkers that are being used as early detection markers, prognostic markers, and markers for predicting treatment responses. This is no more evident than in the recent advances in testing colorectal cancers for specific molecular alterations in order to guide treatment with the monoclonal antibody therapies cetuximab and panitumumab, which target the epidermal growth factor receptor (EGFR). In this review, we update a prior review published in 2010 and describe our current understanding of the molecular pathogenesis of colorectal cancer and how these alterations relate to emerging biomarkers for early detection and risk stratification (diagnostic markers), prognosis (prognostic markers), and the prediction of treatment responses (predictive markers). PMID:24178577
Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.

Science.gov (United States)

Han, Lei; Zhang, Yu; Zhang, Tong

2016-08-01

The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained increasing interest recently. Most existing works assume that inverse covariance estimators contain sparse structure and then construct models with the ℓ 1 regularization. In this paper, different from existing works, we study the inverse covariance estimation problem from another perspective by efficiently modeling the low-rank structure in the inverse covariance, which is assumed to be a combination of a low-rank part and a diagonal matrix. One motivation for this assumption is that the low-rank structure is common in many applications including the climate and financial analysis, and another one is that such assumption can reduce the computational complexity when computing its inverse. Specifically, we propose an efficient COmponent Pursuit (COP) method to obtain the low-rank part, where each component can be sparse. For optimization, the COP method greedily learns a rank-one component in each iteration by maximizing the log-likelihood. Moreover, the COP algorithm enjoys several appealing properties including the existence of an efficient solution in each iteration and the theoretical guarantee on the convergence of this greedy approach. Experiments on large-scale synthetic and real-world datasets including thousands of millions variables show that the COP method is faster than the state-of-the-art techniques for the inverse covariance estimation problem when achieving comparable log-likelihood on test data.
Evidence for a genetic overlap between body dysmorphic concerns and obsessive-compulsive symptoms in an adult female community twin sample.

Science.gov (United States)

Monzani, Benedetta; Rijsdijk, Fruhling; Iervolino, Alessandra C; Anson, Martin; Cherkas, Lynn; Mataix-Cols, David

2012-06-01

Body dysmorphic disorder (BDD) is thought to be etiologically related to obsessive-compulsive disorder (OCD) but the available evidence is incomplete. The current study examined the genetic and environmental sources of covariance between body dysmorphic and obsessive-compulsive symptoms in a community sample of adult twins. A total of 2,148 female twins (1,074 pairs) completed valid and reliable measures of body dysmorphic concerns and obsessive-compulsive symptoms. The data were analyzed using bivariate twin modeling methods and the statistical programme Mx. In the best-fitting model, the covariation between body dysmorphic and obsessive-compulsive traits was largely accounted for by genetic influences common to both phenotypes (64%; 95% CI: 0.50-0.80). This genetic overlap was even higher when specific obsessive-compulsive symptom dimensions were considered, with up to 82% of the phenotypic correlation between the obsessing and symmetry/ordering symptom dimensions and dysmorphic concerns being attributable to common genetic factors. Unique environmental factors, although influencing these traits individually, did not substantially contribute to their covariation. The results remained unchanged when excluding individuals reporting an objective medical condition/injury accounting for their concern in physical appearance. The association between body dysmorphic concerns and obsessive-compulsive symptoms is largely explained by shared genetic factors. Environmental risk factors were largely unique to each phenotype. These results support current recommendations to group BDD together with OCD in the same DSM-5 chapter, although comparison with other phenotypes such as somatoform disorders and social phobia is needed. Copyright © 2012 Wiley Periodicals, Inc.
Are the invariance principles really truly Lorentz covariant?

International Nuclear Information System (INIS)

Arunasalam, V.

1994-02-01

It is shown that some sections of the invariance (or symmetry) principles such as the space reversal symmetry (or parity P) and time reversal symmetry T (of elementary particle and condensed matter physics, etc.) are not really truly Lorentz covariant. Indeed, I find that the Dirac-Wigner sense of Lorentz invariance is not in full compliance with the Einstein-Minkowski reguirements of the Lorentz covariance of all physical laws (i.e., the world space Mach principle)
Covariate selection for the semiparametric additive risk model

DEFF Research Database (Denmark)

Martinussen, Torben; Scheike, Thomas

2009-01-01

This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared...... and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number...... of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare...

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